DETAILED ACTION
The amendment filed on 07/29/2026 has been entered.
Claims 7, 20, 31, and 32 were amended in the claim set filed on 07/29/2026.
Applicant’s election without traverse, at least one of the features (Claims 15) in the reply filed on 01/13/2026 is acknowledged.
Applicant is reminded that upon the cancelation of claims to a non-elected invention, the inventorship must be corrected in compliance with 37 CFR 1.48(a) if one or more of the currently named inventors is no longer an inventor of at least one claim remaining in the application. A request to correct inventorship under 37 CFR 1.48(a) must be accompanied by an application data sheet in accordance with 37 CFR 1.76 that identifies each inventor by his or her legal name and by the processing fee required under 37 CFR 1.17(i).
Claims 61-64 were added in the claim set filed on 07/29/2026. No new matter was added.
Claims 2, 8, 13-14, 16-19, 27-30 and 34 were canceled in the claim set filed on 07/29/2026.
Claims 1, 7, 15, 20, 26, 31-33, 35-39, and 61-64 in the claim set filed on 07/29/2026 are currently under examination.
Response to the Arguments
Objections to the Drawings in the previously mailed non-final have been withdrawn in light of applicants Drawings supplement filed on 07/29/2026 and arguments.
Objections to the Claims in the previously mailed non-final have been withdrawn in light of applicants Claim amendments. However, as necessitated by amendment, new grounds of objection are made as documented below in the Objection section on Pg. 4.
Arguments regarding previous rejection of claims 2, 8, 13-14, 16-19, 27-30 and 34 are moot as the claims were canceled in the instant claim set. The previous rejection of claims 2, 8, 13-14, 16-19, 27-30 and 34 have been withdrawn.
Applicant’s arguments regarding previous rejection(s) of claim(s) 1, 7, 15, 20, 26, 31-33 and 35-39 under 35 U.S.C. 112 have been fully considered and are persuasive. The 35 U.S.C. 112 rejections documented in the previously mailed non-final have been withdrawn in light of applicants claim amendments and arguments on Pg. 10.
Applicant’s arguments regarding previous rejection(s) of claim(s) 1, 7, 15, 20, 26, 31-33 and 35-39 under 35 U.S.C. 101 have been fully considered but are not persuasive. The 35 U.S.C. 101 rejections documented in the previously mailed non-final have been maintained and revised in light of applicants claim amendments and arguments on Pg. 11-16. Additionally, as necessitated by amendment, new grounds of rejection for claims 61-64 are made as documented below in the 35 U.S.C. 101 rejection in this office action on Pg. 4-8.
As necessitated by amendment, the 35 U.S.C. 103 rejections of claim(s) 1, 7, 15, 20, 26, 31-33 and 35-39 documented in the previously mailed non-final have been withdrawn in light of applicants claim amendments. However, after further consideration and search, new grounds of rejection are made as documented below in the 35 U.S.C. 103 rejection in this office action on Pg. 9-25.
Additionally, as necessitated by amendment, new grounds of rejection for claims 61-64 are made as documented below in the 35 U.S.C. 103 rejection in this office action on Pg. 9-25.
The new grounds of rejection for claims 1, 7, 15, 20, 26, 31-33, 35-39 and 61-34 are documented below in this Final Office Action are necessitated by claim amendments filed on 07/29/2026.
Priority
This application claims the benefit of U.S. provisional patent application
63/001,236, filed March 27, 2020.Accordingly, the priority date of the instant claim set is determined to be March 27, 2020.
Claim Objections
Claim 64 is objected to under 37 CFR 1.75 as being a substantial duplicate of claim 39. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
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, 7, 15, 20, 26, 31-33, 35-39, and 61-64 are rejected under 35 U.S.C. 101 because the claimed invention is directed towards an abstract idea/mental process of organizing or analyzing features in a way that can be performed mentally with the physical aid of a general computer and routine and conventional methods, without significantly more. The claim(s) recite(s) abstract ideas. This judicial exception is not integrated into a practical application because no additional elements integrate the judicial exceptions into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because no additional elements are considered significantly more than the judicial exceptions.
Claim analysis
The instant claim 1 is directed towards: A method for classifying likely presence or likely absence of oral cancer in a human subject, comprising: a) providing saliva sample from the human subject, the saliva sample comprising mouth-sourced cells, wherein the mouth-sourced cells comprise oral microbiome cells and somatic cells from the human subject; b) isolating RNA from the saliva sample; c) sequencing nucleic acids derived from the RNA from the sample to produce metatranscriptomic sequence information; d) determining, from the sequence information, a feature set including two or more feature types selected from:(1) microbial taxon activity features for one or more microbial taxa, comprising transcriptional activity of the one or more microbial taxa in the saliva sample, (2) microbial gene function activity features for one or more microbial gene orthologs, comprising gene expression of the one or more microbial gene orthologs in the saliva sample, and(3) host gene expression features for one or more somatic cell genes of the subject, comprising gene expression of the one or more somatic cell genes of the human subject in the saliva sample; and e) executing by computer a classification model trained using saliva-derived metatranscriptomic feature data from subjects with oral cancer and saliva-derived metatranscriptomic feature data from subjects without oral cancer, wherein the classification model uses the two or more feature types in the feature set to assign, to the human subject, a class label of likely presence of oral cancer or likely absence of oral cancer.
The determining from the sequence information, a feature set is considered an abstract ideas (mental process) related to organizing or analyzing information in a way that can be performed mentally or is analogous to human mental work and is also considered to be an active step requiring the analysis of a sample.
The computer is considered a general computer that is just applied to execute the classification model.
The steps of providing a saliva sample, isolating RNA from the saliva sample, sequencing nucleic acid from RNA from the sample, determining a feature set from the sequence information, executing a classification model by a computer, using metatranscriptomic feature data from subjects with and without oral cancer to assign to assign subject classification of likely presence or absence of cancer are all considered active steps that are routine and conventional as demonstrated by the 35 USC § 103 rejections stated below.
Dependent claims set forth further limitations about the saliva sample, classification model, feature set(s), cancer, inference of OSCC, outputting the inferred state of oral cancer using a generic computer, administration of a non-particular therapeutic intervention, and confirmatory diagnostic step.
According to the 2019 Patent Eligibility Guidance an initial two step analysis is required for determining statutory eligibility.
Step 1. Is the claim directed to a process, machine, manufacture, or composition of matter? In the instant case, the Step 1 requirement is satisfied as the claims are directed towards a process.
Step 2A Prong one. Does the claim recite a law of nature, a natural phenomenon or an abstract idea? Yes, abstract idea.
Regarding claim 1, “A method for classifying likely presence or likely absence of oral cancer in a human subject, comprising: a) providing saliva sample from the human subject, the saliva sample comprising mouth-sourced cells, wherein the mouth-sourced cells comprise oral microbiome cells and somatic cells from the human subject; b) isolating RNA from the saliva sample; c) sequencing nucleic acids derived from the RNA from the sample to produce metatranscriptomic sequence information; d) determining, from the sequence information, a feature set including two or more feature types selected from:(1) microbial taxon activity features for one or more microbial taxa, comprising transcriptional activity of the one or more microbial taxa in the saliva sample, (2) microbial gene function activity features for one or more microbial gene orthologs, comprising gene expression of the one or more microbial gene orthologs in the saliva sample, and(3) host gene expression features for one or more somatic cell genes of the subject, comprising gene expression of the one or more somatic cell genes of the human subject in the saliva sample; and e) executing by computer a classification model trained using saliva-derived metatranscriptomic feature data from subjects with oral cancer and saliva-derived metatranscriptomic feature data from subjects without oral cancer, wherein the classification model uses the two or more feature types in the feature set to assign, to the human subject, a class label of likely presence of oral cancer or likely absence of oral cancer.” The determining from the sequence information, a feature set is considered an abstract idea (mental process) related to organizing or analyzing information in a way that can be performed mentally or is analogous to human mental work.
Step 2A prong two. Does the claim recite additional elements that integrate the judicial exception into a practical application? No, there are no additional steps that integrate the claims into a practical application. Regarding the dependent claims 37 and 38, the following elements were recited: claim 37 recited “outputting the inferred state of oral cancer in the subject to a user interface device or to computer-readable memory”, and claim 38 recited “delivering and/or administering to the subject a therapeutic intervention effective to treat the oral cancer”, which are of great generality being routine and conventional as demonstrated in the prior art rejections documented below. Furthermore, the user interface is a general user interface and there is an absence of a particular of treatment claimed.
Step 2B. Does the claim recite additional elements that are significantly more than the judicial exceptions? No, there are no additional elements that are significantly more than the judicial exceptions.
Regarding claim 1, the claim requires the routine and conventional active steps of providing a saliva sample, isolating RNA from the saliva sample, sequencing nucleic acid from RNA from the sample, determining a feature set from the sequence information, executing a classification model by a computer, using metatranscriptomic feature data from subjects with and without oral cancer to assign to assign subject classification of likely presence or absence of cancer similar to that of Apte et al. (“Apte”; Patent App. Pub. WO 2017156031 A1, Sept. 14, 2017). in view of Kondoh et al. (“Kondoh”; Patent App. Pub. WO 2007018143 A1, Feb. 15, 2007, English translation provided), as discussed in the 35 U.S.C. 103 rejection documented below.
Dependent claims require further limitations of the saliva sample, classification model, feature set(s), cancer, inference of OSCC, outputting the inferred state of oral cancer using a generic computer, administration of a non-particular therapeutic intervention, and confirmatory diagnostic step, which are all routine and conventional based on Apte et al. (“Apte”; Patent App. Pub. WO 2017156031 A1, Sept. 14, 2017) in view of Kondoh et al. (“Kondoh”; Patent App. Pub. WO 2007018143 A1, Feb. 15, 2007, English translation provided) and Adami et al. (“Adami”; U.S. Patent App. Pub. US 20120231468 A1, Sept. 13, 2012)..
Response to Arguments
Applicant's arguments filed 07/29/2026 (Pg. 11-16) with respect to claims 1, 7, 15, 20, 26, 31-33, 35-39, and 61-64 have been fully considered but they are not persuasive. To clarify some instances argued in the response filed 07/29/2026 see responses to each argument made by Applicant below:
Applicants’ argument: “Regardless of whether amended claim I recites an abstract idea - and Applicant respectfully contends that it does not - claim I is not directed to an abstract idea under Step 2A, Prong Two of the Alice/MPEP framework when properly viewed as a whole, at least because claim I integrates any alleged judicial exception into the practical application of an improvement in oral cancer classification technology.” (Pg. 12)
Response: Applicant’s arguments have been fully considered and found unpersuasive because applicants amendments do not overcome the lack of patentably matter under U.S.C. 35 101. The previously presented and amended claims recite an abstract idea of determining a feature set from the sequence information requiring an abstract idea/mental process of organizing or analyzing features in a way that can be performed mentally with the physical aid of a general computer and routine and conventional methods of providing a saliva sample, isolating RNA from the saliva sample, sequencing nucleic acid from RNA from the sample, determining a feature set from the sequence information, executing a classification model by a computer, using metatranscriptomic feature data from subjects with and without oral cancer to assign to assign subject classification of likely presence or absence of cancer similar, without significantly more. The judicial exceptions are not integrated into a practical application because the claim limitations do not appear to improve the current technology or technical field beyond well-understood, routine, conventional activity. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims provide no specific limitations that provide significantly more.
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.
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.
Claims 1, 7, 15, 20, 26, 31-33, 35-39, 61 and 64 are rejected under 35 U.S.C. 103 as being unpatentable over Apte et al. (“Apte”; Patent App. Pub. WO 2017156031 A1, Sept. 14, 2017). in view of Kondoh et al. (“Kondoh”; Patent App. Pub. WO 2007018143 A1, Feb. 15, 2007, English translation provided).
Apte discloses “Embodiments of a system and method for characterizing a mouth-associated condition in relation to a user can include one or more of: a handling network operable to collect containers including material from a set of users, the handling network including a sequencing system operable to determine microorganism sequences from sequencing the material; a microbiome characterization system operable to determine microbiome composition data and microbiome functional diversity data based on the microorganism sequences, collect supplementary data associated with the mouth-associated condition for the set of users, and transform the supplementary data and features extracted from the microbiome composition data and the microbiome functional diversity data into a characterization model for the mouth-associated condition; and/or a therapy system operable to promote a treatment to the user based on characterizing the user with the characterization model in relation to the mouth-associated condition.” (Abstract).
Regarding claim 1 step (a), Apte teaches a method comprising “e.g., evaluating) a mouth-associated condition in relation to a user (e.g., a human subject)” (Para. 18). Apte teaches a method comprising “the biological sample can be collected from one or more of the subject's … mouth … in a non-invasive manner (e.g., using a swab and a vial).…samples can include.. tissue samples, and/or any other samples… the biological sample can be taken from any suitable body region.” (Para. 71). “mouth” reads on saliva, cheek, gums, tongue or throat).
Regarding claim 1 step (b), Apte teaches a method comprising “sample processing in … can include any one or more of: lysing a biological sample, disrupting membranes in cells of a biological sample, separation of undesired elements… from the biological sample,
purification of nucleic acids… in a biological sample” (Para. 32).
Regarding claim 1 step (c), Apte teaches a method comprising “sequencing of purified nucleic acids can include methods involving targeted amplicon sequencing and/or metagenomic sequencing implementing techniques including one or more of: sequencing-by-synthesis techniques (e.g., Illumina sequencing), capillary sequencing techniques (e.g., Sanger sequencing), pyrosequencing techniques, and nanopore sequencing techniques (e.g., using an Oxford Nanopore technique)” (Para. 34). Apte teaches a method wherein “based upon analysis of RNAs” (Para. 39). “nanopore sequencing techniques” reads on sequencing nucleic acids derived from RNA from the sample to produce metatranscriptomic sequence information.
Regarding claim 1 steps (d-e), Apte teaches a method comprising “a method 100 for characterizing a mouth-associated condition in relation to a user can include one or more of: generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset based on biological samples (e.g., microorganism genetic sequences derived from the samples)… and performing a characterization process for one or mouth-associated conditions, the characterization process derived from the supplementary dataset and features extracted from at least one of the microbiome composition dataset and microbiome functional diversity dataset S130” (Para. 30). Apte teaches a method comprising “Block S110 functions to process each of an aggregate set of biological samples, in order to determine compositional and/or functional aspects associated with the microbiome… compositional and functional aspects can include compositional aspects at the microorganism level, including parameters related to distribution of microorganisms across different groups of kingdoms, phyla, classes, orders, families, genera, species, subspecies, strains, and/or any other suitable infraspecies taxon (e.g., as measured in total abundance of each group, relative abundance of each group, total number of groups represented, etc.)... Compositional and functional aspects can additionally or alternatively include compositional aspects at the genetic level (e.g., regions determined by multilocus sequence typing, 16S sequences, 18S sequences, ITS sequences, other genetic markers, other phylogenetic markers, etc.). Compositional and functional aspects can include the presence or absence or the quantity of genes associated with specific functions (e.g. enzyme activities, transport functions, immune activities, etc.).” (Para.31). Apte teaches a method comprising “In performing the characterization process, Block S130 can use computational methods (e.g., statistical methods, machine learning methods, artificial intelligence methods, bioinformatics methods, etc.) to characterize a subject as exhibiting features characteristic of a group of subjects with a health condition. However, the characterization process can be performed in any suitable manner” (Para. 43) and “In variations of Block S130, performing a characterization process can include generating one or more characterizations of mouth-associated conditions …the characterization process of Block S130 can facilitate identification of which microorganism population(s) (e.g., taxonomic groups, microbiome composition features, etc.) are upregulated or downregulated in relation to mouth-associated conditions, and/or which microbiome functional aspects (e.g., in relation to Clusters of Orthologous Groups / Kyoto Encyclopedia of Genes and Genomes pathways, microbiome functional diversity features, etc.) are upregulated or downregulated in relation to mouth-associated conditions.” (Para. 44).
Regarding claim 1 steps (d-e), Apte teaches a method comprising “characterizing a mouth-associated condition in Block S130 can include generating a diagnostic analysis of a mouth-associated condition (e.g., estimating a risk of being inflicted by the mouth-associated condition, diagnosing the presence of the mouth-associated condition, etc.) and/or associated complications, such as based on at least one of microbiome composition features, microbiome functional diversity features, and/or other suitable features” (Para. 45). “based on at least one of microbiome composition features, microbiome functional diversity features, and/or other suitable features” reads on a feature set including two or more features. Apte teaches a method comprising “models that can be used to characterize and/or diagnose subjects according to at least one of their microbiome composition and functional features (e.g., as a clinical diagnostic, as a companion diagnostic, etc.)….mouth-associated conditions, which can include any one or more of… oral cancer” (Para. 19). Apte teaches a method comprising “assigning users from the population of users to one or more subgroups” (Para.48). “mouth-associated conditions, which can include any one or more of… oral cancer” and “assigning users from the population of users to one or more subgroups” reads on assign, to the human subject, a class label of likely presence of oral cancer or likely absence of oral cancer.
Thus, Apte suggests a method comprising: a) providing a biological sample from a human subject comprising mouth-sourced cells, wherein the mouth-sourced cells comprise oral microbiome cells and somatic cells from the human subject; c) sequencing nucleic acids derived from the RNA from the sample to produce metatranscriptomic sequence information; d) determining, from the sequence information, a feature set including two or more feature types selected from:(1) microbial taxon activity features for one or more microbial taxa, comprising transcriptional activity of the one or more microbial taxa in the saliva sample, (2) microbial gene function activity features for one or more microbial gene orthologs, comprising gene expression of the one or more microbial gene orthologs in the saliva sample, and (3) host gene expression features for one or more somatic cell genes of the subject, comprising gene expression of the one or more somatic cell genes of the human subject in the saliva sample; and e) executing by computer a classification model trained using saliva-derived metatranscriptomic feature data from subjects with oral cancer and saliva-derived metatranscriptomic feature data from subjects without oral cancer, wherein the classification model uses the two or more feature types in the feature set to assign, to the human subject, a class label of likely presence of oral cancer or likely absence of oral cancer. Apte further teaches that “As a person skilled in the art will recognize from the previous detailed description and from the figures and claims, modifications and changes can be made to the embodiments of the invention without departing from the scope of this invention as defined in the following claims” (Para. 82).
However, Apte does not explicitly teach limitation isolating RNA from a saliva sample in step b. Thus, the ordinary artisan would be motivated to modify the method as suggested by Apte to provide the limitation regarding providing a non-invasive mouth source biological sample and isolating RNA to characterize and classify oral cancer in human subjects.
Kondoh discloses “Dysplasias is classified into mild, moderate and severe stages based on the histopathological evidence and is considered to be a series of event produced following the cancer development process. However, inconsistencies are often observed between the result of the pathological diagnosis and the clinical course in patients with the condition. Since the treatment regimens for cancer widely vary depending on the stages and grades of the cancer to be treated, there is a demand for a more accurate and objective diagnostic method. As a result of the analysis made on various genes, a gene is found which shows a specific expression in each of the cancerous state and the precancerous state. Thus, provided is use of the gene in a diagnostic method, a diagnostic agent, a screening method for a therapeutic agent, a vector for use in the treatment, a treatment method for cancer and others.” (Abstract).
Kondoh teaches a method comprising “As one embodiment of the test method including the step of measuring the expression level of the gene …. prepared by a method known to those skilled in the art from… saliva… of the subject” (Para. 28). Kondoh teaches a method comprising “an RNA sample is prepared from a subject” (Para. 33). “saliva… of the subject” and “an RNA sample is prepared from a subject” reads on isolating RNA from the saliva sample. Thus, Apte and Kondoh suggest providing a biological saliva sample from the human subject and isolating RNA from the saliva sample. Accordingly, Apte and Kondoh suggest all the limitations of claim 1.
Apte and Kondoh are both considered to be analogous to the claimed invention because they are in the same field of diagnosing diseases of the mouth using classification models. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the methods of providing a non-invasive biological sample from the mouth, sequencing nucleic acids derived from the RNA, determining a feature set selected from two or mor features from the sequencing information, and using a classification model trained with the feature set data to assign a classification of likely presence or likely absence of as suggested by Apte to incorporate the method comprising the isolation of RNA from the saliva sample as suggested by Kondoh and provide a method for classifying likely presence or likely absence of oral cancer in a human subject according to the limitations of claim 1. These claim elements were known in the art and one of skill in the art could have combined these elements by known methods with no change in their respective functions, and the combination would have yielded the predictable outcome according to the limitations of claim 1. Doing so would allow for a more accurate diagnostic method for oral cancer.
The teachings of Apte and Kondoh are documented above in the rejection of claim 1 under 35 U.S.C. 103. Claims 7, 15, 20, 26, 31, 33, 35-39 and 61 depend on claim 1. Claim 32 depends on claim 31, which depends on claim 1. Claim 64 is independent, yet similar to the limitations of claim 39.
Regarding claims 7 and 61, Apte teaches a method wherein “the biological sample can be collected from one or more of the subject's... mouth… in a non-invasive manner…samples can include.. tissue samples, and/or any other samples… the biological sample can be taken from any suitable body region.” (Para. 71). “mouth” reads on saliva, cheek, gums, tongue or throat. “any suitable body region” reads on cheek, gums, tongue or throat. “tissue” reads on cells. “collected from… mouth… in a non-invasive manner” reads on providing a saliva sample comprising mouth sourced cells. Thus, Apte and Kondoh suggest a method wherein the somatic cells from the human subject comprise cells selected from cheek cells, gum cells and tongue cells; and wherein the somatic cells from the human subject further comprise throat cells.
Regarding claims 15, Apte teaches a method wherein “a set of features useful for characterizations of... mouth-associated conditions can include features derived from one or more of the following taxa… Actinobacteria… Tannerella forsythia… Streptococcus, Rothia, Actinomyces, … Prevotella,… Selenomonas… and/or any other suitable taxa” (Para. 61; Claim 10). “Tannerella forsythia” reads on a negatively associated feature. Thus, Apte and Kondoh suggest a method wherein the classification model uses at least one of the features selected from “Actinobaculum sp. oral taxon 183, Actinomyces massiliensis, Actinomyces sp. oral taxon 448, Alloscardovia omnicolens, Selenomonas sp. CM52, Mycoplasma sanitarium, Parvimonas sp. oral taxon 110, Rothia sp. HMSC062H08, K01697, K12452, Actinomyces johnsonii, Prevotella loescheii, Streptococcus cristatus, Streptococcus sobrinus, Streptococcus sp. HTPH0090, Tannerella forsythia, and K02909.
Regarding claim 20, as stated above in claim 1, Apte teaches a method comprising “a method 100 for characterizing a mouth-associated condition in relation to a user can include one or more of: generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset based on biological samples (e.g., microorganism genetic sequences derived from the samples)” (Para. 30) and “ Compositional and functional aspects can include the presence or absence or the quantity of genes associated with specific functions (e.g. enzyme activities, transport functions, immune activities, etc.)” (Para.31). Furthermore, Kondoh teaches a method comprising “ expression analysis of a gene whose expression changes with the pathology of cancer” (Para. 1) and “The gene that serves as an indicator for cancer testing may be a single gene or a combination of two or more” (Pg. 7, para. 2). “one or more” and “two or more” read on at least ten. Note, "Where the general conditions of a claim are disclosed in the prior art, it is not inventive to discover the optimum or workable ranges by routine experimentation." (MPEP 2144.05). Thus, Apte and Kondoh suggest a method wherein the feature set used by the classification model includes at least 10 microbial taxon activity features, at least 10 microbial gene ortholog function activity features and at least 10 host gene expression features.
Regarding claim 26, Apte teaches a method wherein “generate one or more features for use in the characterization process (e.g., generating a characterization model). Features can include any one or more of… chemical functional features (e.g., cysteine metabolism, etc.), systemic functional features (e.g., systemic immune function; functions associated with systemic diseases; etc.), and/or any suitable functional features.” (Para. 47). Thus, Apte and Kondoh suggest a method wherein the feature set used by the classification model includes one or more features selected from a pro-inflammatory activity feature, a hydrogen sulfide production activity feature, a microbial contribution to cancer- specific energy metabolism feature, a protein fermentation as a tumor genic mechanism feature, tox burden feature, and microbial antibiotic resistance in tumorigenesis feature.
Regarding claim 31 and 33, Apte teaches a method wherein “oral cancer” (Para. 19). “oral cancer” reads on OSCC. Kondoh teaches a method wherein “oral squamous cell carcinoma” (Para. 5) and “wherein the oral cancer or esophageal cancer is squamous cell carcinoma” (Claim 34). Thus, Apte and Kondoh suggest a method wherein the cancer is oral squamous cell carcinoma (OSCC); and wherein the oral cancer is selected from squamous cell carcinoma, verrucous carcinoma, minor salivary gland carcinoma, lymphoma, and benign oral cavity tumor.
Regarding claim 32, Apte teaches a method wherein “a diagnostic analysis of a mouth-associated condition (e.g., estimating a risk of being inflicted by the mouth-associated condition, diagnosing the presence of the mouth-associated condition, etc.) and/or associated complications, such as based on at least one of microbiome composition features, microbiome functional diversity features, and/or other suitable features.” (Para. 45). “estimating a risk of being inflicted by the mouth-associated condition” reads on class label is "likely presence of OSCC" or "unlikely presence of OSCC. Kondoh teaches a method wherein “determine cancer and predict risk ” (Para.21). Kondoh teaches a method wherein “The presence or absence of cancer, the malignancy of cancer, and the like are determined” (Para.44). Thus, Apte and Kondoh suggest a method wherein the class label is "likely presence of OSCC" or "unlikely presence of OSCC.
Regarding claim 35, Apte teaches a method wherein “specific classifications of subjects” (Para. 51) and “generating a set of microbiome feature vectors (e.g., a feature vector for each user of subgroup or population of users) based on microbiome composition features… microbiome functional diversity features… where the set of microbiome feature vectors can be used in training the characterizations model and/or other suitable models. Additionally or alternatively, combinations of features can be used in a feature vector, where features can be grouped and/or weighted in providing a combined feature as part of a feature set” (Para. 52). Furthermore, Apte teaches a method wherein “identification of a "normal" or baseline microbiome composition and/or functional features, as assessed from subjects of a population of subjects who are identified to be in good health” (Para. 67). “subgroup or population of users” reads on subgroups with a presence or absence of oral cancer and subgroups with different stages of oral cancer. Kondoh teaches a method wherein “grade of dysplasia can be identified” (Para. 6) and “diagnosis of cancer according to the stage and grade becomes possible,” (Para.123). Thus, Apte and Kondoh suggest a method wherein the classification model classifies a stage of oral cancer.
Regarding claim 36, Apte teaches a method wherein “accuracy; and/or other suitable criteria, which can be determined based on user preferences, etc.), and/or any other suitable criteria” (Para 49.). “accuracy” reads on sensitivity. Thus, Apte and Kondoh suggest a method wherein the classification model is selected to have a sensitivity of at least 90% and a specificity of at least 90%.
Regarding claim 37, Apte teaches a method wherein “characterizations outputted from different characterization models can be used in determining and/or promoting a therapy” (Para. 57). Apte also teaches a method wherein “The method 100 and/or system of the embodiments can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions. … communication interface” (Para. 81). Thus, Apte and Kondoh suggest a method further comprising: e) outputting the inferred state of oral cancer in the subject to a user interface device or to computer-readable memory.
Regarding claim 38, Apte teaches a method wherein “an interface for providing mouth-associated condition information in an embodiment of a method for microbiome characterization” (Para. 14). Apte teaches a method wherein “method 100 can additionally or alternatively include one or more of: determining a therapy for preventing, ameliorating, and/or otherwise modifying a mouth-associated condition” (Para. 30). Apte teaches a method wherein “therapies to a user (e.g., subject; care provider who administer the therapy; etc.) for treating a mouth-associated condition” (Para. 27). Apte teaches a method wherein “a therapy system (e.g., treatment system) 230 operable to promote a treatment to the user based on characterizing the user with the characterization model in relation to the mouth-associated condition” (Para. 18). Thus, Apte and Kondoh suggest a method further comprising: e) delivering and/or administering to the subject a therapeutic intervention effective to treat the oral cancer.
Regarding claims 39 and 64, Apte teaches a method wherein “and supplementary features (e.g., biometric features derived from the supplementary biometric sensor data such as image data associated with mouth-associated conditions for the set of users, etc.” (Para. 52) and “biopsy” (Para. 71). Thus, Apte and Kondoh suggest a method further comprising: e) for a subject inferred to have oral cancer, performing a confirmatory diagnostic step selected from biopsy or imaging; and A method for classifying likely presence or likely absence of oral cancer in a human subject, comprising: a) providing a saliva sample from the human subject, the saliva sample comprising mouth-sourced cells, wherein the mouth-sourced cells comprise oral microbiome cells and somatic cells from the human subject; b) isolating RNA from the saliva sample; c) sequencing nucleic acids derived from the RNA from the sample to produce metatranscriptomic sequence information; d) determining, from the sequence information, a feature set including two or more feature types selected from: (1) microbial taxon activity features for one or more microbial taxa, comprising transcriptional activity of the one or more microbial taxa in the saliva sample, (2) microbial gene function activity features for one or more microbial gene orthologs, comprising gene expression of the one or more microbial gene orthologs in the saliva sample, and (3) host gene expression features for one or more somatic cell genes of the subject, comprising gene expression of the one or more somatic cell genes of the human subject in the saliva sample; e) executing by computer a classification model trained using saliva-derived metatranscriptomic feature data from subjects with oral cancer and saliva-derived metatranscriptomic feature data from subjects without oral cancer, wherein the classification model uses the two or more feature types in the feature set to assign, to the human subject, a class label of likely presence of oral cancer or likely absence of oral cancer; and f) responsive to assigning a class label of likely presence of oral cancer to the human subject, performing a confirmatory diagnostic step.
Response to Arguments
Applicant's arguments filed 07/29/2026 (Pg. 16-18) with respect to claims 1, 7, 15, 20, 26, 31-33, 35-39, 61 and 64 have been fully considered but do not apply to the new grounds of rejection. To clarify some instances argued in the response filed 07/29/2026 see responses to each argument made by Applicant below:
Applicants’ argument: “Apte fails to teach or suggest determining a likely presence of oral cancer or likely absence of oral cancer using two or more feature types in a feature set determined from metatranscriptomic sequence information, where the metatranscriptomic sequence information is derived from RNA.” (Pg. 16-17)
Response: Applicant’s arguments have been fully considered but not found persuasive because as stated in the new grounds of rejection of claim 1, documented above in the Final office action, Apte and Kondoh do suggest determining a likely presence of oral cancer or likely absence of oral cancer using two or more feature types in a feature set determined from metatranscriptomic sequence information, where the metatranscriptomic sequence information is derived from RNA.
Applicants’ argument: “Applicant further notes with appreciation that claim 20 is considered not obvious over the cited references.” (Pg. 17)
Response: Applicant’s arguments have been fully considered but not found persuasive. Although not previously rejected in the Non-final mailed on 05/08/2026, as necessitated by the amendment filed 07/29/2026, claim 20 is considered obvious over the prior art used for the new grounds of rejection as documented in the Final office action above “Regarding claim 20, as stated above in claim 1, Apte teaches a method comprising “a method 100 for characterizing a mouth-associated condition in relation to a user can include one or more of: generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset based on biological samples (e.g., microorganism genetic sequences derived from the samples)” (Para. 30) and “ Compositional and functional aspects can include the presence or absence or the quantity of genes associated with specific functions (e.g. enzyme activities, transport functions, immune activities, etc.)” (Para.31). Furthermore, Kondoh teaches a method comprising “ expression analysis of a gene whose expression changes with the pathology of cancer” (Para. 1) and “The gene that serves as an indicator for cancer testing may be a single gene or a combination of two or more” (Pg. 7, para. 2). “one or more” and “two or more” read on at least ten. Note, "Where the general conditions of a claim are disclosed in the prior art, it is not inventive to discover the optimum or workable ranges by routine experimentation." (MPEP 2144.05). Thus, Apte and Kondoh suggest a method wherein the feature set used by the classification model includes at least 10 microbial taxon activity features, at least 10 microbial gene ortholog function activity features and at least 10 host gene expression features.”
Applicants’ argument: “Apte does not teach or suggest isolating RNA from a saliva sample… Moreover, Apte teaches sample processing that separates and removes undesired elements such as RNA while purifying nucleic acids such as DNA.” (Pg. 17-18)
Response: Applicant’s arguments have been fully considered and found unpersuasive. While Apte does mention an example stating, “sample processing that removes undesired elements such as RNA while purifying nucleic acids such as DNA”, that does not exclude RNA as the nucleic acids of interest. Furthermore, Apte teaches a method wherein “based upon analysis of RNAs” (Para. 39), hence, Apte does suggest isolating RNA from a sample sourced from the mouth.
Applicants’ argument: “Apte does not teach or suggest … sequencing RNA-derived nucleic acids to produce metatranscriptomic sequence information, or using transcriptional activity or gene expression to determine a feature set including two or more of microbial taxon activity features, microbial gene function activity features, and/or host gene expression features.” (Pg. 17)
Response: Applicant’s arguments have been fully considered but not found persuasive because as stated in the new grounds of rejection for claim 1, documented above in the Final office action, Apte and Kondoh do suggest sequencing RNA-derived nucleic acids to produce metatranscriptomic sequence information, or using transcriptional activity or gene expression to determine a feature set including two or more of microbial taxon activity features, microbial gene function activity features, and/or host gene expression features. Furthermore, as stated above Nanopore sequencing reads on sequencing RNA-derived nucleic acids to produce metatranscriptomic sequence information.
Applicants’ argument: “Apte fails to teach or suggest executing a classification model trained using saliva-derived metatranscriptomic feature data from subjects with oral cancer and subjects without oral cancer, where the classification model uses the two or more feature types in the feature set to assign likely presence or likely absence of oral cancer.” (Pg. 17)
Response: Applicant’s arguments have been fully considered but not found persuasive because as stated in the new grounds of rejection for claim 1, documented above in the Final office action, Apte and Kondoh do suggest executing a classification model trained using saliva-derived metatranscriptomic feature data from subjects with oral cancer and subjects without oral cancer, where the classification model uses the two or more feature types in the feature set to assign likely presence or likely absence of oral cancer.
Applicants’ argument: “Kondoh, which allegedly discloses classification of oral cancers, does not remedy the deficiencies of Apte. For instance, Kondoh does not teach or suggest a classifier that uses two or more RNA-derived, metatranscriptomic-based feature types selected from microbial taxon transcriptional activity, microbial gene function activity, and host gene expression to assign likely presence or likely absence of oral cancer” (Pg. 18)
Response: In response to applicant's argument stated above, the test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981).
Claims 62-63 are rejected under 35 U.S.C. 103 as being unpatentable over Apte et al. (“Apte”; Patent App. Pub. WO 2017156031 A1, Sept. 14, 2017). in view of Kondoh et al. (“Kondoh”; Patent App. Pub. WO 2007018143 A1, Feb. 15, 2007, English translation provided) as applied to claim 1, and further in view of Adami et al. (“Adami”; U.S. Patent App. Pub. US 20120231468 A1, Sept. 13, 2012).
The teachings of Apte and Kondoh are documented above in the rejection of claims 1, 7, 15, 20, 26, 31-33, 35-39, 61 and 64 under 35 U.S.C. 103. Claim 62 and 63 depend on claim 1. However, Kondoh and Apte do not explicitly teach the limitations of claims 62-63.
Adami discloses “The invention relates to methods and kits for detecting the likelihood that a subject has squamous cell carcinoma or neoplasia.” (Field of Invention)
Regarding claim 62, teaches a method wherein “All diagnoses were verified by histopathological examination” (Para. 190). Thus, Apte, Kondoh, and Adami suggest a method further comprising, responsive to assigning the class label of likely presence of oral cancer to the human subject, performing a confirmatory diagnostic step comprising histopathological evaluation.
Regarding claim 63, Adami teaches a method comprising “Analysis of RNA in urine and saliva” (Para. 6). Adami teaches a method comprising “a nucleic acid extraction reagent to isolate nucleic acids from a sample” (Para. 17). Adami teaches a method comprising “then subjected to standard RNA isolation, followed by DNAse 1 treatment with the Aurum Total RNA Mini-kit” (Para. 174) Thus, Apte, Kondoh and Adami suggest a method wherein isolating RNA from the saliva sample comprises exposing the saliva sample to an agent that degrades DNA.
Apte, Kondoh and Adami are considered to be analogous to the claimed invention because they are in the same field of diagnosing diseases of the mouth using classification models. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the methods of providing a non-invasive biological sample from the mouth, isolating RNA from a saliva sample of human subject, sequencing nucleic acids derived from the RNA, determining a feature set selected from two or mor features from the sequencing information, and using a classification model trained with the feature set data to assign a classification of likely presence or likely absence of as suggested by Apte and Kondoh to incorporate the method comprising performing a confirmatory diagnostic step comprising histopathological evaluation and wherein isolating RNA from the saliva sample comprises exposing the saliva sample to an agent that degrades DNA as suggested by Adami and provide a method for classifying likely presence or likely absence of oral cancer in a human subject according to the limitations of claims 62 and 63. These claim elements were known in the art and one of skill in the art could have combined these elements by known methods with no change in their respective functions, and the combination would have yielded the predictable outcome according to the limitations of claim 1. Doing so would allow for a more accurate diagnostic method for oral cancer.
Response to Arguments
Applicant's arguments filed 07/29/2026 (Pg. 16-18) with respect to claims 62-63 have been fully considered but do not apply to the new grounds of rejection. Arguments against Apte and Kondoh are not persuasive as discussed above.
Conclusion of Response to Arguments
In view of the amendments, new grounds of rejections and above responses to arguments, no claims are in condition for allowance.
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KENDRA R VANN-OJUEKAIYE whose telephone number is (571)270-7529. The examiner can normally be reached M-F 9:00 AM- 5:00 PM.
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/KENDRA R VANN-OJUEKAIYE/Examiner, Art Unit 1682
/WU CHENG W SHEN/Supervisory Patent Examiner, Art Unit 1682
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