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 .
Election/Restrictions
Applicant’s election without traverse of Group I (claims 286-303) in the reply filed on 4/1/2026 is acknowledged.
Claims 304 and 305 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to nonelected inventions, there being no allowable generic or linking claim.
Claims 286-303 are pending and are examined on the merits herein.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 4/14/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner, except where noted.
The information disclosure statement filed 4/14/2025 fails to comply with 37 CFR 1.98(a)(2), which requires a legible copy of each cited foreign patent document; each non-patent literature publication or that portion which caused it to be listed; and all other information or that portion which caused it to be listed. A legible copy of non-patent literature document no. 161, Shukla et al., has not been provided, and so this reference has not been considered.
Drawings
The drawings are objected to because Figure 15 is not legible. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
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. Specifically, such a hyperlink appears in para. 696.
Claim Objections
Claim 299 is objected to because of the following informality: in lines 2-3, “site as that of each of plurality of the control biological samples” should read “site as that of each of the plurality of
Claim Interpretation
The term “subsampling” as used in instant claim 286 is not specifically defined in the instant specification. In the instant specification, regarding subsampling of a test biological sample specifically, para. 171 states, “Normalizing or calculating a normalized gene expression value can comprise subsampling of gene expression counts. Normalizing or calculating a normalized gene expression value can comprise subsampling to a target number of assigned reads or a minimum number of assigned reads per sample. An assigned read can be a sequencing read that is assigned to a gene or transcript. For example, an assigned read can be an RNA sequencing read that is aligned to a gene or transcript and included in a gene expression count for that gene or transcript.” Thus, prior art that teaches any manipulation of sequence reads of gene expression counts from a test biological sample, where said manipulation involves the exclusion of any reads, will be considered to read on the claimed subsampling limitation.
Additionally regarding claim 286, it is noted that the gene expression counts from the control biological samples are not required to be used to generate the normalized gene expression values, and that there is no specification for how the gene expression counts from the test biological sample need be normalized.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in 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.
Claims 286-287, 290-300, and 303 are rejected under 35 U.S.C. 103 as being unpatentable over Pan et al. (US 2020/00199671 A1).
Pan teaches methods for measuring RNA molecules utilizing sequencing libraries to detect the presence or absence of a disease (Abstract). Para. 19 describes using Pan’s teachings in a method related to cancer, where matched samples are collected from multiple subjects with and without cancer (where “matched” samples indicates they can be comparable, as required by the instant claims), RNA is sequenced, and then expression levels of biomarkers are compared, where the cancer samples have higher levels of a particular biomarker compared to that of the non-cancerous samples (where the higher levels of biomarkers indicate aberrantly expressed genes as claimed; instant claim 291).
A control data set of RNA sequences can include sequences obtained from one or more healthy subjects (i.e. a plurality of independently obtained controls; para. 72). Healthy controls can be a database of sequence data from one or more healthy subjects (paras. 92 and 94). In the embodiment of Pan described above, it would be prima facie obvious to gather healthy control gene expression data and then put this data into a database for ease of comparison. This would allow the control data to be used repeatedly with multiple cancerous samples, rather than obtaining new control data for every comparison. This would save time and monetary resources, as healthy samples would not need to be repeatedly gathered and examined. Additionally, utilizing a healthy control database can allow for easy sharing of control gene expression data among many labs and practitioners worldwide, also allowing the database to grow if additional data is collected, and expanding the ability of the database to be used to make matched, accurate comparisons with cancer data. Pan even teaches the use and utility of such a publicly available database that contains healthy control data (para. 94).
Pan also teaches various embodiments in which test/cancer sample data is filtered. Para. 9 describes that cfRNA can come from a biological test sample from subject, and notes that sequence read filtering can occur by comparing cfRNA reads to sequence reads from healthy cells. Paras. 17, 67, and 71 note similar filtering methods. Thus, it would be prima facie obvious to perform this filtering in the method of Pan described above so that only those sequence reads that differ between cancerous and non-cancerous samples are examined. This would allow pinpointed analysis to evaluate biomarkers for particular cancers, and thus could more easily allow for diagnostics. By filtering reads, this would also allow for less computationally intensive analyses for those reads that remain included. This filtering is considered analogous to the claimed subsampling.
Paras. 16 and 136 note that sequence reads and gene expression data from patients can be normalized. Pan also teaches the use of reference sequences and internal standards generally, including the use of typical reference genes (para. 55). The reference also notes the normalization of both cancer and non-cancer sequencing reads (paras. 306-307). It would generally be prima facie obvious to the ordinary artisan to normalize the cancer and non-cancerous samples before comparison of expression values, as this would decrease error, noise, and other sources of variability in the data, and would therefore increase the accuracy of results. As Pan is drawn to methods of diagnosis and treatment (e.g. paras. 81 and 156), ensuring the accuracy of comparisons would lower false negative and false positive rates, ensuring less waste of resources, less stress on true-negative patients, and likely better prognoses and treatment interventions for true-positive patients (instant claim 298).
Pan teaches that the data generated from their invention can then be used to make treatment decisions (paras. 64-65, 121-122, and 156). Specific treatments, particularly for cancer, are recited (e.g. para. 270). Para. 156 states, “Methods disclosed herein can be used in making therapeutic decisions, guidance and monitoring, as well as development and clinical trials of cancer therapies. For example, treatment efficacy can be monitored by comparing patient cfRNA in samples from before, during, and after treatment with particular therapies such as molecular targeted therapies (monoclonal drugs), chemotherapeutic drugs, radiation protocols, etc. or combinations of these. In some embodiments, cfRNA is monitored to see if certain cancer biomarkers increase or decrease after treatment, which can allow a physician to alter a treatment (continue, stop or change treatment, for example) in a much shorter period of time than afforded by methods of monitoring that track traditional patient symptoms. In some embodiments, a method further comprises the step of diagnosing a subject based on the RNA-derived sequences, such as diagnosing the subject with a particular stage or type of cancer associated with a detected cfRNA biomarker, or reporting a likelihood that the patient has or will develop such cancer. In embodiments, methods disclosed herein further comprise selecting a treatment based on the condition detected. In embodiments, the selected treatment is administered to the subject. Where the condition is cancer, or a particular cancer type and/or stage, an appropriate anti-cancer therapy may be selected. Non-limiting examples of anti-cancer therapies include radiation therapy, surgical resection, administration of an anti-cancer agent (e.g., an immunotherapy agent, a chemotherapy agent, or the like), or a combination of one or more of these.” Thus, after evaluating biomarkers in the methods of Pan described above, subjects could be treated based on their biomarker results and conditions. These treatments are considered encompassed by the “wellness recommendation” and “therapeutic agent” language of the instant claims (instant claim 295).
Thus, claims 286, 291, 295, and 298 are prima facie obvious over Pan.
Regarding claim 287, Pan notes that up to 25 or more biomarkers may be used (para. 8) and generally teaches analyzing more than one biomarker (e.g. para. 19). Figure 9 shows the analysis of 20 genes that showed the greatest difference in expression level between cancerous and non-cancerous samples in relation to lung cancer. Therefore, it would be prima facie obvious that the method of Pan described above could be used on multiple aberrantly expressed genes, and the ordinary artisan would be motivated to examine more than one gene, simply because this would provide more accurate diagnostic results for a patient, as a false negative or false positive would be less likely as additional data is added to a diagnostic method.
Thus, claim 287 is prima facie obvious over Pan.
Regarding claims 290 and 296, Pan teaches that their treatments can involve the use of immunotherapy agents, and that therapies can target particular molecules (para. 156). Combining these teachings, it would thus be prima facie obvious that the treatment used could target a gene that encodes an immune modulatory protein. As the teachings of Pan used in the rejection of claim 286 above focus on cancer, which is a disease that affects the immune system, there would be genes that would be aberrantly expressed in cancer samples that are related to immune modulation. By providing therapies that target these genes, the immune system altering effects of cancer may be mitigated, which may improve patient symptoms and prognosis.
Thus, claims 290 and 296 are prima facie obvious over Pan.
Regarding claim 292, Pan provides examples of their method in which biomarkers in cfRNA and matched tissue were examined in subjects with and without cancer (paras. 41 and 302-303). Figures 16A-D display the expression levels of the biomarkers. For several of the biomarkers, expression is higher in non-cancer samples compared to those of breast and/or lung cancer (see FABP7, GABRG1, KLK5, and LALBA of Figure 16A, CSN1S1, CXCL17, and NKX2-1 in Figure 16B, and PTPRZ1 and SLC34A2 in Figure 16C). Thus, biomarkers with lower expression in cancer samples compared to non-cancerous samples can be examined in the method of Pan. It would be prima facie obvious to examine biomarkers with these expression patterns in the method of Pan described above in the rejection of claim 286 because any biomarker that differs in expression between cancerous and non-cancerous samples can provide valuable diagnostic data, whether that difference is higher or lower expression. This is because any difference from a non-cancerous baseline can indicate disease, and different cancers may have different aberrant expression patterns, where expression in increased in one cancer but decreased in another (see for example PTPRZ1 in Figure 16C, where expression appears higher compared to that of non-cancerous samples for lung cancer, but lower compared to that of non-cancerous samples for breast cancer). By examining a wide variety of biomarkers that differ in this manner, better diagnostic criteria can be developed and utilized. As expression is generally evaluated in the teachings of Pan, determining expression of any known and potentially informative RNA biomarkers would be possible for the ordinary artisan.
Thus, claim 292 is prima facie obvious over Pan.
Regarding claim 293, Pan teaches that the data of their invention can be made available within the context of a database, and that specifically multiple databases may be used (para. 189). One of the databases can specifically contain data related to sick subjects with a known condition or disorder. Additionally, Pan teaches that training sets of data can be used to develop classifiers before test sets are examined (Figure 17A), allowing for the evaluation of aberrant genes before the test sample is examined. Thus, it would be prima facie obvious that once the training set is fully evaluated, complete with examined biomarkers (see Figure 17A, which notes the evaluation of “dark channel” biomarkers, which according to para. 63 are aberrantly expressed in disease samples), that said biomarkers which are associated with a particular disease or condition would be saved to then be evaluated in the test sample. As this biomarker information would be more easily stored and later applied via a computer rather than manually, and Pan teaches the use of databases to store disease biomarker information, it would also be prima facie obvious to store this information in a database, as is alluded to by Pan in the reference’s database teachings.
Thus, claim 293 is prima facie obvious over Pan.
Regarding claim 294, Pan teaches the generation of reports that include the expression levels for the measured RNA, as well as an indication of disease (e.g. cancer) present in a patient (para. 122). Thus, it would be prima facie obvious that the generation of such a report in relation to the methods of Pan described above in the rejection of claim 286 would highlight the genes that were aberrantly expressed between the patient and control samples, as these are the determinants of disease. This would provide more information than a simple report indicating whether or not a disease is likely to be present, and would allow users/clinicians to also evaluate the data to determine the validity of machine conclusions, providing a check to the method to avoid clear false negatives or false positives.
Thus, claim 294 is prima facie obvious over Pan.
Regarding claim 297, Pan teaches various embodiments in which more than 10 non-cancerous samples are used. In Example 1, 112 non-cancer samples were used (para. 281), in Example 3, 38 non-cancerous samples were used as controls (para. 302), and in Example 5, at least 105 non-cancer samples were used (para. 313). Thus, in the methods of Pan described above in the rejection of claim 286, it would be prima facie obvious that data from more than 10 non-cancerous samples could be used in the control sample database. By providing more control data, this would ensure the accuracy of expression conclusions regarding said data (e.g. ensuring that the effects of any control outliers are minimal). Additionally, many of the control samples of Pan are matched for various criteria compared to cancer samples (e.g. the control samples of para. 302 are age-matched, and those of para. 313 are age, gender, and ethnicity matched). By providing a large number of control samples, this would allow for a wider range of potential matching for these criteria with cancer samples, which would allow for better limiting of the effects of confounding variables. As Pan teaches the measurement of many control samples, and the actual methods of the teachings of Pan would not be altered by incorporating these teachings, there would be a reasonable expectation of success.
Thus, claim 297 is prima facie obvious over Pan.
Regarding claim 299, Pan teaches that control data can be taken from public databases that include tissue RNA-seq data (para. 94). Thus, it would be prima facie obvious to use such data in the control sample database of Pan described above in the rejection of claim 286, as this would allow for control data that is more readily relevant to cancer tissue samples, making for gene expression comparisons that are likely more accurate due to this increase in control of confounding factors. Pan teaches various embodiments in which tissue samples are taken from cancer patients (e.g. paras. 19, 281, 298, and 301), but for a non-cancerous individual, obtaining tissue samples solely for comparative purposes is generally unnecessarily invasive. By using a database that already contains RNA-seq data from tissues, this would avoid having to obtain such invasive samples, while still providing all the comparative benefits described above. As Pan teaches that such control tissue data is in a publicly available database (see para. 94), there would be a reasonable expectation of success.
Thus, claim 299 is prima facie obvious over Pan.
Regarding claim 300, para. 309 describes a working example in which duplicate sequencing reads were removed from analysis. Thus, it would be prima facie obvious for the ordinary artisan to remove duplicate reads in the method described above in the rejection of claim 286. This would ensure that read counts for particular markers or variants are not inflated, which may lead to inaccurate results or conclusions, potentially affecting any resulting patient diagnoses, prognoses, or treatment.
Thus, claim 300 is prima facie obvious over Pan.
Regarding claim 303, Pan teaches that treatments may be used to monitor biomarker expression, particularly during the course of treatment to determine treatment efficacy (para. 156). Particularly, “cfRNA is monitored to see if certain cancer biomarkers increase or decrease after treatment, which can allow a physician to alter a treatment (continue, stop or change treatment, for example) in a much shorter period of time than afforded by methods of monitoring that track traditional patient symptoms,” (para. 156). Thus, the link between treatments and expression is made clear by Pan. Furthermore, the reference teaches that computer systems and computer-readable media/instructions can be used to implement the teachings of the invention (paras. 20-21). In para. 122, Pan teaches that computers may be used to generate reports that can indicate disease type and a therapeutic classification for a patient, which involves determining the best treatment category for a patient based on their gene expression data (para. 121).
As the purpose of the treatments of Pan is to produce beneficial or desired results related to a patient’s condition (para. 64), it would thus be prima facie obvious to use the computer methods and instruction of Pan in conjunction with the gene expression data to place patients in therapeutic classifications for treatments that would be likely to be effective, and then monitor said efficacy over the course of the treatment. If the treatment was effective or not effective, then a positive or negative association, respectively, with said treatment and gene expression data would be generated. This association would not only be useful for the patient initially examined, as it would inform if treatments should be adjusted, but it would also be useful for any additional patients examined that exhibit similar gene expression data, as negatively associated treatments could be avoided, saving resources and potentially allowing more effective treatments to be preferentially used sooner, improving patient outcomes. There would be a reasonable expectation of success as this would simply be a combination of the various teachings of Pan involving computer methods/instructions and treatments with the general methods of the invention, and would involve basic mathematical comparisons.
Thus, claim 303 is prima facie obvious over Pan.
Claims 288-289 and 301-302 are rejected under 35 U.S.C. 103 as being unpatentable over Pan et al. (US 2020/00199671 A1), in view of Cheever et al. (Clin. Cancer Research, 2011), and in view of Graddis et al. (Int J Clin Exp Pathol, 2011).
Pan teaches the methods of claims 286-287, 290-300, and 303, as described above. However, the reference does not teach the specific development of treatments and clinical trials or cancer vaccines as claimed. Para. 156 mentions that the methods of the reference can be used to develop clinical trials, but does not provide details on how this would be done. As noted above, this paragraph also discusses the use of anti-cancer/immunotherapies. Pan also specifically notes that prostate cancer can be examined with the methods of their invention (paras. 152 and 154-155).
Cheever teaches the development of a therapeutic cancer vaccine for patients who have prostate cancer (Abstract). This vaccine elicits an immune response in patients in response to prostatic acid phosphatase (PAP), which is expressed in prostate cancer cells (Abstract and page OF1, column 1, para. 1). Cheever explains the development of the vaccine, from preclinical data, to Phase I-III clinical trials, to safety analyses, and ways to improve vaccine efficacy are discussed (pages OF1-OF6). Cheever also notes a specific mechanisms of action of the vaccine on the immune system (pages OF4-OF5, “Mechanism of Therapeutic Efficacy”).
Graddis teaches the examination of PAP in human tissues (Abstract). In particular, the reference notes that the examination of PAP RNA is possible (pages 295-296, joining para. and page 296, column 1, para. 3). Page 298 details a qPCR analysis conducted by Graddis (“Quantitative polymerase chain reaction”), and Table 2 shows qPCR results of examining PAP in various normal and tumor tissues, providing a clear result that PAP is overexpressed in tumor tissues of the prostate.
Prior to the effective filing date of the claimed invention, it would have been prima facie obvious for one of ordinary skill in the art to use the guidance of Cheever and Graddis to apply the information obtained by the methods of Pan into specific means of developing anti-cancer therapies that can be approved for use in treating cancer patients. Specifically, Pan is used to identify genes that are differentially expressed in cancer samples/patients compared to controls. Pan also has a particular interest in overexpressed biomarkers in disease/cancer (e.g. paras. 19, 30, 145, and 287). Cheever and Graddis provide evidence that an overexpressed biomarker in a cancer (PAP) can be evaluated as a treatment target, and Cheever specifically provides a roadmap for the development of a successful anti-cancer vaccine treatment for that target via clinical trials. For Cheever, this development lead to drug approval in the US, and the vaccine is shown to increase survival in a cancer population that has generally low prolonged survival (Abstract and Figure 1). The ordinary artisan would thus be motivated to evaluate similarly overexpressed targets in other cancers to develop additional vaccines that can aid in prolonging patient survival. There would be a reasonable expectation of success in combining these methods as the use of immunotherapies is already well-known, as evidenced by Pan, and methods for evaluating drug/vaccine efficacy are also well-known, as Cheever teaches each step of their vaccine development, and notes the development of another similar vaccine treatment (page OF5, column 1, para. 4), showing that other vaccines outside of their own can be developed.
Thus, claims 288-289 and 301-302 are prima facie obvious over Pan, in view of Cheever, and in view of Graddis.
Conclusion
No claims are currently allowable.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FRANCESCA F GIAMMONA whose telephone number is (571)270-0595. The examiner can normally be reached M-Th, 7-5pm.
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, Gary Benzion can be reached at (571) 272-0782. 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.
/FRANCESCA FILIPPA GIAMMONA/Examiner, Art Unit 1681