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 .
Applicant’s Response
Applicant’s response, filed 12/08/2025, has been fully considered. Rejections and/or objections not reiterated from previous Office Actions are hereby withdrawn. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Claims Status
Claims 1-54 and 69 were previously canceled.
Claims 55-68 are pending.
Claims 55-68 are examined.
Priority
The instant application is a continuation of US Application No. 15/569334, filed 10/25/2017, which is a national stage application of PCT/EP2016/059401, filed 04/27/2016. The instant application also claims priority to UK application 1603731.9, filed 03/03/2016, application 1603663.4, filed 03/02/2016, and application 1507100.4, filed 04/27/2015. Therefore, the Effective Filing Date (EFD) assigned to each of the claims 55-68 is the UK filing date of application 1507100.4, filed 04/27/2015.
Withdrawn Objections/Rejections
The rejection of claims 55-68 under 35 USC 103 over Landau et al. in view of Hacohen et al. and further in view of Robertson et al. is withdrawn in view of the newly claimed priority.
Claim Objections
Claim 55 is objected to because of the following informalities:
In claim 55, step iv), “wherein a clonal mutation 1s a mutation” should read “wherein a clonal mutation is a mutation”
Appropriate correction is required.
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.
Claims 55-68 are rejected under 35 U.S.C. 103 as being unpatentable over Landau et al. (“Evolution and Impact of Subclonal Mutations in Chronic Lymphocytic Leukemia”, published February 2013, IDS reference and Extended Experimental Procedures attached with previous Office Action) in view of Hacohen (US 2016/0339090 A1, PCT filed December 2014, IDS reference) and further in view of Sykes et al. (US 2014/0101786 A1, published April 10, 2014). This is a new grounds of rejection as necessitated by the corrected priority date.
Regarding claim 55, Landau et al. teaches a method comprising:
a) using a processor to perform a computational pipeline (Landau et al. teaches a computer-implemented method (see Section “Experimental Procedures” and thus inherently teaches using a processor to perform the steps) comprising:
i) receiving DNA and/or RNA sequence data, wherein the DNA and/or RNA sequence data were generated by a sequencing platform pipeline from a tumor sample from the subject and a non-tumor sample from the subject (Abstract; page 721, Section “Experimental Procedures”);
ii) determining mutations present in said tumor sample by aligning and comparing, a somatic variant calling algorithm, the DNA and/or RNA sequence data from said tumor sample with the DNA and/or RNA sequence data from the nun-tumor sample (page 723, column 2);
iii) obtaining a cancer cell fraction probability for each mutation identified in ii) by integrating a tumor copy number estimate, a non-tumor copy number estimate and a tumor purity estimate obtained from said DNA and/or RNA sequence data with variant allele frequencies (page 716, column 1);
iv) identifying one or more clonal mutations, wherein a clonal mutation is a mutation of the mutations identified in ii) that is present in essentially all tumor cells, and where the probability the cancer cell fraction (P(CCF)) is such that the 95% confidence interval of the cancer cell fraction is greater than or equal to 0.75 (Section “Extended Experimental Procedures”, “Estimation of Mutation Cancer Cell Fraction Using ABSOLUTE” paragraph 3 (attached with this Office Action));
v) and c) characterization of the clonal mutations in a tumor can be readily adopted for clinical applications that leads to the development of therapeutic paradigms that not only target specific drivers (i.e., “targeted therapy”) but also the evolutionary landscape of the markers (page 721, column 2, paragraph 4).
Landau et al. does not teach receiving DNA and/or RNA sequence data in FASTQ format, using software implementing a Burrows and Wheeler Alignment (BWA) algorithm, or identifying one or more clonal neoantigens, wherein a clonal neoantigen is an antigen encoded by a sequence which comprises a clonal mutation identified in iv), and step b) selectively expanding tumor infiltrating lymphocytes isolated from the tumor of the subject that target the one or more clonal neoantigens, and the cell-based immunotherapy comprising administering to the subject a composition comprising the selectively expanded tumor infiltrating lymphocytes.
However, Hacohen et al. teaches Bioinformatics analysis being conducted by performing sequence analysis of exome and RNA-seq fastq files leveraging existing bioinformatic pipelines that have been used and validated extensively (paragraph [0454]). Furthermore, Hacohen et al. teaches using the Burrows-Wheeler Alignment Tool to align the read pairs to the human genome (paragraph [0455]). Hacohen et al. also teaches selecting a tumor-specific non-silent mutation not present in the non-tumor sample where each neo-epitope binds to the HLA protein of the subject (paragraphs [0043] and [0044]). Hacohen et al. also teaches T-cell inducing cancer vaccines formulated to target a subject’s tumor (paragraph [0008]) and administering cells to the subject to treat the tumor (paragraph [0053]).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have incorporated the fastq format, bwa algorithm, identification of clonal neoantigens, and administration of treatment of Hacohen et al. to the method of Landau et al. because Landau et al. is directed to analyzing the evolution and impact of subclonal mutations in leukemia (Abstract) and Hacohen et al. is directed to a cancer neoantigen vaccine (Abstract) that can be used on a patient with Leukemia (paragraph [0026]). Thus, one of ordinary skill in the art would have had a reasonable expectation of success of treating a patient with Leukemia using a neoantigen vaccine by combining prior art elements and one would have been motivated to combine the prior art references in order to formulate a vaccine using analyzed neoantigens (see Hacohen et al. paragraph [0012]) for treating a patient’s Leukemia.
Hacohen et al. does not teach the claim elements of step b) selectively expanding tumor infiltrating lymphocytes isolated from the tumor of the subject that target the one or more clonal neoantigens, and the cell-based immunotherapy comprising administering to the subject a composition comprising the selectively expanded tumor infiltrating lymphocytes.
However, Sykes et al. teaches generating autologous T-cells in mice (Abstract). Sykes et al. teaches using animal models to expand T cells with a desired specificity (paragraph [0008]) and teaches that tumor associated antigens are the antigens selectively expressed on tumor cells and provide potential targets for cancer immunotherapy, and that the infusion of in vitro expanded autologous tumor-infiltrating lymphocytes following lymphodepletion was reported to achieve an objective response in over half of the patients with metastatic melanoma (paragraph [0770]).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art to have incorporated the treatment using selectively expanded tumor infiltrating lymphocytes of Sykes et al. to the method of Landau et al. because Landau et al. is directed to clonal evolution as a key feature of cancer progression (Abstract) and teaches that subclonal mutations contribute to response to therapy (page 714, column 2). Sykes et al. is directed to a method for selectively expanding T cells (paragraph [0008]) as a therapeutic method for cancer (paragraph [0038]), and teaches that tumor associated antigens are the antigens selectively expressed on tumor cells and provide potential targets for cancer immunotherapy (paragraph [0770]). Thus, one of ordinary skill in the art would have a reasonable expectation of success of treating a cancer by combining the prior art elements as the prior art references are directed to cancer biomarkers and one would be motivated to do so because TILs are reported to cause a response in over half of metastatic melanoma patients follow lymphodepletion and in order to personalize the cancer target.
Regarding claim 56, the claim is directed to the processor receiving DNA and/or RNA sequence data from a tumor sample from the subject comprising the processor receiving DNA and/or RNA sequence data from a plurality of tumor samples from the subject, the processor determining mutations present in said tumor sample being performed for each of the plurality of tumor samples, and identifying, by a processor, one or more clonal neoantigens that are characteristic of a tumor in the subject further comprising identifying a clonal mutation which is a mutation present in all samples. Landau et al. teaches the method of claim 55 in view of Hacohen et al. and further in view of Sykes et al. Landau et al. also teaches gathering two samples from a subject (Summary) and performed the analysis on the 18 patients of which were sampled twice (page 715, column 1, paragraph 3).
Regarding claim 57, the claim is directed to the mutations being single nucleotide variants. Landau et al. teaches the method of claim 55 in view of Hacohen et al. and further in view of Sykes et al. Landau et al. also teaches the mutations being single nucleotide variants (page 715, column 1, Section “Results”; page 715, column 2, paragraph 4).
Regarding claim 58, the claim is directed to the sequence data being Exome sequencing data, RNA-seq data, whole genome sequencing data, and/or targeted gene panel sequencing data. Landau et al. teaches the method of claim 55 in view of Hacohen et al. and further in view of Sykes et al. Landau et al. also teaches the sequence data being exome sequencing data (page 715, column 1, paragraph 3).
Regarding claim 59, the claim is directed to identifying the subject’s HLA allele profile by processing said DNA and/or RNA sequence data from the non-tumor sample form the subject to determine if a clonal neoantigen peptide will bind to an MHC molecule of the subject. Landau et al. teaches the method of claim 55 in view of Hacohen et al. and further in view of Sykes et al.
Landau et al. does not teach the claim elements of identifying the subject’s HLA allele profile by processing said DNA and/or DNA sequence data from the non-tumor sample form the subject to determine if a clonal neoantigen peptide will bind to an MHC molecule of the subject.
However, Hacohen et al. teaches identifying the patient’s HLA allotype by sequencing normal DNA of the patient and tumor DNA, therefore determining that the mutations in the cancer will bind to the patient’s HLA protein (paragraphs [0096] and [0049]).
Regarding claim 60, the claim is directed to obtaining a sequence alignment file comprising DNA sequence data from the non-tumor sample from the subject aligned to a plurality of sequences of known HLA alleles. Landau et al. teaches the method of claim 59 in view of Hacohen et al. and further in view of Sykes et al.
-Landau et al. does not teach the claim elements of obtaining a sequence alignment file comprising DNA sequence data from the non-tumor sample from the subject aligned to a plurality of sequences of known HLA alleles.
However, Hacohen et al. teaches identifying the patient’s HLA allotype by sequencing normal DNA of the patient (paragraph [0096]).
Regarding claim 61, the claim is directed to predicting, by said processor, binding of said one or more identified clonal neoantigens to an MHC molecule expressed by said subject. Landau et al. teaches the method of claim 59 in view of Sykes et al. and further in view of Sykes et al.
- Landau et al. does not teach the claim elements of predicting binding of said one or more identified clonal neoantigens to an MHC molecule expressed by said subject.
However, Hacohen et al. teaches formulating a cancer treatment using a subject-specific peptide specific to the subject and the tumor that has determined binding to the HLA protein of the subject with an IC50 less than 500nM (paragraph [0049]).
Regarding claim 62, the claim is directed to obtaining, by the processor, a plurality of peptide sequences of length between 9 and 11 amino acids comprising a mutated amino acid associated with a clonal mutation of said identified one or more clonal mutations, and providing said peptide sequences and a predicted 4-digit HLA type for the subject as input to an algorithm that predicts the binding affinity of each peptide to the patient’s specific HLA alleles. Landau et al. teaches the method of claim 61 in view of Hacohen et al. and further in view of Sykes et al.
Landau et al. does not teach the claim elements of selecting obtaining, by the processor, a plurality of peptide sequences of length between 9 and 11 amino acids comprising a mutated amino acid associated with a clonal mutation of said identified one or more clonal mutations, and providing said peptide sequences and a predicted 4-digit HLA type for the subject as input to an algorithm that predicts the binding affinity of each peptide to the patient’s specific HLA alleles.
However, Hacohen et al. teaches formulating a cancer treatment using a subject-specific peptide specific to the subject and the tumor that has determined binding to the HLA protein of the subject with an IC50 less than 500nM (paragraph [0049]). Hacohen et al. states that the neoantigen peptide can range from 5 to about 50 amino acids length (paragraph [0013]) and thus encompasses between 9 and 11 amino acids. Hacohen et al. also teaches identifying the patient’s HLA allotype and using validated algorithms to predict which tumor-specific mutations create epitopes that could bind to the patient’s HLA allotype (paragraph [0096]).
Regarding claim 63, the claim is directed to selecting one or more clonal neoantigens predicted to bind to an MHC molecule expressed by said subject with a binding affinity below 500 nM. Landau et al. teaches the method of claim 61 in view of Hacohen et al. and further in view of Sykes et al.
Landau et al. does not teach the claim elements of selecting one or more clonal neoantigens predicted to bind to an MHC molecule expressed by said subject with a binding affinity below 500 nM.
However, Hacohen et al. teaches formulating a cancer treatment using a subject-specific peptide specific to the subject and the tumor that has determined binding to the HLA protein of the subject with an IC50 less than 500nM (paragraph [0049]).
Regarding claim 64, the claim is directed to receiving RNA-seq data from a tumor sample from the subject and identifying the one or more clonal neoantigens, and selecting a clonal neoantigen that is encoded by a transcript expressed in the tumor sample. Landau et al. teaches the method of claim 55 in view of Hacohen et al. and further in view of Sykes et al. Landau et al. also teaches receiving RNA sequencing data (page 716, column 1).
Landau et al. does not teach the claim elements of identifying the one or more clonal neoantigens, and selecting a clonal neoantigen that is encoded by a transcript expressed in the tumor sample.
However, Hacohen et al. teaches Bioinformatics analysis being conducted by performing sequence analysis of exome and RNA-seq fastq files leveraging existing bioinformatic pipelines that have been used and validated extensively (paragraph [0454]). Hacohen et al. also teaches selecting a tumor-specific non-silent mutation not present in the non-tumor sample where each neo-epitope binds to the HLA protein of the subject (paragraphs [0043] and [0044]).
Regarding claim 65, the claim is directed to determining a cancer cell fraction probability (P(CCF)) that depends on the number of reads with said mutation in DNA sequence data from a tumor sample of said subject (a), the total read depth at the genomic location of said mutation in said DNA sequence data (N), and an expected variant allele frequency for a given cancer cell fraction (VAF(CCF)). Landau et al. teaches the method of claim 55 in view of Hacohen et al. and further in view of Sykes et al. Landau et al. also teaches determining Binom(a|N, f(c)), where f(c) is the expected allele frequency for a given cancer cell fraction, and ‘a’ is the number of reads observed with said mutation, and N is the total number of sequencing reads (page 724, column 1).
Regarding claim 66, Landau et al. teaches the method of claim 65 in view of Hacohen et al. and further in view of Sykes et al. Landau et al. also teaches that the cancer cell fraction probability is calculated as Binom(a|N, f(c)), where f(c) is the expected allele frequency for a given cancer cell fraction, and ‘a’ is the number of reads observed with said mutation, and N is the total number of sequencing reads (page 724, column 1).
Regarding claim 67, Landau et al. teaches the method of claim 65 in view of Hacohen et al. and further in view of Sykes et al. Landau et al. also teaches calculating the expected allele-fraction of f of a mutation present in one copy in a fraction c of cancer cells is calculated by f(c) = αc/(2(1-α) + αq) (page 724, column 1).
Regarding claim 68, the claim is directed to obtaining a cancer cell fraction probability for each mutation identified in ii) for each of said plurality of tumor samples and a clonal mutation is a mutation identified in ii) where the probability of the cancer cell fraction (P(CCF) is such that the 95% confidence interval of the cancer cell fraction being greater than or equal to 0.75 in each of said plurality of samples. Landau et al. teaches the method of claim 56 in view of Hacohen et al. and further in view of Sykes et al. Landau et al. also teaches gathering two samples from a subject (Summary) and performed the analysis on the 18 patients of which were sampled twice (page 715, column 1, paragraph 3). The analysis includes that the probability of the cancer cell fraction (P(CCF) is such that the 95% confidence interval of the cancer cell fraction being greater than or equal to 0.75 in each of said plurality of samples (Section “Extended Experimental Procedures”, “Estimation of Mutation Cancer Cell Fraction Using ABSOLUTE” paragraph 3).
Response to Arguments
Applicant states that “In view of the priority claim remarks submitted above, the instant application is entitled to an earliest priority date and effective filing date of April 27, 2015. Because Robertson et al. was published after the application’s effective filing date, Robertson et al. does not constitute prior art for the purpose of AIA 35 U.S.C. § 102 and 103. The combination of Landau and Hacohen does not render the instant claims obvious.”
A new grounds of rejection has been set forth in view of the updated priority date for the instant claims.
Conclusion
No claims are allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Emilie A Smith whose telephone number is (571)272-7543. The examiner can normally be reached 9am - 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, Larry D Riggs can be reached at (571)270-3062. 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.
/E.A.S./Examiner, Art Unit 1686
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686
Prosecution Insights