DETAILED ACTION
Notice of AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Status of the Claims
Claims 1-20 are pending.
Claims 1, 11 and 13 are independent.
Claims 1-2, 4-5, 8, 10, 15, 17 and 19 are objected to.
Claims 1-20 are rejected.
Priority
This US Application 17/857,821 (07/05/2022) claims priority from US Application 63/257,910 (10/20/2021) as reflected in the filing receipt mailed on Jul. 14, 2022. The claims to the benefit of priority are acknowledged; and the effective filing date of claims 1-20 is 10/20/2021.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 07/05/2022, 10/01/2022 and 10/01/2025 were considered.
Drawings
In the instant drawings, several figures are executed in color (e.g. Figs. 8, 14, 22A/B, 24A/B/C and 25A/B and many others, ending in Fig. 50). Color photographs and color drawings are not accepted in utility applications unless a petition filed under 37 CFR 1.84(a)(2) is granted. Any such petition must be accompanied by the appropriate fee set forth in 37 CFR 1.17(h), one set of color drawings or color photographs, as appropriate, if submitted via the USPTO patent electronic filing system or three sets of color drawings or color photographs, as appropriate, if not submitted via the via USPTO patent electronic filing system, and, unless already present, an amendment to include the following language as the first paragraph of the brief description of the drawings section of the specification. The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. Color photographs will be accepted if the conditions for accepting color drawings and black and white photographs have been satisfied. See 37 CFR 1.84(b)(2).
Specification Objections
The specification is objected to because pgs. 21-30, 32-34 and 54-61 contain embedded hyperlinks and/or other form of browser-executable codes. Applicant is required to delete the embedded hyperlink and/or other form of browser-executable code; references to websites should be limited to the top-level domain name without any prefix such as http:// or other browser-executable code. See MPEP § 608.01.
Claim objections
Claims 1-2, 4-5, 8, 10, 15, 17 and 19 are objected to because of the following informalities related to grammar/punctuation. Appropriate correction is required. With regard to any suggested amendment below to overcome an objection, in the subsequent examination it is assumed that each amendment is made. However, equivalent amendments also would be acceptable. Any amendments in response to the following objections should be applied throughout the claims, as appropriate.
Claim 1 recites "(J)… at least one of (1) transmitting …" which should read "(J)… at least one of: (1) transmitting …" adding a colon before the list. In contrast, the recited "(C)… outputs based on: (1) detection …" does not present the same issue.
Claim 1 recites "(E) … sample; and (F) …" which has an improper "and" since (F) is not the last element listed in the claim. In contrast, the recited "(I)… and (J) …" does not present the same issue.
Claim 1 recites "(I) generating a report comprising, for the tumor …" which should read "(I) generating a report comprising: for the tumor …" for proper punctuation/grammar.
In claim 1, at step "(G)," a new line is needed. The claim recites step (G) in line with step (F). As set forth in 37 CPR 1.75, each element or step of the claim should be separated by a line indentation (608.01(m) Form of Claims). Sub-steps / elements should be indented from their parent step / element. This rule should be applied throughout the claims as needed. Same issue exists for the steps recited in claims 2, 5, 8 and 10.
Claim 4 recites a "determining" step and a "providing" step. When a list contains only two list elements, then the comma before "and" is improper, i.e. "X and Y" not "X, and Y."
In claim 17, the recited elements should be separated by semi-colons and not commas because one or more list elements themselves already include comma-separated sub-lists. As such, "reference database, (1) … values, (2) …, and (3) … ." should read "reference database; (1) … values; (2) …; and (3) … ." Same issue occurs in claim 19. Contrast claim 11, not similarly objected to.
Claim interpretation
112(f) interpretation of particular recitations
Recited "DNA ploidy and allelic imbalance analysis" (claims 1, 11 and 13-15)
The above recitation includes means (or an equivalent, nonce term, here "analysis") and function and/or result (here "DNA ploidy and allelic imbalance analysis"). The above recitations are not sufficiently well-known and not accompanied by sufficient structure in the claims to prevent invoking. Therefore, each is interpreted as invoking. Having invoked, each above recitation has been analyzed as clearly linking to sufficient structure in the specification, as supported at ([00208]). Thus, the above recitations have been interpreted as properly invoking 112(f).
Recited "more allelic imbalance identification techniques" (claims 1, 11 and 14)
The above recitation include means (or an equivalent, nonce term, here "techniques") and function and/or result (here "more allelic imbalance identification"). The above recitations are not sufficiently well-known and not accompanied by sufficient structure in the claims to prevent invoking. Therefore, each is interpreted as invoking. Having invoked, each above recitation has been analyzed as clearly linking to sufficient structure in the specification, as supported at ([00208]). Thus, the above recitations have been interpreted as properly invoking 112(f).
Recited "gene/variant/substitution/germline callers" (claim 8)
The above recitation include means (or an equivalent, nonce term, here "callers") and function and/or result (here "gene/variant/substitution/germline callers"). The above recitations are not sufficiently well-known and not accompanied by sufficient structure in the claims to prevent invoking. Therefore, each is interpreted as invoking. Having invoked, each above recitation has been analyzed as clearly linking to sufficient structure in the specification, as supported at ([00209]). Thus, the above recitations have been interpreted as properly invoking 112(f).
Recited "clonality analysis" (claims 1, 10-11 and 13)
The above recitation include means (or an equivalent, nonce term, here "analysis") and function and/or result (here "clonality analysis"). The above recitations are not sufficiently well-known and not accompanied by sufficient structure in the claims to prevent invoking. Therefore, each is interpreted as invoking. Having invoked, each above recitation has been analyzed as clearly linking to sufficient structure in the specification, as supported at ([00209]). Thus, the above recitations have been interpreted as properly invoking 112(f).
Recited "rescue process" (claim 8)
The above recitation include means (or an equivalent, nonce term, here "process") and function and/or result (here "rescue"). The above recitations are not sufficiently well-known and not accompanied by sufficient structure in the claims to prevent invoking. Therefore, each is interpreted as invoking. Having invoked, each above recitation has been analyzed as clearly linking to sufficient structure in the specification, as supported at ([00210]). Thus, the above recitations have been interpreted as properly invoking 112(f).
Recited "RNA gene expression analysis" (claims 1, 11 and 13)
The above recitation include means (or an equivalent, nonce term, here "analysis") and function and/or result (here "RNA gene expression analysis"). The above recitations are not sufficiently well-known and not accompanied by sufficient structure in the claims to prevent invoking. Therefore, each is interpreted as invoking. Having invoked, each above recitation has been analyzed as clearly linking to sufficient structure in the specification, as supported at ([00207]). Thus, the above recitations have been interpreted as properly invoking 112(f).
Claim Rejections - 35 USC § 112(b)
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.
Claims 1-20 are rejected under 35 U.S.C. 112(b)as being indefinite for failing to particularly point out and distinctly claim the subject matter the invention. Dependent claims are rejected similarly, unless otherwise noted below. The following issues cause the respective claims to be rejected under 112(b) as indefinite:
Claims 1, 8, 11 and 14 recite " high-confidence aberrant copy number segments", "high-confidence fusion genes", and "high-confidence structural variants" in which the recited "high" is a term of relative or vague degree or form of association, neither defined in the specification (e.g. [00127]) nor having a well-known and sufficiently defined value in the art and in the instant context. MPEP 2173.05(b) pertains.
Claims 1, 11 and 20 are indefinite because the relationship between the claim elements is unclear.
Claim 1 recites "each sample" (B)(2)(vii) and the various preceding instances of "sample" and "samples" in step (B)(1). The relationship between said elements is unclear.
Claim 11 recites "(D) … and (E)" but there is no conjunction between step (H) and the last step, (I). It is unclear how steps (F) to (I) relate to the rest of the claim elements.
Claim 20 recites "values used for the report" which has an unclear relationship to the recited "a report comprising two or more of: …" in claim 13.
The following recitations require but lack antecedent basis, rendering their claims indefinite:
a. Claim 1, "each variant class" ((B)(2)(v)). The term "variant class" plural needs to be instantiated in the claims. One option could be "...(v) microsatellite instability and/or mutational burden scores for each [[variant]] class of a plurality of variant classes...,"
b. Similar issue as above appears for claims 17 and 19.
c. In claim 1, the relation is unclear between "RNA fusions" (E)(1) and the earlier-recited "RNA fusions" (B)(2)(i). If related to the same element, this later instance should recite "the RNA fusions".
d. In claim 3, the meaning of "Step 1(E)" is unclear because there is no previous recitation of "Step 1(E)".
e. Claim 5 repeats the above issue with "the coverage score".
f. Claim 13 repeats the above issue with "the DNA" step (A)(8).
g. In claim 14, the recited "based on..., and on prioritization..." present an unclear relationship between "based" and the second "on..." due to the comma and the extent of intervening recitation.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 USC § 101 because the claimed inventions are directed to one or more Judicial Exceptions (JEs) without significantly more. Regarding JEs, "Claims directed to nothing more than abstract ideas..., natural phenomena, and laws of nature are not eligible for patent protection" (MPEP 2106.04 §I). Abstract ideas include mathematical concepts and procedures for evaluating, analyzing or organizing information, which are a type of mental process (MPEP 2106.04(a)(2)).
101 background
MPEP 2106 organizes JE analysis into Steps 1, 2A (Prong One & Prong Two), and 2B as analyzed below. MPEP 2106 and the following USPTO website provide further explanation and case law citations: uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials.
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter (MPEP 2106.03)?
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e., a law of nature, a natural phenomenon, or an abstract idea (MPEP 2106.04(a-c))?
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application by an additional element (MPEP 2106.04(d))?
Step 2B: Do the claims recite a non-conventional arrangement of elements in addition to any identified judicial exception(s) (MPEP 2106.05)?
Analysis of instant claims
Step 1: Are the claims directed to a 101 process, machine, manufacture, or composition of matter (MPEP 2106.03)?
Claims 1-20 are directed to a 101 process, here a "method," with process steps such as "generating" etc.
[Step 1: claim 1-20: Yes].
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e., a law of nature, a natural phenomenon, or an abstract idea (MPEP 2106.04(a-c))?
Background
With respect to Step 2A, Prong One, the claims recite judicial exceptions in the form of abstract ideas. MPEP § 2106.04(a)(2) further explains that abstract ideas are defined as:
• mathematical concepts (mathematical formulas or equations, mathematical relationships
and mathematical calculations) (MPEP 2106.04(a)(2)(I));
• certain methods of organizing human activity (fundamental economic principles or practices, managing personal behavior or relationships or interactions between people) (MPEP 2106.04(a)(2)(II)); and/or
• mental processes (concepts practically performed in the human mind, including observations, evaluations, judgments, and opinions) (MPEP 2106.04(a)(2)(III)).
Analysis of instant claims
Mathematical concepts recited in instant claims 1, 6, 17 and 19, include the terms:
• " per million (TPM) values" (claims 1, 6, 17 and 19);
" generating cohort classification scores" (claims 1 and 11); and
• "quality threshold is at least 20 Phred … 70% genome coverage … threshold … about 20% " (claim 5).
Said terms are being identified as mathematical concepts. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one having ordinary skill in the art. Thus, the recited terms correspond to verbal equivalents of mathematical concepts because they constitute actions executed by a group of mathematical steps in a form of a mathematical algorithm; thus mathematical concepts (MPEP 2106.04(a)(2)). A mathematical concept need not be expressed in mathematical symbols, because "words used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989).
Mental processes, defined as concepts or steps practically performed in the human mind such as steps of observations, evaluations, judgments, analysis, opinions or organizing information include:
• "generating … datasets" (claims 1 and 11);
• "implementing a workflow" (claims 1 and 11);
• "generating a report" (claims 1 , 11 and 13);
• "interrogating … mutation against a database" (claims 2 and 18);
• "identifying … orthogonal supportive indicators" (claims 1-2, 11, 16 and 18);
• classifying germline mutation pathogenicity" (claim 3);
• determining the anti-cancer therapy" (claims 4, 12 and 20); and
• prioritizing genetic alterations (claims 1, 7 and 16).
Under the BRI, the recited limitations are mental processes because a human mind is sufficiently capable of generate datasets/databases, implement a workflow, interrogate/compare a mutation against a database, classify pathogenicity, identify indicators, determine a therapy and prioritize alteration.
Dependent claims 2 and 17-19 recite further details about "classification scores"; dependent claim 7 recites further details about the criteria used for "for prioritizing allelic imbalances"; dependent claim 16 recites further details about "identifying … orthogonal supportive indicators"; not reciting any additional non-abstract elements; all reciting further aspects of the information being analyzed, the manner in which that analysis is performed. Hence, the claims explicitly recite numerous elements that, individually and in combination, constitute abstract ideas. The instant claims must therefore be examined further to determine whether they integrate that abstract idea into a practical application (MPEP 2106.04(d)).
[Step 2A Prong One, abstract idea: claims 1-20: Yes].
Step 2A, 1st prong, 1st Mayo/Alice question: law of nature -- MPEP 2106.I and 2106.04
The instant claims recite a natural correlation by correlating the measurement of an amount of a RNA and DNA naturally found in the body with a disease-specific classification score. (see MPEP 2106.04(b).I).
[Step 2A, 1st prong, law of nature: claims 1-20: Yes].
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application by an additional element (MPEP 2106.04(d))?
Background
MPEP 2106.04(d).I lists the following example considerations for evaluating whether a judicial exception is integrated into a practical application:
An improvement in the functioning of a computer or an improvement to other technology or another technical field, as discussed in MPEP §§ 2106.04(d)(1) and 2106.05(a);
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, as discussed in MPEP § 2106.04(d)(2);
Implementing a judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, as discussed in MPEP § 2106.05(b);
Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP § 2106.05(c); and
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP § 2106.05(e).
Analysis of instant claims
Instant claims 1-2, 11, 13 and 16-19 recite additional elements that are not abstract ideas:
• "computing device" (claim 1);
• "computing system" (claim 11 and 13);
• "processors" (claims 11, 13, 16-17 and 19);
• "identifying … orthogonally-validated mutation" (claims 2 and 18);
• "determination of a number of … variants and … fusions in a sample" (claims 1, 11 and 13);
• "accessing a plurality of databases" (claim 1);
• "performing an RNA gene expression analysis" (claims 1, 11 and 13);
• "performing a DNA ploidy and allelic imbalance analysis" (claims 1, 11 and 13);
• "performing … variant calling analysis"(claims 1, 11 and 13);
• "providing a report" (claims 1, 11 and 13);
• "storing the report in a non-volatile computer-readable storage medium" (claims 1 and 11).
Dependent claims 6, 14-15 recite further details about the "RNA gene expression analysis" and dependent claims 8-10 and 15 recite further details about "variant calling analysis".
The recited limitations in 1-2, 11, 13 and 16-19 are interpreted to require the use of a computer. The use of a computer is broadly interpreted and not actually described in the claims or specification. Hence, the claims explicitly recite steps executed by computers and therefore can be described as computer functions or instructions to implement on a generic computer.
Further steps directed to additional non-abstract elements of a computing device/computer do not describe any specific computational steps by which the "computer parts" perform or carry out the judicial exceptions, nor do they provide any details of how specific structures of the computer, such as the computer-readable recording media, are used to implement these functions. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions.
The recited "identifying … orthogonally-validated mutation" (claims 2 and 18); "determination of a number of … variants and … fusions in a sample" (claims 1, 11 and 13); "accessing a plurality of databases" (claim 1); "performing an RNA gene expression analysis" (claims 1, 11 and 13); "performing a DNA ploidy and allelic imbalance analysis" (claims 1, 11 and 13); and "performing … variant calling analysis"(claims 1, 11 and 13) read on data gathering activities or the type of data being gathered; not amounting to a practical application. The type of data doesn’t change that it is mere data gathering or conventional computer receiving means.
Claims directed to "accessing a database" and "soring a report" read on receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321 - MPEP 2106.05(a) pertains; which constitutes just necessary data gathering and outputting and therefore correspond to insignificant extra-solution activity.
Merely "providing the report to one or more users for determination of an anti-cancer therapy" cannot be a practical application because the limitation does not provide an actual treatment to the patient. These additional elements appear to be insignificant extra-solution activity (MPEP 2106.05(g) because they merely serve as necessary data gathering/outputting and do not amount to a practical application.
Hence, these are mere instructions to apply the abstract idea using a computer and insignificant extra-solution activity and therefore the claims do not integrate that abstract idea into a practical application (see MPEP 2106.04(d) § I; 2106.05(f); and 2106.05(g)). The courts have weighed in and consistently maintained that when, for example, a memory, display, processor, machine, etc .... are recited so generically (i.e., no details are provided) that they represent no more than mere instructions to apply the judicial exception on a computer and these limitations may be viewed as nothing more than generally linking the use of the judicial exception to the technological environment of a computer (MPEP 2106.05(f)).
In Step 2A, Prong One above, claim steps and/or elements were identified as part of one or more judicial exceptions (JEs).
In this Step 2A, Prong Two immediately above claim steps and/or elements were identified as part of one or more additional elements. Additional elements are further discussed in Step 2B below.
Here in Step 2A, Prong Two, no additional step or element clearly demonstrates integration of the JE(s) into a practical application.
At this point in examination it is not yet the case that any of the Step 2A, Prong Two considerations enumerated above clearly demonstrates integration of the identified JE(s) into a practical application. Referring to the considerations above, none of 1. an improvement, 2. treatment, 3. a particular machine or 4. a transformation is clear in the record.
For example, regarding the first consideration at MPEP 2106.04(d)(1), the record, including for example the specification, does not yet clearly disclose an explanation of improvement over the previous state of the technology field. The claims do not yet clearly result in such an improvement (e.g. specification: [19-20, 214, 420, 550, 561, 583, 729-905, etc.).
For example, regarding the second consideration at MPEP § 2106.04(d)(2), the record, including for example the specification, does not yet clearly disclose an explanation of a particular treatment or prophylaxis for a disease or medical condition. The claims do not yet clearly result in such treatment (e.g. specification: [0216]).
[Step 2A Prong Two: claims 1-20 - No]
Step 2B: Do the claims recite a non-conventional arrangement of elements in addition to any identified judicial exception(s) (MPEP 2106.05)?
According to analysis so far, the additional elements described above do not provide significantly more than the judicial exception. A determination of whether additional elements provide significantly more also rests on whether the additional elements or a combination of elements represents other than what is well-understood, routine, and conventional. Conventionality is a question of fact and may be evidenced as: a citation to an express statement in the specification or to a statement made by an applicant during examination that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s).
Claims 1-2, 11, 13 and 16-19 recite a computer or computer functions, interpreted as instructions to apply the abstract idea using a computer, where the computer does not impose meaningful limitations on the judicial exceptions; which can be performed without the use of a computer (MPEP 2106.04(d) § I; and MPEP 2106.05(f)).
With respect to claims 1 and those claims dependent therefrom, the computer-related elements or the general purpose computer and the analysis do not rise to the level of significantly more than the judicial exception. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, which the courts have found to not provide significantly more when recited in a claim with a judicial exception (Alice Corp., 573 U.S. at225-26, 110 USPQ2d at 1984; see MPEP 2106.05(A)).
Further, the courts have found that receiving and outputting data are well-understood, routine, and conventional functions of a computer when claimed in a merely generic manner or as insignificant extra-solution activity (see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network), Versa ta Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015), and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93, as discussed in MPEP 2106.05(d)(Il)(i)).
With respect to the instant claims, the prior art review to Koboldt ("Best practices for variant calling in clinical sequencing." Genome medicine 12(1):91 (2020), as cited on the attached Form PTO-892) recites that Next-generation sequencing technologies such as RNA-seq, variant calling and whole genome sequencing, which enable a dramatic expansion of clinical genetic testing both for inherited conditions and diseases such as cancer (pg. 1 para. 1), is routine, well-understood and conventional in the art. As such, the claims simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (MPEP2106.05(d)). The data gathering steps as recited in the instant claims constitute a general link to a technological environment which is insufficient to constitute an inventive concept which would render the claims significantly more than the judicial exception (MPEP2106.05(g)&(h)).
When the claims are considered as a whole, they do not integrate the abstract idea into a practical application; they do not confine the use of the abstract idea to a particular technology; they do not solve a problem rooted in or arising from the use of a particular technology; they do not improve a technology by allowing the technology to perform a function that it previously was not capable of performing; and they do not provide any limitations beyond generally linking the use of the abstract idea to a broad technological environment. See MPEP 2106.05(a) and 2106.05(h).
[Step 2B: claims 1-20: No]
Conclusion: Instant claims are directed to non-statutory subject matter
For these reasons, the claims in this instant application, when the limitations are considered individually and as a whole, are directed to an abstract idea and lack an inventive concept. Hence, the claimed invention does not constitute significantly more than the abstract idea, so instant claims 1-20 are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
The following is a quotation of pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under pre-AIA 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
A. Claims 1-11 and 13-20are rejected under 35 U.S.C. 103(a) as being unpatentable over Tuch ("Tumor transcriptome sequencing reveals allelic expression imbalances associated with copy number alterations." PloS one 5(2):e9317 (2010)) in view of Saeidian ("Research techniques made simple: whole-transcriptome sequencing by RNA-seq for diagnosis of monogenic disorders." Journal of investigative dermatology 140(6):1117-1126 (2020)) as evidenced by Rentzsch ("CADD: predicting the deleteriousness of variants throughout the human genome." Nucleic acids research 47(D1):D886-D894 (2019)) in view of Smith ("Classification of genes: standardized clinical validity assessment of gene–disease associations aids diagnostic exome analysis and reclassifications." Human mutation 38(5):600-608 (2017)) in view of Walsh ("Integrating somatic variant data and biomarkers for germline variant classification in cancer predisposition genes." Human mutation 39(11):1542-1552 (2018)), as cited on the attached Form PTO-892.
Tuch discloses the use of computer software (pg. 12 col. 1 para. 1-2) to combine transcriptome sequencing and genome sequencing to characterize the genomic mutations underlying alterations in gene expression in a tumor (pg. 10 col. 2 para. 2). Bullet points indicate the teachings of the instant features over the prior art. Instantly claimed elements which are considered to be equivalent to the prior art teachings are described in bold for all claims.
Regarding claims 9-10, the prior art teaches step (E2) of claim 1 as described below, and therefore claims 9-10, which further limit steps (E5) and (E7) of claim 1, do not further narrow the embodiment of claim 1 to which the art has been applied.
Claim 1 recites:
(A) generating, based on sequencing of a tumor sample and a healthy control germline sample, a plurality of datasets comprising:
(1) a first dataset based on whole transcriptome sequencing of RNA in the tumor sample obtained from a patient;
(2) a second dataset based on a whole genome sequencing (WGS) of DNA derived from the tumor sample obtained from the patient; and
(3) a third dataset based on WGS of DNA in the healthy control germline sample;
• Tuch teaches the use of computer software (pg. 12 col. 1 para. 1-2) to combine transcriptome sequencing and genome sequencing to characterize the genomic mutations underlying alterations in gene expression in a tumor (pg. 10 col. 2 para. 2); wherein analysis were performed on tumor and normal samples obtained from patients undergoing oral surgery (i.e. germline DNA samples) (pg. 11 col. 1 para. 3) comprising RNA library preparation (i.e. first dataset) (pg. 11 col. 1 para. 4) and DNA library preparation (i.e. a second dataset including DNA from each tumor sample and a third dataset including DNA from each normal sample) (pg. 11 col. 2 para. 2).
(B) accessing a plurality of databases comprising:
(1) a first reference database comprising, for a reference cohort of tumor samples, a plurality of individual sample gene expression transcripts per million (TPM) values;
• Tuch teaches the measurement of gene expression in carcinoma and normal tissue by RNA sequencing yielding 256 million sequence reads per sample (pg. 2 col. 1 para. 3 and Fig. 1); wherein the results were pulled into a database (i.e. a reference database of gene expression transcripts reported as per million values) (pg. 2 Fig. 1).
(2) a second reference database comprising, … annotations for at least one of (i) RNA fusions, (ii) somatic structural variants, (iii) somatic substitutions, (iv) somatic insertions and deletions (indels), (v) microsatellite instability and/or mutational burden scores for each variant class, (vi) germline variants, (vii) somatic mutation patterns or signatures in each sample, or (vii) allelic imbalances; and
• Tuch teaches gene annotation of structural mutations to assist with the detection of somatic mutations and accurately measure allele-specific expression (pg. 1 para. 1) and to report heterozygous amplifications and deletions association with the allelic imbalance shown via distributions of allelic imbalance for genomic regions (i.e. analysis of annotated second database) (pg. 9 Fig. 6).
(3) a third database comprising a plurality of gene identifiers corresponding to a plurality of known cancer genes;
• Tuch teaches unique gene identifiers used for allelic imbalance analysis (pg. 9 Fig. 6); wherein there is widespread allelic imbalance between normal and tumor samples: 185 to 345 sites from 121 to 209 unique genes associated with the enrichment for the same cancer-related functions (pg. 10 col. 2 para. 1)
(C) performing an RNA gene expression analysis using the first dataset, the first reference database, and the third database, to generate, for the tumor sample, a first plurality of outputs based on:
(1) detection of established cancer genes having aberrant gene expression in the tumor sample relative to that observed in normal control subjects; and
(2) prioritization of the detected aberrantly- expressed cancer genes in the tumor sample;
• Tuch teaches the use of the first dataset, the first reference database, and the third database as described above, sequencing tumor and normal genomes of one patient to determine copy number changes (CNCs) between the normal and tumor samples. (pg. 10 col. 2 para. 2).
• Tuch does not teach "detection of … aberrant gene expression in the tumor sample" and related prioritization analysis. However, Saeidian teaches the application of whole-transcriptome sequencing of RNA with appropriate bioinformatics (i.e. computer-implemented steps) to identify mutations that result in aberrant transcriptome expression (pg. 1117 para. 1) in diagnostic settings for confirmation of the pathogenic consequences of mutations (pg. 1122 Fig. 4); wherein comparison to normal samples are made to confirm aberrant splicing (pg. 1123 Fig. 5); wherein prioritization of candidate genes is facilitated by quantitative assessment of the transcript levels to support the pathogenicity of the sequence variant (i.e. first plurality of outputs) (pg. 1121 col. 2 para. 1).
(D) performing a DNA ploidy and allelic imbalance analysis using the second dataset, the third dataset, and the third database, to generate, for the tumor sample, a second plurality of outputs based on:
(1) detection of high-confidence aberrant copy number segments in the tumor sample by applying one or more allelic imbalance identification techniques; and
(2) prioritization of allelic imbalances in the tumor sample based on a set of criteria comprising an overlap of the high-confidence aberrant copy number segments in the tumor sample with the known cancer genes in the third database;
• Tuch teaches the use of the second dataset, the third dataset, and the third database as described above; wherein allelic imbalance analysis by RNA-seq (i.e. allelic imbalance identification technique) between tumor and normal tissues includes the analysis of mutations that impact the underlying genomic position directly in one of the two haplotypes (e.g., a point mutation or a deletion/duplication that changes the copy number of one allele relative to the other) (i.e. DNA ploidy analysis) (pg. 5 col. 2 para. 2); wherein the investigation whether copy number mutations (i.e. comprising aberrant copy number) in oral squamous cell carcinoma development were driving the changes in gene expression was done by applying a copy number variation (CNV) segmentation algorithm to generate copy number segments (pg. 8 col. 1 para. 3); wherein validation of the CNV yielded high confidence results (i.e. second plurality of outputs) from microarray analysis (i.e. (pg. 15 col. 2 para. 2) and sets of genes allelically imbalanced in patients overlap significantly (pg. 7 col. 1 para. 1).
(E) performing, based on the RNA gene expression analysis of Step (C) and the DNA ploidy and allelic imbalance analysis of Step (D), a variant calling analysis to generate, for the tumor sample, a third plurality of outputs based on:
(1) detection of RNA fusions;
(2) detection of somatic structural variants;
(3) detection of somatic substitutions;
(4) detection of somatic insertions and deletions (indels);
(5) assessment of microsatellite instability and/or mutational burden across variant classes;
(6) detection of germline variants;
(7) clonality analysis;
(8) determination of a number of structural variants and gene fusions in the DNA of the tumor sample; and/or
(9) determination of somatic mutation patterns or signatures in the tumor sample;
• Tuch teaches gene annotation of structural mutations describing gene amplifications and deletions association with the allelic imbalance are shown via distributions of allelic imbalance for genomic regions (i.e. third plurality of outputs) (pg. 9 Fig. 6) to assist with the detection of somatic mutations and accurately measure allele-specific expression (pg. 1 para. 1).
(F) implementing a workflow comprising:
(1) identifying orthogonal supportive indicators based on consistency of two or more outputs in at least two of the first, second, and third pluralities of outputs generated in Step (C), Step (D), and Step (E), respectively;
(2) prioritizing genetic alterations based on the orthogonal supportive indicators;
(3) generating global classifications based on the orthogonal supportive indicators; and
(4) classifying at least one somatic mutation in an established cancer gene that is detected in both the first dataset and the second dataset as being orthogonally validated;
• Tuch teaches the use of the first, second, and third pluralities of outputs as described above; wherein the identification of orthogonal supportive indicators is done by comparing/validating the gene expression measurements identified with RNA-seq to orthogonal technologies (e.g., RT-qPCR and microarray) (pg. 2 col.2 para. 2) to assist with the detection of somatic mutations and accurately measure allele-specific expression (pg. 1 para. 1).
• Tuch does not teach "prioritizing/classifying genetic alterations based on the orthogonal supportive indicators. However, Saeidian teaches a workflow comprising RNA-Seq technique and bioinformatics analysis steps including include variant calling, variant prioritization, homozygosity mapping, validation of variants of unknown significance in the genome, quantitative gene expression analysis, and differential gene expression (pg. 1118 Fig. 1); wherein filtering of the annotated variants for prioritization assists in identification of candidate genes with pathogenic profile by first focusing on exonic sequence variants and removal of benign synonymous variants with a Combined Annotation Dependent Depletion score, CADD < 20 (pg. 1119 col. 1 para. 1); wherein CADD is a widely used measure of variant deleteriousness that can effectively prioritize causal variants in genetic analyses (i.e. global classification of variants used to assist classification of mutation in a gene) (pg. D886 col. 1 para. 1) by integrating all annotations for any given variant into a single score transformed into a PHRED-like rank score based on the genome-wide distribution of scores (pg. D886 col. 2 para. 2), as evidenced by Rentzsch.
(G) generating cohort classification scores for each individual level output in each of the first, second, and third pluralities of outputs for the tumor sample based on the reference cohort of tumor samples in at least one of the first reference database or the second reference database; and
(H) generating disease-specific classification scores for each individual level output in each of the first, second, and third pluralities of outputs for the tumor sample based on a subset of the reference cohort of tumor samples in at least one of the first reference database or the second reference database, wherein the subset of the reference cohort of tumor samples is of a same cancer type;
• Tuch teaches the use of the first, second, and third pluralities of outputs for a tumor sample as described above.
• Tuch does not teach classification scores for individual outputs neither the disease-specific classification scores for individual outputs. However, Smith teaches a method for classification of genes based on a scoring scheme that goes as follows: one point per publication reporting independent probands, one point per pathogenic/likely pathogenic variant reported in a patient; one point if the gene function and/or expression is consistent with disease phenotype, and second point if gene product physically interacts with a gene product implicated in similar disease; one point if in vitro experiments show the same disease pathology after a similar genetic modification and second point if mutational mechanism of patient-reported alterations is determined by functional studies; one point if gene function in an animal model is similar to the pathology reported in the human disease and second point if both phenotype and genotype of the animal model match human disease (pg. 602 Fig. 1).
(I) generating a report comprising, for the tumor sample, the prioritized allelic imbalances, the microsatellite instability and/or mutational burden across variant classes, the germline variants, outputs of the clonality analysis, the number of structural variants and gene fusions in the DNA, the somatic mutation patterns or signatures, the at least one orthogonally-validated somatic mutation, the cohort classification scores, and the disease specific classification scores; and
• Tuch teaches the identification of orthogonal supportive indicators (pg. 2 col.2 para. 2) to assist with the detection of somatic mutations and accurately measure allele-specific expression (i.e. orthogonally-validated somatic mutation) (pg. 1 para. 1) and the analysis of nested genetic duplications that give rise to the amplified state observed in the tumor (i.e. clonality analysis) (pg. 8 col. 1 para. 5).
• Saeidian teaches the cohort classification scores, and the disease specific classification scores as described above.
• Walsh teaches microsatellite instability as an additional assay to provide evidence consistent with genetic mismatch repair deficiency (pg. 1549 Table 1), cancer signatures as evidence of germline abnormalities (pg. 1549 Table 1), the use of RNA-seq to reveal structural variants in tumors (pg. 1550 col. 1 para. 3); and the use of somatic data types such as tumor signatures (i.e. the somatic mutation patterns or signatures) (pg. 1546 col. 2 para. 5).
(J) providing the report to one or more users for determination of an anti-cancer therapy, wherein providing the report comprises at least one of
(1) transmitting the report to a computing device,
(2) displaying the report on a display screen, or (3) storing the report in a non-volatile computer-readable storage medium that is accessible to the one or more users.
• Tuch does not teach the recitation above. However, Saeidian teaches the reporting of data obtained by RNA-seq visualized (i.e. transmitting the report to a computing device) by Integrative Genomics Viewer (i.e. displaying a report on a display screen) (pg. 1121 Fig. 3 and pg. 1122 Fig. 4); wherein information about the specific mutations is required for potential application of allele-specific treatment approaches (i.e. determining the anti-cancer therapy) (pg. 1117 col. 1 para. 1).
Claim 2 recites:
wherein generating the cohort classification scores further comprises: (1) interrogating the at least one orthogonally-validated somatic mutation against a fourth database that associates a plurality of somatic mutations with a plurality of specific cancer types or pan-cancer markers; and (2) identifying the at least one orthogonally- validated somatic mutation as associated with a specific cancer type or pan-cancer hotspot when there is a match.
• Tuch teaches the identification of orthogonal supportive indicators (here, interpreted as measurements orthogonally validated) by comparing/validating the gene expression measurements identified with RNA-seq to orthogonal technologies (e.g., RT-qPCR and microarray) (pg. 2 col.2 para. 2) to assist with the detection of somatic mutations and accurately measure allele-specific expression (pg. 1 para. 1); wherein concordance was assessed with these other methods at the level of differential gene expression between oral squamous cell carcinoma tumor and normal tissue samples (i.e. somatic mutation as associated with a specific cancer type).
Claim 3 recites:
further comprising classifying germline mutation pathogenicity by integration of data derived in Step 1(E) relating to acquired somatic mutation patterns or signatures.
• Tuch does not teach the recitation above. However, Walsh teaches integrating somatic variant data and biomarkers for germline variant classification in cancer predisposition genes (pg. 1542 Title); wherein tumor RNA sequencing data showing altered splicing support germline pathogenicity and tumor phenotypic features such as mutational signatures support evidence of pathogenicity (pg. 1 para. 1).
Claim 4 recites:
further comprising determining the anti-cancer therapy based on values used for the report, and providing the anti-cancer therapy in the report.
• Tuch does not teach the recitation above. However, Saeidian teaches the reporting of data obtained by RNA-seq (pg. 1121 Fig. 3 and pg. 1122 Fig. 4); wherein information about the specific mutations is required for potential application of allele-specific treatment approaches (i.e. determining the anti-cancer therapy) (pg. 1117 col. 1 para. 1).
Claim 5 recites:
further comprising determining that the second and third datasets have at least one of (1) a quality score satisfying a quality threshold, wherein the quality score indicates genome mapping quality, and the quality threshold is at least 20 Phred, (2) a coverage metric satisfying a coverage threshold, wherein the coverage score indicates genome coverage, and the coverage threshold is at least about 70% genome coverage, or (3) a tumor cell content satisfying a tumor purity threshold, wherein the tumor cell content indicates tumor purity corresponding to the DNA in the tumor sample, and the tumor purity threshold is at least about 20% tumor purity.
• Tuch teaches the use of the second dataset and the third datasets as described above; wherein following evaluation by pathology to verify classification of tumor or normal tissue status samples were further assessed for quality prior to library construction (pg. 11 col. 1 para. 4).
• Tuch does not teach a quality score threshold. However, Saeidian teaches filtering the annotated variants dataset for prioritization by removal of variants with a Combined Annotation Dependent Depletion score, CADD < 20 (i.e. ensuring data quality by maintaining threshold of 20 and above) (pg. 1119 col. 1 para. 1); wherein CADD is a measure reported in PHRED (pg. D886 col. 2 para. 2), as evidenced by Rentzsch.
Claim 6 recites:
wherein performing the RNA gene expression analysis further comprises detecting over-expressed or under-expressed genes based on the TPM values satisfying a percentile threshold relative to the first reference database.
• Tuch teaches the measurement of gene expression in carcinoma and normal tissue by RNA sequencing yielding 256 million sequence reads per sample (pg. 2 col. 1 para. 3 and Fig. 1); wherein analysis involved structural variation underlying gene expression to identify the over-expression of Cortactin as 14-fold up-regulated (i.e. threshold) (pg. 8 col. 1 para. 5).
Claim 7 recites:
wherein the set of criteria for prioritizing allelic imbalances in the tumor sample further includes at least one of whole-genome duplication (WGD) or an aberrant copy number segment having a direction that is consistent with cancer gene function.
• Tuch teaches the measurement of gene expression in carcinoma and normal tissue by RNA sequencing yielding 256 million sequence reads per sample (i.e. transcripts per million) (pg. 2 col. 1 para. 3 and Fig. 1); wherein analysis involved structural variation underlying gene expression to identify the over-expression of Cortactin as 14-fold up-regulated (pg. 8 col. 1 para. 5).
Claim 8 recites:
the variant calling analysis comprising at least one of:
(i) detection of RNA fusions, wherein detection of RNA fusions comprises employing a plurality of independent fusion gene callers on raw data,
(ii) detection of RNA fusions, wherein detection of RNA fusions comprises detection of high-confidence fusion genes, and employing a rescue process to recover detected high-confidence fusion genes that were not detected by at least two independent variant callers as a reference for known cancer genes, wherein rescued fusions are required to have at least one spanning read,
(iii) detection of somatic structural variants, wherein detection of somatic structural variants comprises deploying a plurality of independent structural variant callers on raw data,
(iv) detection of somatic structural variants, wherein detection of somatic structural variants comprises selection of high-confidence structural variants by merging all calls having more than a first predetermined number of base pairs (bp) by a window that includes a breakpoint, the window having a size that is a second predetermined number of bps,
(v) detection of somatic substitutions, wherein detection of somatic substitutions comprises employing a plurality of independent substitution callers on raw data,
(vi) detection of somatic indels, wherein detection of somatic indels comprises generating one or more indel signatures and using the one or more indel signatures to determine if a somatic indel is a repeat-mediated deletion, a microhomology association, or an insertion,
(vii) assessment of microsatellite instability and/or mutational burden across variant classes, or
(viii) detection of germline variants, wherein detection of germline variants comprises deploying a plurality of independent germline callers on raw data.
• Tuch teaches step (iv) above as the use of computer software (pg. 12 col. 1 para. 1-2) to combine transcriptome sequencing and genome sequencing to characterize the genomic mutations underlying alterations in gene expression in a tumor (pg. 10 col. 2 para. 2) to assist with the detection of somatic mutations and accurately measure allele-specific expression (pg. 1 para. 1); wherein gene annotation of structural mutations describing gene amplifications and deletions association with the allelic imbalance are shown via distributions of allelic imbalance for genomic regions (pg. 9 Fig. 6); wherein only high confidence results from the microarray platform are used for validation of copy number variation analysis (i.e. selection of high-confidence structural variants) (pg. 15 col. 2 para. 2); wherein a CNV calling and segmentation algorithm handled system sequencing reads and included window size of 100 kb and 20-30 break points (pg. 13 col. 2 para. 2).
Claim 11 recites:
(A) generating, by one or more processors of a computing system, based on sequencing of a tumor sample and a healthy control germline sample, a plurality of datasets comprising: (1) a first dataset based on whole transcriptome sequencing of RNA in the tumor sample obtained from a patient; (2) a second dataset based on a whole genome sequencing (WGS) of DNA derived from the tumor sample obtained from the patient; and (3) a third dataset based on WGS of DNA in the healthy control germline sample
• Tuch teaches the recitation above as applied for claim 1 step (A).
(B) performing, by the one or more processors, an RNA gene expression analysis using the first dataset to generate, for the tumor sample, a first plurality of outputs based on detection of established cancer genes having aberrant gene expression in the tumor sample relative to that observed in normal control subjects
• Tuch and Saeidian teach the recitation above as applied for claim 1 step (C) (1).
(C) performing, by the one or more processors, a DNA ploidy and allelic imbalance analysis using the second dataset to generate, for the tumor sample, a second plurality of outputs based on detection of high-confidence aberrant copy number segments in the tumor sample by applying one or more allelic imbalance identification techniques
• Tuch teaches the recitation above as applied for claim 1 step (D) (1).
(D) performing, by the one or more processors, based on the RNA gene expression analysis of Step (B) and the DNA ploidy and allelic imbalance analysis of Step (C), a variant calling analysis to generate, for the tumor sample, a third plurality of outputs based on a plurality of: (1) detection of RNA fusions; (2) detection of somatic structural variants; (3) detection of somatic substitutions; (4) detection of somatic insertions and deletions (indels); (5) assessment of microsatellite instability and/or mutational burden across variant classes; (6) detection of germline variants; (7) clonality analysis; (8) determination of a number of structural variants and gene fusions in the DNA of the tumor sample; and/or (9) determination of somatic mutation patterns or signatures in the tumor sample
• Tuch teaches the recitation above as applied for claim 1 step (E).
(E) implementing, by the one or more processors, a workflow comprising: (1) identifying, by the one or more processors, orthogonal supportive indicators based on consistency of two or more outputs in at least two of the first, second, and third pluralities of outputs generated in Steps (B), (C), and (D), respectively; (2) classifying, by the one or more processors, at least one somatic mutation in an established cancer gene that is detected in both the first dataset and the second dataset as being orthogonally validated
• Tuch and Saeidian teach the recitation above as applied for claim 1 step (F).
(F) generating, by the one or more processors, cohort classification scores for each individual level output in each of the first, second, and third pluralities of outputs for the tumor sample based on a reference cohort of tumor samples
• Tuch and Smith teach the recitation above as applied for claim 1 step (G).
(G) generating, by the one or more processors, disease-specific classification scores for each individual level output in each of the first, second, and third pluralities of outputs for the tumor sample based on a subset of the reference cohort of tumor samples, wherein the subset of the reference cohort of tumor samples is of a same cancer type
• Tuch and Smith teach the recitation above as applied for claim 1 step (H).
(H) generating, by the one or more processors, a report comprising, for the tumor sample, based on Steps (A)-(G), information corresponding to a plurality of allelic imbalances, microsatellite instability and/or mutational burden across variant classes, germline variants, clonality analysis, structural variants and gene fusions in the DNA, somatic mutation patterns or signatures, orthogonally- validated somatic mutations, cohort classification scores, and disease specific classification scores
• Tuch, Saeidian and Walsh teach the recitation above as applied for claim 1 step (I).
(I) providing, by the one or more processors, the report to one or more users for determination of an anti-cancer therapy, wherein providing the report comprises at least one of (1) transmitting, by the one or more processors, the report to a computing device, (2) displaying, by the one or more processors, the report on a display screen, or (3) storing the report in a non-volatile computer- readable storage medium of the computing system.
• Tuch and Saeidian teach the recitation above as applied for claim 1 step (J).
Claim 13 recites:
A) performing, by one or more processors of a computing system, based on a first plurality of outputs from an RNA gene expression analysis and a second plurality of outputs from a DNA ploidy and allelic imbalance analysis, a variant calling analysis to generate, for a tumor sample, a third plurality of outputs based at least on two or more of: (1) detection of RNA fusions; (2) detection of somatic structural variants; (3) detection of somatic substitutions; (4) detection of somatic insertions and deletions (indels); (5) assessment of microsatellite instability and/or mutational burden across variant classes; (6) detection of germline variants; (7) clonality analysis; (8) determination of a number of structural variants and gene fusions in the DNA of the tumor sample; or (9) determination of somatic mutation patterns or signatures in the tumor sample
• Tuch teaches the recitation above as applied for claim 1 step (E).
(B) generating, by the one or more processors, for the tumor sample, a report comprising two or more of: (1) prioritized allelic imbalances; (2) microsatellite instability or mutational burden across variant classes; (3) the detected germline variants; (4) outputs of the clonality analysis; (5) the number of structural variants and gene fusions in the DNA; or (6) the somatic mutation patterns or signatures; and (C) providing, by the one or more processors, the report for determination of an anti-cancer therapy.
• Tuch does not teach the recitation above. However ,Saeidian teaches the reporting of data obtained by RNA-seq visualized (i.e. transmitting the report to a computing device) by Integrative Genomics Viewer (i.e. displaying a report on a display screen) (pg. 1121 Fig. 3 and pg. 1122 Fig. 4); wherein information about the specific mutations is required for potential application of allele-specific treatment approaches (i.e. determining the anti-cancer therapy) (pg. 1117 col. 1 para. 1).and prioritization of candidate genes facilitated by quantitative assessment of the transcript levels to support the pathogenicity of the sequence variant (i.e. first plurality of outputs) (pg. 1121 col. 2 para. 1).
Claim 14 recites:
(1) wherein the first plurality of outputs from the RNA gene expression analysis is based on detection of established cancer genes having aberrant gene expression in the tumor sample relative to that observed in normal control subjects, and on prioritization of the detected aberrantly-expressed cancer genes in the tumor sample, and
(2) wherein the second plurality of outputs from the DNA ploidy and allelic imbalance analysis is based on detection of high-confidence aberrant copy number segments in the tumor sample by applying one or more allelic imbalance identification techniques, and on prioritization of allelic imbalances in the tumor sample based on a set of criteria comprising an overlap of the high-confidence aberrant copy number segments in the tumor sample with known cancer genes.
• Tuch and Saeidian teach the recitation above as applied for claim 1 steps (C) and (D).
Claim 15 recites:
wherein: the RNA gene expression analysis is performed using a first dataset corresponding to whole transcriptome sequencing of RNA in the tumor sample obtained from a patient; and the DNA ploidy and allelic imbalance analysis is performed using a second dataset corresponding to a whole genome sequencing (WGS) of DNA derived from the tumor sample obtained from the patient, and a third dataset corresponding to WGS of DNA in the healthy control germline sample.
• Tuch teaches the recitation above as applied for claim 1 step (A).
Claim 16 recites:
(A) identifying, by the one or more processors, orthogonal supportive indicators based on consistency of two or more outputs in at least two of the first plurality of outputs, the second plurality of outputs, and the third plurality of outputs; (B) prioritizing, by the one or more processors, genetic alterations based on the orthogonal supportive indicators; (C) generating, by the one or more processors, global classifications based on the orthogonal supportive indicators; and (D) classifying, by the one or more processors, at least one somatic mutation in an established cancer gene that is detected in both the first dataset and the second dataset as being orthogonally validated.
• Tuch and Saeidian teach the recitation above as applied for claim 1 step (F1 to F4).
Claim 17 recites:
generating, by the one or more processors, cohort classification scores for each individual level output in each of the first plurality of outputs, the second plurality of outputs, and the third plurality of outputs for the tumor sample based on a reference cohort of tumor samples in at least one of a first reference database or a second reference database
• Tuch and Smith teach the recitation above as applied for claim 1 step (G).
(1) wherein the first reference database comprises, for the reference cohort of tumor samples, a plurality of individual sample gene expression transcripts per million (TPM) values,
• Tuch teaches the recitation above as applied for claim 1 step (B1).
(2) wherein the second reference database comprises, for the reference cohort of tumor samples, at an individual sample level, annotations for at least one of (i) RNA fusions, (ii) somatic structural variants, (iii) somatic substitutions, (iv) somatic insertions and deletions (indels), (v) microsatellite instability or mutational burden scores for each variant class, (vi) germline variants, (vii) somatic mutation patterns or signatures in each sample, or (vii) allelic imbalances, and (3) wherein the report further comprises the cohort classification scores.
• Tuch teaches the recitation above as applied for claim 1 step (B2).
Claim 18 recites:
wherein generating the cohort classification scores comprises: (1) interrogating the at least one orthogonally-validated somatic mutation against a fourth database that associates a plurality of somatic mutations with a plurality of specific cancer types or pan-cancer markers; and (2) identifying the at least one orthogonally-validated somatic mutation as associated with a specific cancer type or pan-cancer hotspot when there is a match.
• Tuch teaches the recitation above as applied for claim 2.
Claim 19 recites:
generating, by the one or more processors, disease-specific classification scores for each individual level output in each of the first plurality of outputs, the second plurality of outputs, and the third plurality of outputs for the tumor sample based on a subset of a reference cohort of tumor samples in at least one of a first reference database or a second reference database,
• Tuch teaches the recitation above as applied for claim 1 step (H).
(1) wherein the first reference database comprises, for the reference cohort of tumor samples, a plurality of individual sample gene expression transcripts per million (TPM) values,
• Tuch teaches the recitation above as applied for claim 1 step (B1).
(2) wherein the second reference database comprises, for the reference cohort of tumor samples, at an individual sample level, annotations for at least one of (i) RNA fusions, (ii) somatic structural variants, (iii) somatic substitutions, (iv) somatic insertions and deletions (indels), (v) microsatellite instability and/or mutational burden scores for each variant class,(vi) germline variants, (vii) somatic mutation patterns or signatures in each sample, or (vii) allelic imbalances, and (3) wherein the report further comprises the disease-specific classification scores.
• Tuch teaches the recitation above as applied for claim 1 step (B2).
Claim 20 recites:
determining the anti-cancer therapy based on values used for the report, and providing the anti-cancer therapy in the report.
• Tuch teaches the recitation above as applied for claim 4.
Rationale for combining (MPEP §2142-2143)
Regarding claims 1-11 and 13-20, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Tuch in view of Saeidian, Smith and Walsh because all references disclose methods for the investigation of genetic imbalances and its gene-disease relationship. The motivation would have been to:
• provide a reliable first-tier diagnostic approach to extend mutation databases in patients with disorders (pg. 1 para. 1 Saeidian);
• obtain up-to-date curation of a gene–disease database combined with critical clinical validity scoring (pg. 600 col. 1 para. 1 Smith); and
• incorporate a standardized approach when considering somatic data for aiding in classifying germline cancer predisposition gene variants (pg. 1543 Fig. 1 Walsh).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the allelic imbalance analysis method of Tuch to the methods by Saeidian, Smith and Walsh because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for investigating genetic imbalances and its gene-disease relationship.
B. Claim 12 is rejected under 35 U.S.C. 103(a) as being unpatentable over Tuch, Saeidian, Smith and Walsh as applied to claim 11 above and further in view of Koboldt ("Best practices for variant calling in clinical sequencing." Genome medicine 12(1):91 (2020)), as cited on the attached Form PTO-892.
Claim 12 recites:
further comprising determining the anti-cancer therapy based on values used for the report, and providing the anti-cancer therapy in the report, wherein the anti-cancer therapy is determined based on interrogation of a therapy database to identify a therapy that aligns with the outputs in the report.
• Neither Tuch or Saeidian or Smith or Walsh teach the recitation above. However, Saeidian teaches specific mutations being required for potential application of allele-specific treatment approaches (i.e. determining the anti-cancer therapy) (pg. 1117 col. 1 para. 1).
• Furthermore, Koboldt teaches tumor-only sequencing as an approach to guide cancer diagnosis, prognosis, and therapy (pg. 7 col. 2 para. 1); wherein valuating the accuracy of variant calls requires access to benchmark datasets (pg. 2 col. 2 para. 5).
Rationale for combining (MPEP §2142-2143)
Regarding claim 12, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Tuch, Saeidian, Smith and Walsh in view of Koboldt because all references disclose methods for the investigation of genetic imbalances and its gene-disease relationship. The motivation would have been to incorporate targeted panels to leverage sequencing techniques to interrogate medically relevant subsets of genes to achieve precision oncology (pg. 1 col. 1 para. 1 Koboldt). Therefore it would have been obvious to one of ordinary skill in the art to substitute the genetic analysis method of Tuch, Saeidian, Smith and Walsh to the method by Koboldt because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for investigating genetic imbalances and its gene-disease relationship.
Conclusion
No claims are allowed.
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/F.F.L./Examiner, Art Unit 1685
/G. STEVEN VANNI/Primary patents examiner, Art Unit 1686