DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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.
Restriction election
Applicant’s election without traverse of Group I and Species 2 (claims 1, 3-9, 12-17, 20, 22, and 40) in the reply filed on 06/03/2026 is acknowledged.
Claims 2 and 16 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a non-elected invention.
Claim Status
Claims 1-9, 12-17, 20, 22, and 40 are pending.
Claims 10-11, 18-18, 21, 23-39, and 41-62 are canceled.
Claims 2 and 16 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a non-elected species, as described above.
Claims 1, 3-9, 12-1, 17, 20, 22, and 40 are under examination.
Claims 1, 3-9, 12-15, 17, 20, 22, and 40 are rejected.
Priority
This application is a 371 of PCT/US20/56166 10/16/2020, which claims benefit of US provisional application 62/916,103 filed 10/16/2019.
Accordingly, each of claims 1, 3-9, 12-15, 17, 20, 22, and 40 are afforded the effective filing date of 10/16/2019.
Information Disclosure Statement
The information disclosure statements (IDS) filed on 04/17/2024 are in compliance with the provisions of 37 CFR 1.97 and have therefore been considered. Signed copies of the IDS documents are included with this Office Action.
The references in the specification is not considered to be an IDS as it is not a proper IDS. 37 CFR 1.98(b) requires a list of all patents, publications, or other information submitted for consideration by the Office and MPEP § 609.04(a) states, "the list may not be incorporated into the specification but must be submitted in a separate paper." Therefore, unless the references have been cited by the examiner on form PTO-892, they have not been considered. See pages 47-50 of the specification in the instant application
Drawings
The Drawings submitted 04/15/2023 are accepted.
Specification
The disclosure is objected to for the following informalities. It is noted that for purposes of the instant Office Action, any reference to the specification pertains to the clean copy of the substitute specification as originally filed on 04/15/2022.
Disclosure
The disclosure is objected to for the following informalities. Paragraphs [0049 and 0058-0059] discloses color references to drawings. Colored drawings are not submitted with the application.
Hyperlinks
The disclosure is objected to because it contains an embedded hyperlink and/or other form of browser-executable code. Applicant is required to delete the embedded hyperlink and/or other form of browser-executable code; references to websites should be limited to the top-level domain name without any prefix such as http:// or other browser-executable code. See MPEP § 608.01. Non-limiting examples include paragraphs [0068, 0316, and 0319]. Applicant will note that this is exemplary and other instances may exist. It is requested that all instances be corrected.
Appropriate correction for all objections to the specification is required.
Claim Rejections - 35 USC § 112
35 U.S.C. 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 4-6 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.
Claims 4-6 incorporate a reference of a Table in the specification within the claim. Incorporation by reference to a specific figure or table "is permitted only in exceptional circumstances where there is no practical way to define the invention in words and where it is more concise to incorporate by reference than duplicating a drawing or table into the claim. Incorporation by reference is a necessity doctrine, not for applicant’s convenience." Ex parte Fressola, 27 USPQ2d 1608, 1609 (Bd. Pat. App. & Inter. 1993).
Claim 5 recites “the pairs of molecular targets”. There is insufficient antecedent basis for this limitation in the claim as there is no previous recitation of “pairs of molecular targets”.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 3-9, 12-15, 17, 20, 22, and 40 are rejected under 35 U.S.C. 101 because the claimed invention is directed to one or more judicial exceptions without significantly more.
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 methods, 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).
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) are as follows:
Independent claim 1:
determining, for each autoantibody species in a first set of autoantibody species, a corresponding abundance value for the respective autoantibody species in the biological fluid sample, thereby obtaining an autoantibody abundance dataset for the subject;
determining, using the autoantibody abundance dataset, values for each of a first set of autoantibody abundance features, thereby obtaining a first feature dataset for the subject;
inputting the first feature dataset into a classifier trained to distinguish between at least two states of the gynecological disorder based on at least values for the first set of autoantibody abundance features, thereby obtaining a probability or likelihood from the classifier that the subject has a particular state of the gynecological disorder.
Dependent claim 14:
determining a plurality of secondary features from the second biological sample, thereby obtaining a secondary feature dataset for the subject;
inputting the secondary feature dataset into the classifier
Independent claim 40:
determining, for each autoantibody species in a first set of autoantibody species, a corresponding abundance value for the respective autoantibody species in the first biological fluid sample, thereby obtaining an autoantibody abundance dataset for the subject
determining, using the autoantibody abundance dataset, values for each of a first set of autoantibody abundance features, thereby obtaining a first feature dataset for the subject;
inputting the first feature dataset into a classifier trained to distinguish between at least two states of the disease condition based on at least values for the first set of autoantibody abundance features, thereby obtaining a probability or likelihood from the classifier that the subject has a particular state of the disease condition.
Dependent claims 3-9, 12-13, 15, 17, 20, and 22 recite further steps that limit the judicial exceptions in independent claim 1 and, as such, also are directed to those abstract ideas. For example, claim 3 further limits the sample of claim 1, claims 4, 6, and 9 further limit the autoantibody species of claim 1, claims 5 and 7-8 further limit the autoantibody features of claim 1, claim 12 further limits the classifier of claim 1, claim 13 further limits disorder secondary features of claim 12, claim 15 further limits the sample of claim 14, and claims 17, 20, and 22 further limit the disorder of claim 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.
The claim recites determining. The human mind is capable of determining, , a corresponding abundance value for the respective autoantibody species, determining, values for each of a first set of autoantibody abundance features, determining a plurality of secondary features and at least two states of the disease condition based on at least values for the first set of autoantibody abundance features, thereby obtaining a probability or likelihood that the subject has a particular state of the disease condition.
The claims recite inputting a dataset into a classifier which is a mathematical concept. The inputting the first feature data set into a classifier is all that is required in the limitation and where it is trained to distinguish between at least two states of the gynecological disorder based on at least values for the first set of autoantibody abundance features, thereby obtaining a probability or likelihood from the classifier that the subject has a particular state of the gynecological disorder thereby distinguishing isan intended result of the inputting.
Therefore, claims 1 and 40 and those claims dependent therefrom recite an abstract idea [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 claims 1 and 40:
obtaining a biological fluid sample from the subject
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”, 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 steps are not sufficient to integrate judicial exceptions into a practical application (MPEP 2106.05(g)) as obtaining a biological sample is insignificant extra-solution activity.
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 claims 1 and 40 and those claims dependent therefrom, the steps of obtaining a biological fluid sample are well-understood, routine, and conventional in the art. The specification discloses samples were collected by gynecologic oncologists with highly similar treatment practices and definitions; minimizing potential confounding, non-biological sources of treatment and survival differences [00011] and our biomarker method requiring a blood sample or uterine lavage has the capacity to be performed in a general practitioners' office, performed by physicians' assistants or nurse practitioners [00076].
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.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 3, 7, 12-13, 17, and 40 is/are rejected under 35 U.S.C. 102(a)(2) and 102(a)(1) as being anticipated by Cohen et al. (US2018/0068083 A1, newly cited).
Claims 1 and 40 is directed to a method for evaluating a gynecological disorder in a subject, the method comprising:
Cohen discloses the classifier may then be used to assesses the likelihood that a patient has cancer relative to a population by classify the patient into a category indicative of a likelihood of having cancer or into another category indicative of a likelihood of not having cancer [abstract]. Cohen further discloses cervical cancer and ovarian cancer, [0072] which the specification states is a type of gynecological disorder [00067].
a) obtaining a biological fluid sample from the subject;
Cohen further discloses samples include, but are not limited to, blood, blood serum, blood plasma, urine, tears, saliva, sweat, biopsy, ascites, cerebrospinal fluid, milk, lymph, bronchial and other lavage samples, or tissue extract samples. In certain embodiments, blood, serum, plasma and bronchial lavage or other liquid samples are convenient test samples for use in the context of the present methods [0071].
b) determining, for each autoantibody species in a first set of autoantibody species, a corresponding abundance value for the respective autoantibody species in the biological fluid sample, thereby obtaining an autoantibody abundance dataset for the subject;
Cohen discloses the quantity methods for detecting the biomarkers [0116-0118] which implies enriching a protein fraction comprising said protein biomarkers.
c) determining, using the autoantibody abundance dataset, values for each of a first set of autoantibody abundance features, thereby obtaining a first feature dataset for the subject; and
Cohen also discloses the quantity methods for detecting the biomarkers [0116-0118] which implies enriching a protein fraction comprising said protein biomarkers. Cohen further discloses, the presence of the biomarkers is not individually quantified as an absolute value to indicate the presence of a cancer, but the measured values are normalized and the normalized value is aggregated (e.g, summed or weighted and summed, etc.) for inclusion within a biomarker composite score [0112]. This implies determining protein abundance features as in present claim 1 (c).
d) inputting the first feature dataset into a classifier trained to distinguish between at least two states of the gynecological disorder based on at least values for the first set of autoantibody abundance features, thereby obtaining a probability or likelihood from the classifier that the subject has a particular state of the gynecological disorder.
Cohen discloses the present invention relate generally to non - invasive methods and tests that measure biomarkers ( e . g . , tumor antigens ) and collect clinical parameters from patients , and computer - implemented machine learning methods , apparatuses , systems , and computer – readable media for assessing a likelihood that a patient has a disease , relative to a patient population or a cohort population [abstract]. Cohen further discloses a classifier is generated using a machine learning system based on training data from retrospective data and subset of inputs ( e . g . at least two biomarkers and at least one clinical parameter ) , wherein each input has an associated weight and the classifier meets a predetermined Receiver Operator Characteristic ( ROC ) statistic , specifying a sensitivity and a specificity, for correct classification of patients [abstract]. Cohen also discloses the classifier may then be used to assesses the likelihood that a patient has cancer relative to a population by classify the patient into a category indicative of a likelihood of having cancer or into another category indicative of a likelihood of not having cancer [abstract].
Claim 3 is directed to the method of claim 1, wherein the biological fluid sample is a blood sample or fraction thereof.
Cohen discloses samples include, but are not limited to, blood, blood serum, blood plasma, urine, tears, saliva, sweat, biopsy, ascites, cerebrospinal fluid, milk, lymph, bronchial and other lavage samples, or tissue extract samples. In certain embodiments, blood, serum, plasma and bronchial lavage or other liquid samples are convenient test samples for use in the context of the present methods [0071].
Claim 7 is directed to the method of claim 1, wherein each respective feature in the first set of autoantibody abundance features comprises a normalized abundance value for a respective autoantibody species in the first set of autoantibody species.
Cohen discloses the presence of the biomarkers are not individually quantified as an absolute value to indicate the presence of a cancer, but the measured values are normalized and the normalized value is aggregated (e.g, summed or weighted and summed, etc.) for inclusion within a biomarker composite score [0112].
Claim 12 is directed to the method of claim 1, wherein the classifier was trained to distinguish between the at least two states of the gynecological disorder based on at least the values for each of the first set of autoantibody abundance features and one or more secondary features of the subject.
Cohen discloses neural networks have the capability of detecting complex nonlinear relationships between variables , to deter mine which variables are the most predictive among a set of variables , and can discover relationships between variables that were not previously known [0213]. Cohen further discloses, one of skill in the art may determine which groups of biomarkers in combination with specific clinical features are the most predictive of a likelihood of having lung cancer, for example , an ANN may be used to determine that a subset of 6 biomarkers and a subset of 5 clinical features are highly predictive , e . g . , 90 % or greater sensitivity at 80 % specificity ,to identify individuals with an increased likelihood of having cancer [0213]. Cohen also discloses the values of a panel of biomarkers in a sample from a patient are measured [0277]. Cohen further discloses the computer implemented method of , wherein the classifier is a neural net , a support vector machine , a decision tree , a random forest , a neural network , or a deep learning neural network [claim 99].
Claim 13 is directed to the method of claim 12, wherein: the gynecological disorder is an ovarian cancer or an endometrial cancer, and the one or more secondary features of the subject comprise two or more of the features selected from the group consisting of an age of the subject, a body mass index of the subject, a pregnancy history of the subject, a breastfeeding history of the subject, a BRCA1 genotype of the subject, a BRCA2 genotype of the subject, a breast cancer history of the subject, and a familial history of endometrial cancer, ovarian cancer, or breast cancer.
Cohen discloses the cancer is selected from the group consisting of : breast cancer , bile duct cancer , bone cancer , cervical cancer , colon cancer , colorectal cancer , gallbladder cancer , kidney cancer , liver or hepatocellular cancer , lobular carcinoma , lung cancer , melanoma , ovarian cancer , pancreatic cancer , prostate cancer , skin cancer , and testicular cancer [claim 105]. Cohen further discloses the computer implemented method, wherein the clinical parameters can consist of age and family history of cancer [claim 95].
Claim 17 is directed to the method of claim 1, wherein the gynecological disorder is an ovarian cancer or an endometrial cancer.
Cohen discloses a panel of markers comprises markers associated with a cancer selected from bile duct cancer , bone cancer , pancreatic cancer , cervical cancer , colon cancer , colorectal cancer , gallbladder cancer , liver or hepatocellular cancer , ovarian cancer , testicular cancer , lobular carcinoma , prostate cancer , and skin cancer or melanoma [0133 and claim 105].
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. Claim(s) 4, 6, 8, and 14-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cohen as applied to claim 1 above, further in view of Vogelstein et al. (WO 2019/067092 A1 published 04/04/2019, cited on IDS dated 04/17/2019).
Claim 4 is directed to the method of claim 1, wherein the first set of autoantibody species comprises at least 5 autoantibody species, wherein each respective autoantibody species of the at least 5 autoantibody species specifically bind to a different molecular target selected from those listed in any of Tables 2-7.
Cohen discloses panel can comprise any number of markers as a design choice, seeking, for example, to maximize specificity or sensitivity of the assay [00134] which reads on the use of panel (set) of at least five biomarkers. An assay of interest may ask for presence of at least one of two or more biomarkers, three or more biomarkers, four or more biomarkers, five or more biomarkers, six or more biomarkers, seven or more biomarkers, eight biomarkers or more as a design choice. Cohen discloses "As used herein, the terms "marker", "biomarker" (or fragment thereof) and their synonyms, which are used interchangeably, refer to molecules that can be evaluated in a sample and are associated with a physical condition. For example, markers include expressed genes or their products (e.g., proteins) or autoantibodies to those proteins that can be detected from human samples, such as blood, serum, solid tissue, and the like, that is associated with a physical or disease condition. Such biomarkers include, but are not limited to,( ... ) any complexes involving any such biomolecules, such as, but not limited to, a complex formed between an antigen and an autoantibody that binds to an available epitope on said antigen. ( ... ) The present markers, as used herein, also refer to autoantibodies produced by the body to those tumor antigens. In one aspect, a "marker" as used herein refers to both tumor antigens and autoantibodies that are capable of being detected in serum of a human subject. It is also understood in the present methods that use of the markers in a panel may each contribute equally to the composite score or certain biomarkers may be weighted wherein the markers in a panel contribute a different weight or amount to the final composite score." [0096]. Cohen is silent on the at least 5 proteins are selected from the proteins listed in tables 2-7.
However, Vogelstein discloses “Methods and materials for assessing and treating cancer“ [title] as well several biomarkers of tables 2-7 of present application, to be used in a panel of one or more biomarkers, five or more, wherein the panel is used to detect cancer such as ovarian or endometrial cancer (see for example paragraphs: [18]-[20],[54]-[59],[168],[170],[174],[193], [215],[239],[279],[280],[282],[348],[695],[829]). Vogelstein discloses at least the following biomarkers: ACVR1B, POT1, RAC1, HIF1A, ERBB4, PBRM1, ... etc of present application.
Claim 6 is directed to the method of claim 1, wherein the first set of autoantibody species comprises at least 5 autoantibody species, wherein each respective autoantibody species of the at least 5 autoantibody species bind to a molecular target in a different pathway or cell type signature selected from those listed in Table 1.
Cohen is silent on pathways.
Vogelstein discloses the therapeutic intervention administered to the subject having a genetic biomarker in NRAS is one or more of a RAS-targeted therapeutic, a receptor tyrosine kinase inhibitor, a Ras-Raf-MEK-ERK pathway inhibitor, a PBK-Akt-mTOR pathway inhibitor, and a farnesyl transferase inhibitor [809] which reads on pathways. Vogelstein further discloses the patient sample is a cell-free nucleic acid sample (e.g., cell-free DNA (cIDNA) and/or cell-free RNA (cfRNA)) [453]. Vogelstein also discloses the construction of a signature matrix using non-negative matrix factorization can be generalized to multiple features relevant to cancer detection and/or classification [453] which reads on a cell type signature. Vogelstein further discloses the biomarkers can be BRCAI, BRCA2, SMAD2, SMAD3, SMAD4, IL2, BCR [695].
Claim 8 is directed to the method of claim 1, wherein each respective feature in the first set of autoantibody abundance features comprises a comparison between an abundance value for a first respective autoantibody species in the first set of autoantibody species and an abundance value for a second respective autoantibody species in the first set of autoantibody species.
Cohen discloses biomarkers include molecules secreted by tumors or cancer , including gene , gene expression , and protein - based products ( tumor markers or antigens , cell free DNA , mRNA , etc ) [00094].
Vogelstein discloses in some embodiments, the MAF of one or more mutations in the selected genetic biomarkers can be compared against the reference distribution, thereby obtaining a score indicates that the likelihood or the probability that the subject has cancer [713]. Vogelstein further discloses in some embodiments, if the score (e.g., likelihood or probability) is equal to or greater than a reference threshold, it can be determined that the subject is likely to have cancer, otherwise, it can be determined that the subject is not likely to have cancer [713]. Vogelstein further discloses in some embodiments, the comparison can provide a score that indicates the likelihood or probability that the subject does not have cancer [713].
Claim 14 is directed to the method of claim 1, the method further comprising: obtaining a second biological sample from the subject; determining a plurality of secondary features from the second biological sample, thereby obtaining a secondary feature dataset for the subject; and inputting the secondary feature dataset into the classifier.
Cohen is silent on a second sample.
However, Vogelstein discloses in some embodiments of identifying a subject as having cancer or treating a subject having cancer (e.g., based on the presence of one or more genetic biomarkers in a first sample obtained from said subject and/or the presence of aneuploidy in a second sample obtained from the subject), the cancer is an ovarian or endometrial cancer [887].
Claim15 is directed to the method of claim 14, wherein the second biological sample is a uterine lavage fluid.
Cohen discloses samples include, but are not limited to, blood, blood serum, blood plasma, urine, tears, saliva, sweat, biopsy, ascites, cerebrospinal fluid, milk, lymph, bronchial and other lavage samples, or tissue extract samples. In certain embodiments, blood, serum, plasma and bronchial lavage or other liquid samples are convenient test samples for use in the context of the present methods [0071].
In regards to claim(s) 4, 6, 8, and 14-15, 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 Cohen with Vogelstein as they both disclose methods and materials for identifying a subject as having cancer (e.g., a localized cancer) are provided in which the presence of two or more members of two or more classes of biomarkers are detected. The skilled person looking for alternative biomarkers to be used in the diagnosing panels, will use the teaching of Vogelstein and obtain the method of present application. One could have therefore combined the elements as claimed by the known methods of Cohen and Vogelstein and that in combination, each element merely would have performed the same function as it did separately for a predictable result.
B. Claim 5, is rejected under 35 U.S.C. 103 as being unpatentable over Cohen in as applied to claim 1 as above, view of Vogelstein, and in further view of Ryunov et al. (Dmitry Rykunov, Noam D. Beckmann, Hui Li, Andrew Uzilov, Eric E. Schadt and Boris Reva, “A new molecular signature method for prediction of driver cancer pathways from transcriptional data”, Nucleic Acids Research, 2016, cited on IDS dated 04/17/2024).
Claim 5 is directed to the method of claim 1, wherein the first set of autoantibody abundance features comprises at least 5 autoantibody abundance features, wherein each respective autoantibody abundance features of the at least 5 autoantibody abundance features is a comparison of the abundances of a pair of autoantibodies that specifically bind to a different pair of molecular targets selected from the pairs of molecular targets listed in any of Tables 2-7.
Cohen discloses panel can comprise any number of markers as a design choice, seeking, for example, to maximize specificity or sensitivity of the assay [00134] which reads on the use of panel (set) of at least five biomarkers, but is silent on a specific biomarker of tables 2-7.
However, Vogelstein discloses as well several biomarkers of tables 2-7 of present application, to be used in a panel of one or more biomarkers, five or more, wherein the panel is used to detect cancer such as ovarian or endometrial cancer (see for example paragraphs: [18]-[20],[54]-[59],[168],[170],[174],[193], [215],[239],[279],[280],[282],[348],[695],[829]). Vogelstein further discloses at least the following biomarkers: ACVR1B, POT1, RAC1, HIF1A, ERBB4, PBRM1, ... etc of present application. Cohen and Vogelstein are silent on a comparison of the abundances of a pair of autoantibodies that specifically bind to a different pair of molecular targets.
However, Rykunov discloses a new molecular signature method for prediction of driver cancer pathways from transcriptional data [title]. Rykunov further discloses two-class separation can be significantly improved by using the weighted sum of non-correlated gene expression traits. In practice, to determine an optimal list of biomarkers, we need to take into account the significance of the expression differences of the biomarker between the classes, the frequency with which the biomarker is found to discriminate between the classes across all subsets considered, and the pairwise correlations among the biomarkers [p. 5, col. 1, par. 3] which reads on using a pair of biomarkers to produce for constructing classification signature of gene expression.
In regards to claim(s) 5, 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 Cohen and Vogelstein with Ryunov as they all disclose methods and materials for identifying a subject as having cancer (e.g., a localized cancer) based on classes of biomarkers. The motivation would have been to modify the data of single biomarker of Cohen and Vogelstein with the comparison score of a pairwise correlation of Ryunov as the two-class separation can be significantly improved by using the weighted sum of non-correlated gene expression traits [p. 5, col. 1, par. 3]. One could have therefore modified the elements as claimed by the known methods of Cohen and Vogelstein with Ryunov, and that in modification, each element merely would have performed the same function as it did separately for a predictable result.
C. Claims 9, 20, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Cohen as applied to claim 1 as above, and in further view of Cotter et al. (US2019/0233892 A1, published 09/01/2019, newly cited).
Claim 9 is directed to the method of claim 1,wherein for each autoantibody species in the first set of autoantibody species, the corresponding abundance value for the respective autoantibody species comprises an abundance of IgG and IgA homologues of first set of autoantibody species in the biological fluid sample.
Cohen is silent on IgG and IgA.
However, Cohen discloses where a biomarker is an auto-antibody the invention will generally detect IgG antibodies, but detection of auto-antibodies with other subtypes is also possible e.g. by using a detection reagent which recognizes the appropriate class of auto-antibody (IgA, IgM, IgE or IgD rather than IgG) [0078].
Claim 20 is directed to the method of claim 1, wherein the gynecological disorder is adenomyosis, endometrial polyps, leiomyoma, or endometriosis.
Cohen discloses the present invention relate generally to non - invasive methods and tests that measure biomarkers ( e . g . , tumor antigens ) and collect clinical parameters from patients , and computer - implemented machine learning methods , apparatuses , systems , and computer – readable media for assessing a likelihood that a patient has a disease , relative to a patient population or a cohort population [abstract]. Cohen is silent on gynecological disorder is adenomyosis, endometrial polyps, leiomyoma, or endometriosis.
However, Cotter discloses relates to biomarkers useful for the diagnosis and/or prognosis of endometriosis [0001]. Cotter further discloses the biomarkers are also useful for monitoring treatment of the disease and can also be used as targets for therapeutic intervention [0001]. Cotter also discloses many types of sample can include auto-antibodies and/or antigens or miRNAs suitable for detection by the invention [0066]. Cohen further discloses the sample can be a tissue sample, e.g. from regions of uterine or vaginal tissues, alternatively, the sample can be or a body fluid sample, e.g. cervical discharge or peritoneal fluid [0066]. Cohen also discloses a bodily fluid sample, e.g. a blood sample, can be treated to extract circulating endometrial cells for analysis [0068]. Cohen further discloses where a biomarker is an auto-antibody the invention will generally detect IgG antibodies, but detection of auto-antibodies with other subtypes is also possible e.g. by using a detection reagent which recognizes the appropriate class of auto-antibody (IgA, IgM, IgE or IgD rather than IgG) [0078]. Cohen also discloses suitable algorithms for use in part (iii) include support vector machine algorithms, artificial neural networks, tree-based methods, genetic programming, etc [0043]. Cohen further discloses the algorithm can preferably classify the data of part (ii) to distinguish between subjects with endometriosis and subjects without based on measured biomarker levels in samples taken from such subjects [0043].
Claim 22 is directed to the method of claim 1, wherein the gynecological disorder is infertility.
Cohen is silent on gynecological disorder is adenomyosis, endometrial polyps, leiomyoma, or endometriosis.
However, Cotter discloses relates to biomarkers useful for the diagnosis and/or prognosis of endometriosis [0001]. Cotter is silent on infertility. However, any of the above disorders in claim 20 can cause infertility so it would be obvious that it would be an additional result from those.
In regards to claim(s) 9 and 20, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Cohen with Cotter as they both discloses the use of biomarker to detect disease. The skilled person has motivation to apply the data of Cotter about specific endometriosis and specific biomarkers characteristic for present, absence and particular stages of the disorder to the method of Cohen in order to evaluate presence I absence/ stage of gynecological disorder. One could have therefore replaced the elements as claimed by the known methods of Cohen and Cotter, and that in modification, each element merely would have performed the same function as it did separately for a predictable result.
Conclusion
No claims are allowed.
Inquiries
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Dawn M. Bickham whose telephone number is (703)756-1817. The examiner can normally be reached M-Th 7:30 - 4:30.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Olivia Wise can be reached at 571-272-2249. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/D.M.B./Examiner, Art Unit 1685
/Soren Harward/Primary Examiner, TC 1600
Prosecution Insights