DETAILED ACTION
Applicant’s response, filed Aug 19 2026, has been fully considered. Rejections and/or objections not reiterated from previous Office Actions are hereby withdrawn. 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 .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Status
Claims 11-14 and 22-28 are pending.
Claims 1-10 and 15-21 are canceled.
Claims 22-28 are newly added.
Claims 11-14 and 22-28 are rejected.
Priority
Applicant's claim for the benefit of a prior-filed application, PCT/CN2020/122821, filed Oct 22 2020, is acknowledged.
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d) to App. No. CN201911088433.6, filed Nov 8 2019. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Accordingly, each of claims 11-14 and 22-28 are afforded the effective filing date of Nov 8 2019.
Information Disclosure Statement
The information disclosure statement (IDS) filed on Aug 17 2026 is in compliance with the provisions of 37 CFR 1.97 and has therefore been considered. A signed copy of the IDS document is included with this Office Action.
Specification
The amendments to the specification submitted Aug 17 2026 are accepted and the outstanding objections from the previous Office Action are withdrawn.
Claim Objections
The outstanding objections to the claims are withdrawn in view of the amendments submitted herein.
Claim Rejections- 35 USC § 112
The outstanding rejections to the claims are withdrawn in view of the amendments submitted herein.
35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 11-14 and 22-28 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. The instant rejection is newly stated and is necessitated by claim amendment.
Claim 11 recites “wherein the DNA methylation haplotype block of the sample of interest, the DNA methylation haplotype block of the respective classification label, regions of the sample of interest where DNA copy number variation occurs, and regions of the respective classification label where DNA copy number variation occurs are those shown in any one, any two, any three, any four, any five or all six of Tables 1-6, or as shown in Table 11 and/or Table 12:”, wherein each of the tables lists a chromosome, a starting site, and a termination site. However, the claim does not disclose what reference genome or database these positions are in reference to. Therefore the claim is indefinite for recitation of locations on a chromosome without reciting a reference sequence for comparison, as one of skill in the art would be unable to determine the locations as recited. The rejection may be overcome by clarifying the reference genome sequence. Claims 12-14 and 22-28 are rejected based on their dependency from claim 11.
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 11-14 and 22-28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to one or more judicial exceptions without significantly more. Any newly recited portions are necessitated by claim amendment.
MPEP 2106 organizes judicial exception analysis into Steps 1, 2A (Prongs One and Two) and 2B as follows below. MPEP 2106 and the following USPTO website provide further explanation and case law citations: uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials.
Framework with which to Evaluate Subject Matter Eligibility:
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter;
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e. a law of nature, a natural phenomenon, or an abstract idea;
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application (Prong Two); and
Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept.
Framework Analysis as Pertains to the Instant Claims:
Step 1
With respect to Step 1: yes, the claims are directed to a method, i.e., a process, machine, or manufacture within the above 101 categories [Step 1: YES; See MPEP § 2106.03].
Step 2A, Prong One
With respect to Step 2A, Prong One, the claims recite judicial exceptions in the form of abstract ideas. The MPEP at 2106.04(a)(2) further explains that abstract ideas are defined as:
mathematical concepts (mathematical formulas or equations, mathematical relationships and mathematical calculations);
certain methods of organizing human activity (fundamental economic practices or principles, managing personal behavior or relationships or interactions between people); and/or
mental processes (procedures for observing, evaluating, analyzing/ judging and organizing information).
The claims also recite a law of nature or a natural phenomenon. The MPEP at 2106.04(b) further explains that laws of nature and natural phenomena include naturally occurring principles/relations and nature-based products that are naturally occurring or that do not have markedly different characteristics compared to what occurs in nature.
With respect to the instant claims, under the Step 2A, Prong One evaluation, the claims are found to recite abstract ideas that fall into the grouping of mental processes (in particular procedures for observing, analyzing and organizing information) and mathematical concepts (in particular mathematical relationships and formulas) as well as a law of nature or a natural phenomenon are as follows:
Independent claim 11: (4) classifying the DNA fragments in the library using a DNA classification method the method of claim 1, wherein the DNA fragments serve as a DNA in the sample of interest,
wherein the DNA classification method comprises:
calculating a methylation haplotype load (MHL) value of a DNA methylation haplotype block of a sample of interest and calculating a DNA copy number variation data of the sample of interest, wherein the sample of interest is the urine sample;
calculating a first similarity between the MHL value of the DNA methylation haplotype block of the sample of interest and an MHL value of a DNA methylation haplotype block of a respective classification label, and calculating a second similarity between the DNA copy number variation data of the sample of interest and a DNA copy number variation data of the respective classification label; and
determining a classification for the DNA in the sample of interest by using a classifier model and based on the first similarity and the second similarity,
wherein the MHL value of the DNA methylation haplotype block of the sample of interest, the MHL value of the DNA methylation haplotype block of the respective classification label, the DNA copy number variation data of the sample of interest, and the DNA copy number variation data in the respective classification label are calculated from sequencing data of the DNA fragments in the library;
wherein the sequencing data is whole genome bisulfite sequencing data obtained at a sequencing depth of 1X-5X, and
wherein the DNA methylation haplotype block of the sample of interest, the DNA methylation haplotype block of the respective classification label, regions of the sample of interest where DNA copy number variation occurs, and regions of the respective classification label where DNA copy number variation occurs are those shown in any one, any two, any three, any four, any five or all six of Tables 1-6, or as shown in Table 11 and/or Table 12 in the claims.
Dependent claim 27: voting for each of groups (I)-(IV), and determining the group with the highest number of votes as the final classification, wherein the event where equal numbers of votes occur means that the category with the highest prediction probability among the groups with the equal number of votes is determined as the final classification.
Dependent claims 24-26 and 28 recite further steps that limit the judicial exceptions in independent claim 11 and, as such, also are directed to those abstract ideas. For example, claim 24 further limits determining the classification to comprising using a random forest model to determine a correlation; claim 25 further limits determining the correlation to comprising ranking values to form a vector and inputting the vector into a random forest model; claim 26 further limits the random forest models to including four random forest binary classifiers comprised of specific comparisons; and claim 28 further limits the DNA methylation haplotype block of the sample of interest and/or the regions of the sample of interest where DNA copy number variation occurs to being the same as those in the respective classification labels.
The abstract ideas recited in the claims are evaluated under the Broadest Reasonable Interpretation (BRI) and determined to each cover performance either in the mind and/or by mathematical operation because the method only requires a user to manually determine a classification for a sample based on its DNA features. Without further detail as to the methodology involved in “classifying”, “calculating”, “determining”, and “voting”, under the BRI, one may simply, for example, use pen and paper to calculate a methylation haplotype load and a DNA copy number variation, calculate a first and second similarity between the MHL and copy numbers for the sample of interest and a classification label, ranking the values to form a vector sequence, and determining a classification for the sample using a classifier, where the classifier is a random forest model that determines a correlations based on the similarity scores using the vector sequences as input. The steps directed to “calculating” an MHL value and DNA copy number variation data, “calculating the similarity” between the sample of interest and a respective classification label, “determining” a classification using a classifier model, where the classifier is a random forest model, require mathematical techniques as the only supported embodiments. The claims explicitly recite mathematical techniques in words, such as “calculating” values and using models, which are explicitly limited to mathematical models in the dependent claims, to determine classifications. The specification as published supports the interpretation of the claims requiring mathematical techniques as the only supported embodiments at: FIG. 3B, 4B-4C; [0174; 0189-0193; 0195].
Further, the claims recite the natural relationship between the methylation or copy number variation status of a patient and the classification of the patient as having a urogenital tumor.
Therefore, claim 11 and those claims dependent therefrom recite an abstract idea and a law of nature/natural phenomenon [Step 2A, Prong 1: YES; See MPEP § 2106.04].
Step 2A, Prong Two
Because the claims do recite judicial exceptions, direction under Step 2A, Prong Two, provides that the claims must be examined further to determine whether they integrate the judicial exceptions into a practical application (MPEP 2106.04(d)). A claim can be said to integrate a judicial exception into a practical application when it applies, relies on, or uses the judicial exception in a manner that imposes a meaningful limit on the judicial exception. This is performed by analyzing the additional elements of the claim to determine if the judicial exceptions are integrated into a practical application (MPEP 2106.04(d).I.; MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the judicial exceptions, the claim is said to fail to integrate the judicial exceptions into a practical application (MPEP 2106.04(d).III).
Additional elements, Step 2A, Prong Two
With respect to the instant recitations, the claims recite the following additional elements:
Independent claim 11: (1) obtaining a urine sample and extracting urine sediment DNAs;
(2) fragmenting the DNAs into fragments of 300-500bp; and
(3) constructing a whole genome library, preferably a whole genome methylation sequencing library, such as a whole genome bisulfite sequencing library, using the obtained DNA fragments.
Dependent claims 12-14 and 22-23 recite steps that further limit the recited additional elements in the claims. For example, claims 12 and 22 further limit the examined human urogenital tumor to being specific types of cancer; claims 13 and 23 further limits the urine sample to being urine sediment of urina sanguinus; claim 14 further limits the DNA fragments to 350-450bp.
Considerations under Step 2A, Prong Two
With respect to Step 2A, Prong Two, the additional elements of the claims do not integrate the judicial exceptions into a practical application for the following reasons. Those steps directed to data gathering, such as “obtaining a urine sample and extracting urine sediment DNAs”, “fragmenting the DNAs into fragments of 300-500bp” or 350-450bp, “constructing a whole genome bisulfite sequencing library”, perform functions of collecting the data needed to carry out the judicial exceptions. Data gathering and outputting do not impose any meaningful limitation on the judicial exceptions, or on how the judicial exceptions are performed. Data gathering and outputting steps are not sufficient to integrate judicial exceptions into a practical application (MPEP 2106.05(g)).
The specification discloses a need to develop new means having good specificity and sensitivity for the detection of urogenital tumors at p. 1, lines 16-18 (see also p. 11, lines 11-32), but does not provide a clear explanation for how the additional elements provide these improvements beyond the function of data gathering as described above. Therefore, the additional elements do not clearly improve the functioning of a computer, or comprise an improvement to any other technical field. Further, the additional elements do not clearly affect a particular treatment; they do not clearly require or set forth a particular machine; they do not clearly effect a transformation of matter; nor do they clearly provide a nonconventional or unconventional step (MPEP2106.04(d)).
Thus, none of the claims recite additional elements which would integrate a judicial exception into a practical application, and the claims are directed to one or more judicial exceptions [Step 2A, Prong 2: NO; See MPEP § 2106.04(d)].
Step 2B (MPEP 2106.05.A i-vi)
According to analysis so far, the additional elements described above do not provide significantly more than the judicial exception. A determination of whether additional elements provide significantly more also rests on whether the additional elements or a combination of elements represents other than what is well-understood, routine, and conventional. Conventionality is a question of fact and may be evidenced as: a citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s).
With respect to the instant claims, the prior art to Feber et al. (Clinical Epigenetics, 2017, 9(8):1-10; previously cited; Methods, p. 2-4), Yao et al. (Oncotarget, 6(38), p.40611; previously cited; Material and Methods, p. 9-10), Daniunaite (Doctoral dissertation, 2017, Vilniaus universitetas; p. 54, par. 3 through p. 57, par. 3; Figure 2.2; previously cited), and Jarrard et al. (US 2018/0135136; previously cited; [0094; 0135]) disclose that extracting urine sediment DNA from a sample, fragmenting the DNA into fragments of 300-500bp or 350-450bp, and constructing a whole genome library as in claims 11 and 14 is a data gathering element that is routine, well-understood and conventional in the art. Further, the specification as published discloses that urine sediment can be obtained via technical means known to a person skilled in the art [0037]. As such, the claims simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (MPEP2106.05(d)). The data gathering steps as recited in the instant claims constitute a general link to a technological environment which is insufficient to constitute an inventive concept which would render the claims significantly more than the judicial exception (MPEP2106.05(g)&(h)).
Taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception(s). Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claims as a whole do not amount to significantly more than the exception itself [Step 2B: NO; See MPEP § 2106.05].
Therefore, the instant claims are not drawn to eligible subject matter as they are directed to one or more judicial exceptions without significantly more. For additional guidance, applicant is directed generally to the MPEP § 2106.
Response to Applicant Arguments
At p. 34, par. 5, through p. 35, par. 1, Applicant submits that claim 11 has been amended to incorporate the sequencing depth and library limitations of original claim 8, and claim 11 now recites a specific physical transformation of matter. Applicant submits that claim 11 integrates the judicial exceptions into a practical application by providing a specific, non-invasive diagnostic tool that achieves high-accuracy tumor diagnosis at a low a sequencing depth, tumor localization via the multi-stage classifier, and prognostic risk stratification.
It is respectfully submitted that this is not persuasive. First, the claims do not actually require performing the sequencing at 1X-5X sequencing depth. The claim recites only step (3) of constructing a library, and later limits the sequencing data being analyzed to having been sequenced at a sequencing depth of 1X-5X. Therefore, the sequencing data is interpreted as a product-by-process limitation which is only limited by the structure of having had 1X-5X sequencing performed. Therefore Applicant’s arguments are not entirely commensurate with the scope of the claims.
Regarding a physical transformation in the claims, the additional elements in the claims merely serve to process DNA from a urine sample for sequencing to provide sequencing data which is analyzed by the judicial exceptions. Therefore, when considering the claims as a whole, the additional elements in the claims serve a data gathering function to the judicial exceptions (see MPEP 2106.05(g)). The transformation from DNA to sequencing data is not a particular transformation which can provide a practical application because, for data, mere "manipulation of basic mathematical constructs [i.e.,] the paradigmatic ‘abstract idea,’" has not been deemed a transformation (see CyberSource v. Retail Decisions, 654 F.3d 1366, 1372 n.2, 99 USPQ2d 1690, 1695 n.2 (Fed. Cir. 2011) (quoting In re Warmerdam, 33 F.3d 1354, 1355, 1360, 31 USPQ2d 1754, 1755, 1759 (Fed. Cir. 1994)); MPEP 2106.05(c)).
The improvements argued by Applicant, those of a specific, non-invasive diagnostic tool that achieves high-accuracy tumor diagnosis at a low a sequencing depth, tumor localization via the multi-stage classifier, and prognostic risk stratification, are all improvements that are a result of the performance of the judicial exceptions rather than the additional elements. The analysis at Step 2A, Prong 2, considers the claims as a whole, i.e., the additional elements in combination with the judicial exceptions (see MPEP 2106.05(a)), although the integration or improvement provided in the claim must flow from the additional elements and not the judicial exceptions to be considered persuasive. As the additional elements in the claims merely provide a data gathering function for the judicial exceptions, which then provide all of the improvements as submitted by Applicant, the claims do not recite a practical application.
At p. 35, par. 2, Applicant submits that the claims cannot be performed using a pen and paper because the calculations for MHL values, running random forest models, and integrating hundreds of selected DNA features cannot practically be performed in the mind. Applicant points to SRI Int'l, Inc. v. Cisco Systems, Inc., 930 F.3d 1295, 1304 (Fed. Cir. 2019) and MPEP §2106.04(a)(2)III.A. which state that “Claims do not recite a mental process when they do not contain limitations that can practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitations”.
It is respectfully submitted that this is not persuasive. The claim includes limitations which encompass purely mental actions as set forth in the above rejections. In MPEP 2106.04(a)(2), section III(A), examples that cannot practically be performed in the mind are provided, and include a method for calculating an absolute position of a GPS receiver and an absolute time of reception of satellite signals, detecting suspicious activity by using network monitors and analyzing network packets (SRI), specific data encryption method for computer communication involving a several-step manipulation of data, a method for rendering a halftone image of a digital image where the method required the manipulation of computer data structures and the output of a modified computer data structure. In contrast, the MPEP notes that the limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. The MPEP therefore makes clear that limitations which cannot practically be performed in the mind are those in which the human mind is not equipped to perform the claim limitations. The term practical is not meant to indicate that as a matter of practicality, one would perform a method preferentially on a computer rather than mentally. The MPEP makes clear that “practical” indicates that a human mind is not capable of performing the recited action. That the performance of such a task would be cumbersome or take a large amount of time because of the scale of the data to be analyzed is not changed by the fact that the human mind is capable of performing the task. Further, the use of a physical aid, such as pen and paper or a computer, does not negate the mental and mathematical nature of said limitations at Step 2A, Prong 1 (see MPEP 2106.05(f)). As discussed in the above rejection, each of the limitations pointed to by Applicant is considered to be able to be performed mentally.
Additionally, even if the claims were considered to not be able to be performed practically in the human mind, the limitations also recite mathematical techniques, as described in the above rejection. Applicant has provided no arguments against the mathematical limitations in the claims. Therefore, the claims would continue to recite mathematical processes even if Applicant’s argument regarding mental processes were found convincing.
At p. 35, par. 3, Applicant submits that the particular integration of MHL and CNV features for multi-class tumor classification is not conventional at Step 2B.
It is respectfully submitted that this is not persuasive. MPEP 2106.05(d) sets forth that, at Step 2B, it is the additional elements which are examined to determine whether they are well-understood, routine, conventional activities previously known to the industry. The analysis at Step 2A, Prong 2, considers the claims as a whole, i.e., the additional elements in combination with the judicial exceptions (see MPEP 2106.05(a)), although the integration or improvement provided in the claim must flow from the additional elements and not the judicial exceptions to be considered persuasive. However, Step 2B requires examining only the additional elements, either alone or in combination with one another, for conventionality. An “inventive concept” is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim as a whole amounts to significantly more than the judicial exception itself (Alice Corp., 573 U.S. at 27-18, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. at 72-73, 101 USPQ2d at 1966)). The limitations pointed to be Applicant are considered to recite a judicial exception as described above and are therefore not considered at Step 2B. The cited references to Feber, Yao, Daniunaite, and Jarrard provide evidence that the additional elements of the claims are well-understood, routine, and conventional in the art.
Claim Rejections - 35 USC § 102
The outstanding rejections from the previous Office Action are withdrawn in view of the amendments submitted herein. Specifically, Levin et al. (US 2022/0213558) does not teach at least “calculating a methylation haplotype load (MHL) value” as recited in amended claim 11, as submitted by Applicant at p. 36, par. 2.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
A. Claims 11-14, 22-24, and 28 are rejected under 35 U.S.C. 103 as being unpatentable over Cheng et al. (Clinical Chemistry, Jul 1 2019, 65(7):927-936; newly cited) in view of Patel et al. (Scientific Reports, 2017, 7(5554):1-12; newly cited) and Drake et al. (WO2019200410; cited on the May 20 2024 IDS). The instant rejection is newly stated and is necessitated by claim amendment.
Cheng discloses noninvasive detection of bladder cancer by the genome-wide assessment of methylomic and copy number aberrations (abstract). Cheng teaches the instant claims as follows.
Claim 11 discloses method for the detection, diagnosis, classification, risk assessment or prognostic assessment of a human urogenital tumor, comprising:
(1) obtaining a urine sample and extracting urine sediment DNAs;
Cheng teaches collecting urine samples from patients and centrifuging to collect cfDNA (p. 928, col. 1, par. 4 through col. 2, par. 3).
Cheng does not teach extracting sediment DNA from urine. See below for teachings by Patel.
(2) fragmenting the DNAs into fragments of 300-500bp;
Cheng does not teach this limitation. See below for teachings by Patel.
(3) constructing a whole genome bisulfite sequencing library, using the obtained DNA fragments; and
Cheng teaches constructing DNA libraries with bisulfite modification followed by shallow-depth whole genome sequencing (p. 928, col. 2, par. 4).
(4) classifying the DNA fragments in the library using a DNA classification method, wherein the DNA fragments serve as a DNA in the sample of interest,
Cheng teaches performing bladder cancer detection by hypomethylation and copy number aberrations (p. 929, col. 2, par. 2).
wherein the DNA classification method comprises:
calculating a methylation haplotype load (MHL) value of a DNA methylation haplotype block of a sample of interest and calculating a DNA copy number variation data of the sample of interest, wherein the sample of interest is the urine sample;
Cheng teaches establishing mean methylation and copy number levels across the whole genome (p. 929, col. 2, par. 2).
Cheng does not teach calculating MHL. See below for teachings by Drake.
calculating a first similarity between the MHL value of the DNA methylation haplotype block of the sample of interest and an MHL value of a DNA methylation haplotype block of a respective classification label, and calculating a second similarity between the DNA copy number variation data of the sample of interest and a DNA copy number variation data of the respective classification label; and
Cheng teaches examining methylation and copy number levels across the whole genome in cancer free control samples and bladder cancer cases (i.e., respective classification labels), determining that bladder cancer cases showed a larger proportion of bins with significant hypomethylation (i.e., a first similarity) and copy number changes (i.e., a second similarity) (p. 929, col. 2, par. 2).
determining a classification for the DNA in the sample of interest by using a classifier model and based on the first similarity and the second similarity,
Cheng does not teach this limitation. See below for teachings by Drake.
wherein the MHL value of the DNA methylation haplotype block of the sample of interest, the MHL value of the DNA methylation haplotype block of the respective classification label, the DNA copy number variation data of the sample of interest, and the DNA copy number variation data in the respective classification label are calculated from sequencing data of the DNA fragments in the library;
Cheng teaches calculating the methylation and copy number levels in the genome-wide bisulfite sequencing data of urinary cfDNA (p. 929, col. 2, par. 2).
wherein the sequencing data is whole genome bisulfite sequencing data obtained at a sequencing depth of 1X-5X, and
Cheng teaches sequencing DNA whole genome bisulfite libraries at 0.8 x coverage of the haploid human genome. Cheng therefore teaches either 1.6 x coverage of the diploid human genome, which is an example that anticipates the instantly claimed range of 1X-5X, or teaches an example of 0.8 x coverage of the haploid human genome that overlaps and anticipates or alternatively makes obvious the instantly claimed range of 1X-5X. It would have been prima facie obvious to one of ordinary skill in the art to select any portions of the disclosed ranges including the instantly claimed ranges from the ranges disclosed in the prior art references, particularly in view of the fact that: "The normal desire of scientists or artisans to improve upon what is already generally known provides the motivation to determine where in a disclosed set percentage ranges is the optimum combination of percentages" In re Peterson 65 USPQ2d 1379 (CAFC 2003). Also In re Malagari, 182 USPQ 549,533 (CCPA 1974) and MPEP 2144.05.
wherein the DNA methylation haplotype block of the sample of interest, the DNA methylation haplotype block of the respective classification label, regions of the sample of interest where DNA copy number variation occurs, and regions of the respective classification label where DNA copy number variation occurs are those shown in any one, any two, any three, any four, any five or all six of Tables 1-6, or as shown in Table 11 and/or Table 12.
As set forth in the above 35 USC 112(b) rejection, the metes and bounds of the chromosome locations in the tables in the claims are not clear. It is therefore not clear whether Cheng teaches identifying the claimed locations. However, as Cheng does teach performing whole genome sequencing, it is considered that all of the locations recited in the claims would have been assessed by Cheng and considered when analyzing the sample for the presence of bladder cancer. Therefore, Cheng is considered to teach the limitation under the BRI.
Cheng does not teach extracting sediment DNA from urine, fragmenting the DNAs into fragments of 300-500bp, calculating MHL, or determining a classification for the DNA in the sample of interest by using a classifier model and based on the first similarity and the second similarity.
However, the prior art to Patel discloses an assessment of single nucleotide variants and copy number alterations in body fluid mutant DNA using Tagged-Amplicon- and shallow Whole Genome-Sequencing (abstract). Patel teaches collecting urine samples from patients, centrifugation of samples, separation of the supernatant from the cell pellet (i.e., sediment as in (1)), and extraction of DNA from the cell pellet (p. 10, par. 3). Patel teaches shearing extracted DNA to an average fragment length of 140-180 bp. Patel therefore teaches a range which makes obvious the instantly claimed range of 140-180 bp. It would have been prima facie obvious to one of ordinary skill in the art to select any portions of the disclosed ranges including the instantly claimed ranges from the ranges disclosed in the prior art references, particularly in view of the fact that: "The normal desire of scientists or artisans to improve upon what is already generally known provides the motivation to determine where in a disclosed set percentage ranges is the optimum combination of percentages" In re Peterson 65 USPQ2d 1379 (CAFC 2003). See also In re Malagari, 182 USPQ 549,533 (CCPA 1974) and MPEP 2144.05. One of ordinary skill in the art would have understood that the DNA could have been fragmented to different lengths, and would have been motivated by routine optimization of a known process. Additionally, In re Brandt, 886 F.3d 1171, 1177, 126 USPQ2d 1079, 1082 (Fed. Cir. 2018)(the court found a prima facie case of obviousness had been made in a predictable art wherein the claimed range of "less than 6 pounds per cubic feet" and the prior art range of "between 6 lbs./ft3 and 25 lbs./ft3" were so mathematically close that the difference between the claimed ranges was virtually negligible absent any showing of unexpected results or criticality.).
Neither Cheng nor Patel teach calculating MHL or determining a classification for the DNA in the sample of interest by using a classifier model and based on the first similarity and the second similarity.
However, the prior art to Drake discloses methods that analyze blood-based cancer diagnostic tests using multiple classes of molecules uses machine learning (ML) to analyze multiple analytes, for example cell-free DNA, cell-free microRNA, and circulating proteins, from a biological sample, as well as using multiple assays, e.g., whole-genome sequencing, whole-genome bisulfite sequencing or EM-seq, small-RNA sequencing, and quantitative immunoassay (abstract). Drake teaches that the term “biological sample” (or just “sample”) refers to any substance obtained from a subject and can include urine [0080]. Drake teaches separating cellular DNA and cfDNA by centrifugation [0123; 0337]. Drake teaches whole genome bisulfite sequencing [0136; 0177; 0351]. Drake teaches determining methylation haplotype load (MHL) [0186] and copy number variants [0138; 0144]. Drake teaches that the system inputs the feature vector into the machine learning model and obtains an output classification of whether the sample has a specified property (abstract; [0103-0105]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, Cheng in view of Patel and Drake because each reference discloses methods for examining DNA to diagnose cancer. The motivation to combine Cheng and Patel would have been to apply a known sample processing technique, as taught by Drake, to a known sequencing and data processing method, as taught by Cheng, as motivated by Patel who teaches that mutant DNA is detected more frequently in both supernatant and cell pellet urine samples that in plasma (p. 8, par. 3; Figure 1C). The motivation to combine Cheng and Drake would have been to analyze biological analytes that are readily obtained (i.e., including metrics such as MHL as taught by Drake and copy number variation data as taught by Cheng) to stratify individuals at risk of or who have cancer and to provide effective characterization of early stage cancer to guide treatment decisions using machine learning approaches to develop and refine classifiers for such use, as taught by Drake [0006]. Further, the motivation to examine MHL would have been to quantitatively estimate tumor load and tissue-of-origin mapping, as taught by Drake [0186]. It is therefore considered that one of ordinary skill in the art would have recognized that the data of Cheng in view of Patel could have been analyzed by the methods of Drake to develop a classifier for urinary sediment DNA.
Regarding claims 12 and 22, Cheng in view of Patel and Drake teach claim 11. Claim 12 adds that the human urogenital tumor is one or more selected from the group consisting of prostate cancer, urothelial cancer, and renal cancer. Claim 22 adds that the renal cancer is kidney renal clear cell carcinoma, the urothelial cancer includes upper tract urothelial cancer and bladder cancer, and the prostate cancer is prostate adenocarcinoma.
Cheng teaches analyzing samples from patients with bladder cancer (p. 928, col. 1, par. 4 through col. 2, par. 1). The specification as published discloses that urothelial cancer includes bladder cancer [0027]. Claim 22 is interpreted as the urothelial cancer may be either upper tract or bladder cancer as the claim recites that urothelial cancer includes both types.
Regarding claims 13 and 23, Cheng in view of Patel and Drake teach claim 11. Claim 13 adds that, in step (1), the urine sample is urina sanguinis. Claim 23 further adds that the urine sample is urine sediment of the urina sanguinis.
As Cheng teaches collecting urine samples from patients (p. 928, col. 1, par. 4 through col. 2, par. 1), and the instant specification as published discloses that urina sanguinis refers to fresh urine [0159], it is considered that Cheng fairly teaches the limitation of claims 13 and 23. Although Cheng does not teach urine sediment as described above, Patel teaches collecting urine samples from patients, centrifugation of samples, separation of the supernatant from the cell pellet (i.e., sediment as in (1)), and extraction of DNA from the cell pellet (p. 10, par. 3).
Regarding claim 14, Cheng in view of Patel and Drake teach claim 11. Claim 14 adds that, in step (2), the DNAs are fragmented into fragments of 350-450bp, which Cheng does not teach.
However, Patel teaches shearing extracted DNA to an average fragment length of 140-180 bp. Patel therefore teaches a range which makes obvious the instantly claimed range of 140-180 bp. It would have been prima facie obvious to one of ordinary skill in the art to select any portions of the disclosed ranges including the instantly claimed ranges from the ranges disclosed in the prior art references, particularly in view of the fact that: "The normal desire of scientists or artisans to improve upon what is already generally known provides the motivation to determine where in a disclosed set percentage ranges is the optimum combination of percentages" In re Peterson 65 USPQ2d 1379 (CAFC 2003). See also In re Malagari, 182 USPQ 549,533 (CCPA 1974) and MPEP 2144.05. One of ordinary skill in the art would have understood that the DNA could have been fragmented to different lengths, and would have been motivated by routine optimization of a known process. Additionally, In re Brandt, 886 F.3d 1171, 1177, 126 USPQ2d 1079, 1082 (Fed. Cir. 2018)(the court found a prima facie case of obviousness had been made in a predictable art wherein the claimed range of "less than 6 pounds per cubic feet" and the prior art range of "between 6 lbs./ft3 and 25 lbs./ft3" were so mathematically close that the difference between the claimed ranges was virtually negligible absent any showing of unexpected results or criticality.).
Regarding claim 24, Cheng in view of Patel and Drake teach claim 11. Claim 24 adds determining, using a random forest model and based on the first similarity and the second similarity, a first correlation between the MHL value of the DNA methylation haplotype block of the respective classification label and a human urogenital tumor, and a second correlation between the DNA copy number variation data of the respective classification label and a human urogenital tumor; and determining the classification for the DNA in the sample of interest using the classifier model and based on the first correlation and the second correlation, which neither Cheng or Patel teach.
However, Drake teaches using models including random forest decision trees [0275; 0363] to analyze multiple types of data, including MHL [0186] and copy number variants [0138; 0144], as described above. Drake teaches that multiple models can be used, where models can be used sequentially or in parallel [0363]. Drake teaches an example where two different analytes (genes and methylation) were analyzed, where two model can be run to output two classifications (i.e., a first and second correlation) and use those as votes to determine which classification has a highest score (i.e., a classifier model) [0397].
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, in the course of routine experimentation and with a reasonable expectation of success, Cheng in view of Patel and Drake to analyze the MHL and copy number variant features taught by Cheng in view of Patel and Drake using the method of Drake where two models, which are Random Forest models, are run to output two classifications and then voted on to determine which classification has the highest score. The nature of the problem to be solved, classifying a disease based on two separate DNA features, as well as the need to incorporate the results from both features, would have led one of ordinary skill in the art to choose an appropriate model to analyze the DNA features. Therefore, it would have been obvious to use the method of Drake in combination with the urinary sediment DNA MHL and copy number data as taught by Cheng in view of Patel and Drake to diagnose urothelial cancer.
Regarding claim 28, Cheng in view of Patel and Drake teach claim 11. Claim 28 adds that the DNA methylation haplotype block of the sample of interest is the same as the DNA methylation haplotype block of the respective classification label; and/or the regions of the sample of interest where DNA copy number variation occurs are the same as the regions of the respective classification label where DNA copy number variation occurs.
Cheng teaches analyzing bins for hypo/hypermethylation and copy number aberration in comparison to other cancer-free controls or bladder cancer cases for statistically significant differences (p. 929, col. 2, par. 2; Fig. 1A), which reads on comparing the same bins (i.e., methylation locations or regions with copy number variations) between samples.
B. Claims 25-27 are rejected under 35 U.S.C. 103 as being unpatentable over Cheng in view of Patel and Drake, as applied to claim 11 above, and in further view of Levin et al. (US 2022/0213558; previously cited). The instant rejection is newly stated and is necessitated by claim amendment.
Regarding claim 25, Cheng in view of Patel and Drake teach claim 11 and 24. Claim 25 adds that determining the first correlation between the MHL value of the DNA methylation haplotype block of the respective classification label and the human urogenital tumor comprises, based on the first correlation, ranking the MHL value of the DNA methylation haplotype block to form a vector sequence, and inputting the vector sequence into the random forest model to determine the first correlation between the MHL value of the DNA methylation haplotype block and the human urogenital tumor; and determining the second correlation between the DNA copy number variation data of the respective classification label and the human urogenital tumor comprises, based on the second correlation, ranking the DNA copy number variation data to form a vector sequence, and inputting the vector sequence into the random forest model to determine the second correlation between the DNA copy number variation data of the classification label and the human urogenital tumor. Neither Cheng, Patel, nor Drake teach these limitations.
However, Levin discloses methods and systems directed to urine-based detection of urologic conditions (abstract). Levin teaches that biological samples may comprise cell-free or cellular biological samples, such as urine samples from a human subject [0047] where a urine sample may contain both a cell-free fraction and a cellular fraction (e.g., bladder, kidney, or prostate tumor cells shed into the urine) (i.e., urine sediment) [0052]. Levin teaches extracting DNA molecules from the sample (i.e., (1)) [0051]. Levin teaches constructing a sequencing library [0135]. Levin teaches sequencing samples to assay genomic loci, including genes that having copy number variation ([0054; 0157]; Table 5). Levin teaches input variables that comprise data indicative of a presence, absence, or relative amount of sequences at each of the plurality of urologic condition-associated genomic loci; for example, an input variable may comprise a number of sequences corresponding to or aligning to each of the plurality of urologic condition-associated genomic loci [0070]. Levin teaches identifying a subset of inputs as the most influential or most important to be included for making high-quality classifications (i.e., classification label) with metrics in order to reduce the number of inputs used to train and use the model [0085]. Using the subset of inputs is considered to read on calculating the similarity between the copy number variation data of the sample of interest DNA and the DNA copy number variation data of a respective classification label as instantly claimed. Levin teaches using a trained algorithm to process the data of the subject to determine a presence, absence, or relative amount of sequences at each of the plurality of urologic condition-associated genomic loci to determine a presence, absence, or relative amount of sequences at each of the plurality of urologic condition-associated genomic loci in the biological sample (i.e., determining a classification) [0068; 0086; 0089-0095], where the trained algorithm is a classifier [0071]. Levin teaches methods for urine-based detection of urologic conditions by using a trained algorithm [0046]. Levin teaches that the trained algorithm may be a random forest algorithm [0014; 0069]. As Levin teaches that the algorithm is trained with a plurality of independent training samples known to be associated with presence of the urologic condition, such as bladder cancer, kidney cancer, and prostate cancer [0075], it is considered that Levin fairly teaches determining a correlation between the copy number variation of the sample of interest and a human urogenital tumor using a random forest model as instantly claimed. Levin teaches that the plurality of urologic condition-associated genomic loci or a subset thereof may be ranked based on metrics indicative of each genomic locus's influence or importance toward making high-quality classifications or identifications of urologic condition in order to select the inputs for the trained algorithm [0085]. Levin teaches that the input variable may comprise a number of sequences corresponding to or aligning to each of the plurality of urologic condition-associated genomic loci (i.e., a vector sequence) [0070].
Regarding claim 26, Cheng in view of Patel and Drake teach claim 11 and 24 and, in further view of Levin, claim 25. Claim 26 adds that the random forest model includes at least three random forest binary classifiers and is selected from any one, any two, any three or all four of the following groups (I)-(IV): (I) normal-vs-renal cancer, normal-vs-urothelial cancer, and normal-vs-prostate cancer; (II) renal cancer-vs-normal, renal cancer-vs-urothelial cancer, and renal cancer-vs-prostate cancer; (III) urothelial cancer-vs-normal, urothelial cancer-vs-renal cancer, and urothelial cancer-vs- prostate cancer; and (IV) prostate cancer-vs-normal, prostate cancer-vs-renal cancer, and prostate cancer-vs- urothelial cancer. Neither Cheng, Patel, nor Drake teach these limitations.
However, Levin teaches that the trained algorithm may comprise a binary classifier, such that each of the one or more output values comprises one of two values (e.g., {0, 1}, {positive, negative}, or {cancerous, non-cancerous}) indicating a classification of the biological sample by the classifier [0071]. Levin teaches that the trained algorithm may be configured to identify the urologic condition (e.g., bladder cancer, kidney cancer, and prostate cancer) [0078-0084]. Levin teaches that the trained algorithm may be a random forest algorithm [0014; 0069]. It is therefore considered that Levin teaches three random forest classifiers to determine whether the subject has bladder cancer, kidney cancer, and prostate cancer in comparison to a non-cancerous state (i.e., (I)).
Regarding claim 27, Cheng in view of Patel and Drake teach claim 11 and 24 and, in further view of Levin, claims 25-26. Claim 26 adds voting for each of groups (I)-(IV), and determining the group with the highest number of votes as the final classification, wherein the event where equal numbers of votes occur means that the category with the highest prediction probability among the groups with the equal number of votes is determined as the final classification.
Claim 26 requires only one of groups (I)-(IV). Under the BRI, voting in claim 27 would occur only when two or more of the groups are required. Therefore, it is considered that as claim 27 does not limit the requirement to at least two different groups, no voting is required to be performed. As Levin is considered to teach group (I) as described above, Levin is also considered to teach the required limitations of claim 27.
Regarding claims 25-27, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, Cheng in view of Patel and Drake with Levin because each reference discloses methods for analyzing DNA to detect cancer. The motivation would have been to use a rapid, accurate screening method for urological conditions such as bladder cancer that are non-invasive and cost-effective, as taught by Levin [0004].
Response to Applicant Arguments
With respect to Applicant’s arguments under 35 USC 103, the arguments have been fully considered but are moot in view of the new grounds of rejection set forth above as necessitated by claim amendment herein.
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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/JANNA NICOLE SCHULTZHAUS/Examiner, Art Unit 1685
