DETAILED ACTION
Applicant’s response, filed 08 May 2026, has been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
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 .
Claim Status
Claims 2, 3, 14, 20, 24, 49, 50, 98-100 are pending and examined herein.
Claims 2, 3, 14, 20, 24, 49, 50, 98-100 are rejected.
Claim 98 is objected to.
Priority
Claims 2, 3, 14, 20, 24, 49, 50, 98-100 are not granted the claim to the benefit of priority to U.S. Provisional application 62/877755 filed 23 July 2019 because there is no disclosure of “determining that a change in the plurality of tumor fractions of the subject across the epoch exceeds a threshold amount and changing, responsive to determining that the change exceeds the threshold amount, a treatment for the subject based on the plurality of tumor fractions, wherein the treatment comprises applying agents for cancer to the subject, wherein the agents for cancer are selected from hormones, immune therapies, radiotherapy, or one or more cancer drugs, wherein the one or more cancer drugs include . Thus, the effective filling date of claims 2, 3, 14, 20, 24, 49, 50, 98-100 is 23 July 2020.
Drawings
The objection to the drawings received 23 July 2020 in Office action mailed 16 December 2025 is withdrawn in view of the amendment to the specification which provides these reference characters received 08 May 2026.
Claim Objections
Claim 98 is objected to because of the following informalities:
Claim 98 recites “Nilotinib, Nilotinib…” in line 38 of the claim but should read “Nilotinib”.
Claim 98 recites “…Bortezomib, or Bortezomib” in line 40 of the claim but should read “… or Bortezomib”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The rejection on the ground of 112/b of claim 14 for reciting “further comprising copy numbers and the allele counts to generate a plurality of features with reduced dimensionality” in Office action mailed 16 December 2025 is withdrawn in view of the amendment of “further comprising applying a dimensionality reduction method to the copy numbers and the allele counts” received 08 May 2026.
The rejection on the ground of 112/b of claim 20 for reciting "the genomic loci having copy number instability” and “the allele loci” in Office action mailed 16 December 2025 is withdrawn in view of the amendment of “a plurality of genomic loci associated with copy number instability” and “a plurality of allele loci in the reference genome” received 08 May 2026.
The rejection on the ground of 112/b of claim 100 for reciting “the DNA fragments” in Office action mailed 16 December 2025 is withdrawn in view of the amendment of “wherein the first plurality of DNA fragments and the second plurality of DNA fragments are cell free DNA fragments” received 08 May 2026.
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.
The rejection below has been modified necessitated by amendment.
Claims 2, 3, 14, 20, 24, 49-50, and 98-100 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
(Step 1)
Claims 2-3, 14, 20, 24, 49, 50, and 98-100 are found to be directed to a statutory category of a process.
(Step 2A prong 1)
Under the BRI, the instant claims recite judicial exceptions that are an abstract idea of the type that is in the grouping of a “mental process”, such as procedures for evaluating, analyzing or organizing information, and forming judgement or an opinion. The instant claims further recite judicial exceptions that are an abstract idea of the type that is in the grouping of a “mathematical concept”, such as mathematical relationships and mathematical equations.
Independent claim 98 recites mental processes of “aligning sequence reads of the at least one million cell-free DNA fragments to a refence genome to obtain a plurality of bin values…”, “determining, based on the plurality of bin values, a plurality of copy numbers”, “aligning a sequence read of each DNA fragment of the second plurality to a corresponding allele locus in the reference genome”, “determining, for each sequenced DNA fragment aligned to an allele locus, an allele type…”, “counting the number of sequenced DNA fragments aligned to each allele locus, for each allele type…”, “inputting the plurality of copy numbers and the allele counts with a trained reference model to generate the tumor fraction estimating the proportion of DNA fragments originated from tumor cells among all DNA fragments in the DNA sample”, repeating the judicial exceptions above across an epoch to obtain a plurality of tumor fractions of the subject across the epoch, and “determining that a change in the plurality of tumor fractions of the subject across the epoch exceeds a threshold amount”.
Independent claim 98 mathematical concepts of “counting the number of sequenced DNA fragments aligned to each allele locus, for each allele type…” and “inputting the plurality of copy numbers and the allele counts with a trained reference model to generate the tumor fraction estimating the proportion of DNA fragments originated from tumor cells among all DNA fragments in the DNA sample”, and repeating the judicial exceptions above across an epoch to obtain a plurality of tumor fractions of the subject across the epoch.
Dependent claim 14 further recites a mathematical concept of “applying a dimensionality reduction method to the copy numbers and the allele counts”.
The claims recite analyzing/evaluating sequencing data through alignment (to obtain bin values and to align reads to a corresponding allele locus), determining copy numbers based on bin the plurality of bin values, determining an allele type, counting reads for allele types to get an allele count, inputting copy number and allele counts into a model to generate a tumor fraction, and determining that a change in the plurality of tumor fractions of the subject across the epoch exceeds a threshold amount. The human mind is capable of analyzing/evaluating sequencing data by performing these processes. The claims recite mathematical concepts of mathematical calculations as counting the number of sequence DNA fragments and inputting the plurality of copy numbers and allele counts into a trained reference model (this reference model encompasses models such as multivariate logistic regression and a regression algorithm which are mathematical models that input numeric data into a mathematical function to produce a numerical output of the estimated tumor fraction see claim 49) and applying the dimensionality reduction method includes mathematical calculations to reduce the dimensionality of the numerical data. Dependent claims 49 (except for the neural network and convolutional neural network which are additional elements addressed below), 50, and 99 further limit the mental process/mathematical concept recited in the independent claim but do not change their nature as a mental process/mathematical concept.
(Step 2A prong 2)
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). Integration into a practical application is evaluated by identifying whether there are any additional elements recited in the claim and evaluating those additional elements to determine whether they integrate the exception into a practical application.
The additional element in claim 98 sequencing a first plurality of DNA fragments in a DNA sample obtained from the DNA sample, wherein the first plurality of DNA fragments comprises at least one million cell -free DNA fragments for the analysis, the additional element in claim 2 of the first and the second sequencing are the same sequencing, the additional element in claim 3 of the sequencing is targeted panel sequencing using probes, the additional element in claim 20 of the first sequencing provides an average coverage of between 20x and 70,000x and the second sequencing provides an average coverage of between 1,000x and 70,000x, the additional element in claim 24 of wherein the DNA sample comprises one or a combination selected from the group of blood, whole blood, plasma, serum, urine, cerebrospinal fluid, fecal, saliva, tears, pleural fluid, pericardial fluid, and peritoneal fluid of the subject do not integrate the judicial exception into a practical application because this is adding insignificant extra solution activity of data gathering. These additional elements are insignificant extra solution activity because they only interact with the judicial exceptions by providing the judicial exceptions data to process.
The additional element in claim 98 of changing, responsive to determining that the change exceeds the threshold amount, a treatment for the subject based on the plurality of tumor fractions, wherein the treatment comprises applying agents for cancer to the subject, wherein the agents for cancer are selected from hormones, immune therapies, radiotherapy, or one or more cancer drugs, wherein the one or more cancer drugs include does not integrate the judicial exceptions into a practical application . This additional element of changing a treatment for the subject based on the plurality of tumor fractions does not integrate the judicial exception into a practical application because this step is mere instructions to apply the exception. The step of changing a treatment for the subject based on the plurality of tumor fractions is mere instructions to apply the exception because this is a general application of the judicial exception (i.e., the claim does not set out how the plurality of the tumor fractions increasing or decreasing is informing the treatment which is selected when changing the treatment) (see MPEP 2106.04(d)(2) and MPEP 2106.05(f)).
The additional elements in claim 49 of using a neural network and a convolutional neural network are not required by the claims because they are listed as alternative embodiments. Thus, under the BRI the model can be a regression model which is a judicial exception (i.e., a mathematical concept). These additional elements do not integrate the judicial exceptions into a practical application because they are not required by the claim. Further, the additional elements of using a neural network and a convolutional neural network amounts to using a computer to perform abstract ideas and is generally linking the abstract idea to the technological environment of neural networks (see MPEP 2106.05(h)) and do not integrate the judicial exceptions into a practical application because this is applying the judicial exceptions to a generic computer without an improvement to computer technology. These additional elements only interact with the judicial exceptions by using a generic computer as a tool to perform the judicial exceptions and generally links the abstract idea to the technological environment of neural networks.
Thus, the additional elements do not integrate the judicial exceptions into a practical application and claims 2, 3, 14, 20, 24, 49-50, and 98-101 are directed to the abstract idea.
(Step 2B)
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because:
The additional element in claim 98 sequencing a first plurality of DNA fragments in a DNA sample obtained from the DNA sample, wherein the first plurality of DNA fragments comprises at least one million cell -free DNA fragments for the analysis and sequencing a second plurality of DNA fragments in the DNA sample, the additional element in claim 2 of the first and the second sequencing are the same sequencing, the additional element in claim 3 of the sequencing is targeted panel sequencing using probes, the additional element in claim 20 of the first sequencing provides an average coverage of between 20x and 70,000x across a plurality of genomic loci associated with copy number instability and the second sequencing provides an average coverage of between 1,000x and 70,000x across a plurality of allele loci in the reference genome, the additional element in claim 24 of wherein the DNA sample comprises one or a combination selected from the group of blood, whole blood, plasma, serum, urine, cerebrospinal fluid, fecal, saliva, tears, pleural fluid, pericardial fluid, and peritoneal fluid of the subject, and the additional element in claim 100 of wherein the first plurality of DNA fragments and the second plurality of DNA fragments are cell free DNA fragments are conventional shown by Venn et al. (WO 2019204360 A1; previously cited) in [0010], [0115], and [0132]-[0135] which shows sequencing at least one million cell-free DNA fragments, a targeted panel using probes, average coverages within the range of 20x and 70,000x and within the range of 1,000x and 70,000x and shows the DNA samples are selected from the same group, Labgaa et al. (Oncogene 37, 3740–3752 (2018); previously cited) which shows targeted deep sequencing of cell-free DNA using probes with coverages within the range of 20x and 70,000x and within the range of 1,000x and 70,000x and utilizing blood samples on page 3742, the instant disclosure which shows that sequence reads are produced by sequencing such as Illumina parallel sequencing which is a commercially available sequencer (see [0140] and [0387] of instant disclosure), and the instant disclosure further shows that a number of targeted cancer assay panels are known in the art (see [0352] of instant disclosure).
The additional element in claim 98 of changing, responsive to determining that the change exceeds the threshold amount, a treatment for the subject based on the plurality of tumor fractions, wherein the treatment comprises applying agents for cancer to the subject, wherein the agents for cancer are selected from hormones, immune therapies, radiotherapy, or one or more cancer drugs, wherein the one or more cancer drugs wherein the one or more cancer drugs include Lenalidomide, Pembrolizumab, Trastuzumab, Bevacizumab, Rituximab, Ibrutinib, Human Papillomavirus Quadrivalent (Types 6, 11, 16, and 18) Vaccine, Pertuzumab, Pemetrexed, Nilotinib, Denosumab, Abiraterone acetate, Promacta, Imatinib, Everolimus, Palbociclib, Erlotinib, or Bortezomib is conventional as shown by Venn et al. (WO 2019204360 A1; previously cited) which shows changing a treatment of the subject (Venn et al. [0034]), Abdueva et al. (US 20190287645 A1; newly cited) which shows changing cancer treatment in cfDNA cancer monitoring (Abdueva et al. [0195]-[0197]), Sun et al. (US 20180032666 A1; newly cited) which shows changing cancer treatment in cfDNA cancer monitoring (Sun et al. [0130]), and Alam et al. (Open Access J Toxicol 2.5 (2018): 555600; newly cited) reviews cancer therapies which include hormone therapies and cancer immune therapies. It is noted that the additional element is “changing the treatment for a subject wherein the wherein the treatment comprises applying agents for cancer to the subject, wherein the agents for cancer are selected from hormones, immune therapies…” and what the change is responsive to (i.e., responsive to determining that a change exceeds a threshold amount) and based on (i.e., based on the plurality of tumor fractions) falls under the abstract idea.
The additional elements in claim 49 of a neural network and a convolutional neural network are not required by the claims because they are listed as alternative embodiments. Thus, under the BRI the model can be a regression model which is a judicial exception (i.e., a mathematical concept). These additional elements do not amount to significantly more because they are not required by the claim. Further, the additional elements of using a neural network and a convolutional neural network (which amounts to using a computer to perform abstract ideas) is conventional as shown by MPEP 2106.05(b) and MPEP 2106.05(d)(II).
Thus, the additional elements do not amount to significantly more than the judicial exceptions because they are conventional.
Response to Arguments
Applicant's arguments filed 08 May 2026 have been fully considered but they are not persuasive.
Arguments (Step 2A, Prong 1):
Applicant argues that the limitations including sequencing a plurality of DNA fragments, aligning sequence reads to corresponding loci of a reference genome, determining allele types and allele counts for sequenced DNA fragments, inputting a plurality of copy numbers and allele counts into a trained reference model to generate tumor fraction estimates and changing a treatment in response to the tumor fractions of the subject exceeding a threshold in claim 98 require processing large-scale genomic sequencing data, performing computational alignment of sequence reads to a reference genome, generating allele counts and copy number values, and applying a trained model to derive a tumor fraction measurement (Reply p. 10-11). Applicant further argues that these operations require specialized computational processing of biological sequencing datasets and cannot be practically be performed in the human mind (Reply p. 11).
This argument has been fully considered but found to be not persuasive. It is noted that sequencing DNA fragments and changing a treatment are identified as additional elements and are not characterized as being mental processes. The step of aligning sequence reads of the at least one million cell-free DNA fragments to a reference genome encompasses any process of aligning reads to a reference genome (such as a look up table to compare reads to reference genome locations) the human mind is capable of making an observation and judgment whether a read aligns to a location and the amount of data being aligned is interpreted as an indication that this mental process is repeated for all sequenced reads (repeating a mental process does not change its nature as a mental process). The step of determining allele types and allele counts encompasses making an observation and judgment when analyzing sequencing data to identify an allele type at a location and count these alleles. The step of inputting a plurality of copy numbers and allele counts into a trained reference model to generate tumor fraction estimates encompass inputting numerical values representing these characteristics into a model (which can be a logistic regression model which is a fitted mathematical equation) to calculate a numerical value using this mathematical method and the human mind is capable of using a mathematical model to determine a numerical output. Thus, the claims recite mental processes because the claims encompass mental processes as described above.
Applicant argues that merely using a trained model does not recite a mathematical concept at most the claims may involve computational techniques within a broader technological process for analyzing genomic sequencing data (Reply p. 11).
This argument has been fully considered but found to not be persuasive. The MPEP states “There is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word "calculating" in order to be considered a mathematical calculation. For example, a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation” (see MPEP 2106.04(a)(2)(I)(C)). The instant disclosure provides that the trained machine learning model can be a logistic regression model and a regression algorithm and using these models encompass performing a calculation using a fitted logistic regression equation using numerical values representing allele counts and copy numbers to output a numerical value representing tumor fraction. Thus, the use of the trained machine learning model encompasses performing a mathematical calculation using a fitted regression model/equation.
Arguments (Step 2A, Prong Two):
Applicant argues the analysis isolates the tumor fraction calculation and characterizes the remaining claim limitations as merely sequencing, data gather, and generic data processing and asserts that the treatment step is merely instructions to apply the abstract idea (Reply p. 13). Applicant argues that this analysis improperly dissects the claim and does not evaluate the ordered combination of claim elements as required (Reply p. 13). Applicant argues that the tumor fraction measurement is integrated into a real-world medical monitoring and treatment workflow (Reply p. 13). Applicant argues that the instant invention addresses technical challenges by combining copy number analysis and allele-specific fragment counting within a trained reference model to produce more accurate tumor fraction from non-invasive sequencing and this improvement enables effective monitoring of tumor burden using liquid biopsy samples (Reply p. 14).
These arguments have been fully considered but found to be not persuasive. The MPEP states at 2106.05(a) “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements… In addition, the improvement can be provided by the additional element(s) in combination with the recited judicial exception”. It is noted that combining copy number analysis and allele specific fragment counting within a trained reference model to produce more accurate tumor fractions is an improvement provided by the judicial exceptions and thus the argued improvement of more accurate effective monitoring of tumor burden is an improvement provided by the judicial exceptions alone. Further, the additional elements of first and second sequencing and changing a treatment for the subject based on the plurality of tumor fractions are analyzed in combination with the identified judicial exceptions. When analyzing the interaction between the judicial exceptions and the sequencing steps, the identified interaction (i.e., combination of judicial exceptions and additional elements) is that the additional elements of sequencing only interacts with the judicial exceptions in a manner which provides data to be processed by the judicial exceptions/abstract idea (thus the improvement is interpreted as not being provided by the combination between sequencing and the judicial exceptions). When analyzing the interaction between the judicial exceptions and the changing a treatment step, the identified interaction is mere instructions to apply the analysis in the context of changing a treatment due to the breadth of how the treatment selected when changing is based on the plurality of tumor fractions (thus the improvement is interpreted as not being provided by the combination between changing a treatment and the judicial exceptions). It is noted that the additional elements themselves alone or in combination do not provide the improvement argued improvement due to the sequencing and changing treatment being recited in a manner which encompasses several techniques already utilized in cfDNA monitoring in cancer. Thus, the improvement is interpreted as being provided by the judicial exception alone which does not constitute as an improvement to a technology.
Applicant argues that the relevant inquiry under Step 2A, Prong Two is not whether the claim specifies a particular drug regimen, but whether the claim integrates the alleged exceptions into a real-world technological or medical application and the instant invention provides a concrete clinical application of the genomic analysis pipeline and directly links the sequencing-based tumor fraction determination to patient treatment management (Reply p. 14).
This argument has been fully considered but found to be not persuasive. It is noted that the claims reciting a particular treatment is one of the many ways to show that the additional elements integrate the judicial exceptions into a practical application under Step 2A, Prong Two. Further as described above, the additional elements of sequencing (which is interpreted as insignificant extra solution activity of data gathering) and changing a treatment (which is interpreted as being mere instructions to apply the judicial exception) only interact with the judicial exceptions by gathering data to process using the abstract data analysis and mere instructions to apply the abstract data analysis to changing the treatment for a subject (see MPEP 2106.05(g) and MPEP 2106.05(f)). Thus, the recited additional elements do not integrate the judicial exceptions into a practical application.
Applicant argues that the relevant inquiry is not whether the underlying computational components are generic, but whether the claimed arrangement and interaction of those components provides a technological solution (Reply p. 15). Applicant further argues that this combination of genomic sequencing techniques and computational modeling represents a technological solution to a problem in cancer diagnostics and monitoring (Reply p. 15).
This argument has been fully considered but found to be not persuasive. The MPEP states “In computer-related technologies, the examiner should determine whether the claim purports to improve computer capabilities or, instead, invokes computers merely as a tool. Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1336, 118 USPQ2d 1684, 1689 (Fed. Cir. 2016)” (see MPEP 2106.05(a)(I)). In the instant case, it is interpreted that the computer only interacts with the abstract ideas in a manner as being utilized as a tool to perform the abstract ideas because the computer itself is not functioning in a different manner but is used as a tool to implement a series of data analysis steps. It is noted that the computational modeling as recited in the claims fall under the abstract idea. As described above, it is interpreted that the judicial exceptions alone provide the argued improvement which does not constitute as an improvement to technology (see MPEP 2106.05(a)).
Applicant argues that the Appeals Review Panel (ARP) determined that claims directed to training a machine learning model was patent eligible because the claims reflected improvements in how the model operated when learning successive tasks (Reply p. 15). Applicant argues that similarly here the claims recited a specific technological workflow for deriving tumor fraction measurements from sequencings data and using longitudinal tumor fraction changes to trigger treatment modifications (Reply p. 15).
This argument has been fully considered but found to be not persuasive. The claims at issue in Desjardins have a different fact pattern than the instant claims. The instant claims do not recite a training process which results in an improvement to a machine learning model itself or recite a process which changes how a machine learning model operates. The instant claims provide a series of abstract data analysis steps for analyzing sequencing data.
Arguments (Step 2B):
Applicant argues that the claims recite a specific and ordered combination of technological steps that process genomic sequencing data to generate clinically actionable tumor fraction measurements and to guide treatment decisions. Applicant further argues that factual support for the claimed limitations in claim are conventional (Reply p. 16-18).
This argument has been fully considered but found to not be persuasive. The MPEP states “Another consideration when determining whether a claim recites significantly more than a judicial exception is whether the additional element(s) are well-understood, routine, conventional activities previously known to the industry” which shows that the analysis for conventionality is reserved for additional elements (i.e., not judicial exceptions) (see MPEP 2106.05(d)). As set out above in the rejection the identified additional elements are conventional as provided by the cited references above.
Claim Rejections - 35 USC § 103
The rejection on the ground of 103 of claims 2, 3, 14, 20, 24, 49, 50, and 98-101 as being unpatentable over Venn et al. (WO 2019204360 A1; previously cited) in view of Adalsteinsson et al. (Nat Commun 8, 1324 (2017); previously cited) in Office action mailed 16 December 2025 is withdrawn in view of the amendment of “determining that a change in the plurality of tumor fractions of the subject across the epoch exceeds a threshold amount and changing, responsive to determining that the change exceeds the threshold amount, a treatment for the subject based on the plurality of tumor fractions, Lenalidomide, Pembrolizumab, Trastuzumab, Bevacizumab, Rituximab, Ibrutinib, Human Papillomavirus Quadrivalent (Types 6, 11, 16, and 18) Vaccine, Pertuzumab, Pemetrexed, Nilotinib, Denosumab, Abiraterone acetate, Promacta, Imatinib, Everolimus, Palbociclib, Erlotinib, or Bortezomib” received 08 May 2026.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The rejection below is newly recited necessitated by amendment.
Claims 2, 3, 14, 20, 24, 49, 50, and 98-100 are rejected under 35 U.S.C. 103 as being unpatentable over Venn et al. (WO 2019204360 A1; previously cited) in view of Adalsteinsson et al. (Nat Commun 8, 1324 (2017); previously cited) in view of Alam (Open Access J Toxicol 2.5 (2018): 555600; newly cited).
Claim 98 is directed to a method for determining, in a DNA sample obtained from a subject, a tumor fraction estimating a proportion of DNA fragments originated from tumor cells, comprising: (a) sequencing a first plurality of DNA fragments in the DNA sample or derived from the DNA sample, wherein the first plurality of DNA fragments comprises at least one million cell-free DNA fragments;
Venn et al. shows sequencing cell-free nucleic acids in a DNA sample obtained from the patient to obtain sequence reads (Venn et al. [0114]). Venn et al. shows millions of cell-free nucleic acid fragments are sequenced (Venn et al. [0115]). Venn et al. shows different sequencing methods are used when deriving certain data from the reads and shows that a whole genome assay plasma looks for copy number variation in the genome and target plasma assay looks for somatic copy number alterations in a targeted panel of genes (Venn et al. [0130]-[0132] and [0135]).
(b) sequencing a second plurality of DNA fragments in the DNA sample; aligning a sequence read of each sequenced DNA fragment of the second plurality to a corresponding allele locus in the reference genome; determining, for each sequenced DNA fragment aligned to an allele locus, an allele type and using the allele type to determine whether the sequenced DNA fragment is originated from a tumor cell or a non-tumor cell;
Venn et al. shows different sequencing methods are used when deriving certain data from the reads and shows that a targeted plasma assay looks for single nucleotide variants, insertions, and deletions (Venn et al. [0135]).Venn et al. shows using sequence reads to identify support for each variant in a variant set by aligning a sequence read in the plurality of sequence reads to a region in a reference genome in order to determine whether the sequence read contains a first variant (Venn et al. [0018]).
and counting the number of sequenced DNA fragments aligned to each allele locus, for each allele type, as an allele count at the allele locus for the allele type; and
Venn et al. shows that a plurality of sequence reads is used to identify support for each variant in a variant set thereby determining an observed frequency of each variant in the variant set (Venn et al. [0009]).
(c) inputting the plurality of copy numbers and the allele counts into a trained reference model to generate the tumor fraction estimating the proportion of DNA fragments originated from tumor cells among all DNA fragments in the DNA sample;
Venn et al. shows determining tumor fraction in cell-free nucleic acids of a liquid biological sample of a subject by evaluating an observed frequency of each respective variant in a first variant set against observed frequency of the respective reference set (Venn et al. [0009]). Venn et al. shows that each variant in the variant set is for a different genetic variation in the genome of the subject (Venn et al. [0047]). Venn et al. shows that the ctDNA fraction (or tumor fraction in cell-free DNA) is estimated by adding the probabilities provided by each variant in the set of variants in logarithmic space which is a regression algorithm (Venn et al. [0173]). Venn et al. shows that observed sequence reads are corrected for background copy number such as sequence reads that support variants that arise from chromosomes or portions of chromosomes that are duplicated in the subject are corrected for this duplication (Venn et al. [0179]). Venn et al. shows that this may be done by normalization of reads based on copy number or allowing for more than one value of ctDNA fraction which enables assessment of heterogeneity within/across tumors (Venn et al. [0179]).
repeating steps (a)-(c) at a plurality of time points across an epoch to obtain a plurality of tumor fractions of the subject across the epoch; and
Venn et al. shows repeating the steps at a plurality of time points across an epoch to obtain a plurality of tumor fractions across an epoch (Venn et al. [0031]).
determining that a change in the plurality of tumor fractions of the subject across the epoch exceeds a threshold amount and changing, responsive to determining that the change exceeds the threshold amount, a treatment for the subject based on the plurality of tumor fractions,
Venn et al. shows changing a treatment of the subject when the tumor fraction of the subject is observed to change by a threshold amount across the epoch (Venn et al. [0034]).
Venn et al. does not show aligning sequence reads to a reference genome to obtain a plurality of bin values respectively corresponding to a plurality of regions of the reference genome, and each bin value represents a count of cell-free nucleic acids from the reference genome that maps to the corresponding bin; and determining, based on the plurality of bin values, a plurality of copy numbers
Like Venn et al., Adalsteinsson et al. shows utilizing cell-free DNA to predict tumor fraction. Adalsteinsson et al. shows aligning cell-free DNA to a reference genome to obtain a plurality of bin values which corresponds to a plurality of regions of the reference genome with each bin value representing a count of cell-free nucleic acids from the reference genome that corresponds to the bin (Adalsteinsson et al. page 7 right col. – page 8 left col.). Adalsteinsson et al. further shows determining a plurality of copy numbers based on the plurality of bin values (Adalsteinsson et al. page 8 left col.).
Venn et al. in view of Adalsteinsson et al. does not show wherein the agents for cancer are selected from hormones, immune therapies, radiotherapy, or one or more cancer drugs, wherein the one or more cancer drugs wherein the one or more cancer drugs include Lenalidomide, Pembrolizumab, Trastuzumab, Bevacizumab, Rituximab, Ibrutinib, Human Papillomavirus Quadrivalent (Types 6, 11, 16, and 18) Vaccine, Pertuzumab, Pemetrexed, Nilotinib, Denosumab, Abiraterone acetate, Promacta, Imatinib, Everolimus, Palbociclib, Erlotinib, or Bortezomib.
Like Venn et al. in view of Adalsteinsson et al., Alam et al. shows treating subjects with cancer. Alam et al. shows cancer treatments including hormone therapy and cancer immunotherapy (Alam et al. page 3 right col.).
Claim 2 is directed to wherein the first and the second sequencing are the same sequencing. Claim 3 is directed to wherein: the sequencing is targeted panel sequencing, the targeted panel sequencing uses a plurality of probes, and each probe in the plurality of probes includes a nucleic acid sequence that corresponds to the sequence, or a complementary sequence thereof, of a portion of the reference genome.
Venn et al. shows a targeted plasma assay that looks for somatic copy number alterations in the targeted panel of genes and SNVs in targeted panel of genes, insertions in targeted panel of genes, and deletions in targeted panel of genes with a coverage of at least 50,000x (Venn et al. [0135]). Venn et al. shows that target DNA sequences are enriched using hybridization probes (Venn et al. [0314]).
Claim 14 is directed to further comprising applying a dimensionality reduction method to the copy numbers and the allele counts.
Venn et al. shows copy numbers and allele counts which are determined which produces features from the sequence reads with reduced dimensionality (i.e., sequencing data which is reduced to a numeric feature) (Venn et al. [0009]-[0010]).
Claim 20 is directed to wherein: the first sequencing provides an average coverage of between 20x and 70,000x across a plurality of genomic loci associated with copy number instability, and the second sequencing provides an average coverage of between 1,000x and 70,000x across a plurality of allele loci in the reference genome.
Venn et al. shows a targeted plasma assay that looks for somatic copy number alterations in the targeted panel of genes and SNVs in targeted panel of genes, insertions in targeted panel of genes, and deletions in targeted panel of genes with a coverage of at least 50,000x (Venn et al. [0135]).
Claim 24 is directed to wherein the DNA sample comprises one or a combination selected from the group consisting of blood, whole blood, plasma, serum, urine, cerebrospinal fluid, fecal, saliva, tears, pleural fluid, pericardial fluid, and peritoneal fluid of the subject.
Venn et al. shows that the DNA sample may be blood, whole blood, plasma, serum, urine, cerebrospinal fluid, fecal, saliva, sweat, tears, pleural fluid, pericardial fluid, or peritoneal fluid of the subject (Venn et al. [0110]).
Claim 49 is directed to wherein the reference model is a multivariate logistic regression, a neural network, a convolutional neural network, a support vector machine, a decision tree, a regression algorithm, or a supervised clustering model.
Venn et al. shows that the ctDNA fraction (or tumor fraction in cell-free DNA) is estimated by adding the probabilities provided by each variant in the set of variants in logarithmic space which is a regression algorithm (Venn et al. [0173]).
Claim 50 is directed to wherein each allele type is a single nucleotide variant associated with a predetermined genomic location, an insertion mutation associated with a predetermined genomic location, a deletion mutation associated with a predetermined genomic location, a somatic copy number alteration, a nucleic acid rearrangement associated with a predetermined genomic locus, or an aberrant methylation pattern associated with a predetermined genomic location.
Venn et al. shows a variant in the first variant set is a single nucleotide variant associated with a predetermined genomic location, an insertion mutation associated with a predetermined genomic location, a deletion mutation associated with a predetermined genomic location, a somatic copy number alteration, a nucleic acid rearrangement associated with a predetermined genomic locus, or any aberrant methylation pattern associated with a predetermined genomic location (Venn et al. [0010]).
Claim 99 is directed to wherein an allele count at each allele locus represents an allele frequency.
Venn et al. shows that a plurality of sequence reads is used to identify support for each variant in a variant set thereby determining an observed frequency of each variant in the variant set (Venn et al. [0009]).
Claim 100 is directed to wherein the DNA fragments are cell free DNA fragments.
Venn et al. shows sequencing cell-free nucleic acids in a DNA sample obtained from the patient to obtain sequence reads (Venn et al. [0114]).
An invention would have been obvious to one or ordinary skill in the art if some motivation in the prior art would have led that person to modify reference teachings to arrive at the claimed invention. It would have been obvious to one of ordinary skill in the art before the effective filling date to have modified the process of estimating tumor fraction of a cell-free DNA sample with sequence read correction for background copy number of Venn et al. to incorporate the process of aligning cell-free DNA to a reference genome to obtain bin values to assign copy number states for each bin of Adalsteinsson et al. because this will allow for a process that can compute and utilize bin specific copy number states for correcting sequence read counts that support a variant used for calculating tumor fraction in a sample which will give context to varying allele counts caused by deletions and duplications in differing regions of the genome (Adalsteinsson et al. page 8 left col.). It would have been further obvious to one of ordinary skill in the art before the effective filling date of the invention to have substituted the treatment of Venn et al. in view of Adalsteinsson et al. with hormone therapy for treating cancer and cancer immunotherapy of Alam et al. because both Venn et al. in view of Adalsteinsson et al. and Alam et al. show treating a subject for cancer and would yield predictable results of using a specific treatment such as hormone therapy and/or cancer immunotherapy when changing the treatment. One would have a reasonable expectation of success because Venn et al. shows obtaining cell-free DNA for estimating tumor fraction utilizing a process for accounting for copy number while Adalsteinsson et al. shows a specific process of analyzing cell-free DNA data to produce copy number states for regions of a genome and Venn et al. in view of Adalsteinsson et al. show changing a treatment for cancer based on monitoring a tumor fraction across an epoch while Alam et al. shows specific classes of cancer treatments (i.e., hormone therapy and cancer immunotherapy) to be used when treating a subject for cancer.
Response to Arguments
Applicant's arguments filed 08 May 2026 have been fully considered but they are not persuasive.
Applicant argues that neither reference teaches the specific analytical framework in claim 98 which requires sequencing a second plurality of DNA fragments, aligning reads to allele loci, determining an allele type for each sequenced DNA fragment and using the allele type to determine whether the fragment originated from a tumor cell or a non-tumor cell, and counting the number of sequencing DNA fragments aligned to each allele locus for each allele type to generate allele counts that are then combined with copy numbers and input into a trained reference model to generate the tumor fraction estimate (Reply p. 19). Applicant further argues that the cited portions of Venn describes identifying variants and determining variant frequencies from sequence reads, but does not disclose classifying individual fragments as tumor-derived or non-tumor-derived or counting fragments by allele type at each allele locus (Reply p. 19).
This argument has been fully considered but found to be not persuasive. Venn et al. shows using sequence reads to identify support for each variant in a variant set by aligning a sequence read in the plurality of sequence reads to a region in a reference genome in order to determine whether the sequence read contains a first variant (Venn et al. [0018]). This step is interpreted as being that sequence reads identifying support for variants in a variant set is using the allele type to determine whether the sequenced DNA fragment is originated from a tumor cell or a non-tumor cell because these variants because Venn et al. shows that such variants in the disclosed variant sets of the present disclosure are presumed to represent ctDNA (see Venn et al. [0086]) thus determining that a read supports a variant in the variant set is a determination that the sequence read is originated from a tumor cell and reads not supporting a variant in a variant set is a determination that the sequence reap is originated from a non-tumor cell.
Applicant further argues Adalsteinsson is directed to estimating tumor fraction from genome-wide copy number signals and does not disclose allele-type determination, fragment-level tumor/non-tumor classification, or combining allele counts with copy number information in a trained reference model as required by the claim (Reply p. 19).
These arguments have been fully considered but found to be not persuasive. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). As described above, Venn et al. in view of Adalsteinsson et al. shows allele-type determination (identifying support for a variant in a variant set see Venn et al. [0018]), fragment-level tumor/non-tumor classification (reads that support variants in the variant set are presumed to have originated from tumor cells and thus reads that do not support variants in the variant set are interpreted as being originating from non-tumor cells see Venn et al. [0086]), and combining allele counts with copy number information is provided by Venn et al. in view of Adalsteinsson et al. where copy number information informs and can correct frequency of observed variants in the presence of copy number duplications or deletions. Thus, the claims are unpatentable over Venn et al. in view of Adalsteinsson et al. in view of Alam et al. as described above.
Conclusion
No claims are allowed.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/J.E.H./Examiner, Art Unit 1685
/KAITLYN L MINCHELLA/Primary Examiner, Art Unit 1685
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