NANTOMICS, LLC et al.

Patent Trials and Appeals Board

Jan 18, 2022

2021001910 (P.T.A.B. Jan. 18, 2022)

UNITED STATES PATENT AND TRADEMARK OFFICE UNITED STATES DEPARTMENT OF COMMERCE United States Patent and Trademark Office Address: COMMISSIONER FOR PATENTS P.O. Box 1450 Alexandria, Virginia 22313-1450 www.uspto.gov APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO. 15/568,487 10/23/2017 Andrew Nguyen 102402-11US2/000249.2US 5457 149345 7590 01/18/2022 Umberg Zipser, LLP 1920 Main Street, Suite 750 Irvine, CA 92614 EXAMINER BORIN, MICHAEL L ART UNIT PAPER NUMBER 1631 NOTIFICATION DATE DELIVERY MODE 01/18/2022 ELECTRONIC Please find below and/or attached an Office communication concerning this application or proceeding. The time period for reply, if any, is set in the attached communication. Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the following e-mail address(es): ipsupport@umbergzipser.com patents@umbergzipser.com rdean@umbergzipser.com PTOL-90A (Rev. 04/07) UNITED STATES PATENT AND TRADEMARK OFFICE BEFORE THE PATENT TRIAL AND APPEAL BOARD Ex parte ANDREW NGUYEN, KAYVAN NIAZI, PATRICK SOON-SHIONG, SHAHROOZ RABIZADEH, and STEPHEN CHARLES BENZ1 Appeal 2021-001910 Application 15/568,487 Technology Center 1600 Before DONALD E. ADAMS, ERIC B. GRIMES, and RACHEL H. TOWNSEND, Administrative Patent Judges. GRIMES, Administrative Patent Judge. DECISION ON APPEAL This is an appeal under 35 U.S.C. § 134(a) involving claims to a method of making synthetic antibodies for cancer treatment, which have been rejected as obvious. We have jurisdiction under 35 U.S.C. § 6(b). We REVERSE. 1 Appellant identifies the real parties in interest as Nant Holdings IP, LLC and NantOmics LLC. Appeal Br. 2. “Appellant” refers to “applicant” as defined in 37 C.F.R. § 1.42. Appeal 2021-001910 Application 15/568,487 2 STATEMENT OF THE CASE “[M]ost, if not all neoplastic diseases are accompanied by a relatively large number of mutations.” Spec. ¶ 4. “Unfortunately, . . . many tumors have developed various immune evading mechanisms.” Id. ¶ 6. Appellant’s invention “is directed to identification and use of various cancer neoepitopes in a patient, particularly where such neoepitopes have not elicited a protective immune response in the patient.” Id. ¶ 8. [O]ne contemplated method . . . commences with an omics analysis to identify mutations in the tumor relative to normal tissue of the same patient, and a step of calculation of one or more neoepitopes is performed to define neoepitopes that are specific to the tumor and patient. So obtained neoepitopes are further subjected to [a] filtering step to, for example, eliminate weakly or non-expressed neoepitopes. Identified expressed neoepitopes may then be subject to additional filtering algorithms. Id. ¶ 23. “[A]fter the in silico identification of suitable neoepitope sequences, corresponding synthetic peptides are then prepared” and used to isolate a recombinant antibody. Id. ¶ 24. “Sequence analysis . . . will then reveal the sequences for the complementarity determining regions.” Id. “This information can then be used as a guide to modify a nucleic acid encoding a human or humanized scFv or other antibody. Once expressed in a suitable expression system, the synthetic antibody (‘synbody’) is then formulated into a desired therapeutic entity.” Id. Appeal 2021-001910 Application 15/568,487 3 Claims 1, 2, 4-7, and 10-20 are on appeal. Claim 1, the only independent claim, is reproduced below: 1. A method of generating a pharmaceutical agent for cancer immune therapy, comprising: using matched normal omics data of a tumor to generate in silico a plurality of n-mers that contain at least one patient- and cancer-specific cancer neoepitope wherein the omics data from each of the tumor and the matched patient normal sample include data selected from the group consisting of whole genomic sequencing data, exome sequencing data, transcriptome data, and combinations thereof; filtering in silico the n-mers to so obtain a subset of neoepitope sequences wherein the filtering is filtering by type of mutation, filtering by strength of expression, filtering by subcellular location, and/or filtering by binding affinity towards an HLA-type of the patient; preparing at least one synthetic n-mer peptide using sequence information from the subset of neoepitope sequences; using the synthetic n-mer peptide to isolate a recombinant antibody; obtaining sequence information of the complementarity determining region of the recombinant antibody; generating a synthetic antibody using the sequence information of the complementarity determining region of the recombinant antibody; and coupling the synthetic antibody to a therapeutic or diagnostic agent to so obtain the pharmaceutical agent. Appeal Br. 7 (Claims App.). Appeal 2021-001910 Application 15/568,487 4 OPINION Claims 1, 2, 4-7, and 10-20 stand rejected under 35 U.S.C. § 103 as obvious based on Chan,2 either of Sanborn ’6703 or Sanborn ’001,4 combined with Larman5 and any one of Goldenberg,6 Jackson,7 or Wong.8 Final Action9 3. The Examiner finds that Chan “teaches using genomics information to generate in silico a plurality of n-mers that contain at least one patient- and cancer-specific cancer neoepitope and filtering the n-mers to so obtain a subset of neoepitope sequences.” Id. The Examiner finds that Chan also teaches “identifying expressed neoepitopes, in particular, identifying neoepitope sequence signatures.” Id. at 4. The Examiner finds that [Sanborn ’670] or [Sanborn ’001] teach in silico filtering of genome sequence data by location-guided synchronous alignment of tumor and normal samples. With regard to criteria for filtering, [Chang] teach filtering based on mutations (91,92), [Sanborn ’670] teach filtering based on mutations (claim 22, paragraphs 43,65,66,72,75), or location (claims 10, 11, paragraphs 43,65,66,72,75), gene copy number, repeat copy number, inversion, deletion, somatic mutation, germ line mutation, etc. (paragraph 15). Id. at 4-5. 2 Chan et al., WO 2015/103037 A2, published July 9, 2015. 3 Sanborn et al., US 2012/0059670 A1, published Mar. 8, 2012. 4 Sanborn et al., US 2012/0066001 A1, published Mar. 15, 2012. 5 Larman et al., Construction of a rationally designed antibody platform for sequencing-assisted selection, PNAS 109(45):18523-18528 (2012). 6 Goldenberg et al., US 2019/0070308 A1, published Mar. 7, 2019. 7 Jackson et al., US 2018/0147294 A1, published May 31, 2018. 8 Wong et al., US 2018/0142016 A1, published May 24, 2018. 9 Office Action mailed June 2, 2020. Appeal 2021-001910 Application 15/568,487 5 The Examiner relies on Larman, Goldenberg, Jackson, and Wong with regard to the claim limitations relating to recombinant and synthetic antibodies. Id. at 5. The Examiner concludes that, [a]t the time of invention, a practitioner could have combined obtaining subset of cancer-specific neoepitopes from set of peptide obtained from omics data, as in [Chan], optionally further filtering sequence data as in [the Sanborn references], recombinantly producing an antibody, and identifying residues of complementary[sic]-determining region (CDR), as in [Chan], producing synthetic antibodies using sequence information of CDRs, as in Larman et al., and coupling a synthetic antibody of interest to a therapeutic or diagnostic agent to obtain a pharmaceutical agent, as in [Chan], or [Goldenberg, Jackson, or Wong]. Id. at 5-6. The Examiner reasons that “the predictable result of obtaining a pharmaceutical agents having desired immunotherapy effect for cancer therapy would be achieved.” Id. at 6. Appellant argues that the Examiner’s rejection “does not account for the filtering step of claim 1.” Appeal Br. 5. Appellant argues that “paragraphs 0091 and 0092 of [Chang] explain merely what somatic mutations are, and that a somatic mutation may result in a neoantigen or neoepitope. The filtering step as recited in claim 1 is not taught in [Chang].” Id. Appellant also argues that [n]one of [Sanborn ’670] claims 10, 11, and 22, and . . . paragraphs 15, 43, 65, 66, 72 & 75 teach a filtering step. Rather, these portions . . . discuss analyses of various genomic positions from a patient’s tumor and germline genomes using the aligned short-read data contained in SAM/BAM-formatted files. Finally, [Sanborn ’001] does not even mention “filter” or “filtering” in the disclosure. Id. at 5-6. Appeal 2021-001910 Application 15/568,487 6 We agree with Appellant that the Examiner has not persuasively shown that the cited references would have made obvious the filtering step recited in claim 1: “filtering in silico the n-mers to so obtain a subset of neoepitope sequences wherein the filtering is filtering by type of mutation, filtering by strength of expression, filtering by subcellular location, and/or filtering by binding affinity towards an HLA-type of the patient.” Appellant’s Specification states that neoepitopes are especially suitable for use herein where omics (o [sic] other) analysis reveals that the neoepitope is actually expressed. . . . Consequently, it is generally preferred that the omics analysis also includes an analysis of gene expression (transcriptomic analysis) to so help identify the level of expression for the gene with a mutation. Spec. ¶ 30. The Specification states that neoepitopes can also be filtered according to sub-cellular location: “For example, it is contemplated that neoepitope sequences are selected for further use if they are identified as having a membrane associated location (e.g., are located at the outside of a cell membrane of a cell).” Id. ¶ 32. The Specification also states that neoepitopes can then be further filtered in silico against an identified patient HLA-type. Such HLA-matching is thought to ensure strong binding of the neoepitopes to the MHC-I complex . . . and the MHC-II complex. . . . Targeting both antigen presentation systems is particularly thought to produce a therapeutically effective and durable immune response. Id. ¶ 33. “In yet another aspect of filtering, the neoepitopes may be compared against a database that contains known human sequences to so avoid use of a human-identical sequence. Moreover, filtering may also include removal of neoepitope sequences that are due to SNPs in the patient.” Id. ¶ 35. Appeal 2021-001910 Application 15/568,487 7 Thus, in light of the Specification, the broadest reasonable interpretation of “filtering,” as recited in claim 1, requires analyzing specific properties affected by the tumor-specific mutations that result in neoepitopes “to so obtain a subset of neoepitope sequences”; i.e., analyzing specific properties and selecting those neoepitopes that have a desired type of mutation, strength of expression, subcellular location, and/or binding affinity towards an HLA-type. The Examiner finds that Chan and Sanborn ’670 disclose this step. Final Action 4-5.10 The Examiner points specifically to Chan’s paragraphs 91 and 92. Id. at 4. Those passages state that somatic mutations can result in expression of epitopes, that Chan’s invention can define epitopes indicative of a specific clinical outcome, and that neoepitopes can comprise a tetrapeptide that contributes to increased binding affinity to MHC Class I molecules. Chan ¶¶ 91, 92. The Examiner has not persuasively shown this description of a potential property of neoepitopes would be interpreted as a description of “filtering” n-mers that contain neoepitopes, as required by claim 1. 10 The Examiner also finds that both Sanborn references “teach in silico filtering of genome sequence data by location-guided synchronous alignment of tumor and normal samples.” Final Action 4. The Examiner, however, does not point to any disclosure in either reference to support this finding. We note that Appellant’s Specification states that “computational analysis of the sequence data may be performed . . . in silico by location- guided synchronous alignment of tumor and normal samples as, for example, disclosed in [the Sanborn references] using BAM files.” Spec. ¶ 26. This discussion, however, is in the context of analyzing omics data to identify neoepitopes, not in the context of filtering. Compare id. ¶¶ 25, 30. Appeal 2021-001910 Application 15/568,487 8 The Examiner also points to claims 10, 11, and 22, and paragraphs 15, 43, 65, 66, 72, and 75 of Sanborn ’670 as disclosing “filtering based on mutations . . . or location.” Final Action 4. The cited claims discuss synchronizing genetic sequence strings by aligning substrings based on locations within a genetic sequence string (claims 10 and 11) or a method of deriving a differential genetic sequence object comprising an attribute that comprises a genetic status that can comprise a somatic or germline mutation. Paragraph 15 of Sanborn ’670 likewise discusses a genetic status that can comprise a somatic or germline mutation, among other things. The Examiner has not persuasively explained how any of these disclosures amount to “filtering” as required by claim 1. Similarly, paragraphs 65, 66, 72, and 75 of Sanborn ’670 state that the disclosed methods can be used to detect and quantify altered gene structures, gene mutations, etc. for conditions or disorders, including cancers, associated with altered expression of a gene or protein. Paragraph 43 of Sanborn ’670 states that the disclosed method of processing allows discovery of somatic or germline sequence variants like point mutations. However, the Examiner has not explained how these disclosures meet the “filtering” limitation of claim 1. In summary, the Examiner has not identified any disclosure or suggestion in the cited references of claim 1’s step of “filtering in silico the n-mers to so obtain a subset of neoepitope sequences wherein the filtering is filtering by type of mutation, filtering by strength of expression, filtering by subcellular location, and/or filtering by binding affinity towards an HLA- type of the patient.” Appeal 2021-001910 Application 15/568,487 9 “An examiner bears the initial burden of presenting a prima facie case of obviousness.” In re Huai-Hung Kao, 639 F.3d 1057, 1066 (Fed. Cir. 2011). In this case, the Examiner has not shown that a method meeting all of the limitations of Appellant’s claims would have been obvious in view of the cited references, and therefore has not made out a prima facie case of obviousness. The rejection under 35 U.S.C. § 103 is reversed. DECISION SUMMARY In summary: Claim(s) Rejected 35 U.S.C. § Reference(s)/Basis Affirmed Reversed 1, 2, 4-7, 10-20 103 Chan, Sanborn ’670, Sanborn ’001, Larman, Goldenberg, Jackson, Wong 1, 2, 4-7, 10-20 REVERSED