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 .
Election/Restrictions
Upon further consideration the restriction dated 3/15/2024 is withdrawn. Pursuant to the procedures set forth in MPEP § 821.04(B), claims 303 and 304, previously withdrawn from consideration (in Applicant’s response received 10/17/2025) as a result of a restriction requirement, are hereby rejoined and fully examined for patentability under 37 CFR 1.104, as presented in the amended claims dated 4/15/2021.
Because all claims previously withdrawn from consideration under 37 CFR 1.142 have been rejoined, the restriction requirement as set forth in the Office action mailed on 3/15/2024 is hereby withdrawn. In view of the withdrawal of the restriction requirement as to the rejoined inventions, applicant(s) are advised that if any claim presented in a divisional application is anticipated by, or includes all the limitations of, a claim that is allowable in the present application, such claim may be subject to provisional statutory and/or nonstatutory double patenting rejections over the claims of the instant application. Once the restriction requirement is withdrawn, the provisions of 35 U.S.C. 121 are no longer applicable. See In re Ziegler, 443 F.2d 1211, 1215, 170 USPQ 129, 131-32 (CCPA 1971). See also MPEP § 804.01.
Status of Claims
Claims 1-9, 11-15, 17, 27-28, 39, 41-42, 44, 50, 57-60, 62-64, 66-69 and 303-304 are pending and examined on the merits.
Claims 10, 16, 18-26, 28-38, 40, 43, 45-49, 51-56, 61, 65, and 70-302 are cancelled.
Priority
The instant application filed on 10/23/2020 is a 371 national stage entry of PCT/US19/28916 having an international filing date of 4/24/2019, and claims the benefit of priority to provisional U.S. Application No. 62/662,198 filed on 4/24/2018. Thus, the effective filing date of the claims is 4/24/2018.
The applicant is reminded that amendments to the claims and specification must comply with 35 U.S.C. § 120 and 37 C.F.R. § 1.121 to maintain priority to an earlier-filed application. Claim amendments may impact the effective filing date if new subject matter is introduced that lacks support in the originally filed disclosure. If an amendment adds limitations that were not adequately described in the parent application, the claim may no longer be entitled to the priority date of the earlier filing.
Information Disclosure Statement
The information disclosure statement (IDS) filed on 6/7/2021 has been entered and considered. A signed copy of the corresponding 1449 form has been included with this Office action.
The IDS form filed on 3/1/2022 has been entered and considered. A signed copy of the
corresponding 1449 form with any deficiencies noted has been included with this Office action.
The information disclosure statement filed July 28, 2021 fails to comply with 37 CFR 1.98(a)(2),
which requires a legible copy of each cited foreign patent document; each non-patent literature
publication or that portion which caused it to be listed; and all other information or that portion which
caused it to be listed. It has been placed in the application file, but the information referred to therein
has not been considered. Specifically, there are missing NPL documents: B19 (Hassoun, 1995), and B20 (Hastie, 2001). Additionally, there are several NPL items provided with no title page indicating title or author, so these may be the missing NPL, however it is not clear due to the missing linking information in the provided documents. The following documents missing title pages begin with the following sections and/or page numbers: "5.3 Applications 243"; "264 5 Adaptive Multilayer Neural Networks I"; "6.1 Support Vector Classification 109"; and "9 Additive Models, Trees, and Related Methods".
The IDS form filed on 5/27/2022 has been entered and considered. A signed copy of the
corresponding 1449 form with any deficiencies noted has been included with this Office action.
The information disclosure statement filed July 28, 2021 fails to comply with 37 CFR 1.98(a)(2),
which requires a legible copy of each cited foreign patent document; each non-patent literature
publication or that portion which caused it to be listed; and all other information or that portion which
caused it to be listed. It has been placed in the application file, but the information referred to therein
has not been considered. Specifically, there are missing Foreign Patent Documents: Cite Numbers 1-4.
Finally, the listing of references in the specification is not a proper information disclosure statement. 37 CFR 1.98(b) requires a list of all patents, publications, or other information submitted for
consideration by the Office, and MPEP § 609.04(a) states, "the list may not be incorporated into the
specification but must be submitted in a separate paper." Therefore, unless the references have been
cited by the examiner on form PTO-892, they have not been considered.
Claim Objections
Claim 59 objected to because of the following informalities: line 10, "the using (c) deems the test subject" should read "the using (d) deems the test subject". Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-9, 11-15, 17, 27-28, 39, 41-42, 44, 50, 57-60, 62-64, 66-69 and 303-304 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 and 303-304 recite "using the set of amounts of sequence reads to determine whether the test subject has the cancer condition or a likelihood that the test subject has the cancer condition". It is not clear how the method is determining whether a subject has the cancer condition, or a likelihood of it, using the set of read counts per reference. Examiner notes that para.0015 of the instant specification discloses several approaches for said determination including setting cutoff values for a desired specificity, using a logistic regression classifier, or comparing distributions of healthy/cancer groups. To further prosecution, the limitation is interpreted as encompassing any of the embodiments disclosed in para.0015 of the instance specification.
Claim 4 recites "a measure of enrichment of the APOBEC induced mutational signature". It is not clear how the measure of enrichment is measured or calculated, whether it is from a wetlab enrichment procedure (targeted amplification), simply when more reads map to the mutational signature over a wildtype reference, or some population-level statistical value based on the distribution of the mutational signature within the population. Examiner notes that para.0310 of the instant specification discloses "the measure of enrichment of the first APOBEC induced mutational signature is in the form of a p-value against an amount of the first APOBEC induced mutational signature across a cohort of the species that does not have the cancer, the test subject is deemed to have the cancer condition or the likelihood of having the cancer condition when the p-value is in a threshold range, and the test subject is deemed to not have the cancer condition or the likelihood of having the cancer condition when the p-value is not in the threshold range", and para.340 discloses "the enrichment of the first APOBEC induced mutational signature is determined by comparing an expected amount of sequence reads for the APOBEC induced mutational signature to the measure of enrichment of the first APOBEC induced mutational signature". Therefore, to further prosecution, the limitation is interpreted as it is described in para.0310 or 340 of the specification.
Claim 6 recites "analyzing the first biological sample or a second biological sample from the test subject for an expression of an APOBEC protein". While claim 1 recites sequencing the cell-free nucleic acid in a sample, it does not specify what kind of nucleic acid isolation and sequencing is to be performed (DNA isolation with whole genome sequencing, targeted sequencing, bisulfite sequencing; or RNA isolation with whole transcriptome RNA-Seq, mRNA-Seq, single-cell RNA-Seq, etc.). The methods of claims 1-5 imply DNA isolation with whole genome sequencing, however claim 6 implies either a proteomics step involving measurement a protein level, or that some kind of RNA-Seq has been performed in order to detect gene expression. Examiner notes that para.0111 of the specification highlights "the terms "sequencing", "sequence determination," and the like as used herein refers generally to any and all biochemical processes that may be used to determine the order of biological macromolecules such as nucleic acids or proteins". However, claim 1 details a "cell -free nucleic acid" sample. Therefore, to further prosecution, claim 6 is interpreted broadly as having a separate sequencing step involving isolating and sequencing RNA from the cell-free nucleic acid sample.
Claims 9 recites "a corresponding targeted panel of sequences from the reference genome for the respective pathogen". There is a lack of antecedent basis for "the reference genome" or "the respective pathogen". To further prosecution, the limitation is interpreted as "a corresponding targeted panel of sequences from a reference genome of a respective pathogen".
Claim 68 recites "the method further comprises performing an end-point analysis of the corresponding amount of the plurality of sequence reads within the human genome, and the using (d) further uses the end-point analysis to determine whether the test subject has the cancer condition or a likelihood that the test subject has the cancer condition". It is not clear how these steps are used to "to determine whether the test subject has the cancer condition or a likelihood that the test subject has the cancer condition". The instant specification does not illuminate the matter, only referring to "block 318 of Figure 2K" of para.0276, however there are no further details about how this information is used in the determination. To further prosecution, this claim is interpreted as simply obtaining a sequence read count of mapped reads to the human genome because no further details are disclosed for how to determine whether the test subject has the cancer condition or a likelihood that the test subject has the cancer condition using said sequence read count.
All other claims depend from claim 1, therefore are also rejected under 35 U.S.C 112(b).
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 1-9, 11-15, 17, 27-28, 39, 41-42, 44, 50, 57-60, 62-64, 66-69 and 303-304 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of a mental process, a mathematical concept, organizing human activity, or a law of nature or natural phenomenon without significantly more. In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea:
Claims 1 and 303-304: “determining, for each respective pathogen in the set of pathogens, a corresponding amount of the plurality of sequence reads that map to a sequence in a pathogen target reference for the respective pathogen” provides a mathematical calculation (summing read counts per reference involves arithmetic) that is considered a mathematical concept, which is an abstract idea.
“using the set of amounts of sequence reads to determine whether the test subject has the cancer condition or a likelihood that the test subject has the cancer condition” provides an evaluation (determining an outcome using sequence data involves evaluating the data against a threshold or predetermined percentile of a distribution) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 2: “evaluating the plurality of sequence reads to obtain an indication as to whether an APOBEC induced mutational signature associated with a first pathogen in the set of pathogens is present or absent”
“using (d) uses the indication as to whether the APOBEC induced mutational signature associated with the first pathogen is present or absent along with the set of amounts of sequence reads to determine whether the test subject has the cancer condition or the likelihood that the test subject has the cancer condition”
Claim 3: “the evaluating is performed by k-mer analysis” provides a comparison (kmer matching involves comparisons) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 4: “a measure of enrichment of the APOBEC induced mutational signature” provides a mathematical calculation (calculating an enrichment score involves mathematical calculations) that is considered a mathematical concept, which is an abstract idea.
Claim 6: “analyzing the first biological sample or a second biological sample from the test subject for an expression of an APOBEC protein associated with a first pathogen in the set of pathogens” provides an evaluation (evaluating sequence reads for expression of a protein) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
“using (d) uses the expression of the APOBEC protein and the set of amounts of sequence reads to determine whether the test subject has the cancer condition or the likelihood that the test subject has the cancer condition” provides an evaluation (determining an outcome using sequence data involves evaluating the data against a threshold or predetermined percentile of a distribution) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 14: “determining a reference amount of sequence reads for a first pathogen in the set of pathogens associated with a predetermined percentile of a first distribution” provides a mathematical calculation (summing read counts per reference involves arithmetic) that is considered a mathematical concept, which is an abstract idea.
“the amount of sequence reads from the respective subject is a percentage of sequence reads measured from the respective subject that map to a sequence in the pathogen target reference for the first pathogen” provides a mathematical calculation (calculating percent reads mapping to a reference) that is considered a mathematical concept, which is an abstract idea.
“comparing (i) a first amount that is the amount of the plurality of sequence reads that map to a sequence in the pathogen target reference for the first pathogen from the test subject to (ii) a second amount that is the reference amount of sequence reads for the first pathogen in the set of pathogens associated with the predetermined percentile of the first distribution, wherein, when the first amount exceeds the second amount by a threshold amount the likelihood that the test subject has the cancer condition is adjusted or a determination is made that the test subject has the cancer condition” provides an evaluation (making a comparison to a threshold) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 15: “determining a reference amount of sequence reads for a first pathogen in the set of pathogens associated with a predetermined percentile of a first distribution” provides a mathematical calculation (determining a percentile cutoff value from a distribution involves statistical analysis which utilizes mathematical calculations) that is considered a mathematical concept, which is an abstract idea.
“thresholding the amount of the plurality of sequence reads that map to a sequence in the pathogen target reference for the first pathogen from the test subject by the reference amount of sequence reads for the first pathogen in the set of pathogens associated with the predetermined percentile of the first distribution to thereby form a scaled amount of the plurality of sequence reads, and comparing (i) the scaled amount of the plurality of sequence reads to (ii) a scaled amount of the plurality of sequence reads associated with a predetermined percentile of a second distribution, wherein each respective subject in a second cohort of subjects contributes to the second distribution a scaled amount of sequence reads from the respective subject” provides an evaluation (making a comparison to a threshold) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea. The limitation also provides a mathematical calculation (scaling is a normalization function involving mathematical calculations) that is considered a mathematical concept, which is an abstract idea. The limitation also provides a mathematical relationship (building a distribution) that is considered a mathematical concept, which is an abstract idea.
“the test subject is deemed to have the cancer condition or the likelihood that the test subject has the cancer condition when the scaled amount of the plurality of sequence reads from the test subject exceeds the scaled amount of plurality of sequence reads associated with the predetermined percentile of the second distribution by a first predetermined cutoff value” provides an evaluation (making a comparison to a threshold) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 27 and 28: “using (d) comprises using the amount of the APOBEC induced mutational signature and the set of amounts of sequence reads to determine whether the test subject has the cancer condition or the likelihood that the test subject has the cancer condition” provides an evaluation (determining an outcome using sequence data involves evaluating the data against a threshold or predetermined percentile of a distribution) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 57: “determining a first amount of the plurality of sequence reads that map to a sequence in a first pathogen target reference for the first pathogen” and “determining a second amount of the plurality of sequence reads that map to a sequence in a second pathogen target reference for the second pathogen” provides a mathematical calculation (summing read counts per reference involves arithmetic) that is considered a mathematical concept, which is an abstract idea.
“thresholding the first amount of the plurality of sequence reads from the test subject that map to a sequence in the first pathogen target reference by a first reference amount of sequence reads for the first pathogen associated with a first predetermined percentile of a first distribution to thereby form a scaled first amount of the plurality of sequence reads from the test subject, wherein each respective subject in a first cohort of subjects that do not have the cancer condition contributes to the first distribution an amount of sequence reads from the respective subject that map to a sequence in the first pathogen target reference for the first pathogen” and “thresholding the second amount of the plurality of sequence reads from the test subject that map to a sequence in the second pathogen target reference by a second reference amount of sequence reads for the second pathogen associated with a second predetermined percentile of a second distribution to thereby determine a scaled second amount of the plurality of sequence reads from the test subject, wherein each respective subject in a second cohort of subjects that do not have the cancer condition contributes to the second distribution an amount of sequence reads from the respective subject that map to a sequence in the second pathogen target reference for the second pathogen” provides an evaluation (determining an outcome using sequence data involves evaluating the data against a threshold or predetermined percentile of a distribution) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
“using (d) deems the test subject to have the cancer condition or a likelihood that the test subject has the cancer condition” provides an evaluation (determining an outcome using sequence data involves evaluating the data against a threshold or predetermined percentile of a distribution) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 58: “the logistic regression individually weights the scaled first amount based on an amount of sequence reads mapping to a sequence in the first pathogen target reference observed in a training cohort of subjects that includes subjects that have the cancer condition and subjects that do not have the cancer condition, and the logistic regression individually weights the scaled second amount based on an amount of sequence reads mapping to a sequence in the second pathogen target reference observed in the training cohort” provides a mathematical relationship (a relationship of amounts of reads in subject groups) that is considered a mathematical concept, which is an abstract idea.
Claim 59: “thresholding the corresponding amount of the plurality of sequence reads that map to a sequence in the pathogen target reference for the respective pathogen based on an amount of sequence reads associated with a predetermined percentile of a respective distribution, wherein each respective subject in a respective cohort of subjects that do not have the cancer condition contributes to the respective distribution an amount of sequence reads from the respective subject that map to a sequence in the pathogen target reference for the respective pathogen, thereby determining a scaled respective amount of the plurality of sequence reads from the test subject” provides an evaluation (making a comparison to a threshold) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea. The limitation also provides a mathematical relationship (building a distribution) that is considered a mathematical concept, which is an abstract idea. The limitation also provides a mathematical calculation (scaling is a normalization function involving mathematical calculations) that is considered a mathematical concept, which is an abstract idea.
“using (c) deems the test subject to have the cancer condition or the likelihood that the test subject has the cancer condition” provides an evaluation (determining an outcome using sequence data involves evaluating the data against a threshold or predetermined percentile of a distribution) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 60: “the classifier is based on a logistic regression algorithm that individually weights each scaled respective amount of the plurality of sequence reads based on a corresponding amount of sequence reads mapping to a sequence in the pathogen target reference of the corresponding pathogen observed in a training cohort of subjects that includes subjects that have the cancer condition and subjects that do not have the cancer condition” provides a mathematical relationship (a relationship of amounts of reads in subject groups) that is considered a mathematical concept, which is an abstract idea.
Claim 62: “the classifier is based on a logistic regression algorithm, a neural network algorithm, a support vector machine algorithm, or a decision tree algorithm that has been trained on a training cohort of subjects that includes subjects that have the cancer condition and subjects that do not have the cancer condition” provides a mathematical relationship (model training involving a relationship of amounts of reads in subject groups) that is considered a mathematical concept, which is an abstract idea.
Claim 63: “thresholding the corresponding amount of the plurality of sequence reads from the test subject that map to a sequence in the pathogen target reference for the respective pathogen on an amount of sequence reads associated with a predetermined percentile of a respective distribution, wherein each respective subject in a respective cohort of subjects that do not have the cancer condition contributes to the respective distribution an amount of sequence reads from the respective subject that map to a sequence in the pathogen target reference for the respective pathogen, thereby determining a scaled respective amount of the plurality of sequence reads from the test subject” provides an evaluation (making a comparison to a threshold) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea. The limitation also provides a mathematical relationship (building a distribution) that is considered a mathematical concept, which is an abstract idea. The limitation also provides a mathematical calculation (scaling is a normalization function involving mathematical calculations) that is considered a mathematical concept, which is an abstract idea.
“using (d) sums each scaled respective amount of the plurality of sequence reads from the test subject to determine an overall oncopathogen load” provides a mathematical calculation (summing involves arithmetic) that is considered a mathematical concept, which is an abstract idea.
“the using (d) indicates that the test subject has the cancer condition or the likelihood that the test subject has the cancer condition when the overall oncopathogen load satisfies a threshold cutoff condition” provides an evaluation (determining an outcome using sequence data involves evaluating the data against a threshold or predetermined percentile of a distribution) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 64: “using (d) calls the test subject as having the cancer condition or the likelihood that the test subject has the cancer condition when the set of amounts of sequence reads exceeds a threshold cutoff condition that is a predetermined specificity for overall oncopathogen load across the set of pathogens determined for a pool of subjects that do not have the cancer condition” provides an evaluation (determining an outcome using sequence data involves evaluating the data against a threshold or predetermined percentile of a distribution) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 66: “comparing the plurality of translated sequence reads to a translation of each sequence in the pathogen target reference” provides a comparison (comparing translated reads to a translated reference) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 67: “k-mer matching the plurality of sequence reads from the test subject to the pathogen target reference in nucleic acid, ribonucleic acid, or protein space” provides a comparison (kmer matching involves comparisons) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 68: “performing an end-point analysis of the corresponding amount of the plurality of sequence reads within the human genome” provides an evaluation (determining and evaluating the sequence reads that map to the human genome) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
“using (d) further uses the end-point analysis to determine whether the test subject has the cancer condition or a likelihood that the test subject has the cancer condition” provides an evaluation (determining an outcome involves evaluating data) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
These recitations are similar to the concepts of collecting information, analyzing it, and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016)), organizing and manipulating information through mathematical correlations in Digitech Image Techs., LLC v Electronics for Imaging, Inc. (758 F.3d 1344, 111 U.S.P.Q.2d 1717 (Fed. Cir. 2014)) and comparing information regarding a sample or test to a control or target data in Univ. of Utah Research Found. v. Ambry Genetics Corp. (774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014)) and Association for Molecular Pathology v. USPTO (689 F.3d 1303, 103 U.S.P.Q.2d 1681 (Fed. Cir. 2012)) that the courts have identified as concepts that can be practically performed in the human mind or are mathematical relationships. Therefore, these limitations fall under the “Mental process” and “Mathematical concepts” groupings of abstract ideas. Additionally, while claims 303 and 304 recite performing some aspects of the analysis on a “computer system comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the one or more programs including instructions” and “A non-transitory computer readable storage medium and one or more computer programs embedded therein for classification, the one or more computer programs comprising instructions which, when executed by a computer system, cause the computer system to perform a method”, there are no additional limitations that indicate that this requires anything other than carrying out the recited mental processes or mathematical concepts in a generic computer environment. Merely reciting that a mental process is being performed in a generic computer environment does not preclude the steps from being performed practically in the human mind or with pen and paper as claimed. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental processes” grouping of abstract ideas. As such, claims 1-9, 11-15, 17, 27-28, 39, 41-42, 44, 50, 57-60, 62-64, 66-69 and 303-304 recite an abstract idea (Step 2A, Prong 1: YES).
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). The judicial exceptions listed above are not integrated into a practical application because the claims do not recite an additional element or elements that reflects an improvement to technology. Specifically, the claims recite the following additional elements:
Claim 1: “obtaining a first biological sample from the test subject” provides insignificant extra-solution activities (obtaining samples is a pre-solution activity involving sample gathering and manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
“sequencing the cell-free nucleic acid in the first biological sample to generate a plurality of sequence reads from the test subject” provides insignificant extra-solution activities (obtaining sequence read data via sequencing a nucleic acid sample is a pre-solution activity involving data gathering and sample manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
“obtaining a set of amounts of sequence reads, each respective amount of sequence reads in the set of amounts of sequence reads for a corresponding pathogen in the set of pathogens” provides insignificant extra-solution activities (obtaining reference read counts via alignment is a pre-solution activity involving data gathering and manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
Claim 6: “a separate sequencing step involving isolating and sequencing RNA from the cell-free nucleic acid sample” (as interpreted above) provides insignificant extra-solution activities (obtaining sequence read data via sequencing a nucleic acid sample is a pre-solution activity involving data gathering and sample manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
Claims 9, 11, and 13: “the determining (c) limits, for the respective pathogen, the mapping of each sequence read in the plurality of sequence reads to the corresponding targeted panel of sequences from the reference genome of the respective pathogen, wherein the mapping comprises a sequence alignment between (i) one or more sequence reads in the plurality of sequence reads and (ii) a sequence in the pathogen target reference for the respective pathogen” (claim 9), “the determining (c) aligns, for the respective pathogen, each sequence read in the plurality of sequence reads using the entire reference genome of the respective pathogen” (claim 11), and “the determining (c) is performed for each respective pathogen in the plurality of pathogens” provides insignificant extra-solution activities (mapping sequence reads to references is a pre-solution activity involving data manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
Claims 14 and 15: “an amount of sequence reads from the respective subject that map to a sequence in the pathogen target reference for the first pathogen” and “map to a sequence in the pathogen target reference for the first pathogen” (claim 15 only) provides insignificant extra-solution activities (mapping sequence reads to references is a pre-solution activity involving data manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
Claim 17: “applying the set of amounts of sequence reads to a classifier to thereby determine either (1) whether the test subject has the cancer condition or (ii) the likelihood that test subject has the cancer condition” provides insignificant extra-solution activities (using a classification model is a pre-solution activity involving data manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
Claim 27: “performing an assay comprising measuring an amount of an APOBEC induced mutational signature of the cell-free nucleic acid in the first biological sample” provides insignificant extra-solution activities (performing an assay is a pre-solution activity involving sample manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
Claim 28: “obtaining a second biological sample from the test subject” provides insignificant extra-solution activities (obtaining samples is a pre-solution activity involving sample gathering and manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
“performing an assay comprising measuring an amount of an APOBEC induced mutational signature of the cell-free nucleic acid in the second biological sample” provides insignificant extra-solution activities (performing an assay is a pre-solution activity involving sample manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
Claim 57: “a classifier inputted with at least the scaled first amount and the scaled second amount indicates that the test subject has the cancer condition” provides insignificant extra-solution activities (using a classification model is a pre-solution activity involving data manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
Claim 59: “a classifier inputted with at least each scaled respective amount of the plurality of sequence reads from the test subject indicates that the test subject has the cancer condition” provides insignificant extra-solution activities (using a classification model is a pre-solution activity involving data manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
Claim 66: “translating the plurality of sequence reads from the test subject in a reading frame to form a plurality of translated sequence reads” provides insignificant extra-solution activities (translating nucleic acid sequences into protein sequences is a pre-solution activity involving data manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
Claim 69: “providing a therapeutic intervention or imaging of the test subject based on the determination of whether the test subject has the cancer condition or the likelihood that the test subject has the cancer condition” provides insignificant extra-solution activities (therapeutic intervention or imaging is a post-solution activity involving a mere field of use) that do not serve to integrate the judicial exceptions into a practical application.
Claims 303 and 304: “computer system comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the one or more programs including instructions” and “A non-transitory computer readable storage medium and one or more computer programs embedded therein for classification, the one or more computer programs comprising instructions which, when executed by a computer system, cause the computer system to perform a method” provides insignificant extra-solution activities (running instructions on generic computer components) that do not serve to integrate the judicial exceptions into a practical application.
The steps for obtaining and mapping data; inputting data into a classification model; and obtaining and sequencing or assaying samples are insignificant extra-solution activities that do not serve to integrate the recited judicial exceptions into a practical application because they are pre- and post-solution activities involving data gathering, data manipulation, and sample manipulation steps (see MPEP 2106.04(d)(2)). Additionally, the steps for providing therapy or imaging restricts use to a particular environment or application without adding significant innovation that does not serve to integrate the judicial exceptions into a practical application because they are post-solution activities involving a mere field of use (see MPEP 2106.04(d)(2) - Integration of a Judicial Exception Into A Practical Application; MPEP 2106.05(g) - Insignificant Extra-Solution Activity; and MPEP 2106.05(h) - Field of Use and Technological Environment). Furthermore, the limitations regarding implementing program instructions do not indicate that they require anything other than mere instructions to implement the abstract idea in a generic way or in a generic computing environment. As such, this limitation equates to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. Therefore, claims 1-9, 11-15, 17, 27-28, 39, 41-42, 44, 50, 57-60, 62-64, 66-69 and 303-304 are directed to an abstract idea (Step 2A, Prong 2: NO).
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that are insignificant extra-solution activities that do not serve to integrate the recited judicial exceptions into a practical application, or equate to mere instructions to apply the recited exception in a generic way or in a generic computing environment.
As discussed above, there are no additional elements to indicate that the claimed “computer system comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the one or more programs including instructions” and “A non-transitory computer readable storage medium and one or more computer programs embedded therein for classification, the one or more computer programs comprising instructions which, when executed by a computer system, cause the computer system to perform a method” requires anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. MPEP 2106.05(f) discloses that mere instructions to apply the judicial exception cannot provide an inventive concept to the claims. Additionally, the limitations for: providing therapy or imaging; obtaining and mapping data; inputting data into a classification model; and obtaining and sequencing or assaying samples are insignificant extra-solution activities that do not serve to integrate the recited judicial exceptions into a practical application. Furthermore, no inventive concept is claimed by these limitations as they are well-understood, routine, and conventional.
The additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, claims 1-9, 11-15, 17, 27-28, 39, 41-42, 44, 50, 57-60, 62-64, 66-69 and 303-304 are not patent eligible.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
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.
Claims 1-2, 6-9, 14-15, 17, 27-28, 39, 41, 44, 50, 57, 59, 63, 68-69, and 303-304 rejected under 35 U.S.C. 103 as being unpatentable over Diehn et al. (WO-2014151117) in view of Leal et al. (Leal et al. "Current and emerging molecular tests for human papillomavirus–related neoplasia in the genomic era." The Journal of Molecular Diagnostics 19.3 (2017): 366-377).
Regarding claim 1, Diehn teaches A method of screening for a cancer condition in a human test subject (Abstract "The methods can also be used for cancer screening, cancer diagnosis, cancer prognosis, and cancer therapy designation").
Diehn also teaches obtaining a first biological sample from the test subject, wherein the first biological sample comprises cell-free nucleic acid from the test subject and potentially cell-free nucleic acid from at least one pathogen in a set of pathogens, and sequencing the cell-free nucleic acid in the first biological sample to generate a plurality of sequence reads from the test subject, wherein each sequence read in the plurality of sequence reads uniquely represents a corresponding unique nucleic acid fragment in the first biological sample (Para.00468 "Provided herein are methods for the ultrasensitive detection of a minority nucleic acid in a heterogeneous sample. The method may comprise (a) obtaining sequence information of a cell-free DNA (cfDNA) sample derived from a subject; and (b) using sequence information derived from (a) to detect cell-free minority nucleic acids in the sample, wherein the method is capable of detecting a percentage of the cell-free minority nucleic acids that is less than 2% of total cfDNA. The minority nucleic acid may refer to a nucleic acid that originated from a cell or tissue that is different from a normal cell or tissue from the subject. For example, the subject may be infected with a pathogen such as a bacteria and the minority nucleic acid may be a nucleic acid from the pathogen").
Diehn also teaches determining an amount of the plurality of sequence reads (Para.00151 "Determining the quantity of the cell-free DNA may comprise determining absolute quantities of the cell-free DNA. The quantity of the cell-free DNA may be determined by counting sequencing reads pertaining to the cell-free DNA").
Diehn also teaches using the set of amounts of sequence reads to determine whether the test subject has the cancer condition or a likelihood that the test subject has the cancer condition (Para.0044 "Further disclosed herein are methods for detecting, diagnosing, prognosing, or therapy selection for a subject suffering from a disease or condition. The method may comprise: (a) obtaining sequence information of a cell-free DNA (cfDNA) sample derived from the subject; and (b) using sequence information derived from (a) to detect cell-free non-germline DNA (cfNG-DNA) in the sample, wherein the method may be capable of detecting a percentage of cfNG-DNA that may be less than 2% of total cfDNA" and para.00506 "A genomic region may comprise a recurrently mutated region. A recurrently mutated region may refer to a region of the genome, usually the human genome, in which there is an increased probability of genetic mutation in a cancer of interest, relative to the genome as a whole. A recurrently mutation region may refer to a region of the genome that contains one or more mutations that is recurrent in the population. For example, a recurrently mutation region may refer to a region of the genome that contains a mutation that is present in two or more subjects in a population. A recurrently mutated region may be characterized by a "Recurrence Index" (RI). The RI generally refers to the number of individual subjects (e.g., cancer patients) with a mutation that occurs within a given kilo base of genomic sequence ( e.g., number of patients with mutations/genomic region length in kb). A genomic region may also be characterized by the number of patients with a mutation per exon. Thresholds for each metric (e.g. RI and patients per exon or genomic region) may be selected to statistically enrich for known/suspected drivers of the cancer of interest. A known/suspected driver of the cancer of interest may be a gene. In non-small cell lung carcinoma (NSCLC), these metrics may enrich for known/suspected drivers (see genes listed in Table 2). Thresholds can also be selected by arbitrarily choosing the top percentile for each metric").
Diehn does not explicitly teach mapping reads to a pathogen reference.
However, Leal teaches aligning reads and interpreting the data for viral presence or other sequence variants (Page 8 Table 2 "Enrich for HPV genome and other gene regions of interest, add barcodes and adapters before sequencing, record signal as nucleotides are added during strand replication, call each nucleotide position, align reads to reference sequence, view aligned reads, interpret for viral presence and/or type and other sequence variants").
Therefore, it would have been obvious to one of ordinary skill in the art as of the effective filing date of the claimed invention to modify the methods of Diehn as taught by Leal in order to detect cancer early and/or monitor treatment efficacy (Diehn, para.0010 "PCT International Publication No. WO 2010/141955 A2 describes methods of detecting cancer by analyzing panels of genes from a patient-obtained sample and determining the mutational status of the genes in the panel", and Leal, page 10 col 1 paragraph 2 "Cell-free DNA assays for HPV DNA in plasma show promise as a noninvasive measure of HPVþ carcinoma burden, and work is underway to evaluate this approach to monitor treatment efficacy, to identify recurrence, and to enhance early cancer detection. [] A combinatorial approach is envisioned in which plasma is analyzed for viral DNA and for mutations common in carcinoma (eg, in PIK3CA). Sequencing panels permit broad and agnostic pathogen detection alongside human genomic characterization that seem important for exploring synergistic mechanisms of carcinogenesis involving infections (viruses, bacteria, fungi, parasites), host immune response polymorphisms, DNA damage markers of prior mutagen/microbe exposure, and DNA repair defects"). One skilled in the art would have a reasonable expectation of success because both approaches are concerned with detecting a cancer condition using cell-free DNA.
Regarding claim 2, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
evaluating the plurality of sequence reads to obtain an indication as to whether an APOBEC induced mutational signature associated with a first pathogen in the set of pathogens is present or absent (Page 1 abstract "Infected cancers share a similar mutation signature, reflecting the effect of apolipoprotein B mRNA-editing catalytic polypeptide enzyme DNA-editing enzymes. It is feasible that genomic tests for characteristic mutations or methylation signatures, along with tests for dysregulated HPV gene expression, add value in predicting behavior of premalignant lesions. Furthermore, these tumor markers in cell-free DNA of plasma or body fluids may one day assist in early detection or monitoring cancer burden during treatment").
Diehn also teaches the using (d) uses the indication as to whether the APOBEC induced mutational signature associated with the first pathogen is present or absent along with the set of amounts of sequence reads to determine whether the test subject has the cancer condition or the likelihood that the test subject has the cancer condition (Combined with Diehn para.00506, obvious to use APOBEC induced mutational signature with pathogen read counts for thresholding detection of a cancer condition).
Regarding claims 6 and 27-28, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Leal also teaches analyzing the first biological sample or a second biological sample from the test subject for an expression of an APOBEC protein associated with a first pathogen in the set of pathogens (Page 4 col 1 second to last paragraph "The best characterized member of the APOBEC family is activation-induced cytidine deaminase, which mediates B-cell somatic hypermutation and has known off target mutagenicity (eg, in MYC and BCL6).32,33 Interferon b up-regulates the expression of at least two APOBEC enzymes (3A and 3G) that induce mutations in single-stranded DNA (both human and viral)" demonstrates it is well-known that the expression of APOBEC is involved in oncogenesis, therefore is obvious to combine with Diehn for determining cancer condition).
Diehn also teaches the using (d) uses the expression of the APOBEC protein and the set of amounts of sequence reads to determine whether the test subject has the cancer condition or the likelihood that the test subject has the cancer condition (Combined with Diehn para.00506, obvious to use APOBEC induced mutational signature with pathogen read counts for thresholding detection of a cancer condition).
Regarding claim 7, Diehn in view of Leal teach the methods of Claim 6 on which this claim depends/these claims depend, respectively.
Leal also teaches the APOBEC protein is APOBEC1, APOBEC2, APOBEC3A, APOBEC3B, APOBEC3C, APOBEC3D, APOBEC3F, APOBEC3G, APOBEC3H, or APOBEC4 (Page 4 col 1 second to last paragraph "The best characterized member of the APOBEC family is activation-induced cytidine deaminase, which mediates B-cell somatic hypermutation and has known off-target mutagenicity (eg, in MYC and BCL6).32, 33 Interferon β up-regulates the expression of at least two APOBEC enzymes (3A and 3G) that induce mutations in single-stranded DNA (both human and viral)").
Regarding claim 8, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Diehn also teaches the sequencing (b) is performed by whole genome sequencing, targeted panel sequencing, or whole genome bisulfate sequencing (Para.00271 "Obtaining the genotype of the tumor in the subject may comprise conducting a sequencing reaction on a sample from the subject. Sequencing may comprise whole genome sequencing. Sequencing may comprise whole exome sequencing").
Regarding claim 9, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Leal also teaches the pathogen target reference for the respective pathogen consists of a corresponding targeted panel of sequences from a reference genome of a respective pathogen and the determining (c) limits, for the respective pathogen, the mapping of each sequence read in the plurality of sequence reads to the corresponding targeted panel of sequences from the reference genome of the respective pathogen, wherein the mapping comprises a sequence alignment between (i) one or more sequence reads in the plurality of sequence reads and (ii) a sequence in the pathogen target reference for the respective pathogen (Page 8 Table 2 "Enrich for HPV genome and other gene regions of interest, add barcodes and adapters before sequencing, record signal as nucleotides are added during strand replication, call each nucleotide position, align reads to reference sequence, view aligned reads, interpret for viral presence and/or type and other sequence variants").
Regarding claims 14 and 15, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Diehn also teaches determining a reference amount of sequence reads for a first pathogen in the set of pathogens associated with a predetermined percentile of a first distribution, wherein each respective subject in a first cohort of at least twenty subjects contributes to the first distribution an amount of sequence reads from the respective subject that map to a sequence in the pathogen target reference for the first pathogen, wherein the amount of sequence reads from the respective subject is a percentage of sequence reads measured from the respective subject that map to a sequence in the pathogen target reference for the first pathogen, and each subject in a first portion of the first cohort of subjects has the cancer condition, and each subject in a second portion of the first cohort of subjects does not have the cancer condition (Para.0579 "A typical database for this purpose may include sequence information from at least 25, at least 50, at least 100, at least 200, at least 300 or more individual tumors", and also details producing a "selector set" in para.0578-593, wherein the method involves utilizing a recurrence index (RI) derived from number of patients that cover particular SNVs or other mutations.
Diehn also teaches comparing (i) a first amount that is the amount of the plurality of sequence reads that map to a sequence in the pathogen target reference for the first pathogen from the test subject to (ii) a second amount that is the reference amount of sequence reads for the first pathogen in the set of pathogens associated with the predetermined percentile of the first distribution, wherein, when the first amount exceeds the second amount by a threshold amount the likelihood that the test subject has the cancer condition is adjusted or a determination is made that the test subject has the cancer condition (Para.0584 "Maximizing the median number of mutations per subject may comprise use of one or more thresholds or filters to evaluate the genomic regions for inclusion in the selector set. The thresholds or filters may be based on the recurrence index. For example, the filter may be a percentile filter of the recurrence index. The percentile filters may be relaxed to permit the assessment of additional genomic regions for inclusion in the selector set. The percentile filter may be set at (2/3) x P, where P is a top percentile of RI. The threshold may be user-defined. The threshold may be greater than or equal to 2/3. Alternatively, the threshold is less than or equal to 2/3. P may also be user-defined. The algorithm may proceed through the list of genomic regions ranked by decreasing RI, iteratively adding regions that maximally increase the median number of mutations per subject").
Regarding claim 15 specifically, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Diehn also teaches the test subject is deemed to have the cancer condition or the likelihood that the test subject has the cancer condition when the scaled amount of the plurality of sequence reads from the test subject exceeds the scaled amount of plurality of sequence reads associated with the predetermined percentile of the second distribution by a first predetermined cutoff value (Para.0603-609 discusses detection of ctDNA [circulating tumor DNA] which is indicative of a cancer condition, using percentile thresholding of groups with and without particular SNVs).
Regarding claim 17, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Diehn also teaches the using (d) comprises: applying the set of amounts of sequence reads to a classifier to thereby determine either (1) whether the test subject has the cancer condition or (ii) the likelihood that test subject has the cancer condition (Para.00258 "The selector set may be used to classify one or more samples from one or more subjects. The selector set may be used to classify two or more samples from two or more subjects. The selector set may be used to classify a plurality of samples from 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 or more subjects").
Regarding claims 28 and 39, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Diehn also teaches obtaining a second biological sample from the test subject, wherein the second biological sample comprises cell-free nucleic acid from the test subject and potentially cell-free nucleic acid from a first pathogen in the set of pathogens (Para.00738 "In some embodiments, the ctDNA content in an individual's blood, or blood derivative, sample is determined at one or more time points, optionally in conjunction with a therapeutic Regimen" demonstrates multiple samples taken from the same subject over time).
Regarding claim 41, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Leal also teaches a respective pathogen in the set of pathogens is Epstein-Barr virus (EBV), human cytomegalovirus (HCMYV), hepatitis B virus (HBV), hepatitis C virus (HCV), human herpes virus (HHV), human mammary tumor virus (HMTV), human papillomavirus 16 (HPV16), human papillomavirus 18 (HPV18), human papillomavirus 60 (HPV-60), human papillomavirus ZM130 (HPV8-ZM 130), human T-cell leukemia virus type 1 (HTLV-1), John Cunningham virus (JCV), molluscum contagiosum virus (MCV), or simian vacuolating virus 40 (SV40) (Page 9 col 1 paragraph 2 "Testing for HPV and Epstein-Barr virus in squamous carcinoma of unknown primary can assist in determining the site of origin and in weighing radiotherapy options").
Regarding claim 44, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Leal also teaches the set of pathogens comprises any combination of human herpes virus 5 CINCY-TOWNE (HHV5-CINC Y-TOWNE) virus, Epstein-Barr B95-8 (EBV-B95-8 virus), molluscum contagiosum virus R17b (MCV-R17b) virus, human papillomavirus 16 (HPV 16) virus, human cytomegalovirus AD169 (HCMV- AD 169) virus, hepatitis B virus (HBV) virus, hepatitis B virus 18 (HPV18) virus, hepatitis C virus (HCV) virus, human papillomavirus 8-ZM130 (HPV8-ZM130) virus, and John Cunningham virus PLYCG (JCV-PLYCG) virus (Page 8 table 2 "Same as above except oligomer targets unspecified viral mRNA, chemiluminescent probes bind HPV16, 18, and 45").
Regarding claim 50, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Diehn also teaches the corresponding amount of the plurality of sequence reads that map to a sequence in the pathogen target reference for the respective pathogen is a percentage of the plurality of sequence reads from the test subject (Para.00468 "the method is capable of detecting a percentage of the cell-free minority nucleic acids that is less than 2% of total cfDNA. The minority nucleic acid may refer to a nucleic acid that originated from a cell or tissue that is different from a normal cell or tissue from the subject. For example, the subject may be infected with a pathogen such as a bacteria and the minority nucleic acid may be a nucleic acid from the pathogen").
Regarding claims 57 and 59, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Diehn also teaches the limitations of these claims, which have significant overlap with claims 13 and 14. By extending the teaching of Diehn cited for claim 14 to a plurality of pathogens from claim 13, as well as the classifier (selector set) from claim 17, the limitations of claims 57 and 59 are taught.
Regarding claim 63, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Diehn also teaches the thresholding limitations as cited for claim 14. Diehn also teaches the using (d) sums each scaled respective amount of the plurality of sequence reads from the test subject to determine an overall oncopathogen load, wherein the using (d) indicates that the test subject has the cancer condition or the likelihood that the test subject has the cancer condition when the overall oncopathogen load satisfies a threshold cutoff condition (Para.00713 "For two or more genomic regions, the quantity of the ctDNA may be a sum of the quantity of the two or more genomic regions", and para.0603-609 discusses detection of ctDNA (circulating tumor DNA) which is indicative of a cancer condition, using percentile thresholding of groups with and without particular SNVs).
Regarding claim 68, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Diehn also teaches performing an end-point analysis by obtaining a sequence read count of mapped reads to the human genome (as interpreted above) (Para.00790 "Paired-end reads were mapped to the hg19 reference genome with BWA 0.6.2 (default parameters), and sorted/indexed with SAMtools. QC was assessed using a custom Perl script to collect a variety of statistics, including mapping characteristics, read quality, and selector on-target rate (e.g., number of unique reads that intersect the selector space divided by all aligned reads), generated respectively by SAMtools flagstat, FastQC, and BEDTools coverageBed, modified to count each read at most once").
Regarding claim 69, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Diehn also teaches the method further comprising: (e) providing a therapeutic intervention or imaging of the test subject based on the determination of whether the test subject has the cancer condition or the likelihood that the test subject has the cancer condition (Para.00879 "Example 5. Use of a selector set to determine a therapeutic regimen for the treatment of a cancer").
Claims 3 and 66-67 rejected under 35 U.S.C. 103 as being unpatentable over Diehn et al. (WO-2014151117) in view of Leal et al. (Leal et al. "Current and emerging molecular tests for human papillomavirus–related neoplasia in the genomic era." The Journal of Molecular Diagnostics 19.3 (2017): 366-377) as applied to claims 1-2, 6-9, 14-15, 17, 27-28, 39, 41, 44, 50, 57, 59, 63, 68-69, and 303-304 above, and further in view of Pettengill et al. (Pettengill et al. "Real-time pathogen detection in the era of whole-genome sequencing and big data: comparison of k-mer and site-based methods for inferring the genetic distances among tens of thousands of Salmonella samples." PLoS One 11.11 (2016): e0166162).
Diehn et al. in view of Leal et al. are applied to claims 1-2, 6-9, 14-15, 17, 27-28, 39, 41, 44, 50, 57, 59, 63, 68-69, and 303-304.
Regarding claim 3, Diehn in view of Leal teach the method of Claim 2 on which this claim depends/these claims depend.
Diehn nor Leal explicitly teach the evaluating is performed by k-mer analysis.
However, Pettengill teaches the evaluating is performed by k-mer analysis (Page 2 paragraph 3 "we assess the efficacy of seven genetic distances (calculated from either k-mer profiles or nucleotide site differences) for accurately estimating the similarity among a diverse set of samples based on WGS data").
Therefore, it would have been obvious to one of ordinary skill in the art as of the effective filing date of the claimed invention to modify the methods of Diehn and Leal as taught by Pettengill in order to better discriminate among pathogens (page 1 last paragraph "Whole-genome sequence (WGS) data provides a powerful means to discriminate among bacterial pathogens at a resolution not possible with other methods"). One skilled in the art would have a reasonable expectation of success because both approaches are using sequence data for identifying pathogens.
Regarding claim 66, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Pettengill also teaches the determining a corresponding amount of the plurality of sequence reads that map to a sequence in the pathogen target reference for the respective pathogen comprises translating the plurality of sequence reads from the test subject in a reading frame to form a plurality of translated sequence reads and comparing the plurality of translated sequence reads to a translation of each sequence in the pathogen target reference ("Using BLAST to identify members of the core genome that reliably “hit” orthologs during both nucleotide and protein sequence bidirectional searches, we identified a total of 1,152 loci that are amenable to automated analyses").
Regarding claim 67, Diehn in view of Leal teach the methods of Claim 1 on which this claim depends/these claims depend, respectively.
Pettengill also teaches the determining a corresponding amount of the plurality of sequence reads that map to a sequence in the pathogen target reference for the respective pathogen comprises k-mer matching the plurality of sequence reads from the test subject to the pathogen target reference in nucleic acid, ribonucleic acid, or protein space (Page 2 paragraph 3 "we assess the efficacy of seven genetic distances (calculated from either k-mer profiles or nucleotide site differences) for accurately estimating the similarity among a diverse set of samples based on WGS data", calculating genetic distance with k-mers involves k-mer matching between a query and reference sequence).
Claims 4-5 rejected under 35 U.S.C. 103 as being unpatentable over Diehn et al. (WO-2014151117) in view of Leal et al. (Leal et al. "Current and emerging molecular tests for human papillomavirus–related neoplasia in the genomic era." The Journal of Molecular Diagnostics 19.3 (2017): 366-377) as applied to claims 1-2, 6-9, 14-15, 17, 27-28, 39, 41, 44, 50, 57, 59, 63, 68-69, and 303-304 above, and further in view of Alexandrov et al. (Alexandrov et al. "Signatures of mutational processes in human cancer." nature 500.7463 (2013): 415-421).
Diehn et al. in view of Leal et al. are applied to claims 1-2, 6-9, 14-15, 17, 27-28, 39, 41, 44, 50, 57, 59, 63, 68-69, and 303-304.
Regarding claims 4 and 5, Diehn in view of Leal teach the method of Claim 2 on which this claim depends/these claims depend.
Diehn nor Leal explicitly teach the indication as to whether the APOBEC induced mutational signature associated with the first pathogen is present or absent comprises a measure of enrichment of the APOBEC induced mutational signature (as interpreted above, the enrichment of the first APOBEC induced mutational signature is determined by comparing an expected amount of sequence reads for the APOBEC induced mutational signature to the measure of enrichment of the first APOBEC induced mutational signature).
However, Alexandrov teaches measuring enrichment of the APOBEC type 2 and 13 mutational signatures (Page 5 col 2 paragraph 3 "Foci of localized substitution hypermutation, termed kataegis after the Greek for thunderstorm, were recently described in breast cancer. Kataegis is characterized by clusters of C.T and/or C.G mutations which are substantially enriched at TpCpN trinucleotides and on the same DNA strand. Foci of kataegis include from a few to several thousand mutations and are often found in the vicinity of genomic rearrangements. The genomic regions affected are different in different cancers. On the basis of the substitution types and sequence context of kataegis substitutions, an underlying role for APOBEC family enzymes was proposed for kataegis as well as for signatures 2 and 13").
Therefore, it would have been obvious to one of ordinary skill in the art as of the effective filing date of the claimed invention to modify the methods of Diehn and Leal as taught by Alexandrov in order to identify the origins of somatic mutations and the processes underlying the development of cancer which have implications for cancer prevention and therapy (Abstract "All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. []. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy". One skilled in the art would have a reasonable expectation of success because Alexandrov hypothesizes that APOBEC mutational signatures as potentially caused by collateral damage from innate immune response to viral infection, leading to certain cancers (Page 5 col 1 last paragraph "Because APOBEC activation constitutes part of the innate immune response to viruses and retrotransposons22 it may be that these mutational signatures represent collateral damage on the human genome from a response originally directed at retro-transposing DNA elements or exogenous viruses. Confirmation of this hypothesis would establish an important new mechanism for initiation of human carcinogenesis"), and Diehn proposes using mutational signatures in sequencing data for detecting cancer (Diehn, para.0010 "PCT International Publication No. WO 2010/141955 A2 describes methods of detecting cancer by analyzing panels of genes from a patient-obtained sample and determining the mutational status of the genes in the panel").
Claims 11-13 and 42 rejected under 35 U.S.C. 103 as being unpatentable over Diehn et al. (WO-2014151117) in view of Leal et al. (Leal et al. "Current and emerging molecular tests for human papillomavirus–related neoplasia in the genomic era." The Journal of Molecular Diagnostics 19.3 (2017): 366-377) as applied to claims 1-2, 6-9, 14-15, 17, 27-28, 39, 41, 44, 50, 57, 59, 63, 68-69, and 303-304 above, and further in view of Brister et al. (Brister et al. "NCBI viral genomes resource." Nucleic acids research 43.D1 (2015): D571-D577).
Diehn et al. in view of Leal et al. are applied to claims 1-2, 6-9, 14-15, 17, 27-28, 39, 41, 44, 50, 57, 59, 63, 68-69, and 303-304.
Regarding claims 11-13 and 42, Diehn in view of Leal teach the method of Claim 1 on which this claim depends/these claims depend.
Diehn nor Leal explicitly teach the specific type of database used for the mapping and counting methods described above.
However, Brister teaches using RefSeq viral database which contains the full genome sequence(s) of one or more viruses (Page 3 col 1 first paragraph "Reviewed viral RefSeq records can be retrieved from the Entrez Nucleotide database").
Therefore, it would have been obvious to one of ordinary skill in the art as of the effective filing date of the claimed invention to modify the methods of Diehn and Leal as taught by Brister in order to detect pathogens (page 1 col 2 first paragraph "reference databases provide curated datasets that enable a number of activities, among them are transfer annotation to related genomes (11–13), sequence assembly and virus discovery (14–17), viral dynamics and evolution (18–20) and pathogen detection". One skilled in the art would have a reasonable expectation of success because a person having ordinary skill in the art would naturally rely on NCBI's refseq databases (specifically viral database) for alignment of sequence reads to a desired genomic reference sequence.
Claims 58, 60, and 62 rejected under 35 U.S.C. 103 as being unpatentable over Diehn et al. (WO-2014151117) in view of Leal et al. (Leal et al. "Current and emerging molecular tests for human papillomavirus–related neoplasia in the genomic era." The Journal of Molecular Diagnostics 19.3 (2017): 366-377) as applied to claims 1-2, 6-9, 14-15, 17, 27-28, 39, 41, 44, 50, 57, 59, 63, 68-69, and 303-304 above, and further in view of Choi et al. (Choi et al. "Evaluation of logistic regression models and effect of covariates for case–control study in rna-seq analysis." BMC bioinformatics 18.1 (2017): 91).
Diehn et al. in view of Leal et al. are applied to claims 1-2, 6-9, 14-15, 17, 27-28, 39, 41, 44, 50, 57, 59, 63, 68-69, and 303-304.
Regarding claims 58, 60, and 62, Diehn in view of Leal teach the method of Claim 57 on which this claim depends/these claims depend.
Diehn nor Leal explicitly teach a classifier based on a logistic regression algorithm that individually weights scaled quantities of mapped reads between condition-control cohorts.
However, Choi teaches applying logistic regression models to read count data (Page 1 Abstract Conclusions "We conclude that implementing the data adaptive method appropriately controls Type-I error rates in RNA-Seq analysis. Firth’s logistic regression provides a concise statistical inference process and reduces spurious associations from inaccurately estimated dispersion parameters in the negative binomial framework" and page 9 col 2 paragraph 3 "In this study, we propose using a logistic regression framework as an alternative to NB regression to analyze RNA-Seq data for case–control studies", demonstrates that logistic regression models are utilized for detection of differentially expressed genes in RNA-Seq experiments for case-control studies. It would be obvious to use this approach for classifying a cancer condition using mapped read counts).
Therefore, it would have been obvious to one of ordinary skill in the art as of the effective filing date of the claimed invention to modify the methods of Diehn and Leal as taught by Choi in order to detect various forms of cancer (page 11 col 1 paragraph 1 "Several studies showed evidence of associations with prostate, colon, and breast cancer and bronchopulmonary dysplasia"). One skilled in the art would have a reasonable expectation of success because both approaches are concerned with analyzing sequence read data in case-control studies.
Claim 64 rejected under 35 U.S.C. 103 as being unpatentable over Diehn et al. (WO-2014151117) in view of Leal et al. (Leal et al. "Current and emerging molecular tests for human papillomavirus–related neoplasia in the genomic era." The Journal of Molecular Diagnostics 19.3 (2017): 366-377) as applied to claims 1-2, 6-9, 14-15, 17, 27-28, 39, 41, 44, 50, 57, 59, 63, 68-69, and 303-304 above, and further in view of Flores-Munguia et al. (Flores-Munguia et al. "Performance assessment of eight high-throughput PCR assays for viral load quantitation of oncogenic HPV types." The Journal of Molecular Diagnostics 6.2 (2004): 115-124).
Diehn et al. in view of Leal et al. are applied to claims 1-2, 6-9, 14-15, 17, 27-28, 39, 41, 44, 50, 57, 59, 63, 68-69, and 303-304.
Regarding claim 64, Diehn in view of Leal teach the method of Claim 1 on which this claim depends/these claims depend.
Diehn nor Leal explicitly teach the using (d) calls the test subject as having the cancer condition or the likelihood that the test subject has the cancer condition when the set of amounts of sequence reads exceeds a threshold cutoff condition that is a predetermined specificity for overall oncopathogen load across the set of pathogens determined for a pool of subjects that do not have the cancer condition.
However, Flores-Munguia teaches the using (d) calls the test subject as having the cancer condition or the likelihood that the test subject has the cancer condition when the set of amounts of sequence reads exceeds a threshold cutoff condition that is a predetermined specificity for overall oncopathogen load across the set of pathogens determined for a pool of subjects that do not have the cancer condition (Page 3 col 2 paragraph 2 "Eight points for each standard curve covering a dynamic range from 100 to 107 were run in triplicate along with non-template controls to set the threshold value"). Although Flores-Munguia et al. do not specifically use sequence read counts, the method is very similar to determining PCR thresholding values.
Therefore, it would have been obvious to one of ordinary skill in the art as of the effective filing date of the claimed invention to modify the sequence data methods of Diehn and Leal with the PCR based methods as taught by Flores-Munguia in order to determine a viral load of HPV types (page 1 abstract "The purpose of the present study was to evaluate a methodology to determine HPV viral load of eight oncogenic HPV types (16, 18, 31, 39, 45, 51, 52, and 58)"). One skilled in the art would have a reasonable expectation of success because both approaches concerned with applying data from hard-to-detect pathogens to cancer risk.
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.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-9, 11-15, 17, 27-28, 39, 41-42, 44, 50, 57-60, 62-64, 66-69 and 303-304 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 115 and 135 of US patent 11869661 in view of Leal et al. (Leal et al. "Current and emerging molecular tests for human papillomavirus–related neoplasia in the genomic era." The Journal of Molecular Diagnostics 19.3 (2017): 366-377). Although the claims at issue are not identical, they are not patentably distinct from each other because both involve screening for a cancer condition, obtaining sequence data pertaining to one or more biological samples, sequencing the samples, and determining whether a cancer condition is present based on the sequencing data.
While US patent 11869661 does not explicitly teach using cell-free DNA or mapping reads of pathogens that may also be in the biological samples to pathogen reference genomes, it would have been obvious to one of ordinary skill in the art to modify these methods, with those taught by Leal as described above for claim 1 of the instant application, in order to use cell-free DNA to detect pathogens in the cell-free sample (Page 9 col 2 paragraph 1 “Analysis of cell-free tumor DNA in blood or saliva may help identify metastasis or local tumor recurrence” and page 8 Table 2 "Enrich for HPV genome and other gene regions of interest, add barcodes and adapters before sequencing, record signal as nucleotides are added during strand replication, call each nucleotide position, align reads to reference sequence, view aligned reads, interpret for viral presence and/or type and other sequence variants"). One skilled in the art would have a reasonable expectation of success because both approaches are concerned with detecting a cancer condition using sequencing data.
Claims 1-9, 11-15, 17, 27-28, 39, 41-42, 44, 50, 57-60, 62-64, 66-69 and 303-304 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 86, and 92 of US patent 11482303 in view of Leal et al. (Leal et al. "Current and emerging molecular tests for human papillomavirus–related neoplasia in the genomic era." The Journal of Molecular Diagnostics 19.3 (2017): 366-377). Although the claims at issue are not identical, they are not patentably distinct from each other because both involve screening for a cancer condition, obtaining sequence data pertaining to one or more biological samples, sequencing the samples, and determining whether a cancer condition is present based on the sequencing data.
While US patent 11482303 does not explicitly teach using cell-free DNA or mapping reads of pathogens that may also be in the biological samples to pathogen reference genomes, it would have been obvious to one of ordinary skill in the art to modify these methods, with those taught by Leal as described above for claim 1 of the instant application, in order to use cell-free DNA to detect pathogens in the cell-free sample (Page 9 col 2 paragraph 1 “Analysis of cell-free tumor DNA in blood or saliva may help identify metastasis or local tumor recurrence” and page 8 Table 2 "Enrich for HPV genome and other gene regions of interest, add barcodes and adapters before sequencing, record signal as nucleotides are added during strand replication, call each nucleotide position, align reads to reference sequence, view aligned reads, interpret for viral presence and/or type and other sequence variants"). One skilled in the art would have a reasonable expectation of success because both approaches are concerned with detecting a cancer condition using sequencing data.
Claims 1-9, 11-15, 17, 27-28, 39, 41-42, 44, 50, 57-60, 62-64, 66-69 and 303-304 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 13, and 14 of US patent 12049672 in view of Leal et al. (Leal et al. "Current and emerging molecular tests for human papillomavirus–related neoplasia in the genomic era." The Journal of Molecular Diagnostics 19.3 (2017): 366-377). Although the claims at issue are not identical, they are not patentably distinct from each other because both involve screening for a cancer condition using cell-free DNA, obtaining sequence data pertaining to one or more biological samples, sequencing the samples, and determining whether a cancer condition is present based on the sequencing data.
While US patent 12049672 does not explicitly teach mapping reads of pathogens that may also be in the biological samples to pathogen reference genomes, it would have been obvious to one of ordinary skill in the art to modify these methods, with those taught by Leal as described above for claim 1 of the instant application, in order to use cell-free DNA to detect pathogens in the cell-free sample (page 8 Table 2 "Enrich for HPV genome and other gene regions of interest, add barcodes and adapters before sequencing, record signal as nucleotides are added during strand replication, call each nucleotide position, align reads to reference sequence, view aligned reads, interpret for viral presence and/or type and other sequence variants"). One skilled in the art would have a reasonable expectation of success because both approaches are concerned with detecting a cancer condition using sequencing data.
Claims 1-9, 11-15, 17, 27-28, 39, 41-42, 44, 50, 57-60, 62-64, 66-69 and 303-304 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 36, and 45 of US patent 11479825 in view of Diehn et al. (WO-2014151117). Although the claims at issue are not identical, they are not patentably distinct from each other because both involve screening for a pathogen using cell-free DNA, obtaining sequence data pertaining to one or more biological samples, sequencing the samples, and mapping the sequence reads to pathogen reference genomes.
While US patent 11479825 does not explicitly teach determining a cancer condition based on the sequence data, it would have been obvious to one of ordinary skill in the art to modify these methods, with those taught by Diehn as described above for claim 1 of the instant application, in order to detect cancer early and/or monitor treatment efficacy (Diehn, para.0010 "PCT International Publication No. WO 2010/141955 A2 describes methods of detecting cancer by analyzing panels of genes from a patient-obtained sample and determining the mutational status of the genes in the panel", and Leal, page 10 col 1 paragraph 2 "Cell-free DNA assays for HPV DNA in plasma show promise as a noninvasive measure of HPVþ carcinoma burden, and work is underway to evaluate this approach to monitor treatment efficacy, to identify recurrence, and to enhance early cancer detection. [] A combinatorial approach is envisioned in which plasma is analyzed for viral DNA and for mutations common in carcinoma (eg, in PIK3CA). Sequencing panels permit broad and agnostic pathogen detection alongside human genomic characterization that seem important for exploring synergistic mechanisms of carcinogenesis involving infections (viruses, bacteria, fungi, parasites), host immune response polymorphisms, DNA damage markers of prior mutagen/microbe exposure, and DNA repair defects"). One skilled in the art would have a reasonable expectation of success because both approaches are concerned with detecting pathogens using cell-free DNA.
Claims 1-9, 11-15, 17, 27-28, 39, 41-42, 44, 50, 57-60, 62-64, 66-69 and 303-304 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 34, and 42 of US patent application 17/968,155 in view of Diehn et al. (WO-2014151117). Although the claims at issue are not identical, they are not patentably distinct from each other because both involve screening for a pathogen using cell-free DNA, obtaining sequence data pertaining to one or more biological samples, sequencing the samples, and mapping the sequence reads to pathogen reference genomes.
While US patent application 17/968,155 does not explicitly teach determining a cancer condition based on the sequence data, it would have been obvious to one of ordinary skill in the art to modify these methods, with those taught by Diehn as described above for claim 1 of the instant application, in order to detect cancer early and/or monitor treatment efficacy (Diehn, para.0010 "PCT International Publication No. WO 2010/141955 A2 describes methods of detecting cancer by analyzing panels of genes from a patient-obtained sample and determining the mutational status of the genes in the panel", and Leal, page 10 col 1 paragraph 2 "Cell-free DNA assays for HPV DNA in plasma show promise as a noninvasive measure of HPVþ carcinoma burden, and work is underway to evaluate this approach to monitor treatment efficacy, to identify recurrence, and to enhance early cancer detection. [] A combinatorial approach is envisioned in which plasma is analyzed for viral DNA and for mutations common in carcinoma (eg, in PIK3CA). Sequencing panels permit broad and agnostic pathogen detection alongside human genomic characterization that seem important for exploring synergistic mechanisms of carcinogenesis involving infections (viruses, bacteria, fungi, parasites), host immune response polymorphisms, DNA damage markers of prior mutagen/microbe exposure, and DNA repair defects"). One skilled in the art would have a reasonable expectation of success because both approaches are concerned with detecting pathogens using cell-free DNA.
Conclusion
No claims are allowed.
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/R.A.P./Examiner, Art Unit 1686
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686