DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Status
Claims 1-20 are pending.
Claims 1-20 are rejected.
Priority
This application is a CON of 16/136,463 filed Sep 20 2018 (now USP 11,894,105), which claims priority to provisional application 62/560,745, filed Sep 20 2017.
Accordingly, each of claims 1-20 are afforded the effective filing date of Sep 20 2017.
Information Disclosure Statement
The information disclosure statements (IDS) filed on Mar 11 2024, Jun 26 2024, and Jul 22 2024 are in compliance with the provisions of 37 CFR 1.97 and have therefore been considered. Signed copies of the IDS documents are included with this Office Action.
Drawings
The Drawings submitted Dec 7 2023 are accepted.
Nucleotide and/or Amino Acid Sequence Disclosures
The sequence listing submitted Mar 11 2024 has been accepted.
Specification
The amendments to the specification submitted Mar 11 2024 are accepted.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to one or more judicial exceptions without significantly more.
MPEP 2106 organizes judicial exception analysis into Steps 1, 2A (Prongs One and Two) and 2B as follows below. MPEP 2106 and the following USPTO website provide further explanation and case law citations: uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials.
Framework with which to Evaluate Subject Matter Eligibility:
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter;
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e. a law of nature, a natural phenomenon, or an abstract idea;
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application (Prong Two); and
Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept.
Framework Analysis as Pertains to the Instant Claims:
Step 1
With respect to Step 1: yes, the claims are directed to a method, i.e., a process, machine, or manufacture within the above 101 categories [Step 1: YES; See MPEP § 2106.03].
Step 2A, Prong One
With respect to Step 2A, Prong One, the claims recite judicial exceptions in the form of abstract ideas. The MPEP at 2106.04(a)(2) further explains that abstract ideas are defined as:
mathematical concepts (mathematical formulas or equations, mathematical relationships and mathematical calculations);
certain methods of organizing human activity (fundamental economic practices or principles, managing personal behavior or relationships or interactions between people); and/or
mental processes (procedures for observing, evaluating, analyzing/ judging and organizing information).
With respect to the instant claims, under the Step 2A, Prong One evaluation, the claims are found to recite abstract ideas that fall into the grouping of mental processes (in particular procedures for observing, analyzing and organizing information) and mathematical concepts (in particular mathematical relationships and formulas) are as follows:
Independent claim 1: determining a consensus sequence read for each family of sequence reads based on signal measurements corresponding to the sequence reads for the family;
determining a consensus sequence alignment for each family of sequence reads, wherein a portion of the consensus sequence alignments correspond to the consensus sequence reads aligned with the targeted fusion reference sequence;
generating a compressed data structure comprising consensus compressed data, the consensus compressed data including the consensus sequence read and the consensus sequence alignment for each family, wherein a data volume of the compressed data structure is less than an original data volume of the plurality of nucleic acid sequence reads and the plurality of sequence alignments; and
detecting a fusion using the consensus sequence reads and the consensus sequence alignments from the compressed data structure.
Dependent claim 12: determining a presence of a process control target corresponding to the control gene reference sequence when a family count is greater than a minimum molecular count threshold and a read count is greater than a read count threshold, wherein the family count is the number of families corresponding to the consensus sequence reads aligned with the control gene reference sequence and the read count is a sum of the numbers of sequence reads for the corresponding families.
Dependent claims 3-11 and 13-20 recite further steps that limit the judicial exceptions in independent claim 1 and, as such, also are directed to those abstract ideas. For example, claims 3-10 further limits detecting a fusion to comprising identifying an eligible consensus sequence and limitations regarding that identification; claim 11 further limits the consensus compressed data to including consensus sequence reads and consensus sequence alignments corresponding to the control gene reference sequence; claims 13-17 further limit the fusion and its detection; claim 18 further limits the mapping of the consensus sequence reads and detecting a fusion; and claims 19-20 further limit determining a consensus sequence alignment.
The abstract ideas recited in the claims are evaluated under the Broadest Reasonable Interpretation (BRI) and determined to each cover performance either in the mind and/or by mathematical operation because the method only requires a user to manually compress nucleic acid sequence reads and detect a fusion. Without further detail as to the methodology involved in “determining”, “generating”, and “detecting”, under the BRI, one may simply, for example, use pen and paper to determine a consensus sequence read for each family of sequence reads, determine a consensus sequence alignment for each family to a targeted fusion reference sequence based on mapping quality of the reads and alignment to the targeted fusion reference sequence and a control gene reference sequence, generate a compressed data structure including the consensus sequence read and the consensus sequence alignment for each family, and detecting a fusion by identifying an eligible consensus sequence read based on characteristics of the alignment by calculating a ratio of read counts to either the mean or sum read count. The steps in dependent claims 16-17 for calculating a ratio of read counts to either the mean or sum read count require mathematical techniques as the only supported embodiments, as calculating a ratio describes a mathematical concept in words.
Therefore, claim 1 and those claims dependent therefrom recite an abstract idea [Step 2A, Prong 1: YES; See MPEP § 2106.04].
Step 2A, Prong Two
Because the claims do recite judicial exceptions, direction under Step 2A, Prong Two, provides that the claims must be examined further to determine whether they integrate the judicial exceptions into a practical application (MPEP 2106.04(d)). A claim can be said to integrate a judicial exception into a practical application when it applies, relies on, or uses the judicial exception in a manner that imposes a meaningful limit on the judicial exception. This is performed by analyzing the additional elements of the claim to determine if the judicial exceptions are integrated into a practical application (MPEP 2106.04(d).I.; MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the judicial exceptions, the claim is said to fail to integrate the judicial exceptions into a practical application (MPEP 2106.04(d).III).
Additional elements, Step 2A, Prong Two
With respect to the instant recitations, the claims recite the following additional elements:
Independent claim 1: receiving, at a processor, a plurality of nucleic acid sequence reads and a plurality of sequence alignments for a plurality of families of sequence reads, wherein each sequence read is associated with a molecular tag sequence, the molecular tag sequence identifying a family of sequence reads resulting from a particular polynucleotide molecule in a nucleic acid sample, each family having a number of sequence reads, wherein a portion of the sequence alignments correspond to sequence reads mapped to a targeted fusion reference sequence; and
storing the compressed data structure in a memory, wherein an amount of memory for the storing the compressed data structure is less than an original amount of memory for storing the plurality of nucleic acid sequence reads and the plurality of sequence alignments.
Dependent claims 2 and 11 recite steps that further limit the recited additional elements in the claims. For example, claim 2 further limits the structure of the received sequence reads; claim 11 further limits the sequence alignments to including a second portion corresponding to sequence reads mapped to a control gene reference sequence;
The claims also include non-abstract computing elements. For example, independent claim 1 includes a processor and a memory.
Considerations under Step 2A, Prong Two
With respect to Step 2A, Prong Two, the additional elements of the claims do not integrate the judicial exceptions into a practical application for the following reasons. Those steps directed to data gathering, such as “receiving”, and to data outputting, such as “storing”, perform functions of collecting the data needed to carry out the judicial exceptions. Data gathering and outputting do not impose any meaningful limitation on the judicial exceptions, or on how the judicial exceptions are performed. Data gathering and outputting steps are not sufficient to integrate judicial exceptions into a practical application (MPEP 2106.05(g)).
Further steps directed to additional non-abstract elements of “a processor” and “a memory” do not describe any specific computational steps by which the “computer parts” perform or carry out the judicial exceptions, nor do they provide any details of how specific structures of the computer, such as the computer-readable recording media, are used to implement these functions. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, and therefore the claim does not integrate that judicial exceptions into a practical application. The courts have weighed in and consistently maintained that when, for example, a memory, display, processor, machine, etc.… are recited so generically (i.e., no details are provided) that they represent no more than mere instructions to apply the judicial exception on a computer, and these limitations may be viewed as nothing more than generally linking the use of the judicial exception to the technological environment of a computer (MPEP 2106.05(f)).
Although the specification as published discloses that “compression rates directly relate to the reduction in the amount of memory required to store the consensus sequence read data from the amount of memory required to store the original sequence read data” at [0092] and that compression “of the sequence read data to provide consensus compressed data provides advantages for transmitting the data to processors in a distributed, clustered, remote, or cloud computing resource” at [0093], such advantages do not represent an improvement in the functioning of the computer itself, as the computer operates in a similar manner on a smaller amount of data. The specification does not provide a clear explanation for how the additional elements provide these improvements. Therefore, the additional elements do not clearly improve the functioning of a computer, or comprise an improvement to any other technical field. Further, the additional elements do not clearly affect a particular treatment; they do not clearly require or set forth a particular machine; they do not clearly effect a transformation of matter; nor do they clearly provide a nonconventional or unconventional step (MPEP2106.04(d)).
Thus, none of the claims recite additional elements which would integrate a judicial exception into a practical application, and the claims are directed to one or more judicial exceptions [Step 2A, Prong 2: NO; See MPEP § 2106.04(d)].
Step 2B (MPEP 2106.05.A i-vi)
According to analysis so far, the additional elements described above do not provide significantly more than the judicial exception. A determination of whether additional elements provide significantly more also rests on whether the additional elements or a combination of elements represents other than what is well-understood, routine, and conventional. Conventionality is a question of fact and may be evidenced as: a citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s).
With respect to the instant claims, the courts have found that receiving and outputting data are well-understood, routine, and conventional functions of a computer when claimed in a merely generic manner or as insignificant extra-solution activity (see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network), Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015), and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93, as discussed in MPEP 2106.05(d)(II)(i)). As such, the claims simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (MPEP2106.05(d)). The data gathering steps as recited in the instant claims constitute a general link to a technological environment which is insufficient to constitute an inventive concept which would render the claims significantly more than the judicial exception (MPEP2106.05(g)&(h)).
With respect to claims 1 and those claims dependent therefrom, the computer-related elements or the general purpose computer do not rise to the level of significantly more than the judicial exception. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, which the courts have found to not provide significantly more when recited in a claim with a judicial exception (Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984; see MPEP 2106.05(A)). The specification as published also notes that computer processors and systems, as example, are commercially available or widely used at [0107]. The additional elements are set forth at such a high level of generality that they can be met by a general purpose computer. Therefore, the computer components constitute no more than a general link to a technological environment, which is insufficient to constitute an inventive concept that would render the claims significantly more than the judicial exceptions (see MPEP 2106.05(b)I-III).
Taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception(s). Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claims as a whole do not amount to significantly more than the exception itself [Step 2B: NO; See MPEP § 2106.05].
Therefore, the instant claims are not drawn to eligible subject matter as they are directed to one or more judicial exceptions without significantly more. For additional guidance, applicant is directed generally to the MPEP § 2106.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
A. Claims 1-3, 5, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over the features of Alcaide et al. (Scientific Reports, 2017, 7(1), p. 1-19; cited on the Mar 11 2024 IDS).
The prior art to Alcaide discloses a molecular barcoding method for the precise detection and quantification of circulating tumor DNA to quantify single-nucleotide variants, indels, and genomic rearrangements (abstract). Alcaide, indicated by the open circles, teaches the instant features, indicated by the closed circles, as follows. Instantly claimed elements which are considered to be equivalent to the prior art teachings are described in bold for all claims.
Claim 1 discloses a method for compressing molecular tagged nucleic acid sequence data for fusion detection, comprising:
receiving, at a processor, a plurality of nucleic acid sequence reads and a plurality of sequence alignments for a plurality of families of sequence reads, wherein each sequence read is associated with a molecular tag sequence, the molecular tag sequence identifying a family of sequence reads resulting from a particular polynucleotide molecule in a nucleic acid sample, each family having a number of sequence reads, wherein a portion of the sequence alignments correspond to sequence reads mapped to a targeted fusion reference sequence;
Alcaide teaches extracting DNA (i.e., nucleic acids) from blood (p. 13, par. 2), using unique, semi-degenerate barcode tags (i.e., molecular tag sequences) (p. 13, par. 3-4) for library preparation (p. 13, par. 4-5). Alcaide teaches performing PCR amplification of the library (p. 14, par. 1), target enrichment using baits designed against somatic SNVs (single nucleotide variations), a NUMT1-BRD4 gene fusion, and a cancer panel (p. 14, par. 2-3), and sequencing of the libraries (i.e., producing nucleic acid sequence reads) (p. 14, par. 3). Alcaide teaches PCR amplification of the tagged DNA fragments results in tagged families with multiple copies of each tagged fragment (Figure 1). Alcaide teaches aligning on-target reads (i.e., a plurality of sequence alignments) using an artificial reference built from the concatenation of the targeted loci and their flanking sequences (i.e., a targeted fusion reference sequence) (p. 16, par. 1).
determining a consensus sequence read for each family of sequence reads based on signal measurements corresponding to the sequence reads for the family;
Alcaide teaches generating consensus sequences for each PCR family (p. 3, Figure 1 legend and p. 16, par. 3).
determining a consensus sequence alignment for each family of sequence reads, wherein a portion of the consensus sequence alignments correspond to the consensus sequence reads aligned with the targeted fusion reference sequence;
Alcaide teaches mapping and aligning the consensus sequences from reads against the concatenated reference (p. 16, par. 3-4).
generating a compressed data structure comprising consensus compressed data, the consensus compressed data including the consensus sequence read and the consensus sequence alignment for each family, wherein a data volume of the compressed data structure is less than an original data volume of the plurality of nucleic acid sequence reads and the plurality of sequence alignments;
storing the compressed data structure in a memory, wherein an amount of memory for the storing the compressed data structure is less than an original amount of memory for storing the plurality of nucleic acid sequence reads and the plurality of sequence alignments; and
Alcaide teaches generating ssDNA (single stranded DNA) and duplex consensus sequences (Figure 1 and p. 16, par. 3-4). Alcaide teaches copying, concatenating, and importing data in Microsoft Excel for further analysis and processing (i.e., storing in memory), as well as extracting lists containing consensus sequences and mapping the smallest list of consensus sequences (p. 16, par. 2-4). See below for discussion of modifying the features of Alcaide to produce a compressed data structure.
It is considered that the consensus sequence read and the consensus sequence alignment for each family as taught by Alcaide would inherently have less than an original data volume of the plurality of nucleic acid sequence reads and the plurality of sequence alignments as instantly claimed.
detecting a fusion using the consensus sequence reads and the consensus sequence alignments from the compressed data structure.
Alcaide teaches using the ssDNA to call variants (Figure 1). As Alcaide teaches targeting SNVs and a gene fusion as described above, it is considered that Alcaide fairly teaches the limitation of the claim.
Alcaide does not teach explicitly teach a compressed data structure as instantly claimed.
However, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the features of Alcaide, first to generate a compressed data structure as instantly claimed because Alcaide teaches determining a consensus sequence read and a consensus sequence alignment for each family as well as creating lists of consensus sequences and other data. Such a modification merely represents using the known technique of storing data, as taught by Alcaide at p. 16, par. 2, produced in the method of Alcaide as described above, which is merely an application of a known technique to a known method and would have yielded no more than the predictable outcome of producing a saved data file, or compressed data structure as instantly claimed.
Regarding claim 2, the features of Alcaide teach the method of claim 1. Claim 2 further limits the sequence reads to resulting from bidirectional sequencing, wherein a forward consensus sequence read and a reverse consensus sequence read are in separate families, including a forward family associated with a first prefix tag and a first suffix tag and a reverse family associated with a second prefix tag and a second suffix tag, the method further comprising combining the forward and reverse families when a reverse complement of the second prefix tag and second suffix tag matches the first prefix tag and the first suffix tag to form a combined family having one consensus sequence read for the compressed data structure.
Alcaide teaches sequencing the plus (i.e., forward) and minus (i.e., reverse) strands of DNA fragments (i.e., bidirectional sequencing) that each have 3’ and 5’ barcodes (i.e., suffix and prefix tags) (Figure 1). Alcaide teaches that the two parental strands derived from every single DNA molecule generate independent PCR families (p. 3, Figure 1 legend). Alcaide teaches determining a consensus sequence for both the plus and minus strands and forming a duplex consensus sequence (Figure 1). As Alcaide teaches only selecting those duplex consensus sequences that showed the expected nucleotides at each of the semi-degenerate barcode sites, it is considered that Alcaide fairly teaches the limitations of the claim regarding combining the forward and reverse families when a reverse complement of the second prefix tag and second suffix tag matches the first prefix tag and the first suffix tag.
Regarding claim 3, the features of Alcaide teach the method of claim 1. Claim 3 further limits the detecting a fusion further to comprising identifying an eligible consensus sequence read based on characteristics of the consensus sequence alignment of the consensus sequence read with the targeted fusion reference sequence.
Alcaide teaches aligning reads to the reference of the targeted loci and removing reads that did not provide data at targeted sites from the analysis of mutant and wildtype alleles (i.e., identifying eligible consensus sequence reads) (p. 16, par. 1)).
Regarding claim 5, the features of Alcaide teach the method of claims 1 and 3. Claim 5 further limits the identifying an eligible consensus sequence read to comprising determining whether the consensus sequence read aligned with the targeted fusion reference sequence spans a fusion breakpoint of the targeted fusion reference sequence.
Alcaide teaches identifying gene fusions (p. 9, par. 5 through p. 10, par. 1) with reads that align to the targeted reference database as described above (p. 16, par. 1). Alcaide teaches that on-target reads used for analysis are those that span targeted sites (i.e., a consensus sequence read spans a fusion breakpoint) (p. 4, par. 2).
Regarding claim 13, the features of Alcaide teach the method of claim 1. Claim 13 further limits the fusion to comprising an intergenic fusion and the targeted fusion reference sequence to comprising a reference sequence for the fusion of two genes at a fusion breakpoint.
Alcaide teaches the identification of several gene fusions, including a NUTM1-BRD4 gene fusion (i.e., an intergenic fusion) (p. 10, par. 1). Alcaide teaches that variant sequences, including the gene fusions, are stored in their reference of the targeted loci (p. 16, par. 2).
B. Claims 4 and 9-12 are rejected under 35 U.S.C. 103 as being unpatentable over the feature of Alcaide, as applied to claims 1 and 3, and in further view of Ion Reporter (ThermoFisher Scientific, 5.0 Software User Guide, MAN0013516 A.0, 1/12/2016, p. 1-406; cited on the Mar 11 2024 IDS).
Regarding claim 4, the features of Alcaide teach the method of claims 1 and 3. Claim 4 further limits the characteristics include a homology characteristic, a mapping quality characteristic and a breakpoint spanning characteristic.
Alcaide teaches identifying gene fusions (p. 9, par. 5 through p. 10, par. 1) with reads that align to the targeted reference database as described above (i.e., a breakpoint spanning characteristic) (p. 16, par. 1). Alcaide doesn’t teach a homology characteristic or a mapping quality characteristic.
However, the prior art to Ion Reporter discloses the user guide for the Ion ReporterTM Software for data analysis, annotation, and reporting of Ion Torrent semiconductor sequencing data (p. 8, par. 1). Ion Reporter teaches fusion analyses (p. 344-382). Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences (i.e., homology), exact matches in the overlap (i.e., mapping quality) (p. 347, Sensitivity), and a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions and p. 374).
Regarding claim 9, the features of Alcaide teach the method of claims 1 and 3. Claim 9 further limits the detecting a fusion to comprising determining whether a number of families corresponding to the eligible consensus sequence reads aligned with the targeted fusion reference sequence is greater than or equal to a minimum molecular count threshold.
Alcaide teaches counting the number of PCR families for generating a consensus sequence (p. 4, par. 2). Alcaide does not teach a minimum molecular count threshold for families when detecting a fusion.
However, Ion Reporter teaches a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions).
Regarding claim 10, the features of Alcaide teach the method of claims 1 and 3. Claim 10 further limits the detecting a fusion to comprising determining whether a read count is greater than or equal to a minimum read count threshold, wherein the read count is a sum of the numbers of sequence reads for the families corresponding to the eligible consensus sequence reads aligned with the targeted fusion reference sequence.
Alcaide does not teach determining whether a read count is greater than or equal to a minimum read count threshold when detecting a fusion.
However, Ion Reporter teaches a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions).
Regarding claim 11, the features of Alcaide teach the method of claim 1. Claim 11 further adds that a second portion of the sequence alignments correspond to sequence reads mapped to a control gene reference sequence, wherein the consensus compressed data further include consensus sequence reads and consensus sequence alignments corresponding to the control gene reference sequence.
Alcaide does not teach mapping reads to a control gene reference sequence.
However, Ion Reporter using five expression control calls that are built into the panel to (p. 352, par. 1). As Ion Reporter teaches reporting read counts aligned to specific expression control sequences (p. 348), it is considered that Ion Reporter fairly teaches the limitations of the claim regarding a control gene reference sequence.
Regarding claim 12, the features of Alcaide teach the method of claim 1, and, in further view of Ion Reporter, claim 11. Claim 12 further adds determining a presence of a process control target corresponding to the control gene reference sequence when a family count is greater than a minimum molecular count threshold and a read count is greater than a read count threshold, wherein the family count is the number of families corresponding to the consensus sequence reads aligned with the control gene reference sequence and the read count is a sum of the numbers of sequence reads for the corresponding families.
Alcaide does not teach determining a presence of a process control target.
However, Ion Reporter teaches a minimum read count threshold for detecting controls (p. 348).
Regarding claims 4 and 9-12, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the method of Alcaide for error correction and identification of targeted gene fusion sequencing data with the method of Ion Reporter for parameter settings for calling gene fusions because all references are in the same field of endeavor. The motivation would have been to set different levels of sensitivity and to perform quality control measurements of the data during fusion calls, as taught by Ion Reporter (p. 347 and p. 352). Specifically for claim 4, it would have been obvious to examine the percentage of overlap between the read and the reference sequence, the quality of the alignment of the overlapped region, and whether the reads span the breakpoint, as taught by Ion Reporter, during implementation of the method of Alcaide in order to examine the evidence supporting a fusion call. Specifically for claim 9, it would have been obvious to apply the read count threshold for each fusion isoform sequence, as taught by Ion Reporter, to the number of PCR families counted by Alcaide because both references Ion Reporter teaches the use of multiple thresholds for calling the presence of a fusion, which could readily be applied to the concept of PCR families. Specifically for claim 10, Ion Reporter already teaches counting the total number of reads for each fusion isoform sequence and applying a threshold. Specifically for claims 11-12, it would have been obvious to include control sequences as taught by Ion Reporter in the method of Alcaide for quality checking purposes, as absence of multiple controls could indicate low-quality sequencing runs or failed amplification, as taught by Ion Reporter (p. 354, par. 1). Thus, one could have combined the elements as claimed by known methods, and that in combination, each element merely would have performed the same function as it did separately. Furthermore, one of ordinary skill in the art would have recognized that the results of the combination were predictable.
C. Claims 6-8 are rejected under 35 U.S.C. 103 as being unpatentable over the features of Alcaide, as applied to claims 1 and 3 as described above, and in further view of Ion Reporter (ThermoFisher Scientific, 5.0 Software User Guide, MAN0013516 A.0, 1/12/2016, p. 1-406; cited on the Mar 11 2024 IDS) and Hovelson et al. (Neoplasia, 2015, 17(4), p. 385-399; SI (Supplementary Information), p. 1-82; cited on the Mar 11 2024 IDS).
Regarding claim 6, the features of Alcaide teach the method of claims 1 and 3. Claim 6 further limits the identifying an eligible consensus sequence read to comprising determining whether first and second homology levels of the consensus sequence read with first and second partner sequences, respectively, of the targeted fusion reference sequence are greater than or equal to a minimum homology threshold.
Alcaide does not teach determining whether first and second homology levels of the consensus sequence read with first and second partner sequences, respectively, of the targeted fusion reference sequence are greater than or equal to a minimum homology threshold.
However, the prior art to Ion Reporter discloses the user guide for the Ion ReporterTM Software for data analysis, annotation, and reporting of Ion Torrent semiconductor sequencing data (p. 8, par. 1). Ion Reporter teaches fusion analyses (p. 344-382). Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences (i.e., homology) (p. 347, Sensitivity).
Neither Alcaide or Ion Reporter teach first and second homology levels with first and second partner sequences.
However, the prior art to Hovelson discloses a catalog of relevant solid tumor somatic genome variants through comprehensive bioinformatics analysis of >700,000 samples (abstract). Hovelson SI teaches analyzing gene fusions with the Ion Reporter Fusion workflow by aligning AmpliSeq panel RNA reads to a gene reference of targeted chimeric fusion transcripts as well as reference sequences for expression imbalance and expression control gene targets (p. 5, par. 2). Hovelson SI teaches that read alignment required at least 70% overall homology to each side (i.e., a first and second partner sequence) of the fusion breakpoint (p. 5, par. 2).
Regarding claim 7, the features of Alcaide teach the method of claims 1 and 3. Claim 7 further limits the identifying an eligible consensus sequence read to comprising determining whether first and second mapping quality values for the consensus sequence read within first and second partner sequences, respectively, of the targeted fusion reference sequence are greater than or equal to a mapping quality threshold.
Alcaide does not teach determining whether first and second mapping quality values for the consensus sequence read within first and second partner sequences, respectively, of the targeted fusion reference sequence are greater than or equal to a mapping quality threshold.
However, Ion Reporter teaches fusion analyses (p. 344-382). Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences and exact matches in the overlap (i.e., mapping quality) (p. 347, Sensitivity).
Neither Alcaide or Ion Reporter teach first and second mapping quality values with first and second partner sequences.
However, the prior art to Hovelson discloses a catalog of relevant solid tumor somatic genome variants through comprehensive bioinformatics analysis of >700,000 samples (abstract). Hovelson SI teaches analyzing gene fusions with the Ion Reporter Fusion workflow by aligning AmpliSeq panel RNA reads to a gene reference of targeted chimeric fusion transcripts as well as reference sequences for expression imbalance and expression control gene targets (p. 5, par. 2). Hovelson SI teaches that read alignment required at least 70% overall homology to each side (i.e., a first and second partner sequence) of the fusion breakpoint (p. 5, par. 2).
Regarding claim 8, the features of Alcaide teach the method of claims 1 and 3, and, in further view of Ion Reporter and Hovelson, claim 7. Claim 8 further limits the identifying an eligible consensus sequence read further comprises determining the mapping quality value by calculating a ratio of a number of matching bases in the consensus sequence read that match the partner sequence to a number of overlapping bases in the consensus sequence read that overlap the partner sequence.
Alcaide does not teach determining a mapping quality value.
However, Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences and exact matches in the overlap (i.e., mapping quality) where the exact matches are expressed as a percentage of the overlap (for example, 50%, 66.66%, and 75%) (p. 347, Sensitivity).
Regarding claims 6-8, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the method of Alcaide for error correction and identification of targeted gene fusion sequencing data with the methods of Hovelson and Ion Reporter for gene fusion analysis because all methods are in the same field of endeavor. The motivation to use the method of Ion Reporter would have been to set different levels of sensitivity and to perform quality control measurements of the data during fusion calls, as taught by Ion Reporter (p. 347 and p. 352). It would have been obvious to use the method of Hovelson for setting an alignment threshold to either side of the fusion breakpoint because Hovelson uses the Ion Reporter software in their analysis. Specifically for claim 6, Hovelson and Ion Reporter explicitly teach each of the claimed elements. Specifically for claims 7-8, it would have been obvious to extend the analysis of the alignment on either side of the fusion breakpoint as taught by Hovelson to include the mapping quality value as taught by Ion Reporter. Thus, one could have combined the elements as claimed by known methods, and that in combination, each element merely would have performed the same function as it did separately. Furthermore, one of ordinary skill in the art would have recognized that the results of the combination were predictable.
D. Claims 14-15 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over the features of Alcaide, as applied to claim 1 as described above, and in further view of Torres-Garcia et al. (Bioinformatics, 2014, 30, p. 2224-2226; cited on the Mar 11 2024 IDS).
Regarding claim 14, the features of Alcaide teach the method of claim 1. Claim 14 further limits the fusion to comprising an intragenic fusion and the targeted fusion reference sequence to comprising a reference sequence for the fusion of two exons at a fusion breakpoint within a same gene.
Alcaide does not teach determining an intragenic fusion.
However, the prior art to Torres-Garcia discloses PRADA, a software platform for RNA-seq data analysis. Torres-Garcia teaches that the fusion module of PRADA aims to detect chimeric transcripts (p. 2224, col. 2, par. 4), with one variant developed to search for fusion transcripts involving two genes and one that searches for intragenic fusions (p. 2225, col. 1, par 2). Torres-Garcia teaches the detection of fusions by the construction of a sequence database that holds all possible exon-exon junctions that match the 3’ end of one gene fused to the 5’ end of a second gene (i.e., a targeted fusion reference sequence) (p. 2224, col. 2, par. 4). Torres-Garcia teaches only one method for identifying intragenic fusions, where transcripts are aligned to a database containing all possible exon-exon junctions. Although Torres-Garcia does not explicitly state that the database contains all possible exon-exon junctions within a same gene, it is considered that such a database must have been constructed to perform the identification of intragenic fusions. As Torres-Garcia teaches identifying intragenic fusions using a sequence database that holds all possible exon-exon junctions, it is considered that Torres-Garcia also fairly teaches the limitations of the claim regarding the targeted fusion reference sequence comprising a reference sequence for the fusion of two exons at a fusion breakpoint within a same gene.
Regarding claim 15, the features of Alcaide teach the method of claim 1, and, in further view of Torres-Garcia, claim 14. Claim 15 further adds a second portion of the consensus sequence alignments which corresponds to the consensus sequence reads aligned with one or more wild type reference sequences for the same gene.
Alcaide teaches Alcaide teaches counting the number of unique molecules (i.e., consensus sequence reads) supporting either mutant or wildtype alleles (p. 16, par. 1). As Alcaide teaches analyzing data supporting wildtype alleles, it is considered that Alcaide teaches alignment to a wild type reference sequence of the same gene.
Alcaide does not teach detecting an intragenic fusion.
However, Torres-Garcia teaches a module for detecting intragenic fusions (p. 2225, col. 1, par 2).
Regarding claim 18, the features of Alcaide teach the method of claim 1. Claim 18 further limits a portion of the consensus sequence reads partially map to the targeted fusion reference sequences, wherein detecting a fusion further comprises detecting a non-targeted fusion based on partially mapped consensus sequence reads.
Alcaide teaches that workflows that analyze sequencing data from enrichment experiments with large gene panels rely on essentially the same algorithm as their targeted method but differ by calling variants for non-reference alleles by searching across coding regions and splice donor/acceptor sites (p. 17, par. 3). Alcaide does not teach partial mapping of the consensus sequence reads.
However, Torres-Garcia teaches that other RNA analysis tools such as Tophat-fusion and Defuse rely on alignments of partial reads to identify gene fusions (p. 2225, col. 2, par. 3).
Regarding claims 14-15 and 18, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the method of Alcaide for error correction and identification of targeted gene fusion sequencing data with the method of Torres-Garcia for identifying intragenic fusions and non-targeted fusions because all methods are in the same field of endeavor. The motivation would have been to perform multifaceted analysis of raw RNA-seq data (abstract) quickly, accurately, and comprehensively (p. 2224, col. 1, par. 1), as taught by Torres-Garcia. Specifically for claim 14, it would have been obvious to combine the intragenic fusion module of Torres-Garcia with the consensus sequence and alignments for gene fusion detection method of Alcaide in view of Lysholm because intragenic fusions are a type of gene fusions. Specifically for claim 15, Alcaide teaches aligning sequencing reads to wild type reference sequences as described above. It would have been also obvious to align sequencing reads to the wild type reads of the targeted intragenic fusions. Specifically for claim 18, it would have been obvious to use one of the other RNA analysis tools discussed by Torres-Garcia to identify non-target fusions not present in a target database using partially mapped reads. Thus, one could have combined the elements as claimed by known methods, and that in combination, each element merely would have performed the same function as it did separately. Furthermore, one of ordinary skill in the art would have recognized that the results of the combination were predictable.
E. Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over the features of Alcaide, as applied to claim 1, and Torres-Garcia, as applied to claims 14-15 as described above, and in further view of Engreitz et al. (Nature, 2016, 539, p. 1-19 as cited on the Mar 11 2024 IDS). Instantly claimed elements which are considered to be equivalent to the prior art teachings are described in bold. The instant rejection is newly stated and is necessitated by claim amendment.
Regarding claim 16, the features of Alcaide teach the method of claim 1, and, in further view of Torres-Garcia, claims 14-15. Claim 16 further limits the detecting a fusion to comprising calculating a ratio of a read count for the intragenic fusion to a mean read count corresponding to the consensus sequence reads aligned with the wild type reference sequences for the same gene.
Alcaide teaches calculating the ratio of mutant versus wild-type DNA (p. 9, par. 3). Alcaide does not teach that the ratio is for the read count of the intragenic fusion to the mean read count of the wild type reference sequence for the same gene.
However, the prior art to Engreitz discloses a study examining how genomic loci that produce long non-coding RNAs influence the expression of neighboring loci (abstract). Engreitz teaches that for each modified allele, allele-specific measurements were normalized to the corresponding alleles in wild-type clones by dividing the value for knockout alleles by the mean of unmodified alleles in wild-type clones (p. 6, col. 2, par. 5).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the method of Alcaide Torres-Garcia for detecting targeted intragenic fusions from sequencing data with the method of Engreitz for dividing the value for knockout alleles by the mean of unmodified alleles because it would be desirable to calculate such a metric for comparing the read count levels of two different alleles. The motivation would have been to normalize the ratio of modified (i.e., mutant) alleles to unmodified (i.e., wild-type) alleles, as taught by Engreitz (p. 6, col. 2, par. 5). Thus, one could have combined the elements as claimed by known methods, and that in combination, each element merely would have performed the same function as it did separately. Furthermore, one of ordinary skill in the art would have recognized that the results of the combination were predictable.
F. Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over the features of Alcaide, as applied to claim 1, and Torres-Garcia, as applied to claims 14-15 as described above, and in further view of Alcaide SI et al. (Scientific Reports, 2017, 7(1), Supplementary Information, p. 1-12; cited on the Mar 11 2024 IDS).
Regarding claim 17, the features of Alcaide teach the method of claim 1, and, in further view of Torres-Garcia, claims 14-15. Claim 17 further limits the detecting a fusion further comprises calculating a ratio of a read count for the intragenic fusion to a sum of read counts corresponding to the consensus sequence reads aligned with the wild type reference sequences and the consensus sequence reads aligned with the targeted fusion reference sequences for the same gene.
Alcaide teaches calculating the ratio of mutant versus wild-type DNA (p. 9, par. 3). Alcaide SI shows this calculation involves a ratio of the mutant molecule count (i.e., consensus sequence reads) to the total molecule count (i.e., a sum of reads aligned to both the wild type reference sequences and the targeted fusion reference sequence for the same gene) (Table S2B). Alcaide does not teach detecting an intragenic fusion.
However, Torres-Garcia teaches a module for detecting intragenic fusions (p. 2225, col. 1, par 2).
Regarding claim 17, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the method of Alcaide and Alcaide SI for error correction and identification of targeted gene fusion sequencing data with the method of Torres-Garcia for identifying intragenic fusions and non-targeted fusions because all methods are in the same field of endeavor. The motivation would have been to perform multifaceted analysis of raw RNA-seq data (abstract) quickly, accurately, and comprehensively (p. 2224, col. 1, par. 1), as taught by Torres-Garcia. Alcaide teaches calculating a ratio as described above. It would have therefore also been obvious to calculate a ratio between the intragenic fusion and the wild type reference sequence.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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A. Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-18 of U.S. Patent No. 11,894,105. Although the claims at issue are not identical, they are not patentably distinct from each other for the following reasons.
Regarding instant claim 1, reference claim 1 discloses the limitations of instant claim 1.
Regarding instant claim 2, reference claim 2 discloses the limitations of instant claim 2.
Regarding instant claim 3, reference claim 1, final limitation, discloses the limitations of instant claim 1.
Regarding instant claim 4, reference claim 3 discloses the limitations of instant claim 4.
Regarding instant claim 5, reference claim 4 discloses the limitations of instant claim 5.
Regarding instant claim 6, reference claim 5 discloses the limitations of instant claim 6.
Regarding instant claim 7, reference claim 6 discloses the limitations of instant claim 7.
Regarding instant claim 8, reference claim 7 discloses the limitations of instant claim 8.
Regarding instant claim 9, reference claim 1, final limitation, discloses the limitations of instant claim 9.
Regarding instant claim 10, reference claim 8 discloses the limitations of instant claim 10.
Regarding instant claim 11, reference claim 9 discloses the limitations of instant claim 11.
Regarding instant claim 12, reference claim 10 discloses the limitations of instant claim 12.
Regarding instant claim 13, reference claim 11 discloses the limitations of instant claim 13.
Regarding instant claim 14, reference claim 12 discloses the limitations of instant claim 14.
Regarding instant claim 15, reference claim 13 discloses the limitations of instant claim 15.
Regarding instant claim 16, reference claim 14 discloses the limitations of instant claim 16.
Regarding instant claim 17, reference claim 15 discloses the limitations of instant claim 17.
Regarding instant claim 18, reference claim 16 discloses the limitations of instant claim 18.
Regarding instant claim 19, reference claim 17 discloses the limitations of instant claim 19.
Regarding instant claim 20, reference claim 18 discloses the limitations of instant claim 20.
B. Claims 1-3, 5, 13, and 19 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 12-13 of U.S. Patent No. 10,892,037 (reference patent) in view of Alcaide et al. (Scientific Reports, 2017, 7(1), p. 1-19; cited on the Mar 11 2024 IDS). Claims 4 and 9-12 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 10,892,037 in view of Alcaide, as applied to claims 1 and 3, and in further view of Ion Reporter (ThermoFisher Scientific, 5.0 Software User Guide, MAN0013516 A.0, 1/12/2016, p. 1-406; cited on the Mar 11 2024 IDS). Claims 6-8 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 10,892,037 in view of Alcaide, as applied to claims 1 and 3, and in further view of Ion Reporter (ThermoFisher Scientific, 5.0 Software User Guide, MAN0013516 A.0, 1/12/2016, p. 1-406; cited on the Mar 11 2024 IDS) and Hovelson et al. (Neoplasia, 2015, 17(4), p. 385-399; SI (Supplementary Information), p. 1-82; cited on the Mar 11 2024 IDS). Claims 14-15 and 18 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 10,892,037 in view of Alcaide, as applied to claim 1 as described above, and in further view of Torres-Garcia et al. (Bioinformatics, 2014, 30, p. 2224-2226; cited on the Mar 11 2024 IDS). Claim 16 is rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 10,892,037 in view of Alcaide, as applied to claim 1, and Torres-Garcia, as applied to claims 14-15 as described above, and in further view of Engreitz et al. (Nature, 2016, 539, p. 1-19 as cited on the Mar 11 2024 IDS). Claim 17 rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 10,892,037 in view of Alcaide, as applied to claim 1, and Torres-Garcia, as applied to claims 14-15 as described above, and in further view of Alcaide SI et al. (Scientific Reports, 2017, 7(1), Supplementary Information, p. 1-12; cited on the Mar 11 2024 IDS).
Regarding instant claim 1, reference claim 1 discloses the limitations of instant claim 1 except for a targeted fusion reference sequence in the 3rd limitation and detecting a fusion in the final limitation.
However, the prior art to Alcaide discloses a molecular barcoding method for the precise detection and quantification of circulating tumor DNA to quantify single-nucleotide variants, indels, and genomic rearrangements (abstract). Alcaide teaches mapping and aligning the consensus sequences from reads against the concatenated reference (p. 16, par. 3-4). Alcaide teaches generating ssDNA (single stranded DNA) and duplex consensus sequences (Figure 1 and p. 16, par. 3-4). Alcaide teaches using the ssDNA to call variants (Figure 1). As Alcaide teaches targeting SNVs and a gene fusion as described above, it is considered that Alcaide fairly teaches the limitation of the claim.
Regarding instant claim 2, reference claim 13 discloses the limitations of instant claim 2.
Regarding instant claims 3-4, reference claims 1 and 12 disclose the limitations of instant claims 3-4 because they disclose the use of mapping quality during consensus sequence determination as recited in claim 4. Regarding claim 4, the reference patent does not disclose a homology characteristic or a mapping quality characteristic.
However, the prior art to Ion Reporter discloses the user guide for the Ion ReporterTM Software for data analysis, annotation, and reporting of Ion Torrent semiconductor sequencing data (p. 8, par. 1). Ion Reporter teaches fusion analyses (p. 344-382). Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences (i.e., homology), exact matches in the overlap (i.e., mapping quality) (p. 347, Sensitivity), and a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions and p. 374).
Regarding instant claim 5, the reference patent does not disclose the limitation of claim 5.
However, Alcaide teaches identifying gene fusions (p. 9, par. 5 through p. 10, par. 1) with reads that align to the targeted reference database as described above (p. 16, par. 1). Alcaide teaches that on-target reads used for analysis are those that span targeted sites (i.e., a consensus sequence read spans a fusion breakpoint) (p. 4, par. 2).
Regarding instant claim 6, the reference patent does not disclose the limitation of claim 6.
However, the prior art to Ion Reporter discloses the user guide for the Ion ReporterTM Software for data analysis, annotation, and reporting of Ion Torrent semiconductor sequencing data (p. 8, par. 1). Ion Reporter teaches fusion analyses (p. 344-382). Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences (i.e., homology) (p. 347, Sensitivity).
However, the prior art to Hovelson discloses a catalog of relevant solid tumor somatic genome variants through comprehensive bioinformatics analysis of >700,000 samples (abstract). Hovelson SI teaches analyzing gene fusions with the Ion Reporter Fusion workflow by aligning AmpliSeq panel RNA reads to a gene reference of targeted chimeric fusion transcripts as well as reference sequences for expression imbalance and expression control gene targets (p. 5, par. 2). Hovelson SI teaches that read alignment required at least 70% overall homology to each side (i.e., a first and second partner sequence) of the fusion breakpoint (p. 5, par. 2).
Regarding instant claim 7, reference claim 1 discloses the limitations of instant claim 7 by using the sequence read having a highest mapping quality.
Regarding instant claim 8, the reference patent does not disclose the limitations of claim 8.
However, Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences and exact matches in the overlap (i.e., mapping quality) where the exact matches are expressed as a percentage of the overlap (for example, 50%, 66.66%, and 75%) (p. 347, Sensitivity).
Regarding instant claim 9, the reference patent does not disclose the limitation of claim 9.
However, Alcaide teaches counting the number of PCR families for generating a consensus sequence (p. 4, par. 2). Alcaide does not teach a minimum molecular count threshold for families when detecting a fusion.
However, Ion Reporter teaches a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions).
Regarding instant claim 10, the reference patent does not disclose the limitation of claim 10.
However, Ion Reporter teaches a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions).
Regarding instant claim 11, the reference patent does not disclose the limitation of claim 11.
However, Ion Reporter using five expression control calls that are built into the panel to (p. 352, par. 1). As Ion Reporter teaches reporting read counts aligned to specific expression control sequences (p. 348), it is considered that Ion Reporter fairly teaches the limitations of the claim regarding a control gene reference sequence.
Regarding instant claim 12, the reference patent does not disclose the limitation of claim 12.
However, Ion Reporter teaches a minimum read count threshold for detecting controls (p. 348).
Regarding instant claim 13, the reference patent does not disclose the limitation of claim 13.
However, Alcaide teaches the identification of several gene fusions, including a NUTM1-BRD4 gene fusion (i.e., an intergenic fusion) (p. 10, par. 1). Alcaide teaches that variant sequences, including the gene fusions, are stored in their reference of the targeted loci (p. 16, par. 2).
Regarding instant claim 14, the reference patent does not disclose the limitation of claim 14.
However, the prior art to Torres-Garcia discloses PRADA, a software platform for RNA-seq data analysis. Torres-Garcia teaches that the fusion module of PRADA aims to detect chimeric transcripts (p. 2224, col. 2, par. 4), with one variant developed to search for fusion transcripts involving two genes and one that searches for intragenic fusions (p. 2225, col. 1, par 2). Torres-Garcia teaches the detection of fusions by the construction of a sequence database that holds all possible exon-exon junctions that match the 3’ end of one gene fused to the 5’ end of a second gene (i.e., a targeted fusion reference sequence) (p. 2224, col. 2, par. 4). Torres-Garcia teaches only one method for identifying intragenic fusions, where transcripts are aligned to a database containing all possible exon-exon junctions. Although Torres-Garcia does not explicitly state that the database contains all possible exon-exon junctions within a same gene, it is considered that such a database must have been constructed to perform the identification of intragenic fusions. As Torres-Garcia teaches identifying intragenic fusions using a sequence database that holds all possible exon-exon junctions, it is considered that Torres-Garcia also fairly teaches the limitations of the claim regarding the targeted fusion reference sequence comprising a reference sequence for the fusion of two exons at a fusion breakpoint within a same gene.
Regarding instant claim 15, the reference patent does not disclose the limitation of claim 15.
Alcaide teaches Alcaide teaches counting the number of unique molecules (i.e., consensus sequence reads) supporting either mutant or wildtype alleles (p. 16, par. 1). As Alcaide teaches analyzing data supporting wildtype alleles, it is considered that Alcaide teaches alignment to a wild type reference sequence of the same gene.
However, Torres-Garcia teaches a module for detecting intragenic fusions (p. 2225, col. 1, par 2).
Regarding instant claim 16, the reference patent does not disclose the limitation of claim 16.
However, Alcaide teaches calculating the ratio of mutant versus wild-type DNA (p. 9, par. 3).
However, the prior art to Engreitz discloses a study examining how genomic loci that produce long non-coding RNAs influence the expression of neighboring loci (abstract). Engreitz teaches that for each modified allele, allele-specific measurements were normalized to the corresponding alleles in wild-type clones by dividing the value for knockout alleles by the mean of unmodified alleles in wild-type clones (p. 6, col. 2, par. 5).
Regarding instant claim 17, the reference patent does not disclose the limitation of claim 17.
However, Alcaide teaches calculating the ratio of mutant versus wild-type DNA (p. 9, par. 3). Alcaide SI shows this calculation involves a ratio of the mutant molecule count (i.e., consensus sequence reads) to the total molecule count (i.e., a sum of reads aligned to both the wild type reference sequences and the targeted fusion reference sequence for the same gene) (Table S2B). Alcaide does not teach detecting an intragenic fusion.
However, Torres-Garcia teaches a module for detecting intragenic fusions (p. 2225, col. 1, par 2).
Regarding instant claim 18, the reference patent does not disclose the limitation of claim 18.
However, Alcaide teaches that workflows that analyze sequencing data from enrichment experiments with large gene panels rely on essentially the same algorithm as their targeted method but differ by calling variants for non-reference alleles by searching across coding regions and splice donor/acceptor sites (p. 17, par. 3).
However, Torres-Garcia teaches that other RNA analysis tools such as Tophat-fusion and Defuse rely on alignments of partial reads to identify gene fusions (p. 2225, col. 2, par. 3).
Regarding instant claim 19, reference claim 1, limitation 6, discloses the limitations of instant claim 19.
Regarding claims 1-3, 5, 13, and 19, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the reference patent with Alcaide because both references are in the same field of endeavor. The motivation would have been to use a method which provides error-suppression based on consensus sequence generation using barcoded adapters, as taught by Alcaide (p. 2, par. 2).
Regarding claims 4 and 9-12, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide with Ion Torrent because each reference discloses methods for identifying variants with consensus sequences. The motivation would have been to set different levels of sensitivity and to perform quality control measurements of the data during fusion calls, as taught by Ion Reporter (p. 347 and p. 352).
Regarding claims 6-8, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide with Ion Torrent and Hovelson because each reference discloses methods for identifying variants with consensus sequences. The motivation would have been to set different levels of sensitivity and to perform quality control measurements of the data during fusion calls, as taught by Ion Reporter (p. 347 and p. 352). It would have been obvious to use the method of Hovelson for setting an alignment threshold to either side of the fusion breakpoint because Hovelson uses the Ion Reporter software in their analysis.
Regarding claims 14-15 and 18, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide for error correction and identification of targeted gene fusion sequencing data with the method of Torres-Garcia for identifying intragenic fusions and non-targeted fusions because all methods are in the same field of endeavor. The motivation would have been to perform multifaceted analysis of raw RNA-seq data (abstract) quickly, accurately, and comprehensively (p. 2224, col. 1, par. 1), as taught by Torres-Garcia.
Regarding claim 16, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide and Torres-Garcia for detecting targeted intragenic fusions from sequencing data with the method of Engreitz for dividing the value for knockout alleles by the mean of unmodified alleles because it would be desirable to calculate such a metric for comparing the read count levels of two different alleles. The motivation would have been to normalize the ratio of modified (i.e., mutant) alleles to unmodified (i.e., wild-type) alleles, as taught by Engreitz (p. 6, col. 2, par. 5).
Regarding claim 17, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide and Torres-Garcia for detecting targeted intragenic fusions from sequencing data with the method of Alcaide SI fusions because all methods are in the same field of endeavor. The motivation would have been to perform multifaceted analysis of raw RNA-seq data (abstract) quickly, accurately, and comprehensively (p. 2224, col. 1, par. 1), as taught by Torres-Garcia.
C. Claims 1-3, 5, 13, and 19 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 13-14 of U.S. Patent No. 11,468,972 (reference patent) in view of Alcaide et al. (Scientific Reports, 2017, 7(1), p. 1-19; cited on the Mar 11 2024 IDS). Claims 4 and 9-12 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 11,468,972 in view of Alcaide, as applied to claims 1 and 3, and in further view of Ion Reporter (ThermoFisher Scientific, 5.0 Software User Guide, MAN0013516 A.0, 1/12/2016, p. 1-406; cited on the Mar 11 2024 IDS). Claims 6-8 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 11,468,972 in view of Alcaide, as applied to claims 1 and 3, and in further view of Ion Reporter (ThermoFisher Scientific, 5.0 Software User Guide, MAN0013516 A.0, 1/12/2016, p. 1-406; cited on the Mar 11 2024 IDS) and Hovelson et al. (Neoplasia, 2015, 17(4), p. 385-399; SI (Supplementary Information), p. 1-82; cited on the Mar 11 2024 IDS). Claims 14-15 and 18 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 11,468,972 in view of Alcaide, as applied to claim 1 as described above, and in further view of Torres-Garcia et al. (Bioinformatics, 2014, 30, p. 2224-2226; cited on the Mar 11 2024 IDS). Claim 16 is rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 11,468,972 in view of Alcaide, as applied to claim 1, and Torres-Garcia, as applied to claims 14-15 as described above, and in further view of Engreitz et al. (Nature, 2016, 539, p. 1-19 as cited on the Mar 11 2024 IDS). Claim 17 rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 11,468,972 in view of Alcaide, as applied to claim 1, and Torres-Garcia, as applied to claims 14-15 as described above, and in further view of Alcaide SI et al. (Scientific Reports, 2017, 7(1), Supplementary Information, p. 1-12; cited on the Mar 11 2024 IDS).
Regarding instant claim 1, reference claim 1 discloses the limitations of instant claim 1 except for a targeted fusion reference sequence in the 3rd limitation and detecting a fusion in the final limitation.
However, the prior art to Alcaide discloses a molecular barcoding method for the precise detection and quantification of circulating tumor DNA to quantify single-nucleotide variants, indels, and genomic rearrangements (abstract). Alcaide teaches mapping and aligning the consensus sequences from reads against the concatenated reference (p. 16, par. 3-4). Alcaide teaches generating ssDNA (single stranded DNA) and duplex consensus sequences (Figure 1 and p. 16, par. 3-4). Alcaide teaches using the ssDNA to call variants (Figure 1). As Alcaide teaches targeting SNVs and a gene fusion as described above, it is considered that Alcaide fairly teaches the limitation of the claim.
Regarding instant claim 2, reference claim 14 discloses the limitations of instant claim 2.
Regarding instant claims 3-4, reference claims 1 and 13 disclose the limitations of instant claims 3-4 because they disclose the use of mapping quality during consensus sequence determination as recited in claim 4. Regarding claim 4, the reference patent does not disclose a homology characteristic or a mapping quality characteristic.
However, the prior art to Ion Reporter discloses the user guide for the Ion ReporterTM Software for data analysis, annotation, and reporting of Ion Torrent semiconductor sequencing data (p. 8, par. 1). Ion Reporter teaches fusion analyses (p. 344-382). Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences (i.e., homology), exact matches in the overlap (i.e., mapping quality) (p. 347, Sensitivity), and a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions and p. 374).
Regarding instant claim 5, the reference patent does not disclose the limitation of claim 5.
However, Alcaide teaches identifying gene fusions (p. 9, par. 5 through p. 10, par. 1) with reads that align to the targeted reference database as described above (p. 16, par. 1). Alcaide teaches that on-target reads used for analysis are those that span targeted sites (i.e., a consensus sequence read spans a fusion breakpoint) (p. 4, par. 2).
Regarding instant claim 6, the reference patent does not disclose the limitation of claim 6.
However, the prior art to Ion Reporter discloses the user guide for the Ion ReporterTM Software for data analysis, annotation, and reporting of Ion Torrent semiconductor sequencing data (p. 8, par. 1). Ion Reporter teaches fusion analyses (p. 344-382). Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences (i.e., homology) (p. 347, Sensitivity).
However, the prior art to Hovelson discloses a catalog of relevant solid tumor somatic genome variants through comprehensive bioinformatics analysis of >700,000 samples (abstract). Hovelson SI teaches analyzing gene fusions with the Ion Reporter Fusion workflow by aligning AmpliSeq panel RNA reads to a gene reference of targeted chimeric fusion transcripts as well as reference sequences for expression imbalance and expression control gene targets (p. 5, par. 2). Hovelson SI teaches that read alignment required at least 70% overall homology to each side (i.e., a first and second partner sequence) of the fusion breakpoint (p. 5, par. 2).
Regarding instant claim 7, reference claim 1 discloses the limitations of instant claim 7 by using the sequence read having a highest mapping quality.
Regarding instant claim 8, the reference patent does not disclose the limitations of claim 8.
However, Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences and exact matches in the overlap (i.e., mapping quality) where the exact matches are expressed as a percentage of the overlap (for example, 50%, 66.66%, and 75%) (p. 347, Sensitivity).
Regarding instant claim 9, the reference patent does not disclose the limitation of claim 9.
However, Alcaide teaches counting the number of PCR families for generating a consensus sequence (p. 4, par. 2). Alcaide does not teach a minimum molecular count threshold for families when detecting a fusion.
However, Ion Reporter teaches a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions).
Regarding instant claim 10, the reference patent does not disclose the limitation of claim 10.
However, Ion Reporter teaches a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions).
Regarding instant claim 11, the reference patent does not disclose the limitation of claim 11.
However, Ion Reporter using five expression control calls that are built into the panel to (p. 352, par. 1). As Ion Reporter teaches reporting read counts aligned to specific expression control sequences (p. 348), it is considered that Ion Reporter fairly teaches the limitations of the claim regarding a control gene reference sequence.
Regarding instant claim 12, the reference patent does not disclose the limitation of claim 12.
However, Ion Reporter teaches a minimum read count threshold for detecting controls (p. 348).
Regarding instant claim 13, the reference patent does not disclose the limitation of claim 13.
However, Alcaide teaches the identification of several gene fusions, including a NUTM1-BRD4 gene fusion (i.e., an intergenic fusion) (p. 10, par. 1). Alcaide teaches that variant sequences, including the gene fusions, are stored in their reference of the targeted loci (p. 16, par. 2).
Regarding instant claim 14, the reference patent does not disclose the limitation of claim 14.
However, the prior art to Torres-Garcia discloses PRADA, a software platform for RNA-seq data analysis. Torres-Garcia teaches that the fusion module of PRADA aims to detect chimeric transcripts (p. 2224, col. 2, par. 4), with one variant developed to search for fusion transcripts involving two genes and one that searches for intragenic fusions (p. 2225, col. 1, par 2). Torres-Garcia teaches the detection of fusions by the construction of a sequence database that holds all possible exon-exon junctions that match the 3’ end of one gene fused to the 5’ end of a second gene (i.e., a targeted fusion reference sequence) (p. 2224, col. 2, par. 4). Torres-Garcia teaches only one method for identifying intragenic fusions, where transcripts are aligned to a database containing all possible exon-exon junctions. Although Torres-Garcia does not explicitly state that the database contains all possible exon-exon junctions within a same gene, it is considered that such a database must have been constructed to perform the identification of intragenic fusions. As Torres-Garcia teaches identifying intragenic fusions using a sequence database that holds all possible exon-exon junctions, it is considered that Torres-Garcia also fairly teaches the limitations of the claim regarding the targeted fusion reference sequence comprising a reference sequence for the fusion of two exons at a fusion breakpoint within a same gene.
Regarding instant claim 15, the reference patent does not disclose the limitation of claim 15.
Alcaide teaches Alcaide teaches counting the number of unique molecules (i.e., consensus sequence reads) supporting either mutant or wildtype alleles (p. 16, par. 1). As Alcaide teaches analyzing data supporting wildtype alleles, it is considered that Alcaide teaches alignment to a wild type reference sequence of the same gene.
However, Torres-Garcia teaches a module for detecting intragenic fusions (p. 2225, col. 1, par 2).
Regarding instant claim 16, the reference patent does not disclose the limitation of claim 16.
However, Alcaide teaches calculating the ratio of mutant versus wild-type DNA (p. 9, par. 3).
However, the prior art to Engreitz discloses a study examining how genomic loci that produce long non-coding RNAs influence the expression of neighboring loci (abstract). Engreitz teaches that for each modified allele, allele-specific measurements were normalized to the corresponding alleles in wild-type clones by dividing the value for knockout alleles by the mean of unmodified alleles in wild-type clones (p. 6, col. 2, par. 5).
Regarding instant claim 17, the reference patent does not disclose the limitation of claim 17.
However, Alcaide teaches calculating the ratio of mutant versus wild-type DNA (p. 9, par. 3). Alcaide SI shows this calculation involves a ratio of the mutant molecule count (i.e., consensus sequence reads) to the total molecule count (i.e., a sum of reads aligned to both the wild type reference sequences and the targeted fusion reference sequence for the same gene) (Table S2B). Alcaide does not teach detecting an intragenic fusion.
However, Torres-Garcia teaches a module for detecting intragenic fusions (p. 2225, col. 1, par 2).
Regarding instant claim 18, the reference patent does not disclose the limitation of claim 18.
However, Alcaide teaches that workflows that analyze sequencing data from enrichment experiments with large gene panels rely on essentially the same algorithm as their targeted method but differ by calling variants for non-reference alleles by searching across coding regions and splice donor/acceptor sites (p. 17, par. 3).
However, Torres-Garcia teaches that other RNA analysis tools such as Tophat-fusion and Defuse rely on alignments of partial reads to identify gene fusions (p. 2225, col. 2, par. 3).
Regarding instant claim 19, reference claim 1, limitation 6, discloses the limitations of instant claim 19.
Regarding claims 1-3, 5, 13, and 19, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the reference patent with Alcaide because both references are in the same field of endeavor. The motivation would have been to use a method which provides error-suppression based on consensus sequence generation using barcoded adapters, as taught by Alcaide (p. 2, par. 2).
Regarding claims 4 and 9-12, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide with Ion Torrent because each reference discloses methods for identifying variants with consensus sequences. The motivation would have been to set different levels of sensitivity and to perform quality control measurements of the data during fusion calls, as taught by Ion Reporter (p. 347 and p. 352).
Regarding claims 6-8, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide with Ion Torrent and Hovelson because each reference discloses methods for identifying variants with consensus sequences. The motivation would have been to set different levels of sensitivity and to perform quality control measurements of the data during fusion calls, as taught by Ion Reporter (p. 347 and p. 352). It would have been obvious to use the method of Hovelson for setting an alignment threshold to either side of the fusion breakpoint because Hovelson uses the Ion Reporter software in their analysis.
Regarding claims 14-15 and 18, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide for error correction and identification of targeted gene fusion sequencing data with the method of Torres-Garcia for identifying intragenic fusions and non-targeted fusions because all methods are in the same field of endeavor. The motivation would have been to perform multifaceted analysis of raw RNA-seq data (abstract) quickly, accurately, and comprehensively (p. 2224, col. 1, par. 1), as taught by Torres-Garcia.
Regarding claim 16, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide and Torres-Garcia for detecting targeted intragenic fusions from sequencing data with the method of Engreitz for dividing the value for knockout alleles by the mean of unmodified alleles because it would be desirable to calculate such a metric for comparing the read count levels of two different alleles. The motivation would have been to normalize the ratio of modified (i.e., mutant) alleles to unmodified (i.e., wild-type) alleles, as taught by Engreitz (p. 6, col. 2, par. 5).
Regarding claim 17, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide and Torres-Garcia for detecting targeted intragenic fusions from sequencing data with the method of Alcaide SI fusions because all methods are in the same field of endeavor. The motivation would have been to perform multifaceted analysis of raw RNA-seq data (abstract) quickly, accurately, and comprehensively (p. 2224, col. 1, par. 1), as taught by Torres-Garcia.
D. Claims 1-3, 5, 13, and 19 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 13-14 of U.S. Patent No. 11,887,699 (reference patent) in view of Alcaide et al. (Scientific Reports, 2017, 7(1), p. 1-19; cited on the Mar 11 2024 IDS). Claims 4 and 9-12 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 11,887,699 in view of Alcaide, as applied to claims 1 and 3, and in further view of Ion Reporter (ThermoFisher Scientific, 5.0 Software User Guide, MAN0013516 A.0, 1/12/2016, p. 1-406; cited on the Mar 11 2024 IDS). Claims 6-8 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 11,887,699 in view of Alcaide, as applied to claims 1 and 3, and in further view of Ion Reporter (ThermoFisher Scientific, 5.0 Software User Guide, MAN0013516 A.0, 1/12/2016, p. 1-406; cited on the Mar 11 2024 IDS) and Hovelson et al. (Neoplasia, 2015, 17(4), p. 385-399; SI (Supplementary Information), p. 1-82; cited on the Mar 11 2024 IDS). Claims 14-15 and 18 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 11,887,699 in view of Alcaide, as applied to claim 1 as described above, and in further view of Torres-Garcia et al. (Bioinformatics, 2014, 30, p. 2224-2226; cited on the Mar 11 2024 IDS). Claim 16 is rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 11,887,699 in view of Alcaide, as applied to claim 1, and Torres-Garcia, as applied to claims 14-15 as described above, and in further view of Engreitz et al. (Nature, 2016, 539, p. 1-19 as cited on the Mar 11 2024 IDS). Claim 17 rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 11,887,699 in view of Alcaide, as applied to claim 1, and Torres-Garcia, as applied to claims 14-15 as described above, and in further view of Alcaide SI et al. (Scientific Reports, 2017, 7(1), Supplementary Information, p. 1-12; cited on the Mar 11 2024 IDS).
Regarding instant claim 1, reference claim 1 discloses the limitations of instant claim 1 except for a targeted fusion reference sequence in the 3rd limitation and detecting a fusion in the final limitation.
However, the prior art to Alcaide discloses a molecular barcoding method for the precise detection and quantification of circulating tumor DNA to quantify single-nucleotide variants, indels, and genomic rearrangements (abstract). Alcaide teaches mapping and aligning the consensus sequences from reads against the concatenated reference (p. 16, par. 3-4). Alcaide teaches generating ssDNA (single stranded DNA) and duplex consensus sequences (Figure 1 and p. 16, par. 3-4). Alcaide teaches using the ssDNA to call variants (Figure 1). As Alcaide teaches targeting SNVs and a gene fusion as described above, it is considered that Alcaide fairly teaches the limitation of the claim.
Regarding instant claim 2, reference claim 14 discloses the limitations of instant claim 2.
Regarding instant claims 3-4, reference claims 1 and 13 disclose the limitations of instant claims 3-4 because they disclose the use of mapping quality during consensus sequence determination as recited in claim 4. Regarding claim 4, the reference patent does not disclose a homology characteristic or a mapping quality characteristic.
However, the prior art to Ion Reporter discloses the user guide for the Ion ReporterTM Software for data analysis, annotation, and reporting of Ion Torrent semiconductor sequencing data (p. 8, par. 1). Ion Reporter teaches fusion analyses (p. 344-382). Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences (i.e., homology), exact matches in the overlap (i.e., mapping quality) (p. 347, Sensitivity), and a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions and p. 374).
Regarding instant claim 5, the reference patent does not disclose the limitation of claim 5.
However, Alcaide teaches identifying gene fusions (p. 9, par. 5 through p. 10, par. 1) with reads that align to the targeted reference database as described above (p. 16, par. 1). Alcaide teaches that on-target reads used for analysis are those that span targeted sites (i.e., a consensus sequence read spans a fusion breakpoint) (p. 4, par. 2).
Regarding instant claim 6, the reference patent does not disclose the limitation of claim 6.
However, the prior art to Ion Reporter discloses the user guide for the Ion ReporterTM Software for data analysis, annotation, and reporting of Ion Torrent semiconductor sequencing data (p. 8, par. 1). Ion Reporter teaches fusion analyses (p. 344-382). Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences (i.e., homology) (p. 347, Sensitivity).
However, the prior art to Hovelson discloses a catalog of relevant solid tumor somatic genome variants through comprehensive bioinformatics analysis of >700,000 samples (abstract). Hovelson SI teaches analyzing gene fusions with the Ion Reporter Fusion workflow by aligning AmpliSeq panel RNA reads to a gene reference of targeted chimeric fusion transcripts as well as reference sequences for expression imbalance and expression control gene targets (p. 5, par. 2). Hovelson SI teaches that read alignment required at least 70% overall homology to each side (i.e., a first and second partner sequence) of the fusion breakpoint (p. 5, par. 2).
Regarding instant claim 7, reference claim 1 discloses the limitations of instant claim 7 by using the sequence read having a highest mapping quality.
Regarding instant claim 8, the reference patent does not disclose the limitations of claim 8.
However, Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences and exact matches in the overlap (i.e., mapping quality) where the exact matches are expressed as a percentage of the overlap (for example, 50%, 66.66%, and 75%) (p. 347, Sensitivity).
Regarding instant claim 9, the reference patent does not disclose the limitation of claim 9.
However, Alcaide teaches counting the number of PCR families for generating a consensus sequence (p. 4, par. 2). Alcaide does not teach a minimum molecular count threshold for families when detecting a fusion.
However, Ion Reporter teaches a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions).
Regarding instant claim 10, the reference patent does not disclose the limitation of claim 10.
However, Ion Reporter teaches a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions).
Regarding instant claim 11, the reference patent does not disclose the limitation of claim 11.
However, Ion Reporter using five expression control calls that are built into the panel to (p. 352, par. 1). As Ion Reporter teaches reporting read counts aligned to specific expression control sequences (p. 348), it is considered that Ion Reporter fairly teaches the limitations of the claim regarding a control gene reference sequence.
Regarding instant claim 12, the reference patent does not disclose the limitation of claim 12.
However, Ion Reporter teaches a minimum read count threshold for detecting controls (p. 348).
Regarding instant claim 13, the reference patent does not disclose the limitation of claim 13.
However, Alcaide teaches the identification of several gene fusions, including a NUTM1-BRD4 gene fusion (i.e., an intergenic fusion) (p. 10, par. 1). Alcaide teaches that variant sequences, including the gene fusions, are stored in their reference of the targeted loci (p. 16, par. 2).
Regarding instant claim 14, the reference patent does not disclose the limitation of claim 14.
However, the prior art to Torres-Garcia discloses PRADA, a software platform for RNA-seq data analysis. Torres-Garcia teaches that the fusion module of PRADA aims to detect chimeric transcripts (p. 2224, col. 2, par. 4), with one variant developed to search for fusion transcripts involving two genes and one that searches for intragenic fusions (p. 2225, col. 1, par 2). Torres-Garcia teaches the detection of fusions by the construction of a sequence database that holds all possible exon-exon junctions that match the 3’ end of one gene fused to the 5’ end of a second gene (i.e., a targeted fusion reference sequence) (p. 2224, col. 2, par. 4). Torres-Garcia teaches only one method for identifying intragenic fusions, where transcripts are aligned to a database containing all possible exon-exon junctions. Although Torres-Garcia does not explicitly state that the database contains all possible exon-exon junctions within a same gene, it is considered that such a database must have been constructed to perform the identification of intragenic fusions. As Torres-Garcia teaches identifying intragenic fusions using a sequence database that holds all possible exon-exon junctions, it is considered that Torres-Garcia also fairly teaches the limitations of the claim regarding the targeted fusion reference sequence comprising a reference sequence for the fusion of two exons at a fusion breakpoint within a same gene.
Regarding instant claim 15, the reference patent does not disclose the limitation of claim 15.
Alcaide teaches Alcaide teaches counting the number of unique molecules (i.e., consensus sequence reads) supporting either mutant or wildtype alleles (p. 16, par. 1). As Alcaide teaches analyzing data supporting wildtype alleles, it is considered that Alcaide teaches alignment to a wild type reference sequence of the same gene.
However, Torres-Garcia teaches a module for detecting intragenic fusions (p. 2225, col. 1, par 2).
Regarding instant claim 16, the reference patent does not disclose the limitation of claim 16.
However, Alcaide teaches calculating the ratio of mutant versus wild-type DNA (p. 9, par. 3).
However, the prior art to Engreitz discloses a study examining how genomic loci that produce long non-coding RNAs influence the expression of neighboring loci (abstract). Engreitz teaches that for each modified allele, allele-specific measurements were normalized to the corresponding alleles in wild-type clones by dividing the value for knockout alleles by the mean of unmodified alleles in wild-type clones (p. 6, col. 2, par. 5).
Regarding instant claim 17, the reference patent does not disclose the limitation of claim 17.
However, Alcaide teaches calculating the ratio of mutant versus wild-type DNA (p. 9, par. 3). Alcaide SI shows this calculation involves a ratio of the mutant molecule count (i.e., consensus sequence reads) to the total molecule count (i.e., a sum of reads aligned to both the wild type reference sequences and the targeted fusion reference sequence for the same gene) (Table S2B). Alcaide does not teach detecting an intragenic fusion.
However, Torres-Garcia teaches a module for detecting intragenic fusions (p. 2225, col. 1, par 2).
Regarding instant claim 18, the reference patent does not disclose the limitation of claim 18.
However, Alcaide teaches that workflows that analyze sequencing data from enrichment experiments with large gene panels rely on essentially the same algorithm as their targeted method but differ by calling variants for non-reference alleles by searching across coding regions and splice donor/acceptor sites (p. 17, par. 3).
However, Torres-Garcia teaches that other RNA analysis tools such as Tophat-fusion and Defuse rely on alignments of partial reads to identify gene fusions (p. 2225, col. 2, par. 3).
Regarding instant claim 19, reference claim 1, limitation 5, discloses the limitations of instant claim 19.
Regarding claims 1-3, 5, 13, and 19, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the reference patent with Alcaide because both references are in the same field of endeavor. The motivation would have been to use a method which provides error-suppression based on consensus sequence generation using barcoded adapters, as taught by Alcaide (p. 2, par. 2).
Regarding claims 4 and 9-12, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide with Ion Torrent because each reference discloses methods for identifying variants with consensus sequences. The motivation would have been to set different levels of sensitivity and to perform quality control measurements of the data during fusion calls, as taught by Ion Reporter (p. 347 and p. 352).
Regarding claims 6-8, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide with Ion Torrent and Hovelson because each reference discloses methods for identifying variants with consensus sequences. The motivation would have been to set different levels of sensitivity and to perform quality control measurements of the data during fusion calls, as taught by Ion Reporter (p. 347 and p. 352). It would have been obvious to use the method of Hovelson for setting an alignment threshold to either side of the fusion breakpoint because Hovelson uses the Ion Reporter software in their analysis.
Regarding claims 14-15 and 18, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide for error correction and identification of targeted gene fusion sequencing data with the method of Torres-Garcia for identifying intragenic fusions and non-targeted fusions because all methods are in the same field of endeavor. The motivation would have been to perform multifaceted analysis of raw RNA-seq data (abstract) quickly, accurately, and comprehensively (p. 2224, col. 1, par. 1), as taught by Torres-Garcia.
Regarding claim 16, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide and Torres-Garcia for detecting targeted intragenic fusions from sequencing data with the method of Engreitz for dividing the value for knockout alleles by the mean of unmodified alleles because it would be desirable to calculate such a metric for comparing the read count levels of two different alleles. The motivation would have been to normalize the ratio of modified (i.e., mutant) alleles to unmodified (i.e., wild-type) alleles, as taught by Engreitz (p. 6, col. 2, par. 5).
Regarding claim 17, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide and Torres-Garcia for detecting targeted intragenic fusions from sequencing data with the method of Alcaide SI fusions because all methods are in the same field of endeavor. The motivation would have been to perform multifaceted analysis of raw RNA-seq data (abstract) quickly, accurately, and comprehensively (p. 2224, col. 1, par. 1), as taught by Torres-Garcia.
E. Claims 1-3, 5, 13, and 19 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 13-14 of U.S. Patent No. 12,243,626 (reference patent) in view of Alcaide et al. (Scientific Reports, 2017, 7(1), p. 1-19; cited on the Mar 11 2024 IDS). Claims 4 and 9-12 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 12,243,626 in view of Alcaide, as applied to claims 1 and 3, and in further view of Ion Reporter (ThermoFisher Scientific, 5.0 Software User Guide, MAN0013516 A.0, 1/12/2016, p. 1-406; cited on the Mar 11 2024 IDS). Claims 6-8 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 12,243,626 in view of Alcaide, as applied to claims 1 and 3, and in further view of Ion Reporter (ThermoFisher Scientific, 5.0 Software User Guide, MAN0013516 A.0, 1/12/2016, p. 1-406; cited on the Mar 11 2024 IDS) and Hovelson et al. (Neoplasia, 2015, 17(4), p. 385-399; SI (Supplementary Information), p. 1-82; cited on the Mar 11 2024 IDS). Claims 14-15 and 18 are rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 12,243,626 in view of Alcaide, as applied to claim 1 as described above, and in further view of Torres-Garcia et al. (Bioinformatics, 2014, 30, p. 2224-2226; cited on the Mar 11 2024 IDS). Claim 16 is rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 12,243,626 in view of Alcaide, as applied to claim 1, and Torres-Garcia, as applied to claims 14-15 as described above, and in further view of Engreitz et al. (Nature, 2016, 539, p. 1-19 as cited on the Mar 11 2024 IDS). Claim 17 rejected on the ground of nonstatutory double patenting as being unpatentable over U.S. Patent No. 12,243,626 in view of Alcaide, as applied to claim 1, and Torres-Garcia, as applied to claims 14-15 as described above, and in further view of Alcaide SI et al. (Scientific Reports, 2017, 7(1), Supplementary Information, p. 1-12; cited on the Mar 11 2024 IDS).
Regarding instant claim 1, reference claim 1 discloses the limitations of instant claim 1 except for a targeted fusion reference sequence in the 3rd limitation and detecting a fusion in the final limitation.
However, the prior art to Alcaide discloses a molecular barcoding method for the precise detection and quantification of circulating tumor DNA to quantify single-nucleotide variants, indels, and genomic rearrangements (abstract). Alcaide teaches mapping and aligning the consensus sequences from reads against the concatenated reference (p. 16, par. 3-4). Alcaide teaches generating ssDNA (single stranded DNA) and duplex consensus sequences (Figure 1 and p. 16, par. 3-4). Alcaide teaches using the ssDNA to call variants (Figure 1). As Alcaide teaches targeting SNVs and a gene fusion as described above, it is considered that Alcaide fairly teaches the limitation of the claim.
Regarding instant claim 2, reference claim 14 discloses the limitations of instant claim 2.
Regarding instant claims 3-4, reference claims 1 and 13 disclose the limitations of instant claims 3-4 because they disclose the use of mapping quality during consensus sequence determination as recited in claim 4. Regarding claim 4, the reference patent does not disclose a homology characteristic or a mapping quality characteristic.
However, the prior art to Ion Reporter discloses the user guide for the Ion ReporterTM Software for data analysis, annotation, and reporting of Ion Torrent semiconductor sequencing data (p. 8, par. 1). Ion Reporter teaches fusion analyses (p. 344-382). Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences (i.e., homology), exact matches in the overlap (i.e., mapping quality) (p. 347, Sensitivity), and a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions and p. 374).
Regarding instant claim 5, the reference patent does not disclose the limitation of claim 5.
However, Alcaide teaches identifying gene fusions (p. 9, par. 5 through p. 10, par. 1) with reads that align to the targeted reference database as described above (p. 16, par. 1). Alcaide teaches that on-target reads used for analysis are those that span targeted sites (i.e., a consensus sequence read spans a fusion breakpoint) (p. 4, par. 2).
Regarding instant claim 6, the reference patent does not disclose the limitation of claim 6.
However, the prior art to Ion Reporter discloses the user guide for the Ion ReporterTM Software for data analysis, annotation, and reporting of Ion Torrent semiconductor sequencing data (p. 8, par. 1). Ion Reporter teaches fusion analyses (p. 344-382). Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences (i.e., homology) (p. 347, Sensitivity).
However, the prior art to Hovelson discloses a catalog of relevant solid tumor somatic genome variants through comprehensive bioinformatics analysis of >700,000 samples (abstract). Hovelson SI teaches analyzing gene fusions with the Ion Reporter Fusion workflow by aligning AmpliSeq panel RNA reads to a gene reference of targeted chimeric fusion transcripts as well as reference sequences for expression imbalance and expression control gene targets (p. 5, par. 2). Hovelson SI teaches that read alignment required at least 70% overall homology to each side (i.e., a first and second partner sequence) of the fusion breakpoint (p. 5, par. 2).
Regarding instant claim 7, reference claim 1 discloses the limitations of instant claim 7 by using the sequence read having a highest mapping quality.
Regarding instant claim 8, the reference patent does not disclose the limitations of claim 8.
However, Ion Reporter teaches High, Medium, and Low threshold settings for overlap between reads and reference sequences and exact matches in the overlap (i.e., mapping quality) where the exact matches are expressed as a percentage of the overlap (for example, 50%, 66.66%, and 75%) (p. 347, Sensitivity).
Regarding instant claim 9, the reference patent does not disclose the limitation of claim 9.
However, Alcaide teaches counting the number of PCR families for generating a consensus sequence (p. 4, par. 2). Alcaide does not teach a minimum molecular count threshold for families when detecting a fusion.
However, Ion Reporter teaches a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions).
Regarding instant claim 10, the reference patent does not disclose the limitation of claim 10.
However, Ion Reporter teaches a minimum read count of valid reads aligned to a specific fusion isoform sequence (i.e., breakpoint spanning reads) (p. 347, Minimum Read Counts for Fusions).
Regarding instant claim 11, the reference patent does not disclose the limitation of claim 11.
However, Ion Reporter using five expression control calls that are built into the panel to (p. 352, par. 1). As Ion Reporter teaches reporting read counts aligned to specific expression control sequences (p. 348), it is considered that Ion Reporter fairly teaches the limitations of the claim regarding a control gene reference sequence.
Regarding instant claim 12, the reference patent does not disclose the limitation of claim 12.
However, Ion Reporter teaches a minimum read count threshold for detecting controls (p. 348).
Regarding instant claim 13, the reference patent does not disclose the limitation of claim 13.
However, Alcaide teaches the identification of several gene fusions, including a NUTM1-BRD4 gene fusion (i.e., an intergenic fusion) (p. 10, par. 1). Alcaide teaches that variant sequences, including the gene fusions, are stored in their reference of the targeted loci (p. 16, par. 2).
Regarding instant claim 14, the reference patent does not disclose the limitation of claim 14.
However, the prior art to Torres-Garcia discloses PRADA, a software platform for RNA-seq data analysis. Torres-Garcia teaches that the fusion module of PRADA aims to detect chimeric transcripts (p. 2224, col. 2, par. 4), with one variant developed to search for fusion transcripts involving two genes and one that searches for intragenic fusions (p. 2225, col. 1, par 2). Torres-Garcia teaches the detection of fusions by the construction of a sequence database that holds all possible exon-exon junctions that match the 3’ end of one gene fused to the 5’ end of a second gene (i.e., a targeted fusion reference sequence) (p. 2224, col. 2, par. 4). Torres-Garcia teaches only one method for identifying intragenic fusions, where transcripts are aligned to a database containing all possible exon-exon junctions. Although Torres-Garcia does not explicitly state that the database contains all possible exon-exon junctions within a same gene, it is considered that such a database must have been constructed to perform the identification of intragenic fusions. As Torres-Garcia teaches identifying intragenic fusions using a sequence database that holds all possible exon-exon junctions, it is considered that Torres-Garcia also fairly teaches the limitations of the claim regarding the targeted fusion reference sequence comprising a reference sequence for the fusion of two exons at a fusion breakpoint within a same gene.
Regarding instant claim 15, the reference patent does not disclose the limitation of claim 15.
Alcaide teaches Alcaide teaches counting the number of unique molecules (i.e., consensus sequence reads) supporting either mutant or wildtype alleles (p. 16, par. 1). As Alcaide teaches analyzing data supporting wildtype alleles, it is considered that Alcaide teaches alignment to a wild type reference sequence of the same gene.
However, Torres-Garcia teaches a module for detecting intragenic fusions (p. 2225, col. 1, par 2).
Regarding instant claim 16, the reference patent does not disclose the limitation of claim 16.
However, Alcaide teaches calculating the ratio of mutant versus wild-type DNA (p. 9, par. 3).
However, the prior art to Engreitz discloses a study examining how genomic loci that produce long non-coding RNAs influence the expression of neighboring loci (abstract). Engreitz teaches that for each modified allele, allele-specific measurements were normalized to the corresponding alleles in wild-type clones by dividing the value for knockout alleles by the mean of unmodified alleles in wild-type clones (p. 6, col. 2, par. 5).
Regarding instant claim 17, the reference patent does not disclose the limitation of claim 17.
However, Alcaide teaches calculating the ratio of mutant versus wild-type DNA (p. 9, par. 3). Alcaide SI shows this calculation involves a ratio of the mutant molecule count (i.e., consensus sequence reads) to the total molecule count (i.e., a sum of reads aligned to both the wild type reference sequences and the targeted fusion reference sequence for the same gene) (Table S2B). Alcaide does not teach detecting an intragenic fusion.
However, Torres-Garcia teaches a module for detecting intragenic fusions (p. 2225, col. 1, par 2).
Regarding instant claim 18, the reference patent does not disclose the limitation of claim 18.
However, Alcaide teaches that workflows that analyze sequencing data from enrichment experiments with large gene panels rely on essentially the same algorithm as their targeted method but differ by calling variants for non-reference alleles by searching across coding regions and splice donor/acceptor sites (p. 17, par. 3).
However, Torres-Garcia teaches that other RNA analysis tools such as Tophat-fusion and Defuse rely on alignments of partial reads to identify gene fusions (p. 2225, col. 2, par. 3).
Regarding instant claim 19, reference claim 1, limitation 5, discloses the limitations of instant claim 19.
Regarding claims 1-3, 5, 13, and 19, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the reference patent with Alcaide because both references are in the same field of endeavor. The motivation would have been to use a method which provides error-suppression based on consensus sequence generation using barcoded adapters, as taught by Alcaide (p. 2, par. 2).
Regarding claims 4 and 9-12, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide with Ion Torrent because each reference discloses methods for identifying variants with consensus sequences. The motivation would have been to set different levels of sensitivity and to perform quality control measurements of the data during fusion calls, as taught by Ion Reporter (p. 347 and p. 352).
Regarding claims 6-8, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide with Ion Torrent and Hovelson because each reference discloses methods for identifying variants with consensus sequences. The motivation would have been to set different levels of sensitivity and to perform quality control measurements of the data during fusion calls, as taught by Ion Reporter (p. 347 and p. 352). It would have been obvious to use the method of Hovelson for setting an alignment threshold to either side of the fusion breakpoint because Hovelson uses the Ion Reporter software in their analysis.
Regarding claims 14-15 and 18, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide for error correction and identification of targeted gene fusion sequencing data with the method of Torres-Garcia for identifying intragenic fusions and non-targeted fusions because all methods are in the same field of endeavor. The motivation would have been to perform multifaceted analysis of raw RNA-seq data (abstract) quickly, accurately, and comprehensively (p. 2224, col. 1, par. 1), as taught by Torres-Garcia.
Regarding claim 16, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide and Torres-Garcia for detecting targeted intragenic fusions from sequencing data with the method of Engreitz for dividing the value for knockout alleles by the mean of unmodified alleles because it would be desirable to calculate such a metric for comparing the read count levels of two different alleles. The motivation would have been to normalize the ratio of modified (i.e., mutant) alleles to unmodified (i.e., wild-type) alleles, as taught by Engreitz (p. 6, col. 2, par. 5).
Regarding claim 17, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the reference patent in view of Alcaide and Torres-Garcia for detecting targeted intragenic fusions from sequencing data with the method of Alcaide SI fusions because all methods are in the same field of endeavor. The motivation would have been to perform multifaceted analysis of raw RNA-seq data (abstract) quickly, accurately, and comprehensively (p. 2224, col. 1, par. 1), as taught by Torres-Garcia.
Conclusion
No claims are allowed.
Claims 19-20 appear to be free of the prior art. The closest prior art to Alcaide et al. (Scientific Reports, 2017, 7(1), p. 1-19) teaches a molecular barcoding method for the precise detection and quantification of circulating tumor DNA (abstract), where DNA is enriched, sequenced, and aligned to an artificial reference built from the concatenation of the targeted loci and their flanking sequences (p. 16, par. 1). Alcaide teaches generating consensus sequences for each PCR family (p. 3, Figure 1 legend and p. 16, par. 3) and mapping/aligning the consensus sequences from reads against an artificial reference built from the concatenation of the targeted loci and their flanking sequences (p. 16, par. 1-4), where the targeted loci include a gene fusion (p. 14, par. 2-3). Alcaide does not teach determining a consensus sequence alignment for each family of sequence reads, comprising selecting the sequence alignment having a highest mapping quality corresponding to the family of sequence reads and comparing the sequence read corresponding to the sequence alignment having the highest mapping quality to the consensus sequence read for the family.
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/J.N.S./Examiner, Art Unit 1685
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685 /DANIEL M SULLIVAN/Director, Art Unit 1600
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