DETAILED ACTION
Applicant's Remarks, filed 12/29/2025, have been fully considered in view of instant application amendments. Herein, "the previous Office action" refers to the Restriction/Species Election of 09/19/2025.
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 .
Status of Claims
Claims 1-15 are currently pending.
Claims 12-13 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention.
Claims 1-11 and 14-15 are under examination herein.
Claims 1-11 and 14-15 are rejected.
Species Election
Applicant’s election in the reply filed on 12/29/2025 is acknowledged. Pursuant to 37 CFR 1.142(b). Because applicant did not distinctly and specifically state “without traverse” in the response, the election has been treated as an election without traverse due to an incomplete response (MPEP § 818.01(a)).
Election of Invention: claims 1-11 and 14-15 (calculating tumor burden based on genetic variants and mutant molecules).
Claims 12-13 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 12/29/2025.
Drawings
The drawings, filed on 06/11/2021, are accepted.
Specification
The substitute specification, filed on 11/23/2021, is entered.
Information Disclosure Statement
The Information Disclosure Statement, filed 06/11/2021, have been considered. A signed copy of all IDS is included with this Office Action.
Priority
The Applicant’s claim for the benefit of:
US Provisional Application No. 62/778,725, filed 12/12/2018,
a CON of PCT/EP2019/084893, filed 12/12/2019, is acknowledged.
Therefore, all claims 1-11 and 14-15 are examined for an effective filing date of 12/12/2018. In future actions, the effective filing date of one or more claims may change, due to claim amendments, or further analysis of the disclosure(s) of the priority application(s).
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 1-11 and 14-15 are rejected under 35 U.S.C. 101, because the claimed invention is directed to an abstract idea without significantly more.
The instant rejection reflects the framework as outlined in the MPEP at 2106.04:
Framework with which to Evaluate Subject Matter Eligibility:
(1) Are the claims directed to a process, machine, manufacture, or composition of matter;
(2A) Prong One: Do the claims recite a judicially recognized exception, i.e. a law of nature, a natural phenomenon, or an abstract idea;
Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application (Prong Two); and
(2B) If the claims do not integrate the judicial exception, do the claims provide an inventive concept.
Framework Analysis as Pertains to the Instant Claims:
With respect to step (1): Yes. The claimed invention (claims 1-10 to methods, claim 14 system, and claim 15 to a computer program) are directed to statutory subject matter. Applicant can consider adding “non-transitory” or the equivalent to computer program product, consistent with the instant specification computer system 320 with non-transitory computer-readable medium [0005, 0029, 0039, 0060, 0063: “processor 315 executing program instructions contained in non-transitory machine readable storage medium, such as system memory 325. The program instructions may be read into system memory 325 from another computer readable medium (e.g., non-transitory machine readable storage medium), such as data storage device 320”], to further clarify the non-transitory nature of the claimed computer program product.
Regarding claims 1-11 and 14-15, the claims are directed to methods/systems for calculating tumor burden based on genetic variants and mutant molecules, therefore the answer is "yes".
With respect to step (2A)(1), the claims recite abstract ideas and natural phenomenon. To determine if the claims recite any concepts that equate to an abstract idea, law of nature, or natural phenomenon, MPEP at 2106.03 teaches abstract ideas include mathematical concepts (mathematical formulas or equations, mathematical relationships, and mathematical calculations), certain methods of organizing human activity, and mental processes (including procedures for collecting, observing, evaluating, and organizing information (see MPEP 2106.04(a)(2)). In the instant application, the claims recite the following limitations that equate to an abstract idea (mental processes and mathematical concepts) and natural phenomenon.
With respect to the instant claims, under the step (2A)(1) evaluation, the claims are found herein to recite abstract ideas that fall into the grouping of mental processes (in particular processes for calculating tumor burden from genetic variants and mutant molecules). The claims directing to abstract ideas are as follows:
Mental processes:
Claims 1 and 10: querying, by the data processing system, the sequence data for one or more variants of the plurality of known variants…modeling, by the data processing system, background in the sample of cell free DNA, wherein the modeling comprises randomly sampling the sequence data a predetermined number of times for one or more types of variants present in the plurality of genomic regions…comparing, by the data processing system, the second MML for each of the one or more variants in the random samples to the first MML for each of the queried one or more variants… determining, by the data processing system, a tumor burden for the subject based on the first MML/number of mutant molecules for each of the queried one or more variants…
Claims 2 and 11: determining, by the data processing system, a distribution of the one or more types of variants present in the plurality of genomic regions, wherein the distribution comprises a first type of variant and a second type of variant.
Claim 3: randomly sampling…selecting at least one base associated with the first/second type of variant a predetermined number of times from the sequence data… selecting at least one base associated with the second type of variant a predetermined number of times from the sequence data.
Claim 8: determining, by the data processing system, whether the subject has minimal residual disease based on the statistical significance of the tumor burden.
Claim 9: predicting, by the data processing system, a clinical outcome of a treatment regimen for the subject based upon whether the subject has the minimal residual disease; and upon determining the subject does have minimal residual disease and predicting a negative clinical outcome, modifying the treatment regimen of the subject.
Mathematical concepts:
Claims 1 and 10: calculating, by the data processing system, a first mutant molecule load (MML)/number of mutant molecules for each of the queried one or more variants based on a first count of the unique molecular identifiers/an allele fraction for each of the queried one or more variants…calculating a second MML/number of mutant molecules for each of the one or more variants in the random samples based on a second count of the unique molecular identifier/an allele fractions for each of the one or more variants in the random samples… generating, by the data processing system, a ratio based on the comparison, wherein the ratio is: (a number of the random samples where the second MML/number of mutant molecules is greater than the first MML/number of mutant molecules): (the predetermined number of times), and the ratio is a probability value for a null-hypothesis that the second MML/number of mutant molecules of the background is greater than the first MML/number of mutant molecules of the queried variant… determining, by the data processing system, a statistical significance of the tumor burden based on the probability value and (variable) significance value.
Claim 3: counting a number of molecules supporting the first/second type of variant.
Claim 5: determining, by the data processing system, the significance value as a variable significance value based on a number of the queried one or more variants while maintaining a predetermined false discovery rate.
Claims 6 and 10: determining the variable significance value…determining a different significance value for each number of the one or more variants of the plurality of variants that are capable of being queried while maintaining the predetermined false discovery rate, and selecting the significance value for the number of the queried one or more variants from the determined different significance values; or (ii) determining an equation relating the significance value to the number of the queried one or more variants while maintaining a predetermined false discovery rate.
Claim 7: wherein the significance value is determined based on the number of the queried one or more variants that are associated with a subject tumor.
Natural phenomenon:
Claim 1: determining a tumor burden for the subject based on the first MML/variants
Claim 7: wherein the significance value is determined based on the number of the queried one or more variants that are associated with a subject tumor.
Claim 8 determining whether the subject has minimal residual disease based on the statistical significance of the tumor burden.
Claim 9: clinical outcome of a treatment regimen for the subject based upon whether the subject has the minimal residual disease; and upon determining the subject does have minimal residual disease and predicting a negative clinical outcome, modifying the treatment regimen of the subject.
Hence, the claims explicitly recite elements that, individually and in combination, constitute abstract ideas and natural phenomenon.
With respect to step (2A), under the broadest reasonable interpretation (BRI), the instant claims recite mental/mathematical steps and natural phenomenon for assessment of tumor burden based on genetic variants and mutant molecules.
Instant claims recite mental processes as to these methodology steps of querying … modeling … sampling … comparing… determining… selecting… predicting… modifying. Under the BRI, one with ordinary skill in the art could be performed said steps simply by mentally Under the BRI, one with ordinary skill in the art could be performed said steps simply by mentally analyzing variant results (see MPEP § 2106.04(a)(2), subsection III). The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation (see, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand."); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1139, 120 USPQ2d 1473, 1474 (Fed. Cir. 2016) (holding that claims to a mental process of "translating a functional description of a logic circuit into a hardware component description of the logic circuit" are directed to an abstract idea, because the claims "read on an individual performing the claimed steps mentally or with pencil and paper")).
Instant claims recite mathematical concepts as to these methodology steps of calculating … count(ing) … ratio… probability value for a null-hypothesis… statistical significance … (variable) significance value… predetermined false discovery rate… determining an equation. Under the BRI, one with ordinary skill in the art could be performed said steps simply by mentally analyzing variant results, mathematically count the target reads and calculate the likelihood ratios, and according to predetermined significance and probability parameters assess the likelihood of true mutant sequences (see MPEP § 2106.04(a)(2), subsection III).
Instant claim limitations equate to a natural phenomenon, when correlating variants, mutant molecule load, and tumor burden with the presence of ctDNA, subject tumor associations, and subject minimal residual disease, as well as, predicting a negative clinical outcome, because these limitations are similar to the concept of a correlation between the presence of myeloperoxidase in a bodily sample (such as blood or plasma) and cardiovascular disease risk in Cleveland Clinic Foundation v. True Health Diagnostics, LLC, 859 F.3d 1352, 1361, 123 USPQ2d 1081, 1087 (Fed. Cir. 2017), which the courts have established as a natural phenomenon.
Because the claims do recite judicial exceptions, direction under step (2A)(2) provides that the claims must be examined further to determine whether they integrate the abstract ideas into a practical application (MPEP 2106.04(d). A claim can be said to integrate a judicial exception into a practical application when it applies, relies on, or uses the judicial exception in a manner that imposes a meaningful limit on the judicial exception. This is performed by analyzing the additional elements of the claim to determine if the abstract idea is integrated into a practical application (MPEP 2106.04(d).I.; MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the judicial exception, the claim is said to fail to integrate into a practical application (MPEP 2106.04(d).III).
With respect to the instant recitations, the claims recite the following additional elements considered for practical application:
Claims 1, 10, 14, and 15: data processing system, system, processors, memory storing a plurality of instructions executable by the one or more processors, computer readable medium.
Claims 1 and 10: obtaining, by a data processing system, sequence data… target regions in a sample of cell free DNA… genomic regions…known variants…unique molecular identifiers.
Claim 4: wherein the at least one base associated with the first type of variant is selected based on a multinucleotide context of the first type of variant, and the at least one base associated with the second type of variant is selected based on the multinucleotide context of the second type of variant.
Said steps that are “in addition” to the recited judicial exception in the instant claims represent those of mere data handling (see MPEP 2106.05(g) (data movement, e.g. obtaining, by a data processing system, sequence data… target regions in a sample of cell free DNA… genomic regions…known variants…unique molecular identifiers; data characterization, e.g. data source), or field of use limitations (sequence data, target/genomic regions, variants, multinucleotide context, unique molecular identifiers) to implement the recited judicial exception in a generic computer environment. These steps are insignificant extra-solution activity and are insufficient to integrate an abstract idea into a practical application (MPEP 2106.05(g).
Further steps herein directed to additional non-abstract elements of data processing system, processors, computer program product/ a computer readable storage medium, processor do not describe any specific computational steps by which the “computer parts” perform or carry out the abstract idea, 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 abstract idea. Hence, these are mere instructions to apply the abstract idea using a computer, and therefore the claim does not integrate that abstract idea into a practical application. The courts have weighed in and consistently maintained that when, for example, a memory, display, processor, machine, etc… are recited so generically (i.e., no details are provided) that they represent no more than mere instructions to apply the judicial exception on a computer, and these limitations may be viewed as nothing more than generally linking the use of the judicial exception to the technological environment of a computer (see MPEP 2106.05(f)).
As such, the claims are lastly evaluated using the step (2B) analysis, wherein it is determined that because the claims recite abstract ideas which do not integrate the abstract ideas into a practical application, the claims also lack a specific inventive concept. The judicial exception alone cannot provide the inventive concept or the practical application and that the identification of whether the additional elements amount to such an inventive concept requires considering the additional elements individually and in combination to determine if they provide significantly more than the judicial exception (MPEP 2106.05.A i-vi).
With respect to the instant claims, the additional elements of data gathering, instructions, and field of use limitations described above do not rise to the level of significantly more than the judicial exception. As directed in the Berkheimer memorandum of 19 April 2018 and set forth in the MPEP, determinations of whether or not additional elements (or a combination of additional elements) may provide significantly more and/or an inventive concept rests in whether or not the additional elements (or combination of elements) represents well-understood, routine, conventional activity. Said assessment is made by a factual determination stemming from a conclusion that an element (or combination of elements) is widely prevalent or in common use in the relevant industry, which is determined by either a citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s).
With respect to the instant recitations, the claims recite the following additional elements considered for inventive concepts:
Claims 1, 10, 14, and 15: data processing system, system, processors, memory storing a plurality of instructions executable by the one or more processors, computer readable medium.
Claims 1 and 10: obtaining, by a data processing system, sequence data… target regions in a sample of cell free DNA… genomic regions…known variants…unique molecular identifiers.
Claim 4: wherein the at least one base associated with the first type of variant is selected based on a multinucleotide context of the first type of variant, and the at least one base associated with the second type of variant is selected based on the multinucleotide context of the second type of variant.
These additional elements do not contribute significantly more to well-known and conventional laboratory test analysis, which are routinely determined and implemented by an one with ordinary skill in the art of as of the effective filing date.
Newman AM et al. [2014: An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. Nature Medicine, vol 20, pages 548-554] teaches CAPP-Seq methods of analyzing circulating tumor DNA (ctDNA) for somatic variants in the plasma of patients undergoing treatment for non-small cell lung cancer for noninvasive assessment of cancer burden. Levels of ctDNA were highly correlated with tumor volume and distinguished between residual disease and treatment-related imaging changes, and measurement of ctDNA levels allowed for earlier response assessment than radiographic approaches [Abstract] (minimal residual disease, modifying therapy regimen).
Yarchoan M et al. [2017: Tumor Mutational Burden and Response Rate to PD-1 Inhibition. N Engl J Med 2017;377:2500-2501 DOI:10.1056/NEJMc1713444]. teaches calculating the mutation burden using the ratio of mutations over total nucleotides (measured in mega bases) (ratio, multinucleotide context) [FIG 1; p1 Col 2]. Yarchoan teaches a significant correlation between the tumor mutational burden and the objective response rate to anti-PD1 or anti-PD-L1 immune checkpoint therapies [p1 Col 2].
Gerstung M et al. [2014: Subclonal variant calling with multiple samples and prior knowledge. Bioinformatics, 30(9), 1198-1204] teaches an algorithm for detecting clonal and subclonal variants that exploits the power of a large sample set for precisely defining the local error rates and which uses prior information to call variants with high specificity and sensitivity (predetermined false discovery rate, significance values, probability value) [p1198 Introduction].
Data (e.g. test results and parameters from generic computer of a test device) remain merely analyzed and manipulated as input/output in the judicial exception. With respect to the instant claims, the steps and 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 1-11 and 14-15 are not patent eligible.
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.
Claims 9-11 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. Claim 11 is also rejected because it depends on and/or does not remedy the deficiencies inherited by the parent claim.
Regarding claim 9, the claim limitation recites “predicting… a clinical outcome of a treatment regimen for the subject based upon whether the subject has the minimal residual disease” wherein said recitation is indefinite, failing to set forth the necessary and sufficient steps for one of ordinary skill in the art for predicting nor modifying for any clinical outcome, tumor, disease, or treatment and would not reasonably be apprised of the scope of the invention.
Further, the term “negative” from “predicting a negative clinical outcome, modifying the treatment regimen of the subject” is a relative term which renders the claim indefinite. The term “negative” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree or type of negative outcomes (e.g. treatment response [0036, 0084], disease recurrence, test failure), and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention nor the resulting steps for modifying the treatment regimen of the subject.
Therefore, said limitations are indefinite as claimed. Clarification is requested through clearer claim language
Claim Rejections - 35 USC § 102
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.
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Note: citations from the instant application are italicized in the following section.
A. Claims 1-11 and 14-15 are rejected under 35 U.S.C 102(a)(1) as being anticipated by Gerstung M et al. [2014: Subclonal variant calling with multiple samples and prior knowledge. Bioinformatics, 30(9), 1198-1204; herein Gerstung, PTO 892 cited].
Regarding instant claim 1:
(a) obtaining, by a data processing system, sequence data for a plurality of target regions in a sample of cell free DNA from a subject, wherein the plurality of target regions are selected from a plurality of genomic regions that comprise a plurality of known variants, and the plurality of known variants are tagged with unique molecular identifiers;
(b) querying, by the data processing system, the sequence data for one or more variants of the plurality of known variants;
(c) calculating, by the data processing system, a first mutant molecule load (MML) for each of the queried one or more variants based on a first count of the unique molecular identifiers for each of the queried one or more variants;
(d) modeling, by the data processing system, background in the sample of cell free DNA, wherein the modeling comprises randomly sampling the sequence data a predetermined number of times for one or more types of variants present in the plurality of genomic regions and calculating a second MML for each of the one or more variants in the random samples based on a second count of the unique molecular identifiers for each of the one or more variants in the random samples;
(e) comparing, by the data processing system, the second MML for each of the one or more variants in the random samples to the first MML for each of the queried one or more variants;
(f) generating, by the data processing system, a ratio based on the comparison, wherein the ratio is: (a number of the random samples where the second MML is greater than the first MML): (the predetermined number of times), and the ratio is a probability value for a null-hypothesis that the second MML of the background is greater than the first MML of the queried variant;
(g) determining, by the data processing system, a tumor burden for the subject based on the first MML for each of the queried one or more variants; and
(h) determining, by the data processing system, a statistical significance of the tumor burden based on the probability value and a significance value.
The prior art to Gerstung teaches an algorithm for detecting clonal and subclonal variants that exploits the power of a large sample set for precisely defining the local error rates and which uses prior information to call variants with high specificity and sensitivity [p.1198 Introduction].
The algorithm was implemented on a computer system/processor 2.2GHz AMD processor, parallelized easily, completing a targeted screen with 100 genes in a few hours on an 8-core machine [p.1200 Col 2: 3.5 Implementation].
Use of sequence data from a database source, such as COSMIC [Fig 1b, p.1200 Col 2: 3.4 Prior data], or polymorphism databases such as Single Nucleotide Polymorphism Database or Ensembl variation [p.1204 Col 1: 5 Discussion] (obtaining, by a data processing system, sequence data for a plurality of target regions). Gerstung used large gene screens in hematological cancers/ myelodysplastic syndromes (MDS) for 111 cancer genes sequenced using barcoded libraries prepared from whole genome amplified DNA. Reads were aligned with the GRCh37 human reference genome [p.1200 Col 2: 4 Results] (selected from a plurality of genomic regions that comprise a plurality of known variants, and the plurality of known variants are tagged with unique molecular identifiers).
Variant/control allele counts and their distribution of samples were parameterized in the algorithm, including their nucleotide context (multinucleotide context) [p.1199 Col 1: 3 Methods] (calculating, by the data processing system, a first mutant molecule load (MML)/number of mutant molecules for each of the queried one or more variants based on a first/second count of the unique molecular identifiers/an allele fraction for each of the queried one or more variants/random samples).
Gerstung’s variant calling relies on a true variant will be present on both strands, and at a higher frequency than both background error rates because it is the sum of the true allele frequency and the error rate. According to a Bayesian method, the null-model is that X and X’ are distributed with the same rate as the control counts X and X’ on either strand, which assumes to contain only errors but no variants, and generates a likelihood equation [FIG 7, p.1199 Col 1: 3.2 Inference] (modeling, by the data processing system, background in the sample of cell free DNA … a ratio based on the comparison… is a probability value for a null-hypothesis that the second MML of the background is greater than the first MML of the queried variant).
The prior distribution about the likelihood of an allele being mutated can be extracted from COSMIC. Prior data/posterior probability that M0 is true can be computed with the Bayes’ formula in Equation 9. They use the probability of the null model, M0 because of its similarity to a P-value in a hypothesis testing scheme and call variants below a certain threshold Pr(M0|D)<P0. The parameter of Equation 11 denotes the prior probabilities that a variant k exists at position j. A higher prior probability results in a lower posterior probability of an artifact for a given signal as quantified by the Bayes factor. [FIG 1b and 1g; p.1200 Col 2: 3.4 Prior data] (determining a tumor burden…a statistical significance of the tumor burden based on the probability value and a significance value).
Regarding instant claim 2:
wherein the modeling further comprises determining, by the data processing system, a distribution of the one or more types of variants present in the plurality of genomic regions, wherein the distribution comprises a first type of variant and a second type of variant.
The prior art to Gerstung teaches variant/control allele counts and their distribution of samples were parameterized in the algorithm [p.1199 Col 1: 3 Methods]
Regarding instant claim 3:
wherein the randomly sampling the sequence data comprises: (i) selecting at least one base associated with the first type of variant a predetermined number of times from the sequence data and counting a number of molecules supporting the first type of variant, and (ii) selecting at least one base associated with the second type of variant a predetermined number of times from the sequence data and counting a number of molecules supporting the second type of variant.
The prior art to Gerstung models a nucleotide counts as a beta-binomial distribution, based on a nucleotide context (multinucleotide context) including forward and backward read orientations and expected numbers of nucleotide counts per read. Variant calling is commonly performed against a matched normal. They construct an aggregate control sample for sample i from the set of all other samples. The latter is justified if the particular variant occurs only rarely, or if the set of reference samples J(i) is chosen such that they are unlikely to contain the variant, e.g. by only selecting samples with a variant allele frequency (VAF) Xi=ni smaller than a predefined threshold, typically ~10%. (variant a predetermined number of times) [p.1199 Col 1: 3 Statistical framework]
Regarding instant claim 4:
wherein the at least one base associated with the first type of variant is selected based on a multinucleotide context of the first type of variant, and the at least one base associated with the second type of variant is selected based on the multinucleotide context of the second type of variant.
The prior art to Gerstung calculates a prior data/posterior probability that M0 is true can be computed with the Bayes’ formula in Equation 9. They use the probability of the null model, M0 because of its similarity to a P-value in a hypothesis testing scheme and call variants below a certain threshold Pr(M0|D)<P0. The parameter of Equation 11 denotes the prior probabilities that a variant k exists at position j. A higher prior probability results in a lower posterior probability of an artifact for a given signal as quantified by the Bayes factor. [FIG 1b and 1g; p.1200 Col 2: 3.4 Prior data] (determining a tumor burden…a statistical significance of the tumor burden based on the probability value and a significance value).
Regarding instant claim 5:
determining, by the data processing system, the significance value as a variable significance value based on a number of the queried one or more variants while maintaining a predetermined false discovery rate.
The prior art to Gerstung used data from 683 MDS samples that were sequenced in the same run and passed quality control steps. Their shearwater algorithm analyzed 258, 830 nt from 43 oncogenic genes. For each call, we annotated polymorphisms present in Ensembl variation (v70) but not in COSMIC (v63) and termed mutations that were missense, nonsense or splice-site variants as non-silent. The distribution of variant allele frequencies of known polymorphisms (based on a number of the queried one or more variants) had two narrow peaks at 0.5 and 1, confirming the accuracy of allele frequency estimates (FIG. 3d). Non-polymorphic calls have a broad distribution with typical frequencies ranging from 0 to 0.5, with slightly more mass toward lower frequencies. This is consistent with their expectation that more variability exists at lower frequencies. The distributions of COSMIC and new variants are similar and more likely, real, thereby, the prior did not lead to overcalling (maintaining a predetermined false discovery rate) which specifically affects variants of low frequencies [p.1202 Col 1-2].
Regarding instant claim 6:
wherein the determining the variable significance value comprises: (i) determining a different significance value for each number of the one or more variants of the plurality of variants that are capable of being queried while maintaining the predetermined false discovery rate, and selecting the significance value for the number of the queried one or more variants from the determined different significance values; or (ii) determining an equation relating the significance value to the number of the queried one or more variants while maintaining a predetermined false discovery rate.
The prior art to Gerstung developed strand-agnostic null model M0 algorithm for calling subclonal variants in cancer samples with great specificity (while maintaining a predetermined false discovery rate) based on variants present bidirectionally (multinucleotide context aware) to increases the specificity of calls, although this does lead to a decrease in power in regions with low coverage and at the flanks of the target regions, where often reads in only one direction are available [p.1204 Col 1-2: Discussion].
Regarding instant claim 7:
wherein the significance value is determined based on the number of the queried one or more variants that are associated with a subject tumor.
The prior art to Gerstung assessed the sensitivity and specificity of their algorithm, and analyzed results with different levels of VAF )and significance (e.g. posterior odd of 1 or P0= 0.5 under a uniform prior and probability of <10-4 with a panel of 500 subject samples, including 32 normals and 2 x20 AML replicates. The remaining samples served for defining the background error distribution and for assessing how reproducible the calls were. To analyze the sensitivity for different combinations of coverage, they simulated mutations at different variant allele frequencies (VAF) using the coverage and strand bias of one of the normal samples (median 128x, 5% 13x, 95% 372x coverage). They computed the Bayes factors of each simulated variant in FIG 2a with a factor of <10-4. Cutoffs were set to a posterior odds of 1 or P0= 0.5 under a uniform prior and probability of <10-4. For a coverage of 250x, the true-positive rate of a 5% variant is 70%, and that of a 10% variant is _85%. Variants present in 20% can be called almost with certainty. When the dispersion is estimated from the data using all samples with VAF <10%, the Bayes factors become larger for variants <10% and only few reach the threshold of <10-4, as the model starts fitting the distribution of true calls [p.1201 Col 1: 4.1].
Regarding instant claim 10:
(a) obtaining, by a data processing system, sequence data for a plurality of target regions in a sample of cell free DNA from a subject, wherein the plurality of target regions are selected from a plurality of genomic regions that comprise a plurality of known variants;
(b) querying, by the data processing system, the sequence data for one or more variants of the plurality of known variants;
(c) calculating, by the data processing system, a first number of mutant molecules for each of the queried one or more variants based on an allele fraction for each of the queried one or more variants;
(d) modeling, by the data processing system, background in the sample of cell free DNA, wherein the modeling comprises randomly sampling the sequence data a predetermined number of times for one or more types of variants present in the plurality of genomic regions and calculating a second number of mutant molecules for each of the one or more variants in the random samples based on an allele fraction for each of the one or more variants in the random samples;
(e) comparing, by the data processing system, the second number of mutant molecules for each of the one or more variants in the random samples to the first number of mutant molecules for each of the queried one or more variants;
(f) generating, by the data processing system, a ratio based on the comparison, wherein the ratio is: (a number of the random samples where the second number of mutant molecules is greater than the first number of mutant molecules) : (the predetermined number of times), and the ratio is a probability value for a null-hypothesis that the second number of mutant molecules of the background is greater than the first number of mutant molecules of the queried variant;
(g) determining, by the data processing system, a variable significance value based on a number of the queried one or more variants while maintaining a predetermined false discovery rate, wherein the determining the variable significance value comprises: (i) determining a different significance value for each number of the one or more variants of the plurality of known variants that are capable of being queried while maintaining the predetermined false discovery rate, and
selecting the significance value for the number of the queried one or more variants from the determined different significance values; or (ii) determining an equation relating the significance value to the number of the queried one or more variants while maintaining a predetermined false discovery rate;
(h) determining, by the data processing system, a tumor burden for the subject based on the first number of mutant molecules for each of the queried one or more variants; and
(i) determining, by the data processing system, a statistical significance of the tumor burden based on the probability value and the variable significance value.
The prior art to Gerstung teaches that:
Use of sequence data from a database source, such as COSMIC [Fig 1b, p.1200 Col 2: 3.4 Prior data], or polymorphism databases such as Single Nucleotide Polymorphism Database or Ensembl variation [p.1204 Col 1: 5 Discussion] (obtaining, by a data processing system, sequence data for a plurality of target regions). Gerstung used large gene screens in hematological cancers/ myelodysplastic syndromes (MDS) for 111 cancer genes sequenced using barcoded libraries prepared from whole genome amplified DNA. Reads were aligned with the GRCh37 human reference genome [p.1200 Col 2: 4 Results] (selected from a plurality of genomic regions that comprise a plurality of known variants, and the plurality of known variants are tagged with unique molecular identifiers).
Variant/control allele counts and their distribution of samples were parameterized in the algorithm, including their nucleotide context (multinucleotide context) [p.1199 Col 1: 3 Methods] (calculating, by the data processing system, a first mutant molecule load (MML)/number of mutant molecules for each of the queried one or more variants based on a first/second count of the unique molecular identifiers/an allele fraction for each of the queried one or more variants/random samples).
Gerstung’s variant calling relies on a true variant will be present on both strands, and at a higher frequency than both background error rates because it is the sum of the true allele frequency and the error rate. According to a Bayesian method, the null-model is that X and X’ are distributed with the same rate as the control counts X and X’ on either strand, which assumes to contain only errors but no variants, and generates a likelihood equation [FIG 7, p.1199 Col 1: 3.2 Inference] (modeling, by the data processing system, background in the sample of cell free DNA … a ratio based on the comparison… is a probability value for a null-hypothesis that the second MML of the background is greater than the first MML of the queried variant).
The prior distribution about the likelihood of an allele being mutated can be extracted from COSMIC. Prior data/posterior probability that M0 is true can be computed with the Bayes’ formula in Equation 9. They use the probability of the null model, M0 because of its similarity to a P-value in a hypothesis testing scheme and call variants below a certain threshold Pr(M0|D)<P0. A higher prior probability results in a lower posterior probability of an artifact for a given signal as quantified by the Bayes factor. [FIG 1b and 1g; p.1200 Col 2: 3.4 Prior data] (determining a tumor burden…a statistical significance of the tumor burden based on the probability value and a significance value).
Regarding instant claim 11:
determining, by the data processing system, a distribution of the one or more types of variants present in the plurality of genomic regions, wherein the distribution comprises a first type of variant and a second type of variant.
The prior art to Gerstung teaches that:
The prior distribution about the likelihood of an allele being mutated can be extracted from COSMIC. Prior data/posterior probability that M0 is true can be computed with the Bayes’ formula in Equation 9. They use the probability of the null model, M0 because of its similarity to a P-value in a hypothesis testing scheme and call variants below a certain threshold Pr(M0|D)<P0. The parameter of Equation 11 denotes the prior probabilities that a variant k exists at position j. A higher prior probability results in a lower posterior probability of an artifact for a given signal as quantified by the Bayes factor. [FIG 1b and 1g; p.1200 Col 2: 3.4 Prior data] (determining a tumor burden…a statistical significance of the tumor burden based on the probability value and a significance value).
Regarding instant claims 14-15:
A system comprising: one or more processors; a memory accessible to the one or more processors, the memory storing a plurality of instructions executable by the one or more processors, the plurality of instructions comprising instructions that when executed by the one or more processors cause the one or more processors to perform the method of claim.
computer readable medium storing a plurality of instructions for controlling a computer system.
The prior art to Gerstung teaches algorithm was implemented on a computer system/processor 2.2GHz AMD processor, parallelized easily, completing a targeted screen with 100 genes in a few hours on an 8-core machine [p.1200 Col 2: 3.5 Implementation].
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 § 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. § 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or
nonobviousness.
Note: quotes from the instant application are italicized in the following section.
A. Claims 8-9 are rejected under 35 U.S.C. § 103 as being unpatentable over Gerstung M et al. (2014). Subclonal variant calling with multiple samples and prior knowledge. Bioinformatics, 30(9), 1198-1204; herein Gerstung, PTO 892 cited], as applied to independent claim 1 above, in view Tie J et al. [2016: Circulating tumor DNA analysis detects minimal residual disease and predicts recurrence in patients with stage Il colon cancer. Science translational medicine, 8(346), 346ra92- 346ra92; herein Tie, PTO 892 cited].
Regarding instant claim 8:
determining, by the data processing system, whether the subject has minimal residual disease based on the statistical significance of the tumor burden.
The prior art to Gerstung teaches an indirect measure of the quality of a predicted genotype can be the correlation with a known phenotype, such as survival, and trained Cox proportional hazards survival models with mutated genes as covariates [p.1203 Col 1].
However, Gerstung did not explicitly teach determining, by the data processing system, whether the subject has minimal residual disease based on the statistical significance of the tumor burden.
The prior art to Tie teaches predicting whether a subject has minimal residual disease based on the classification of a sample into healthy or ctDNA containing groups. Tie discloses that detection of ctDNA after resection of stage II colon cancer may identify patients at higher risk of recurrence (predicting… a clinical outcome of a treatment regimen for the subject based upon whether the subject has the minimal residual disease…predicting a negative clinical outcome) (Abstract).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present application to combine the teachings of Gerstung and Tie. Gerstung teaches a subclonal variant calling algorithm with prior knowledge from large sample set to lower the local error rates and call variants with high specificity and sensitivity [p.1198 Introduction]. Tie teaches ctDNA evaluation for recurrent colon cancer prediction and adjuvant treatment decisions [Abstract].
One of ordinary skill in the art would have been motivated to use the low error variant calling from Gerstung, with Tie’s minimum residual disease analysis to direct chemotherapy without the increased errors and risks inherent in current surveillance with carcinoembryonic antigen (CEA) and computed tomography (CT) imaging [Tie at p1 Col 2].
Combining these prior art elements would have been obvious because, in the setting of an overall low risk of cancer recurrence, like Tie’s stage II colon cancer patients, identification of a high-risk subset of patients with a low error rate, minimally invasive ctDNA analysis & algorithm can optimize adjuvant therapy outcomes [Tie at p1 Col 2].
One of ordinary skill in the art would predict combining Gerstung and Tie with a reasonable expectation of success as each is analogously applicable to teach ctDNA analysis of minimal residual disease. The invention is therefore prima facie obvious.
Regarding instant claim 9:
predicting, by the data processing system, a clinical outcome of a treatment regimen for the subject based upon whether the subject has the minimal residual disease; and
upon determining the subject does have minimal residual disease and predicting a negative clinical outcome, modifying the treatment regimen of the subject.
The prior art to Gerstung teaches an indirect measure of the quality of a predicted genotype can be the correlation with a known phenotype, such as survival, and trained Cox proportional hazards survival models with mutated genes as covariates [p.1203 Col 1].
However, Gerstung did not explicitly teach predicting, by the data processing system, a clinical outcome of a treatment regimen for the subject based upon whether the subject has the minimal residual disease… predicting a negative clinical outcome, modifying the treatment regimen of the subject.
As applied to claims 1 and 8, the prior art to Tie teaches predicting whether a subject has minimal residual disease based on the classification of a sample into healthy or ctDNA containing groups. Tie discloses detecting minimal residual disease in 1046 plasma samples from 230 patients with resected stage II colon cancer (Abstract). The detection of ctDNA after resection of stage II colon cancer may identify patients at higher risk of recurrence (predicting… a clinical outcome of a treatment regimen for the subject based upon whether the subject has the minimal residual disease…predicting a negative clinical outcome) and informs adjuvant treatment decisions (modifying the treatment regimen of the subject).
Conclusion
No claims are allowed.
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/VR/
Examiner
Art Unit 1685
/MARY K ZEMAN/ Primary Examiner, Art Unit 1686