DETAILED ACTION
Notice of AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Status of the Claims
Claims 1-75 are canceled.
Claims 76-95 are pending.
Claims 76-77, 81 and 93-95 are objected to.
Claims 76-95 are rejected.
Priority
This US Application 18/169,870 (02/15/2023) is a CON of US Application 17/267,914 (02/11/2021) which is a 371 of PCT/CA2019/051186 (08/28/2019) which claims priority from US Application 62/724,760 (08/30/2018), as reflected in the filing receipt mailed on 04/25/2023. The claims to the benefit of priority are acknowledged; and the effective filing date of claims 76-95 is 08/30/2018.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 02/15/2023, 11/03/2023, 01/11/2024, 08/12/2024, 10/03/2024 and 08/01/2025 were considered by the examiner.
Drawings
In the instant drawings filed 02/15/2023, Fig. 2C and Fig. 6B are executed in color. Color photographs and color drawings are not accepted in utility applications unless a petition filed under 37 CFR 1.84(a)(2) is granted. Any such petition must be accompanied by the appropriate fee set forth in 37 CFR 1.17(h), one set of color drawings or color photographs, as appropriate, if submitted via the USPTO patent electronic filing system or three sets of color drawings or color photographs, as appropriate, if not submitted via the via USPTO patent electronic filing system, and, unless already present, an amendment to include the following language as the first paragraph of the brief description of the drawings section of the specification. The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. Color photographs will be accepted if the conditions for accepting color drawings and black and white photographs have been satisfied. See 37 CFR 1.84(b)(2).
Specification Objections
The disclosure is objected to because it contains an embedded hyperlink and/or other form of browser-executable code in pg. 22 line 27, pg. 44 line 12, pg. 45 line 12 and pg. 50 line 19. 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.
Claim objections
Claim 76 is objected to because of the following informality: steps (c) and (d) are indented too far. Steps (c) and (d) should be present the same indentation as steps (a) and (b).
Claim 77 is objected to because of the following informality: the recited " major histocompatibility complex (MHC)-associated peptides (MAPs)" have been introduced in claim 76 and therefore, only "MAPS" should be recited from claim 77 forward.
Claim 81 is objected to because of the following informality: verb-subject agreement is improper for the recited "said subsequences comprises" which should read "said subsequences comprise."
Claims 93-95 are objected to because of the following informality: two separate claims are numbered with the number 93. Each claim should be numbered with consecutive numbers (608.01(j) Numbering of Claims). The numbering of claims is not in accordance with 37 CFR 1.126 which requires the original numbering of the claims to be preserved throughout the prosecution. When claims are canceled, the remaining claims must not be renumbered. When new claims are presented, they must be numbered consecutively beginning with the number next following the highest numbered claims previously presented (whether entered or not). Misnumbered claim 93 (i.e. second instance of claim 93 in the list), claim 94 and claim 95 have been renumbered claims 94-96. For compact prosecution, it is interpreted that the now renumbered claim 95 ("wherein the ability of the tumor antigen candidate to induce T cell activation is assessed by measuring cytokine production by T cells contacted with cells having said tumor antigen candidate bound to MHC class I molecules at their cell surface") depends on now renumbered claim 94 ("further comprising assessing the ability of the tumor antigen candidate to induce T cell activation").
Claim 96 (i.e. original claim 95) is objected to because of the following informality related to punctuation. The claim is missing a period at the end.
Appropriate correction is required.
For compact prosecution, said renumbered claims now read:
93. (New) The method of claim 76, further comprising assessing the frequency of T cells recognizing the tumor antigen candidate in a cell population.
94. (New) The method of claim 76, further comprising assessing the ability of the tumor antigen candidate to induce T cell activation.
95. (New) The method of claim 94, wherein the ability of the tumor antigen candidate to induce T cell activation is assessed by measuring cytokine production by T cells contacted with cells having said tumor antigen candidate bound to MHC class I molecules at their cell surface.
96. (New) The method of claim 76, further comprising assessing the ability of said tumor antigen candidate to induce T-cell-mediated tumor cell killing and/or to inhibit tumor growth
Claim Rejections - 35 USC § 112
112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION —The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 76-96 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter the invention. Dependent claims are rejected similarly, unless otherwise noted below. The following issues cause the respective claims to be rejected under 112(b) as indefinite:
Claim 76 recites “(k-mers)” (step (a)(i)) which is indefinite because it is unclear if the term recites exemplary claim language (see MPEP 2173.05(d)) or just another term for subsequences.
Claim 76 recites " (c) comparing the sequences of major histocompatibility complex (MHC)-associated peptides (MAPs) from said tumor with the sequences of the tumor-specific proteome database of (a) and the personalized tumor proteome database of (b) to identify the MAPs" which is unclear. The Applicant must clarify what steps are takento compare MAPs to identify MAPs. As it appears in the claims such clarity is absent.
Claim 80 recites "about" which is a term of relative or vague degree or form of association, neither defined in the specification nor having a well-known and sufficiently particular definition in the art and in the instant context; thus indefinite. The recited term does not properly define the limitation recited.
Claim 82 recites "(contigs)" which is indefinite because it recites exemplary claim language (see MPEP 2173.05(d)). It is unclear if the term in parenthesis refers to the preceding term or if it is just exemplary.
In claim 88, the relationship is unclear between the recited steps (a) to (h) and the parent claim 76's steps (a) to (d). It is unclear if steps in claim 88 are meant to replace at least steps (a) to (d) from claim 76 or further limit steps (a) to (b). In the latter case, claim 88 may be amended to steps (e) to (l) to overcome this rejection.
The following recitations require but lack antecedent basis, rendering their claims indefinite because there is no previous recitations of the followings terms as written:
Claim 76, "the sequences of major histocompatibility complex (MHC)-associated peptides (MAPs)"
Claim 90, "the coding sequence"
Claim 91, "the frequency"
Claims 93-96, " the ability"
112(d)
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 87 is rejected under 112(d) as being of improper dependent form for failing to further limit the subject matter of the claim upon which they depend. MPEP 608.01(n).III pertains. Claim 87 recites "wherein the k-mer derived from the MAP encoding sequence is absent from said normal k-mer database" which is not clearly limiting, and it is not clear that the rest of the claim differs in scope from claim 76. MPEP 2111.02 pertains. Applicant may cancel the claims, amend the claims to place the claims in proper dependent form, rewrite the claims in independent form, or present a sufficient showing that the dependent claims comply with the statutory requirements
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 76-96 are rejected under 35 USC § 101 because the claimed inventions are directed to one or more Judicial Exceptions (JEs) without significantly more. Regarding JEs, "Claims directed to nothing more than abstract ideas..., natural phenomena, and laws of nature are not eligible for patent protection" (MPEP 2106.04 §I). Abstract ideas include mathematical concepts and procedures for evaluating, analyzing or organizing information, which are a type of mental process (MPEP 2106.04(a)(2)).
101 background
MPEP 2106 organizes JE analysis into Steps 1, 2A (Prong One & Prong Two), and 2B as analyzed below. MPEP 2106 and the following USPTO website provide further explanation and case law citations: uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials.
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter (MPEP 2106.03)?
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e., a law of nature, a natural phenomenon, or an abstract idea (MPEP 2106.04(a-c))?
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application by an additional element (MPEP 2106.04(d))?
Step 2B: Do the claims recite a non-conventional arrangement of elements in addition to any identified judicial exception(s) (MPEP 2106.05)?
Analysis of instant claims
Step 1: Are the claims directed to a 101 process, machine, manufacture, or composition of matter (MPEP 2106.03)?
The instant claims are directed to a method (claims 76-96) which falls within one of the categories of statutory subject matter.
[Step 1: claims 76-96: Yes]
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e., a law of nature, a natural phenomenon, or an abstract idea (MPEP 2106.04(a-c))?
Background
With respect to Step 2A, Prong One, the claims recite judicial exceptions in the form of abstract ideas. MPEP § 2106.04(a)(2) further explains that abstract ideas are defined as:
• mathematical concepts (mathematical formulas or equations, mathematical relationships
and mathematical calculations) (MPEP 2106.04(a)(2)(I));
• certain methods of organizing human activity (fundamental economic principles or practices, managing personal behavior or relationships or interactions between people) (MPEP 2106.04(a)(2)(II)); and/or
• mental processes (concepts practically performed in the human mind, including observations, evaluations, judgments, and opinions) (MPEP 2106.04(a)(2)(III)).
Analysis of instant claims
With respect to the instant claims, under the Step 2A, Prong One evaluation, the claims are found to recite abstract ideas that fall into the grouping of mathematical concepts (in particular mathematical relationships and formulas) and mental processes (in particular procedures for observing, analyzing and organizing information) as well as a law of nature or a natural phenomenon are as follows.
Mental processes, defined as concepts or steps practically performed in the human mind such as steps of observations, evaluations, judgments, analysis, opinions or organizing information include:
• "(i) extracting a set of subsequences (k-mers) comprising at least 33 base pairs from tumor RNA-sequences " (independent claim 76);
• "(iii) extracting the tumor subsequences that are absent in the corresponding control subsequences, thereby obtaining tumor-specific subsequences" (independent claim 76);
• "(ii) inserting the single-base mutations identified in (i) in the reference genome sequence, thereby creating a personalized tumor genome sequence" (claims 76 and 88);
• "(ii) comparing the set of tumor subsequences of (i) to a set of corresponding control subsequences comprising at least 33 base pairs extracted from RNA-sequences from normal cells" (claims 76 and 88);
• "(i) comparing the tumor RNA-sequences to a reference genome sequence to identify single-base mutations in said tumor RNA-sequences" (claims 76 and 88);
• "(c) comparing the sequences of major histocompatibility complex (MHC)-associated peptides (MAPs) from said tumor with the sequences of the tumor-specific proteome database of (a) and the personalized tumor proteome database of (b) to identify the MAPs" (independent claim 76);
• "(d) identifying a tumor antigen candidate among the MAPs identified in (c), wherein a tumor antigen candidate is a peptide whose sequence and/or encoding sequence is overexpressed or overrepresented in tumor cells relative to normal cells" (independent claim 76);
• "(iv) …translating the tumor-specific subsequences, thereby obtaining the tumor- specific proteome database" (claims 76 and 88);
• "(iii) … translating the expressed protein-coding transcripts from said personalized tumor genome sequence, thereby obtaining the personalized tumor proteome database" (claims 76 and 88); and
• "assembling overlapping tumor-specific subsequences into longer tumor subsequences (contigs)" (claim 82)
• "generating a personalized normal proteome database using corresponding normal cells, wherein said identifying in (d) comprises excluding said MAP if its sequence is detected in the normal personalized proteome database" (claim 84);
• "generating 24- or 39- nucleotide k-mer databases from said tumor RNA-sequences and from RNA-sequences from normal cells to obtain a tumor k-mer database and a normal k-mer database, comparing the tumor k-mer database and a normal k-mer database to 24- or 39-nucleotide k-mer derived from the MAP encoding sequence, wherein an overexpression or overrepresentation of the k-mer derived from the MAP encoding sequence in said tumor k-mer database relative to said normal k-mer database is indicative that the corresponding MAP is a tumor antigen candidate" (claim 85);
• " (c) generating a tumor-specific proteome database by: (i) extracting a set of subsequences comprising at least 33 nucleotides from said tumor RNA-sequences; … (iii) extracting the tumor subsequences that are absent, or underexpressed by at least 4-fold, in the corresponding control subsequences, thereby obtaining tumor-specific subsequences" (claim 88);
• "(ii) inserting the single-base mutations identified in (i) in the reference genome sequence, thereby creating a personalized normal genome sequence" (claim 88); and
• "(i) extracting a set of subsequences comprising at least 24 nucleotides from said RNA-sequences from normal cells and said tumor RNA-sequences" (claim 88).
• "(i) comparing RNA-sequences from normal cells to a reference genome sequence to identify single-base mutations in said normal RNA-sequences" (claim 88)
• "(g) comparing the sequences of the MAPs obtained in (a) with the sequences of the tumor- specific proteome database of (c) and the personalized tumor proteome database of (d) to identify the MAPs; and (h) identifying a tumor antigen candidate among the MAPs identified in (f), wherein a tumor antigen candidate corresponds to a MAP (1) whose sequence is not present in the personalized normal proteome database; and (2) (i) whose sequence is present in the personalized tumor proteome database: and/or (ii) whose encoding sequence is overexpressed or overrepresented in said tumor k-mer database relative to said normal k-mer database" (claim 88);
• "(iii) … translating the expressed protein-coding transcripts from said personalized normal genome sequence, thereby obtaining the personalized normal proteome database" (claim 88).
• "selecting MAPs having a length of 8 to 11 amino acids" (claim 89);
• "comparing the coding sequence of said tumor antigen candidate to sequences from normal tissues" (claim 90);
• "assessing the binding of the tumor antigen candidate to an MHC molecule" (claim 91);
• "assessing the frequency of T cells recognizing the tumor antigen candidate in a cell population" (claim 93);
• "assessing the ability of the tumor antigen candidate to induce T cell activation" (claim 94); and
• "assessing the ability of said tumor antigen candidate to induce T-cell-mediated tumor cell killing and/or to inhibit tumor growth" (claim 96).
Under the BRI, the recited limitations are mental processes because a human mind is also sufficiently capable of extracting/selecting sequences to make k-mers, inserting mutations in said sequences using a pen and paper, comparing data, identify an antigen candidate, select a MAP of a certain length and assess (i.e. which reads on data evaluation) information regarding the antigen's abilities; and generate databases using a pen and paper. Here, the "assessing steps" read on data evaluations to encompass data produced by the physical steps rather than requiring the actual assays. Further, translating an RNA sequence into a protein sequence can be done using pen and paper.
Dependent claims 81, 86-87, 92 and 95 recite further steps that limit the judicial exceptions in independent claim 76 and, as such, also are directed to those abstract ideas. For example, claim 81 recites further details about the subsequences extracted; claims 86-87 recite further details about the k-mer derived from MAPs; claim 92 recites further details about the binding of the tumor antigen candidate to an MHC molecule; claim 95 recites further details about the assessed ability to induce T cell activation.
Furthermore, the instant claims recite a natural correlation by correlating a nucleic acid sequence naturally found in the body with its corresponding tumor specific antigen candidate. (see MPEP 2106.04(b).I).
[Step 2A Prong One: claims 76-96: Yes ]
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application by an additional element (MPEP 2106.04(d))?
Background
MPEP 2106.04(d).I lists the following example considerations for evaluating whether a judicial exception is integrated into a practical application:
An improvement in the functioning of a computer or an improvement to other technology or another technical field, as discussed in MPEP §§ 2106.04(d)(1) and 2106.05(a);
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, as discussed in MPEP § 2106.04(d)(2);
Implementing a judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, as discussed in MPEP § 2106.05(b);
Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP § 2106.05(c); and
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP § 2106.05(e).
Analysis of instant claims
Instant claims 76-79, 83-85 and 88 recite additional elements that are not abstract ideas:
• "in-silico" (claims 76 and 88);
• "(1) isolating and sequencing major histocompatibility complex (MHC)-associated peptides (MAPs) from the tumor cell sample, and/or (2) performing whole transcriptome sequencing on the tumor cell sample, to obtain the tumor RNA-sequences" (claim 77);
• "(i) releasing said MAPs from said cell sample by mild acid treatment; and (ii) subjecting the released MAPs to chromatography" (claim 78);
• "filtering the released peptides with a size exclusion column prior to said chromatography" (claim 79);
• "subjecting the isolated MAPs to mass spectrometry (MS) sequencing analysis" (claim 83);
• "(a) isolating and sequencing MAPs in a tumor cell sample; (b) performing whole transcriptome sequencing on said tumor cell sample, thereby obtaining tumor RNA-sequences;
Dependent claim 80 recites further details about the size exclusion column.
Considerations under Step 2A, Prong Two
The recited limitations in claims 76-96 are interpreted as requiring the use of a computer. Hence, the claims explicitly recite steps executed by computers and therefore can be described as computer functions or instructions to implement on a generic computer. Further steps directed to additional non-abstract elements of a computing device/computer do not describe any specific computational steps by which the "computer parts" perform or carry out the judicial exceptions, nor do they provide any details of how specific structures of the computer are used to implement these functions. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions.
The judicial exceptions in the claims are considered to perform the claimed abstract idea with a computer, which is not sufficient to integrate an abstract idea into a practical application (see MPEP 2106.05(f)); since steps that can be performed mentally and merely performing the mental process in a computer environment do not negate the fact that something that can be carried out in the human mind. See MPEP 2106.04(a)(2).III.C.
The recited "isolating and sequencing … in a sample" steps (claims 77 and 88) reads on detecting DNA in a patient sample, being an insignificant extra-solution activity since this limitation serve to gather data that is utilized as input for the judicial exception. See MPEP 2106.05(g) and MPEP 2106.04(d).
The recited "releasing said MAPs from said cell sample by mild acid treatment; and (ii) subjecting the released MAPs to chromatography" (claim 78); "filtering the released peptides with a size exclusion column prior to said chromatography" (claim 79) and "subjecting the isolated MAPs to mass spectrometry (MS) sequencing analysis" (claim 83) read on physical steps necessary for data gathering activities; not amounting to a practical application.
With respect to claims 76 and 88, the computer-related elements or the general purpose computer and the recited in-silico does not rise to the level of significantly more than the judicial exception. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, which the courts have found to not provide significantly more when recited in a claim with a judicial exception (Alice Corp., 573 U.S. at225-26, 110 USPQ2d at 1984; see MPEP 2106.05(A)). The specification as published also notes that computer processors and systems, as example, are known and widely used examples of algorithms that may be used without limitation (pg. 50 line 31). The additional elements are set forth at such a high level of generality that they can be met by a general purpose computer. Therefore, the computer components constitute no more than a general link to a technological environment, which is insufficient to constitute an inventive concept that would render the claims significantly more than the judicial exceptions (see MPEP 2106.05(b)I-III).
Hence, these are mere instructions to apply the abstract idea using a computer and insignificant extra-solution activity and therefore the claims do not integrate that abstract idea into a practical application (see MPEP 2106.04(d) § I; 2106.05(f); and 2106.05(g)).
In Step 2A, Prong One above, claim steps and/or elements were identified as part of one or more judicial exceptions (JEs).
In this Step 2A, Prong Two immediately above claim steps and/or elements were identified as part of one or more additional elements. Additional elements are further discussed in Step 2B below.
Here in Step 2A, Prong Two, no additional step or element clearly demonstrates integration of the JE(s) into a practical application.
[Step 2A Prong Two: claims 76-96: No]
Step 2B: Do the claims recite a non-conventional arrangement of elements in addition to any identified judicial exception(s) (MPEP 2106.05)?
According to analysis so far, the additional elements described above do not provide significantly more than the judicial exception. A determination of whether additional elements provide significantly more also rests on whether the additional elements or a combination of elements represents other than what is well-understood, routine, and conventional. Conventionality is a question of fact and may be evidenced as: a citation to an express statement in the specification or to a statement made by an applicant during examination that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s).
Claims 76-96 recite a computer or computer functions, interpreted as instructions to apply the abstract idea using a computer, where the computer does not impose meaningful limitations on the judicial exceptions; which can be performed without the use of a computer (MPEP 2106.04(d) § I; and MPEP 2106.05(f)).
The computer-related elements or the general purpose computer and the in-silico steps do not rise to the level of significantly more than the judicial exception. The claims state a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, which the courts have found to not provide significantly more when recited in a claim with a judicial exception (Alice Corp., 573 U.S. at225-26, 110 USPQ2d at 1984; see MPEP 2106.05(A)).
With respect to the instant claims, the prior art review to Yang ("Defining the pathogenesis of inflammatory and immune diseases through database mining." Frontiers in Bioscience-Elite 4(7):2433-2441 (2012); newly cited) discloses that using genomes, transcriptomes, proteomes, and antigen-omes data-based searchable databases to investigate immune-related diseases (pg. 2433 col. 1 para. 1) involving cell based experimental studies (i.e. sequencing and isolation steps) (pg. 2436 col. 2 para. 2) is routine, well-understood and conventional in the art.
When the claims are considered as a whole, they do not integrate the abstract idea into a practical application; they do not confine the use of the abstract idea to a particular technology; they do not solve a problem rooted in or arising from the use of a particular technology; they do not improve a technology by allowing the technology to perform a function that it previously was not capable of performing; and they do not provide any limitations beyond generally linking the use of the abstract idea to a broad technological environment. See MPEP 2106.05(a) and 2106.05(h).
The instant claims constitute insignificant extra solution activity, and when considered individually, are insufficient to constitute inventive concepts that would render the claims significantly more than an abstract idea (see MPEP 2106.05(g)). Hence, these elements, when considered individually, are insufficient to constitute inventive concepts that would render the claims significantly more than an abstract idea (see MPEP 2106.05(d)).
[Step 2B: claims 76-96: No]
Conclusion: Instant claims are directed to non-statutory subject matter
For the reasons above, the claims in this instant application, when the limitations are considered individually and as a whole, are directed to an abstract idea and lack an inventive concept not clearly anything significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter 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 pre-AIA 35 U.S.C. 103(a) 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.
A. Claims 76-77, 81-85, 87-89 and 91-93 are rejected under 35 U.S.C. 103(a) as being unpatentable over Nguyen (US 2018 / 0141998 A1) in view of Patil ("Elucidating the cancer-specific genetic alteration spectrum of glioblastoma derived cell lines from whole exome and RNA sequencing." Oncotarget 6(41):43452 (2015)) in view of Adekiya ("Structural analysis and epitope prediction of MHC class-1-chain related protein-a for cancer vaccine development." Vaccines 6.1 (2017)) in view of Slebos ("Proteomic analysis of colon and rectal carcinoma using standard and customized databases." Scientific data 2(1):1-15 (2015)) in view of Kalaora ("Use of HLA peptidomics and whole exome sequencing to identify human immunogenic neo-antigens." Oncotarget 7(5):5110 (2016)), as cited on the attached Form PTO-892.
Claim 76 recites:
…
(i) extracting a set of subsequences (k-mers) comprising at least 33 base pairs from tumor RNA-sequences;
(ii) comparing the set of tumor subsequences of (i) to a set of corresponding control subsequences comprising at least 33 base pairs extracted from RNA-sequences from normal cells;
• Nguyen teaches a method for generating an agent for cancer immune therapy by using matched (i.e. comparing step) 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, filtering in silico the n-mers to so obtain a subset of neoepitope sequences (claim 1); wherein the matched normal omics data are at least one of whole genomic sequencing data, exome sequencing data, and transcriptome data (i.e. data represented by RNA sequences) (claim 2) (i.e. extracting k-mer subsequences from tumor RNA sequences) wherein each of the plurality of n-mer peptides has a length of between 7 and 11 amino acids (claim 4). Here, the range of 7-mer to 11-mer peptide is equivalent to a range of 21-mer to 33-mer RNA subsequences because a set 3 base pairs (i.e. one codon) would be required to produce one amino acid in the 7-mer to 11-mer range as taught by Nguyen (claims 1 and 4).
generating a tumor-specific proteome database by:
…
(iii) extracting the tumor subsequences that are absent in the corresponding control subsequences, thereby obtaining tumor-specific subsequences; and
• Nguyen does not teach the recitation above. However, Patil teaches generating a comprehensive catalogue of cancer-specific genetic alterations of glioblastoma cell lines (i.e. generating tumor-specific database) (pg. 43452 Abstract); wherein the analysis of said comparison yielded a distribution of different classes of RNAs that are differentially regulated across the six GBM cell lines compared to normal (i.e. control) brain samples (i.e. step (a)(iii))(pg. 43460 Fig. 6).
generating a tumor-specific proteome database by:
…
(iv) in silico translating the tumor-specific subsequences, thereby obtaining the tumor- specific proteome database
• Nguyen does not teach the recitation above. However, Patil teaches generating a comprehensive catalogue of cancer-specific genetic alterations of glioblastoma cell lines (i.e. generating tumor-specific database) (pg. 43452 Abstract). Further, Adekiya teaches mRNA sequences being translated into an amino acid sequence via the translate tool on the ExPASy server (i.e. as in step (a)(iv)) (pg. 2 para. 3). Here, the catalog taught by Patil of cancer specific alterations and the translated protein sequences by Adekiya would read on the claimed proteome database.
((b) generating a personalized tumor proteome database by:
(i) comparing the tumor RNA-sequences to a reference genome sequence to identify single-base mutations in said tumor RNA-sequences;
(ii) inserting the single-base mutations identified in (i) in the reference genome sequence, thereby creating a personalized tumor genome sequence;
(iii) in silico translating the expressed protein-coding transcripts from said personalized tumor genome sequence, thereby obtaining the personalized tumor proteome database
• Nguyen does not teach the recitation above. However, Slebos teaches a customized protein database construction (i.e. personalized tumor proteome database) to annotate variations predicted from RNA-Seq including mapping to dbSNP135 and COSMIC64 databases (i.e. step (b)(i)), generating a protein database by appending (i.e. reading on inserting) proteins (i.e. expression product of RNA sequences) with nonsynonymous protein coding single nucleotide variants for each sample (i.e. tumor related database) (i.e. step (b)(ii)) (pg. 4 para. 5). Furthermore, Adekiya teaches mRNA sequences being translated into an amino acid sequence via the translate tool on the ExPASy server (i.e. in silico translating the expressed protein-coding transcripts from said personalized tumor genome sequence as in step (b)(iii)) (pg. 2 para. 3).
c) comparing the sequences of major histocompatibility complex (MHC)-associated peptides (MAPs) from said tumor with the sequences of the tumor-specific proteome database of (a) and the personalized tumor proteome database of (b) to identify the MAPs; and
(d) identifying a tumor antigen candidate among the MAPs identified in (c), wherein a tumor antigen candidate is a peptide whose sequence and/or encoding sequence is overexpressed or overrepresented in tumor cells relative to normal cells
• Nguyen does not teach the recitation above. However, Kalaora teaches identifying neo-antigens peptides in a melanoma patient among the expressed mutated peptides (i.e. identifying a tumor antigen candidate) presented on the Human Leucocyte Antigen (HLA) molecules (i.e. major histocompatibility complex (MHC)-associated peptides) (pg. 5110 Abstract); wherein the whole genomes of matched normal and metastatic tumor DNAs from a melanoma patient was sequenced to identify mutated antigens presented on human melanoma tumor cells (i.e. comparing sequences from tumor and personalized – patient data identify the antigens among MAPs) (pg. 5111 col. 1 para. 3).
Claim 77 recites:
wherein the above-noted method further comprises (1) isolating and sequencing major histocompatibility complex (MHC)-associated peptides (MAPs) from the tumor cell sample, and/or (2) performing whole transcriptome sequencing on the tumor cell sample, to obtain the tumor RNA-sequences
• Nguyen does not teach the recitation above. However, Kalaora teaches that HLA peptides were isolated from 2x108 cells, which is the estimated number of cells in clinically detectable solid human tumors (pg. 5114 col. 1 para. 3); wherein said peptides were sequenced by electrospray tandem mass spectrometry (pg. 5114 col. 1para. 6).
Claim 81 recites:
wherein said subsequences comprises from 33 to 54 base pairs
• Nguyen teaches a method for generating an agent for cancer immune therapy by using matched (i.e. comparing step) 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, filtering in silico the n-mers to so obtain a subset of neoepitope sequences (claim 1); wherein the matched normal omics data are at least one of whole genomic sequencing data, exome sequencing data, and transcriptome data (i.e. data represented by RNA sequences) (claim 2) (i.e. extracting k-mer subsequences from tumor RNA sequences) wherein each of the plurality of n-mer peptides has a length of between 7 and 11 amino acids (claim 4). Here, the range of 7-mer to 11-mer peptide is equivalent to a range of 21-mer to 33-mer RNA subsequences because a set 3 base pairs (i.e. one codon) would be required to produce one amino acid in the 7-mer to 11-mer range as taught by Nguyen (claims 1 and 4).
• Nguyen teaches "21-mer to 33-mer RNA subsequences" range which makes obvious the instantly claimed range of 33 to 54 base pairs. It would have been prima facie obvious to one of ordinary skill in the art to select any portions of the disclosed ranges including the instantly claimed ranges from the ranges disclosed in the prior art references, particularly in view of the fact that: "The normal desire of scientists or artisans to improve upon what is already generally known provides the motivation to determine where in a disclosed set percentage ranges is the optimum combination of percentages" In re Peterson 65 USPQ2d 1379 (CAFC 2003). See also In re Malagari, 182 USPQ 549,533 (CCPA 1974) and MPEP 2144.05 modifying the values for identity, coverage and e-value would improve the quality of the data being filtered for the database created since it would yield more complete sequences (with less sequences overlaps when it comes to e-values) being identified by the method.
Claim 82 recites:
assembling overlapping tumor-specific subsequences into longer tumor subsequences (contigs)
• Nguyen does not teach the recitation above. However, Patil teaches oncogenic gene fusions from RNA-seq data (pg. 43460 col. 2 para. 2); wherein tumor-specific subsequences overlap into longer tumor subsequences (pg. 43461 Fig. 7).
Claim 83 recites:
wherein said sequencing of MAPs comprises subjecting the isolated MAPs to mass spectrometry (MS) sequencing analysis
• Nguyen does not teach the recitation above. However, Kalaora teaches identifying neo-antigens peptides in a melanoma patient as a fraction of the expressed mutated peptides presented on the Human Leucocyte Antigen (HLA) molecules (i.e. major histocompatibility complex (MHC)-associated peptides) via HLA peptidome mass spectrometry (pg. 5110 Abstract).
Claim 84 recites:
wherein said method further comprises generating a personalized normal proteome database using corresponding normal cells, and wherein said identifying in (d) comprises excluding said MAP if its sequence is detected in the normal personalized proteome database
• Nguyen does not teach the recitation above. However, Slebos teaches using customized databases and the analysis of 60 normal epithelial samples by MS instrument to produce proteomics quality control datasets for basal xenografts (i.e. generating a personalized normal proteome database using corresponding normal cells) (pg. 2 para. 2). Further, Kalaora teaches identifying neo-antigens peptides in a melanoma patient among the expressed mutated peptides presented on the Human Leucocyte Antigen (HLA) molecules (i.e. major histocompatibility complex (MHC)-associated peptides) (pg. 5110 Abstract); wherein the whole genomes of matched normal and metastatic tumor from a melanoma patient was sequenced to identify mutated antigens presented on human melanoma tumor cells (i.e. excluding said MAP if its sequence is detected in the normal personalized proteome database) (pg. 5111 col. 1 para. 3).
Claim 85 recites:
wherein the method further comprises generating 24- or 39- nucleotide k-mer databases from said tumor RNA-sequences and from RNA-sequences from normal cells to obtain a tumor k-mer database and a normal k-mer database; and comparing the tumor k-mer database and a normal k-mer database to 24- or 39-nucleotide k-mer derived from the MAP encoding sequence, wherein an overexpression or overrepresentation of the k-mer derived from the MAP encoding sequence in said tumor k-mer database relative to said normal k-mer database is indicative that the corresponding MAP is a tumor antigen candidate
• Nguyen teaches a method for generating an agent for cancer immune therapy by using matched normal omics data of a tumor (i.e. comparing relative to said normal) to generate in silico a plurality of n-mers that contain at least one patient - and cancer - specific cancer neoepitope, filtering in silico the n-mers to so obtain a subset of neoepitope sequences (claim 1); wherein the matched normal omics data are at least one of whole genomic sequencing data, exome sequencing data, and transcriptome data (i.e. data represented by RNA sequences) (claim 2) (i.e. extracting k-mer subsequences from tumor RNA sequences) wherein each of the plurality of n-mer peptides has a length of between 7 and 11 amino acids (claim 4); wherein the step of filtering includes at least one of filtering by type of mutation, filtering by strength of expression (i.e. an overexpression or overrepresentation of the k-mer derived from the MAP encoding sequence in said tumor k-mer database relative to said normal k-mer database is indicative that the corresponding MAP is a tumor antigen candidate), filtering by sub-cellular location, and filtering by binding affinity towards an HLA-type of the patient (i.e. reading on major histocompatibility complex (MHC)-associated peptides) (claim 7).
• Here, the range of 7-mer to 11-mer peptide is equivalent to a range of 21-mer to 33-mer RNA subsequences because a set 3 base pairs (i.e. one codon) would be required to produce one amino acid in the 7-mer to 11-mer range as taught by Nguyen (claims 1 and 4).
• Nguyen teaches "21-mer to 33-mer RNA subsequences" range which makes obvious the instantly claimed range of 24- or 39- nucleotide k-mer databases. It would have been prima facie obvious to one of ordinary skill in the art to select any portions of the disclosed ranges including the instantly claimed ranges from the ranges disclosed in the prior art references, particularly in view of the fact that: "The normal desire of scientists or artisans to improve upon what is already generally known provides the motivation to determine where in a disclosed set percentage ranges is the optimum combination of percentages" In re Peterson 65 USPQ2d 1379 (CAFC 2003). See also In re Malagari, 182 USPQ 549,533 (CCPA 1974) and MPEP 2144.05 modifying the values for identity, coverage and e-value would improve the quality of the data being filtered for the database created since it would yield more complete sequences (with less sequences overlaps when it comes to e-values) being identified by the method.
Claim 87 recites:
wherein the k-mer derived from the MAP encoding sequence is absent from said normal k-mer database
• Nguyen teaches a method for generating an agent for cancer immune therapy by using matched normal omics data of a tumor (i.e. absent from said normal k-mer database) to generate in silico a plurality of n-mers that contain at least one patient - and cancer - specific cancer neoepitope, filtering in silico the n-mers to so obtain a subset of neoepitope sequences (claim 1); wherein the step of filtering includes at least one of filtering by type of mutation, filtering by strength of expression filtering by sub-cellular location, and filtering by binding affinity towards an HLA-type of the patient (i.e. reading on k-mer derived from the MAP encoding sequence) (claim 7).
Claim 88 recites:
(a) isolating and sequencing MAPs in a tumor cell sample;
(b) performing whole transcriptome sequencing on said tumor cell sample, thereby obtaining tumor RNA-sequences;
• Nguyen does not teach the recitation above. However, Patil teaches generating a comprehensive catalogue of cancer-specific genetic alterations of glioblastoma cell lines (i.e. generating tumor-specific database) (pg. 43452 Abstract); wherein RNA isolation, quantification and whole RNA sequencing (pg. 43465 col. 2 para. 2) for analysis of potential oncogenic gene fusions from RNA-seq data (pg. 43460 col. 2 para. 2) (i.e. reading on isolating sequencing and analyzing RNA data from tumor cells as in steps (a) – (b)).
(c) generating a tumor-specific proteome database by:
(i) extracting a set of subsequences comprising at least 33 nucleotides from said tumor RNA-sequences;
(ii) comparing the set of tumor subsequences of (i) to a set of corresponding control subsequences comprising at least 33 nucleotides extracted from RNA-sequences from normal cells;
• Nguyen teaches a method for generating an agent for cancer immune therapy by using matched (i.e. comparing step) 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, filtering in silico the n-mers to so obtain a subset of neoepitope sequences (claim 1); wherein the matched normal omics data are at least one of whole genomic sequencing data, exome sequencing data, and transcriptome data (i.e. data represented by RNA sequences) (claim 2) (i.e. extracting k-mer subsequences from tumor RNA sequences) wherein each of the plurality of n-mer peptides has a length of between 7 and 11 amino acids (claim 4). Here, the range of 7-mer to 11-mer peptide is equivalent to a range of 21-mer to 33-mer RNA subsequences because a set 3 base pairs (i.e. one codon) would be required to produce one amino acid in the 7-mer to 11-mer range as taught by Nguyen (claims 1 and 4).
(c) generating a tumor-specific proteome database by:
…
(iii) extracting the tumor subsequences that are absent, or underexpressed by at least 4-fold, in the corresponding control subsequences, thereby obtaining tumor-specific subsequences; and
• Nguyen does not teach the recitation above. However, Patil teaches generating a comprehensive catalogue of cancer-specific genetic alterations of glioblastoma cell lines (i.e. generating tumor-specific database) (pg. 43452 Abstract); wherein the analysis of said comparison yielded a distribution of different classes of RNAs that are differentially regulated across the six GBM cell lines compared to normal (i.e. control) brain samples (i.e. step (c)(iii))(pg. 43460 Fig. 6).
(c) generating a tumor-specific proteome database by:
…
(iv) in silico translating the tumor-specific subsequences, thereby obtaining the tumor- specific proteome database
• Nguyen does not teach the recitation above. However, Patil teaches generating a comprehensive catalogue of cancer-specific genetic alterations of glioblastoma cell lines (i.e. generating tumor-specific database) (pg. 43452 Abstract). Further, Adekiya teaches mRNA sequences being translated into an amino acid sequence via the translate tool on the ExPASy server (i.e. as in step (c)(iv)) (pg. 2 para. 3). Here, the catalog taught by Patil of cancer specific alterations and the translated protein sequences by Adekiya would read on the claimed proteome database.
(iii) extracting the tumor subsequences that are absent, or underexpressed by at least 4-fold, in the corresponding control subsequences, thereby obtaining tumor-specific subsequences; and
(iv) in silico translating the tumor-specific subsequences, thereby obtaining the tumor- specific proteome database
• Nguyen does not teach the recitation above. However, Kalaora teaches identifying neo-antigens peptides in a melanoma patient among the expressed mutated peptides presented on the Human Leucocyte Antigen (HLA) molecules (i.e. major histocompatibility complex (MHC)-associated peptides) (pg. 5110 Abstract); wherein the whole genomes of matched normal and metastatic tumor DNAs from a melanoma patient was sequenced to identify mutated antigens presented on human melanoma tumor cells (i.e. comparing sequences from tumor and personalized – patient data identify the antigens among MAPs) (pg. 5111 col. 1 para. 3). Further, Adekiya teaches mRNA sequences being translated into an amino acid sequence via the translate tool on the ExPASy server (i.e. reading on in silico translating the expressed protein-coding transcripts from said personalized tumor genome sequence as in step (c)(iv)) (pg. 2 para. 3).
(d) generating a personalized tumor proteome database by:
(i) comparing the tumor RNA-sequences to a reference genome sequence to identify single-base mutations in said tumor RNA-sequences;
(ii) inserting the single-base mutations identified in (i) in the reference genome sequence, thereby creating a personalized tumor genome sequence;
(iii) in silico translating the expressed protein-coding transcripts from said personalized tumor genome sequence, thereby obtaining the personalized tumor proteome database
• Nguyen does not teach the recitation above. However, Slebos teaches a customized protein database construction (i.e. personalized proteome database) to annotate variations predicted from RNA-Seq including mapping to dbSNP135 and COSMIC64 databases (i.e. step (d)(i)), generating a protein database by appending (i.e. reading on inserting) proteins (i.e. expression product of RNA sequences) with nonsynonymous protein coding single nucleotide variants for each sample (i.e. tumor related database) (i.e. step (d)(ii)) (pg. 4 para. 5). Furthermore, Adekiya teaches mRNA sequences being translated into an amino acid sequence via the translate tool on the ExPASy server (i.e. reading on in silico translating the expressed protein-coding transcripts from said personalized tumor genome sequence as in step (d)(iii)) (pg. 2 para. 3).
(e) generating a personalized normal proteome database by:
(i) comparing RNA-sequences from normal cells to a reference genome sequence to identify single-base mutations in said normal RNA-sequences;
(ii) inserting the single-base mutations identified in (i) in the reference genome sequence, thereby creating a personalized normal genome sequence;
(iii) in silico translating the expressed protein-coding transcripts from said personalized normal genome sequence, thereby obtaining the personalized normal proteome database
• Nguyen does not teach the recitation above. However, Slebos teaches a customized protein database construction (i.e. reading on personalized proteome database) using customized databases that included the analysis of 60 normal epithelial samples by MS instrument to produce proteomics quality control datasets for basal xenografts (i.e. generating a personalized normal proteome database) (pg. 2 para. 2) to annotate variations predicted from RNA-Seq including mapping to dbSNP135 and COSMIC64 databases (i.e. step (e)(i)), generating a protein database by appending (i.e. reading on inserting) proteins (i.e. expression product of RNA sequences) with nonsynonymous protein coding single nucleotide variants for each sample (i.e. step (e)(ii)) (pg. 4 para. 5). Furthermore, Adekiya teaches mRNA sequences being translated into an amino acid sequence via the translate tool on the ExPASy server (i.e. reading on in silico translating the expressed protein-coding transcripts from said personalized tumor genome sequence as in step (e)(iii)) (pg. 2 para. 3).
(f) generating a normal and a tumor k-mer database by
(i) extracting a set of subsequences comprising at least 24 nucleotides from said RNA-sequences from normal cells and said tumor RNA-sequences;
(g) comparing the sequences of the MAPs obtained in (a) with the sequences of the tumor- specific proteome database of (c) and the personalized tumor proteome database of (d) to identify the MAPs; and
(h) identifying a tumor antigen candidate among the MAPs identified in (f), wherein a tumor antigen candidate corresponds to a MAP
(1) whose sequence is not present in the personalized normal proteome database; and
(2) (i) whose sequence is present in the personalized tumor proteome database: and/or (ii) whose encoding sequence is overexpressed or overrepresented in said tumor k-mer database relative to said normal k-mer database
• Nguyen teaches a method for generating an agent for cancer immune therapy by using matched normal omics data of a tumor (i.e. comparing relative to said normal) to generate in silico a plurality of n-mers that contain at least one patient - and cancer - specific cancer neoepitope, filtering in silico the n-mers to so obtain a subset of neoepitope sequences (claim 1); wherein the matched normal omics data are at least one of whole genomic sequencing data, exome sequencing data, and transcriptome data (i.e. data represented by RNA sequences) (claim 2) (i.e. extracting k-mer subsequences from tumor RNA sequences) wherein each of the plurality of n-mer peptides has a length of between 7 and 11 amino acids (claim 4); wherein the step of filtering includes at least one of filtering by type of mutation, filtering by strength of expression, filtering by sub-cellular location, and filtering by binding affinity towards an HLA-type of the patient (i.e. reading on major histocompatibility complex (MHC)-associated peptides) (claim 7). Here, the range of 7-mer to 11-mer peptide is equivalent to a range of 21-mer to 33-mer RNA subsequences because a set 3 base pairs (i.e. one codon) would be required to produce one amino acid in the 7-mer to 11-mer range as taught by Nguyen (claims 1 and 4).
• Nguyen does not teach steps (g) and (h)1-2. However, Vinals teaches an approach to screen human genome in-silico for the identification of tumor-specific and tumor-associated antigens (i.e. reading on major histocompatibility complex (MHC)-associated peptides) via a database screening method (i.e. step (h)) (pg. 2607 Abstract); wherein sequences from selected libraries are compared to identify (i.e. step (g)) the genes that are specifically expressed, or significantly overexpressed, in tumoral tissues, and not found, or scarcely found, in normal adult tissues (i.e. step (h)(1)(2)) (pg. 2608 col. 1 para. 2).
Claim 89 recites:
wherein said method further comprises selecting MAPs having a length of 8 to 11 amino acids
• Nguyen teaches a method for generating an agent for cancer immune therapy by 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, filtering in silico the n-mers to so obtain a subset of neoepitope sequences (claim 1); wherein the matched normal omics data are at least one of whole genomic sequencing data, exome sequencing data, and transcriptome data (i.e. data represented by RNA sequences) (claim 2) wherein each of the plurality of n-mer peptides has a length of between 7 and 11 amino acids (claim 4);
• Nguyen teaches an overlapping range from 7-11 mer peptides which anticipates or alternatively makes obvious the instantly claimed range of 8 to 11 amino acids. It would have been prima facie obvious to one of ordinary skill in the art to select any portions of the disclosed ranges including the instantly claimed ranges from the ranges disclosed in the prior art references, particularly in view of the fact that: "The normal desire of scientists or artisans to improve upon what is already generally known provides the motivation to determine where in a disclosed set percentage ranges is the optimum combination of percentages" In re Peterson 65 USPQ2d 1379 (CAFC 2003). Also In re Malagari, 182 USPQ 549,533 (CCPA 1974) and MPEP 2144.05.
Claim 91 recites:
further comprising assessing the binding of the tumor antigen candidate to an MHC molecule
• Nguyen does not teach the recitation above. However, Kalaora teaches identifying neo-antigens peptides in a melanoma patient among the expressed mutated peptides presented on the Human Leucocyte Antigen (HLA) molecules (i.e. major histocompatibility complex (MHC)-associated peptides) (pg. 5110 Abstract); wherein binding of all possible neo-antigens was analyzed by a prediction algorithm (pg. 5113 col. 2 para. 2).
Claim 92 recites:
wherein said binding is assessed using an MHC binding prediction algorithm
• Nguyen does not teach the recitation above. However, Kalaora teaches identifying neo-antigens peptides in a melanoma patient among the expressed mutated peptides presented on the Human Leucocyte Antigen (HLA) molecules (i.e. major histocompatibility complex (MHC)-associated peptides) (pg. 5110 Abstract); wherein binding of all possible neo-antigens was analyzed by a prediction algorithm (pg. 5113 col. 2 para. 2).
Claim 93 recites:
further comprising assessing the frequency of T cells recognizing the tumor antigen candidate in a cell population
• Nguyen does not teach the recitation above. However, Kalaora teaches identifying neo-antigens peptides in a melanoma patient among the expressed mutated peptides presented on the Human Leucocyte Antigen (HLA) molecules (i.e. major histocompatibility complex (MHC)-associated peptides) (pg. 5110 Abstract); wherein synthetic peptides of the selected sequences are then pulsed on antigen presenting cells to evaluate their immunogenicity when introduced to autologous T- cells (i.e. assessing the frequency of T cells recognizing the tumor antigen candidate in a cell population) (pg. 5110 col. 2 para. 1).
Rationale for combining (MPEP §2142-2143)
Regarding claims 76-77, 81-85, 87-89 and 91-93, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Nguyen in view of Patil, Adekiya, Slebos and Kalaora because all references disclose methods for identifying a tumor antigen candidate via database analyses. The motivation would have been to:
• incorporate a depth characterization of the genomic alterations present in cancer (pg. 43453 col. 1 para. 1 Patil);
• predict antigenic epitopes that elicit a desired immune response (pg. 1 Abstract Adekiya);
• incorporate customized databases including genomic, epigenomic, transcriptomic, proteomic, and clinical data to achieve prioritization of candidate drivers by integrating multiple types of data (pg. 13 para. 4 Slebos); and
• incorporate analysis of the mutated HLA-I peptidome of human melanoma tumor cells, using a strategy that combines neoantigen prediction, whole-exome sequencing and mass spectrometry analysis (pg. 5111 col. 1 para. 2 Kalaora).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the identifying a tumor antigen candidate via database analyses of Nguyen to the methods by Patil, Adekiya, Slebos and Kalaora because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for identifying a tumor antigen candidate via database analyses.
B. Claims 78-80 are rejected under 35 U.S.C. 103(a) as being unpatentable over Nguyen, Patil, Adekiya, Slebos and Kalaora as applied to claims 76-77 above further in view of Gaddum ("Identification of potential CTL epitopes of bovine RSV using allele-specific peptide motifs from bovine MHC class I molecules." Veterinary immunology and immunopathology 54(1-4):211-219 (1996)), as cited on the attached Form PTO-892.
Claim 78 recites:
wherein said isolating MAPs comprises (i) releasing said MAPs from said cell sample by mild acid treatment; and (ii) subjecting the released MAPs to chromatography
Claim 79 recites:
wherein said method further comprises filtering the released peptides with a size exclusion column prior to said chromatography
Claim 80 recites:
wherein said size exclusion column has a cut-off of about 3000 Da
• Neither Nguyen or Patil or Adekiya or Slebos or Kalaora teach the recitation above. However, Gaddum teaches the characterization of peptide form MHC class I molecules (pg. 211 Title), wherein peptides were eluted in 0.1% trifluoroacetic acid (i.e. mild acid as in claim 78) and separated from the MHC class I molecules either by reverse phase HPLC (i.e. chromatography as in claims 78-79) or by using a 3 kDa cut-off membrane filter (i.e. reading on size exclusion filtering technique with a cut-off of about 3000 Da as in claims 79-80) (pg. 214 para. 3).
Regarding claims 79-80, the filtering step by a membrane filter taught by Gaddum performs the claimed function of filtering performed by the size exclusion column with the same claimed cutoff (i.e. 3000 Da). Thus, prima facie has been established. See MPEP 2144.05 (a change in form, proportions, or degree "will not sustain a patent"); In re Williams, 36 F.2d 436, 438, 4 USPQ 237 (CCPA 1929) ("It is a settled principle of law that a mere carrying forward of an original patented conception involving only change of form, proportions, or degree, or the substitution of equivalents doing the same thing as the original invention, by substantially the same means, is not such an invention as will sustain a patent, even though the changes of the kind may produce better results than prior inventions."). See also KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 416, 82 USPQ2d 1385, 1395 (2007) (identifying "the need for caution in granting a patent based on the combination of elements found in the prior art").
Rationale for combining (MPEP §2142-2143)
Regarding claims 78-80, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Nguyen, Patil, Adekiya, Slebos and Kalaora in view of Gaddum because all references disclose methods for identifying antigens with associated with MHC molecules. The motivation would have been to incorporate well established experimental ways to studied antigen candidates associating with the MHC class I molecules (pg. 212 para. 4 Gaddum).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the identifying antigens with associated with MHC molecules of Nguyen, Patil, Adekiya, Slebos and Kalaora to the methods by Gaddum because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for identifying antigens with associated with MHC molecules.
C. Claim 86 is rejected under 35 U.S.C. 103(a) as being unpatentable over Nguyen, Patil, Adekiya, Slebos, Kalaora and Yang as applied to claims 76 and 85 above further in view of Vinals ("Using in silico transcriptomics to search for tumor-associated antigens for immunotherapy." Vaccine 19(17-19):2607-2614 (2001)) in view of Argani ("Discovery of new markers of cancer through serial analysis of gene expression: prostate stem cell antigen is overexpressed in pancreatic adenocarcinoma." Cancer research 61(11):4320-4324 (2001)), as cited on the attached Form PTO-892.
Claim 86 recites:
wherein the k-mer derived from the MAP encoding sequence is overexpressed or overrepresented by at least 10-fold in said tumor k-mer database relative to said normal k-mer database
• Neither Nguyen or Patil or Adekiya or Slebos or Kalaora or Yang teach the recitation above. However, Vinals teaches an approach to screen human genome in-silico for the identification of tumor-specific and tumor-associated antigens (i.e. reading on major histocompatibility complex (MHC)-associated peptides) via a database screening method (pg. 2607 Abstract); wherein sequences from selected libraries are compared to identify the genes that are specifically expressed, or significantly overexpressed, in tumoral tissues, and not found, or scarcely found, in normal adult tissues (pg. 2608 col. 1 para. 2). Further, Argani teaches the serial analysis of gene expression to quantify gene expression in human tissues (pg. 4320 Abstract); wherein the identification of differentially expressed genes compared gene expression patterns in pancreatic cancer with those in nonneoplastic tissues (i.e. normal samples) (pg. 4320 col. 2 para. 5) to reveal gene tags expressed at levels of 10-fold difference between the two groups (pg. 4321 col. 1 para. 1).
Rationale for combining (MPEP §2142-2143)
Regarding claim 86, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Nguyen, Patil, Adekiya, Slebos, Kalaora and Yang in view of Vinals and Argani because all references disclose methods for identifying a tumor antigen candidate via database analyses. The motivation would have been to:
• incorporate antigen screening via database searches for tissue-specific gene or a tumor-associated gene and compare data to normal adult tissues. (pg. 2608 col. 1 para. 1 Vinals) and
• establish the validity of analyses of SAGE databases to identify novel tumor markers for potential diagnostic and therapeutic implications (pg. 4320 Abstract Argani).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the identifying a tumor antigen candidate via database analyses of Nguyen, Patil, Adekiya, Slebos, Kalaora and Yang to the methods by Vinals and Argani because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for identifying a tumor antigen candidate via database analyses.
D. Claims 90, 94 and 96 are rejected under 35 U.S.C. 103(a) as being unpatentable over Nguyen, Patil, Adekiya, Slebos, Kalaora as applied to claim 76 above further in view of Vinals as cited on the attached Form PTO-892.
Claim 90 recites:
further comprising comparing the coding sequence of said tumor antigen candidate to sequences from normal tissues
• Neither Nguyen or Patil or Adekiya or Slebos or Kalaora teach the recitation above. However, Vinals teaches an approach to screen human genome in-silico for the identification of tumor-specific and tumor-associated antigens (i.e. reading on major histocompatibility complex (MHC)-associated peptides) via a database screening method (pg. 2607 Abstract); wherein sequences from selected libraries are compared to identify the genes that are specifically expressed, or significantly overexpressed, in tumoral tissues, and not found, or scarcely found, in normal adult tissues (pg. 2608 col. 1 para. 2).
Claim 94 recites:
further comprising assessing the ability of the tumor antigen candidate to induce T cell activation
• Neither Nguyen or Patil or Adekiya or Slebos or Kalaora teach the recitation above. However, Vinals teaches that preclinical data suggest that cell-mediated immune responses targeting self-antigens are able, under appropriate conditions, to induce tumor regression, and a rapidly growing number of trials are testing this concept in the clinic (i.e. reading on assessing the ability of the tumor antigen candidate to induce T cell activation) (pg. 2607 col. 1 para. 1).
Claim 96 recites:
further comprising assessing the ability of said tumor antigen candidate to induce T-cell-mediated tumor cell killing and/or to inhibit tumor growth
• Neither Nguyen or Patil or Adekiya or Slebos or Kalaora teach the recitation above. However, Vinals teaches that preclinical data suggest that cell-mediated immune responses targeting self-antigens are able, under appropriate conditions, to induce tumor regression (i.e. reading on inhibit tumor growth via T-cell-mediated tumor cell killing) and a rapidly growing number of trials are testing this concept in the clinic (pg. 2607 col. 1 para. 1).
Rationale for combining (MPEP §2142-2143)
Regarding claims 90, 94 and 96, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Nguyen, Patil, Adekiya, Slebos and Kalaora in view of Vinals because all references disclose methods for identifying a tumor antigen candidate via database analyses. The motivation would have been to incorporate antigen screening via database searches for tissue-specific gene or a tumor-associated gene and compare data to normal adult tissues. (pg. 2608 col. 1 para. 1 Vinals).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the identifying a tumor antigen candidate via database analyses of Nguyen, Patil, Adekiya, Slebos and Kalaora to the methods by Vinals because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for identifying a tumor antigen candidate via database analyses.
E. Claim 95 is rejected under 35 U.S.C. 103(a) as being unpatentable over Nguyen, Patil, Adekiya, Slebos, Kalaora and Vinals as applied to claims 76 and 94 above further in view of Gaddum as cited on the attached Form PTO-892.
Claim 95 recites:
wherein the ability of the tumor antigen candidate to induce T cell activation is assessed by measuring cytokine production by T cells contacted with cells having said tumor antigen candidate bound to MHC class I molecules at their cell surface
• Neither Nguyen or Patil or Adekiya or Slebos or Kalaora or Vinals teach the recitation above. However, However, Gaddum teaches the characterization of peptide form MHC class I molecules (pg. 211 Title), wherein the understanding of class I immune response involves the understanding of means of inducing secondary signals, e.g. cytokine production (pg. 217 para. 5).
Rationale for combining (MPEP §2142-2143)
Regarding claim 95, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Nguyen, Patil, Adekiya, Slebos, Kalaora and Vinals in view of Gaddum because all references disclose methods for identifying antigens with associated with MHC molecules. The motivation would have been to incorporate well established experimental ways to studied antigen candidates associating with the MHC class I molecules (pg. 212 para. 4 Gaddum).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the identifying antigens with associated with MHC molecules of Nguyen, Patil, Adekiya, Slebos, Kalaora and Vinals to the methods by Gaddum because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for identifying antigens with associated with MHC molecules.
Conclusion
No claims are allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FRANCINI A FONSECA LOPEZ whose telephone number is (571)270-0899. The examiner can normally be reached Monday - Friday 8AM - 5PM ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Olivia Wise can be reached at (571) 272-2249. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/F.F.L./Examiner, Art Unit 1685
/JANNA NICOLE SCHULTZHAUS/Examiner, Art Unit 1685
Prosecution Insights