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 .
Status of the Claims
Claims 4 and 13-36 are cancelled.
Claims 1-3, 5-12 and 37-45 are currently pending and under exam herein.
Claims 1-3, 5-12 and 37-45 are rejected.
Claim 37 does not have a claim status. It appears to be an original claim but is not denoted as one.
Priority
The instant application claims benefit to provisional application No. 63/192,558 filed on 24 May 2021. Domestic benefit is acknowledged. Thus, the effective filing date of claims 1-45 is 24 May 2021.
Drawings
The Drawings filed on 5/22/2024 were considered. It appears figures 7A and 7B were not properly copied over from the provisional application.
Claim Interpretation
Claim 40 is interpreted as being dependent on claim 39.
Claim Rejections - 35 USC § 112
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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 40 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 40 recites the limitation " the graphical feature." There is insufficient antecedent basis for this limitation in the claim. Examiner believes Claim 40 may be a dependent claim of Claim 39.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-3, 5-12 and 37-45 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite: (a) mathematical concepts, (e.g., mathematical relationships, formulas or equations, mathematical calculations); and (b) mental processes, i.e., concepts performed in the human mind, (e.g., observation, evaluation, judgement, opinion).
Subject matter eligibility evaluation in accordance with MPEP 2106:
Eligibility Step 1
Claims 1-3, 5-12 and 37-45 are directed to a method (process) for visualization of the antigen binding profile for a set of clonotypes. Thus, the claims are encompassed by the categories of statutory subject matter, and therefore satisfy the subject matter eligibility requirements under step 1.
[Step 1: YES]
Eligibility Step 2A: First it is determined in Prong One whether a claim recites a judicial exception, and if so, then it is determined in Prong Two whether the recited judicial exception is integrated into a practical application of that exception.
Eligibility Step 2A: Prong One
In determining whether a claim is directed to a judicial exception, examination is performed that analyzes whether the claim recites a judicial exception, i.e., whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim.
Independent claim 1 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
Obtaining a clonotype group comprising a set of individual immune cells from the immune cell receptor dataset (i.e., mental processes and mathematical concepts). Examiner considers this data analysis using algorithms which is a mathematical concept. Additionally, it is a mental process as receptor sequences could be compared by hand in order to form clonotype groups;
identifying at least one interaction between at least one cell of the set of individual immune cells in the clonotype group and a plurality of antigens (i.e., mental processes)
selecting a visualization schema to visualize the at least one interaction (i.e., mental processes); and
rendering a visualization of the clonotype group according to the visualization schema, wherein the visualization displays the at least one interaction (i.e., mental processes).
Dependent claims 2-3 and 5-12 further recite the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas, as noted below.
Dependent claim 2 further recites
wherein the at least one interaction comprises a plurality of interactions between at least one cell of the set of individual immune cells in the clonotype group and the plurality of antigens (i.e., mental processes).
Dependent claim 3 further recites
wherein the at least one interaction comprises a plurality of interactions between a plurality of cells of the set of individual immune cells in the clonotype group and the plurality of antigens (i.e., mental processes).
Dependent claim 5 further recites
wherein each immune cell receptor sequence comprises at least one heavy chain region sequence and at least one light chain region sequence (i.e., mental processes).
Dependent claim 6 further recites
wherein obtaining the clonotype group comprises: comparing the immune cell receptor sequences associated with a first immune cell and a second immune cell from the sample; and identifying the first immune cell and the second immune cell as members of a same clonotype if one or more immune cell receptor sequence comparison criteria is met (i.e., mental processes).
Dependent claim 7 further recites
wherein the immune cell receptor dataset comprises antigen binding information for the plurality of immune cell receptor sequences, and wherein identifying the at least one interaction between the at least one cell of the set of individual immune cells in the clonotype group and the plurality of antigens comprises using the antigen binding information to identify the at least one interaction (i.e., mental processes).
Dependent claim 8 further recites
wherein identifying the at least one interaction between the at least one cell of the set of individual immune cells in the clonotype group and the plurality of antigens comprises determining the at least one cell as binding to an antigen if the at least one cell has at least a pre-determined number of copies of immune cell receptor sequences that bind the antigen (i.e., mental processes).
Dependent claim 9 further recites
wherein selecting the visualization schema comprises: selecting a spatial arrangement of the plurality of antigens based on a relationship between first human leukocyte antigen (HLA) alleles present in the plurality of antigens and second HLA alleles expressed by the immune cells of the sample (i.e., mental processes).
Dependent claim 10 further recites
wherein selecting the visualization schema comprises: selecting a representation for each of the plurality of antigens, wherein the representation for a particular antigen of the plurality of antigens represents information of at least one of a number of cells in the clonotype group that bind to the particular antigen or a proportion of cells in the clonotype group that bind to the particular antigen (i.e., mental processes).
Dependent claim 11 further recites
wherein selecting the visualization schema comprises: selecting a representation indicating different subsets of individual immune cells within the clonotype group, wherein each different subset binds to a different combination of antigens (i.e., mental processes).
Dependent claim 12 further recites
further comprising obtaining additional clonotype groups, each additional clonotype group comprising a distinct set of individual immune cells; and rendering an additional visualization for each additional clonotype group according to the visualization schema (i.e., mental processes).
Independent claim 37 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
obtaining clonotype data that identifies a clonotype group derived from an immune cell sequence dataset (i.e., mental processes);
identifying a set of interactions for the clonotype group, wherein an interaction in the set of interactions is between a set of cells in the clonotype group and a plurality of antigens in which each cell of the set of cells binds to the plurality of antigens (i.e., mental processes);
generating a binding diagram for the clonotype group based on the set of interactions that has been identified, wherein the binding diagram includes a set of interaction representations that visually represents the set of interactions for the clonotype group (i.e., mental processes); and
wherein an interaction representation in the set of interaction representations visually relates the plurality of antigens and visually indicates a number of cells in the set of cells that bind to the plurality of antigens (i.e., mental processes).
Dependent claims 39-44 further recite the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas, as noted below.
Dependent claim 39 further recites
wherein the binding diagram includes a graphical feature for a corresponding antigen that provides a visual indication of at least one of a number of cells in the clonotype group that bind to the corresponding antigen or a proportion of cells in the clonotype group that bind to the corresponding antigen (i.e., mental processes).
Dependent claim 40 further recites
wherein the graphical feature is a shape indicator having a size that visually indicates the number of cells in the clonotype group that bind to the corresponding antigen and at least one of a color, a shade, a texture, or a pattern that visually indicates the proportion of cells in the clonotype group that bind to the corresponding antigen (i.e., mental processes).
Dependent claim 41 further recites
wherein generating the binding diagram comprises: selecting a visualization schema that includes the set of interaction representations (i.e., mental processes).
Dependent claim 42 further recites
wherein the interaction representation includes a set of edges with each edge of the set of edges connecting two antigens of the plurality of antigens (i.e., mental processes).
Dependent claim 43 further recites
wherein the interaction representation includes a set of curves and wherein each curve in the set of curves has a same thickness that indicates the number of cells in the set of cells that bind to the plurality of antigens (i.e., mental processes).
Dependent claim 44 further recites
wherein the binding diagram includes a spatial arrangement of a collection of antigens that are of interest based on a matching of first human leukocyte antigen (HLA) alleles present in the collection of antigens to second HLA alleles expressed by immune cells in the clonotype group (i.e., mental processes).
The abstract ideas recited in the claims are evaluated under the broadest reasonable interpretation (BRI) of the claim limitations when read in light of and consistent with the specification. As noted in the foregoing section, the claims are determined to contain limitations that can practically be performed in the human mind with the aid of a pencil and paper, and therefore recite judicial exceptions from the mental process grouping of abstract ideas. Additionally, the recited limitations that are identified as judicial exceptions from the mathematical concepts grouping of abstract ideas are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind.
Therefore, claims 1-3, 5-12, 37 and 39-44 recite an abstract idea.
[Step 2A Prong One: YES]
Eligibility Step 2A Prong Two: In determining whether a claim is directed to a judicial exception, further examination is performed that analyzes if the claim recites additional elements that when examined as a whole integrates the judicial exception(s) into a practical application (MPEP 2106.04(d)). A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The claimed additional elements are analyzed to determine if the abstract idea is integrated into a practical application (MPEP 2106.04(d)(I); MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the abstract idea, the claim fails to integrate the abstract idea into a practical application (MPEP 2106.04(d)(III)).
The judicial exceptions identified in Eligibility Step 2A Prong One are not integrated into a practical application because of the reasons noted below.
The additional element in independent claim 1 includes:
Obtaining the immune cell receptor dataset from a sample, the immune cell receptor dataset including a plurality of immune cell receptor sequences, wherein each immune cell receptor sequence is associated with an individual immune cell in the sample
The additional element in dependent claims 38 and 45 include:
Displaying the information with a graphical user interface.
The additional element of obtaining the immune cell receptor dataset from a sample, the immune cell receptor dataset including a plurality of immune cell receptor sequences, wherein each immune cell receptor sequence is associated with an individual immune cell in the sample is known (claim 1) is an insignificant extra-solution activity that are part of the data gathering process used in the recited judicial exceptions (see MPEP 2106.05(g)). The additional element of the use of a graphical user interface (Claim 38 and Claim 45) merely invokes a computer as a tool and does not improve the technology of a generic computer (see MPEP 2106.05(a)).
Claims 2-3, 5-12, 37 and 39-44 do not recite any elements in addition to the judicial exception, and thus are part of the judicial exception.
Thus, the additionally recited elements merely invoke a computer as a tool, and/or amount to insignificant extra-solution data gathering activity, and as such, when all limitations in claims 1-3, 5-12 and 37-45 have been considered as a whole, the claims are deemed to not recite any additional elements that would integrate a judicial exception into a practical application, and therefore claims 1-3, 5-12 and 37-45 are directed to an abstract idea (MPEP 2106.04(d)).
[Step 2A Prong Two: NO]
Eligibility Step 2B: Because the claims recite an abstract idea, and do not integrate that abstract idea into a practical application, the claims are probed for a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application (MPEP 2106.05). Identifying whether the additional elements beyond the abstract idea amount to such an inventive concept requires considering the additional elements individually and in combination to determine if they amount to significantly more than the judicial exception (MPEP 2106.05A i-vi).
The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception(s) because of the reasons noted below.
The additional elements recited in independent claim 1 and dependent claims 38 and 45 are identified above, and carried over from Step 2A: Prong Two along with their conclusions for analysis at Step 2B. Any additional element or combination of elements that was considered to be insignificant extra-solution activity at Step 2A: Prong Two was re-evaluated at Step 2B, because if such re-evaluation finds that the element is unconventional or otherwise more than what is well-understood, routine, conventional activity in the field, this finding may indicate that the additional element is no longer considered to be insignificant; and all additional elements and combination of elements were evaluated to determine whether any additional elements or combination of elements are other than what is well-understood, routine, conventional activity in the field, or simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, per MPEP 2106.05(d).
The additional element of obtaining the immune cell receptor dataset from a sample, the immune cell receptor dataset including a plurality of immune cell receptor sequences, wherein each immune cell receptor sequence is associated with an individual immune cell in the sample (claim 1) the use of a graphical user interface are conventional. Evidence for the conventionality is shown by Setlif et al., Afik et al. (Shaked Afik; Yates, K. B.; Bi, K.; Darko, S.; Godec, J.; Gerdemann, U.; Swadling, L.; Douek, D. C.; Klenerman, P.; Barnes, E.; Sharpe, A. H.; W. Nicholas Haining; Yosef, N. Targeted Reconstruction of T Cell Receptor Sequence from Single Cell RNA-Seq Links CDR3 Length to T Cell Differentiation State. Nucleic Acids Research 2017, 45 (16), e148–e148.) and Borcherding et al. (Borcherding, N.; Bormann, N. L.; Kraus, G. ScRepertoire: An R-Based Toolkit for Single-Cell Immune Receptor Analysis. F1000Research 2020, 9, 47).
Setlif et al. teaches gathering an immune cell receptor dataset from a sample while performing receptor sequencing and identifying antigen receptor interactions (abstract). Afik et al. also teaches a method of single cell RNA-sequencing that allows simultaneous measurement of T-cell receptor sequences and global transcriptional profile from single cells (abstract). Borcherding et al. also teaches a method of single cell sequencing for the purpose of immune cell receptor profiling (abstract).
The additional element of the use of a graphical user interface (claims 38 and 45) merely invokes a computer as a tool and does not improve the technology of a generic computer (see MPEP 2106.05(a)).
Claims 2-3, 5-12, 37 and 39-44 do not recite any elements in addition to the judicial exception.
Therefore, when taken alone, all additional elements in claims 1-3, 5-12 and 37-45 do not amount to significantly more than the above-identified judicial exception(s). Even when evaluated as a combination, the additional elements fail to transform the exception(s) into a patent-eligible application of that exception. Thus, claims 1-3, 5-12 and 37-45 are deemed to not contribute an inventive concept, i.e., amount to significantly more than the judicial exception(s) (MPEP 2106.05(II)).
[Step 2B: NO]
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1,2,3,5,6,7,11 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Setliff et al. (Cell. 2019 Nov 28;179(7):1636–1646) in view of Fähnrich et al. (BMC Bioinformatics 18, 164 (2017)) in view of Samir et al. (BMC Med Genomics 13, 29 (2020)) With respect to the limitation a method for visualizing immune cells within an immune cell receptor dataset, the method comprising: obtaining the immune cell receptor dataset from a sample, the immune cell receptor dataset including a plurality of immune cell receptor sequences, wherein each immune cell receptor sequence is associated with an individual immune cell in the sample of Independent claim 1 Setliff et al. teaches Libra-seq which transforms antibody-antigen interactions into sequencing-detectable events by conjugating barcoded DNA oligos to each antigen in a screening library. All antigens are labeled with the same fluorophore, which enables sorting of antigen-positive B cells by fluorescence-activated cell sorting (FACS) before encapsulation of single B cells via droplet microfluidics. Antigen barcodes and B-cell receptor transcripts are tagged with a common cell barcode from bead-delivered oligos, enabling direct mapping of B-cell receptor sequence to antigen specificity (Results, LIBRA-seq method and validation, paragraph 1).
With respect to the limitation wherein the at least one interaction comprises a plurality of interactions between at least one cell of the set of individual immune cells in the clonotype group and the plurality of antigens of dependent claim 2, Setliff et al. teaches Libra-seq which transforms antibody-antigen interactions into sequencing-detectable events by conjugating barcoded DNA oligos to each antigen in a screening library. All antigens are labeled with the same fluorophore, which enables sorting of antigen-positive B cells by fluorescence-activated cell sorting before encapsulation of single B cells via droplet microfluidics. Antigen barcodes and B-cell receptor transcripts are tagged with a common cell barcode from bead-delivered oligos, enabling direct mapping of B-cell receptor sequence to antigen specificity (Results, LIBRA-seq method and validation, paragraph 1).
Regarding the limitations of dependent claim 3 in which at least one interaction comprises a plurality of interactions between a plurality of cells of the set of individual immune cells in the clonotype group and the plurality of antigens, Setliff et al. teaches high-throughput mapping of paired heavy- and light-chain BCR sequences to their cognate antigen specificities to map the antigen specificity of thousands of B cells from two HIV-infected subjects. LIBRA-seq is a technology that allows the user to identify interactions between individual cells and multiple antigens at the single cell level (abstract).
Regarding the limitation of dependent claim 5 in wherein each immune cell receptor sequence comprises at least one heavy chain region sequence and at least one light chain region sequence. Setliff et al. also teaches Libra-seq which was developed to simultaneously recover both antigen specificity and paired heavy and light chain B-cell receptor sequences. (Introduction, 3rd paragraph)
Regarding the limitation of dependent claim 7 wherein the immune cell receptor dataset comprises antigen binding information for the plurality of immune cell receptor sequences, and wherein identifying the at least one interaction between the at least one cell of the set of individual immune cells in the clonotype group and the plurality of antigens comprises using the antigen binding information to identify the at least one interaction Setliff et al. also teaches a technology for high-throughput mapping of paired heavy-/light-chain B-cell receptor sequences to their cognate antigen specificities. B cells are mixed with a panel of DNA-barcoded antigens, such that both the antigen barcode(s) and BCR sequence are recovered via single-cell next-generation sequencing (abstract).
Setliff et al. does not explicitly teach the limitations of obtaining a clonotype group comprising a set of individual immune cells from the immune cell receptor dataset (claim 1); identifying at least one interaction between at least one cell of the set of individual immune cells in the clonotype group and a plurality of antigens (claim 1); selecting a visualization schema to visualize the at least one interaction (claim 1); rendering a visualization of the clonotype group according to the visualization schema, wherein the visualization displays the at least one interaction (claim 1); wherein each immune cell receptor sequence comprises at least one heavy chain region sequence and at least one light chain region sequence (claim 5); obtaining the clonotype group comprises: comparing the immune cell receptor sequences associated with a first immune cell and a second immune cell from the sample; and identifying the first immune cell and the second immune cell as members of a same clonotype if one or more immune cell receptor sequence comparison criteria is met (claim 6); selecting a representation indicating different subsets of individual immune cells within the clonotype group, wherein each different subset binds to a different combination of antigens (claim 11); and obtaining additional clonotype groups, each additional clonotype group comprising a distinct set of individual immune cells; and rendering an additional visualization for each additional clonotype group according to the visualization schema (claim 12).
With respect to the limitation of independent claim 1, of obtaining a clonotype group comprising a set of individual immune cells from the immune cell receptor dataset Fähnrich et al. teaches ClonoCalc a computational tool for processing raw next generation sequencing data of T-cell or B-cell receptor sequences to clonotype groups (Implementation, ClonoCalc, 2nd Bullet point).
With respect to the limitation of dependent claim 6, teaches comparing the immune cell receptor sequences associated with a first immune cell and a second immune cell from the sample; and identifying the first immune cell and the second immune cell as members of a same clonotype if one or more immune cell receptor sequence comparison criteria is met, Fähnrich et al. teaches a method relating immune cell receptor sequences to clonotypes (Implementation, ClonoCalc, 2nd Bullet point)
Regarding the limitation of independent claim 1, selecting a visualization schema to visualize the at least one interaction and rendering a visualization of the clonotype group according to the visualization schema, wherein the visualization displays the at least one interaction Samir et al. teaches a visualization where multiple variables can be represented by size, shape, or color. A shape can be used to denote clonotype group or individual cell while color can be defined to show interaction with an antigen or a group of antigens (Figure 2).
Regarding the limitation of dependent claim 11, selecting a representation indicating different subsets of individual immune cells within the clonotype group, wherein each different subset binds to a different combination of antigens, Samir et al. teaches a visualization where multiple variables can be represented by size, shape, or color. A shape can be used to denote clonotype group or subset within a clonotype group while color can be defined to show interaction with an antigen or a combination of antigens (Figure 2).
Regarding the limitation of dependent claim 12, obtaining additional clonotype groups, each additional clonotype group comprising a distinct set of individual immune cells; and rendering an additional visualization for each additional clonotype group according to the visualization schema Samir et al. teaches a visualization where multiple variables can be represented by size, shape, or color. A shape can be used to denote clonotype group or subset within a clonotype group while color can be defined to show interaction with an antigen or a combination of antigens (Figure 2).
A person of ordinary skill in the art before the effective filing date would be motivated to take the sequencing data of immune cell receptors gathered from the method of Setliff et al. and to determine clonotypes using immune cell receptor sequence information using the method of Fähnrich et al. because a person of ordinary skill in the art would be motivated to process their immune cell receptor dataset to gain useful information on clonotypes. There is a reasonable expectation of success because Fähnrich et al. was previously used to determine clonotype groups from immune cell receptor sequences. Additionally, a person of ordinary skill in the art before the effective filing date of the claimed invention would be motivated to use a visualization method taught by Samir et al. with the immune cell receptor dataset generated from Setliff et al. with clonotypes identified by using the method of Fähnrich et al. because a person of ordinary skill in the art would be motivated to visualize their dataset in order to help interpret it and to draw conclusions. There is a reasonable expectation of success because the method of Samir et al. was previously used to successfully visualize data.
Dependent claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Setliff et al. in view of Fähnrich et al. in view of Samir et al. as applied to claims 1,2,3,5,6,7,11 and 12 under 35 U.S.C. 103 above, and further in view of Shugay et al. (Nucleic Acids Research, Volume 46, Issue D1, 4 January 2018, Pages D419–D427)
As applied to independent claim 1 (detailed above), Setliff et al. in view of Fähnrich et al. in view of Samir et al., teaches a method of visualizing immune cells within an immune cell receptor dataset.
Setliff et al. in view of Fähnrich et al. in view of Samir et al. does not explicitly teach identifying the at least one interaction between the at least one cell of the set of individual immune cells in the clonotype group and the plurality of antigens comprises determining the at least one cell as binding to an antigen if the at least one cell has at least a pre-determined number of copies of immune cell receptor sequences that bind the antigen (Claim 8).
In regards to the limitation of dependent claim 8, wherein identifying the at least one interaction between the at least one cell of the set of individual immune cells in the clonotype group and the plurality of antigens comprises determining the at least one cell as binding to an antigen if the at least one cell has at least a pre-determined number of copies of immune cell receptor sequences that bind the antigen, Shugay et al. teaches a method for linking antigen specificities with TCR sequences (abstract).
A person of ordinary skill in the art would be motivated to modify the methods of Setliff et al. in view of Fähnrich et al. in view of Samir et al. by incorporating the knowledge of the relationship between receptor sequences and antigen binding of Shugay et al. A person of ordinary skill in the art would have been motivated to combine Setliff et al. in view of Fähnrich et al. in view of Samir et al. with Shugay et al. because Shugay et al. teaches the relationship between antigen binding and receptor sequences. There is a reasonable expectation of success because a person of ordinary skill in the art could infer an antigen binding to a receptor by matching sequences of receptors known to bind to the antigen.
Dependent claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Setliff et al. in view of Fähnrich et al. in view of Samir et al. as applied to claims 1,2,3,5,6,7,11 and 12 under 35 U.S.C. 103 above, and further in view of Pierini et al. (Mol Biol Evol. 2018 Sep 1;35(9):2145-2158)
As applied to independent claim 1 (detailed above), Setliff et al. in view of Fähnrich et al. in view of Samir et al. teaches a method of visualizing immune cells within an immune cell receptor dataset.
Setliff et al. in view of Fähnrich et al. in view of Samir et al. does not explicitly teach selecting a spatial arrangement of the plurality of antigens based on a relationship between first human leukocyte antigen (HLA) alleles present in the plurality of antigens and second HLA alleles expressed by the immune cells of the sample (Claim 9).
In regards to the limitation of dependent claim 9, selecting a spatial arrangement of the plurality of antigens based on a relationship between first human leukocyte antigen (HLA) alleles present in the plurality of antigens and second HLA alleles expressed by the immune cells of the sample, Pierini et al. teaches the relationship between HLA alleles and antigen binding. For all five human MHC genes, the genetic distance between two alleles of a heterozygous genotype was positively correlated with the total number of peptides bound by these two alleles. In accordance with the major antigen-presentation pathway of MHC class I molecules, HLA-B and HLA-C alleles showed particularly strong correlations for peptides derived from intracellular pathogens (abstract).
It would have been obvious for a person to modify the methods of Setliff et al. in view of Fähnrich et al. in view of Samir et al. by incorporating the knowledge of the relationship between the HLA alleles and antigen binding taught by Pierini. A person of ordinary skill in the art would be motivated to modify the visualization taught by Setliff et al. in view of Fähnrich et al. in view of Samir et al. with the relationship between the HLA alleles. There is a reasonable expectation of success because the known relationship of the HLA gene with antigen binding would lead a person of ordinary skill in the art to visualize that relationship.
Dependent claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Setliff et al. in view of Fähnrich et al. in view of Samir et al. as applied to claims 1,2,3,5,6,7,11 and 12 under 35 U.S.C. 103 above, and further in view of Doncheva et al. (J Proteome Res. 2018 Dec 5;18(2):623–632.)
As applied to independent claim 1 (detailed above), Setliff et al. in view of Fähnrich et al. in view of Samir et al. teaches a method of visualizing immune cells within an immune cell receptor dataset.
Setliff et al. in view of Fähnrich et al. in view of Samir et al. does not explicitly teach selecting the visualization schema comprises: selecting a representation for each of the plurality of antigens, wherein the representation for a particular antigen of the plurality of antigens represents information of at least one of a number of cells in the clonotype group that bind to the particular antigen or a proportion of cells in the clonotype group that bind to the particular antigen (Claim 10).
In regards to the limitation of dependent claim 10, selecting the visualization schema comprises: selecting a representation for each of the plurality of antigens, wherein the representation for a particular antigen of the plurality of antigens represents information of at least one of a number of cells in the clonotype group that bind to the particular antigen or a proportion of cells in the clonotype group that bind to the particular antigen Doncheva et al. teaches a representation of protein interactions where node color represents binding strength (Figure 2).
It would have been obvious for a person to modify the methods of Setliff et al. in view of Fähnrich et al. in view of Samir et al. by using the representation taught by Doncheva et al. A person of ordinary skill in the art would be motivated to modify the protein binding diagram to an antigen binding diagram. There is a reasonable expectation of success because Doncheva et al. was previously used to visualize interaction data.
Claims 37, 38, 39, 40, 41, 42, 43, 45 are rejected under 35 U.S.C. 103 as being unpatentable over Fähnrich et al. (BMC Bioinformatics 18, 164 (2017)) in view of Setliff et al. (Cell. 2019 Nov 28;179(7):1636–1646) in view of Rivas et al. (PLoS Comput Biol 6(6): e1000807) in view of Noell et al. (European Respiratory Review 2018 27(147): 170110)
Regarding the limitation of independent claim 37, obtaining clonotype data that identifies a clonotype group derived from an immune cell sequence dataset, Fähnrich et al. teaches a method to identify clonotypes from an immune cell sequence dataset (Implementation, ClonoCalc, 2nd Bullet point).
Regarding the limitation of dependent claim 38, using a graphical user interface on a display system, Fähnrich et al. teaches using a graphical user interface (Figure 2).
Regarding the limitation of dependent claim 45, displaying multiple diagrams on a graphical user interface, Fähnrich et al. teaches displaying multiple diagrams on a graphical user interface (Figure 2).
Fähnrich et al. does not explicitly teach identifying a set of interactions for the clonotype group, wherein an interaction in the set of interactions is between a set of cells in the clonotype group and a plurality of antigens in which each cell of the set of cells binds to the plurality of antigens (claim 37); generating a binding diagram for the clonotype group based on the set of interactions that has been identified, wherein the binding diagram includes a set of interaction representations that visually represents the set of interactions for the clonotype group (claim 37); and wherein an interaction representation in the set of interaction representations visually relates the plurality of antigens and visually indicates a number of cells in the set of cells that bind to the plurality of antigens (claim 37); the binding diagram includes a graphical feature for a corresponding antigen that provides a visual indication of at least one of a number of cells in the clonotype group that bind to the corresponding antigen or a proportion of cells in the clonotype group that bind to the corresponding antigen (claim 39); the graphical feature is a shape indicator having a size that visually indicates the number of cells in the clonotype group that bind to the corresponding antigen and at least one of a color, a shade, a texture, or a pattern that visually indicates the proportion of cells in the clonotype group that bind to the corresponding antigen (claim 40); selecting a visualization schema that includes the set of interaction representations (claim 41); the interaction representation includes a set of edges with each edge of the set of edges connecting two antigens of the plurality of antigens (claim 42); the interaction representation includes a set of curves and wherein each curve in the set of curves has a same thickness that indicates the number of cells in the set of cells that bind to the plurality of antigens (claim 43).
Regarding the limitation of independent claim 37, identifying a set of interactions for the clonotype group, wherein an interaction in the set of interactions is between a set of cells in the clonotype group and a plurality of antigens in which each cell of the set of cells binds to the plurality of antigens, Setliff et al. teaches high-throughput mapping of paired heavy- and light-chain BCR sequences to their cognate antigen specificities to map the antigen specificity of thousands of B cells from two HIV-infected subjects. LIBRA-seq is a technology that allows the user to identify interactions between individual cells and multiple antigens at the single cell level (abstract).
A person of ordinary skill in the art would be motivated to combine the receptor sequencing information and the antigen binding information obtained from Setliff et al. with the method to generate clonotypes based on receptor sequence data from Fähnrich et al. in order to gain clonotype information from their receptor sequence and antigen specificity dataset. There would be a reasonable expectation of success because Fähnrich et al. was successful at identifying clonotype groups from immune cell receptor sequences.
Fähnrich et al. in view of Setliff et al. does not explicitly teach generating a binding diagram for the clonotype group based on the set of interactions that has been identified, wherein the binding diagram includes a set of interaction representations that visually represents the set of interactions for the clonotype group (claim 37); and wherein an interaction representation in the set of interaction representations visually relates the plurality of antigens and visually indicates a number of cells in the set of cells that bind to the plurality of antigens (claim 37); the binding diagram includes a graphical feature for a corresponding antigen that provides a visual indication of at least one of a number of cells in the clonotype group that bind to the corresponding antigen or a proportion of cells in the clonotype group that bind to the corresponding antigen (claim 39); the graphical feature is a shape indicator having a size that visually indicates the number of cells in the clonotype group that bind to the corresponding antigen and at least one of a color, a shade, a texture, or a pattern that visually indicates the proportion of cells in the clonotype group that bind to the corresponding antigen (claim 40); selecting a visualization schema that includes the set of interaction representations (claim 41); the interaction representation includes a set of edges with each edge of the set of edges connecting two antigens of the plurality of antigens (claim 42); the interaction representation includes a set of curves and wherein each curve in the set of curves has a same thickness that indicates the number of cells in the set of cells that bind to the plurality of antigens (claim 43).
Regarding the limitation of independent claim 37, generating a binding diagram for the clonotype group based on the set of interactions that has been identified, wherein the binding diagram includes a set of interaction representations that visually represents the set of interactions for the clonotype group, Rivas et al. teaches. a protein interaction network where edges represent interactions between proteins. This plot could be adopted to a binding diagram between antigens and cells or clonotype groups (Figure 3).
Regarding the limitation of dependent claim 41, generating the binding diagram comprises: selecting a visualization schema that includes the set of interaction representations, Rivas et al. teaches a protein interaction network where edges represent interactions between proteins. This plot could be adopted to a binding diagram between antigens and cells or clonotype groups (Figure 3).
A person of ordinary skill in the art would have been motivated to combine the method of Fähnrich et al. in view of Setliff et al. with the visualization taught by Rivas et al. There would be a strong motivation to modify the protein interaction graphic to a binding diagram of clonotype groups or cells with antigen interaction. There is a reasonable expectation of success because Rivas et al. has already been used to visualize interactions.
Fähnrich et al. in view of Setliff et al. in view of Rivas et al. does not explicitly teach an interaction representation in the set of interaction representations visually relates the plurality of antigens and visually indicates a number of cells in the set of cells that bind to the plurality of antigens (claim 37); the binding diagram includes a graphical feature for a corresponding antigen that provides a visual indication of at least one of a number of cells in the clonotype group that bind to the corresponding antigen or a proportion of cells in the clonotype group that bind to the corresponding antigen (claim 39); the graphical feature is a shape indicator having a size that visually indicates the number of cells in the clonotype group that bind to the corresponding antigen and at least one of a color, a shade, a texture, or a pattern that visually indicates the proportion of cells in the clonotype group that bind to the corresponding antigen (claim 40); the interaction representation includes a set of edges with each edge of the set of edges connecting two antigens of the plurality of antigens (claim 42); the interaction representation includes a set of curves and wherein each curve in the set of curves has a same thickness that indicates the number of cells in the set of cells that bind to the plurality of antigens (claim 43).
Regarding the limitation of independent claim 37, an interaction representation in the set of interaction representations visually relates the plurality of antigens and visually indicates a number of cells in the set of cells that bind to the plurality of antigens, Noell et al. teaches using a graph-based representation where node size is a quantifiable property, such as number of cells or antigens, and edges represent a connection, such as number interactions or interaction strength (Figure 2).
Regarding the limitation of dependent claim 40, the graphical feature is a shape indicator having a size that visually indicates the number of cells in the clonotype group that bind to the corresponding antigen and at least one of a color, a shade, a texture, or a pattern that visually indicates the proportion of cells in the clonotype group that bind to the corresponding antigen, Noell et al. teaches using a graph-based representation where node size is a quantifiable property, such as number of cells or antigens, and edges represent a connection, such as number interactions or interaction strength (Figure 2). Other properties such as color, shade or texture can also be used to show proportion of cells that bind to an antigen using a graph-based representation (Figure 2).
Regarding the limitation of dependent claim 42, the interaction representation includes a set of edges with each edge of the set of edges connecting two antigens of the plurality of antigens, Noell et al. teaches using a graph-based representation where node size is a quantifiable property, such as number of cells or antigens, and edges represent a connection, such as number interactions or interaction strength (Figure 2).
Regarding the limitation of dependent claim 43, the interaction representation includes a set of curves and wherein each curve in the set of curves has a same thickness that indicates the number of cells in the set of cells that bind to the plurality of antigens, Noell et al. teaches using a graph-based representation where node size is a quantifiable property, such as number of cells or antigens, and edges represent a connection, such as number interactions or interaction strength. The edges thickness could be used to denote the number of cells that bind to a particular antigen (Figure 2).
A person of ordinary skill in the art would be motivated to combine the binding and clonotype information taught by Fähnrich et al. in view of Setliff et al. with the visualization taught by Rivas et al. in view of Noell et al. because graph-based method would be useful to show antigen-cell interactions. There would be a reasonable expectation of success because Noell et al. has already visualized graph-based interactions.
Dependent claim 44 is rejected under 35 U.S.C. 103 as being unpatentable over Fähnrich et al. (BMC Bioinformatics 18, 164 (2017)) in view of Setliff et al. (Cell. 2019 Nov 28;179(7):1636–1646) in view of Rivas et al. (PLoS Comput Biol 6(6): e1000807) in view of Noell et al. (European Respiratory Review 2018 27(147): 170110) in view of Pierini et al. (Mol Biol Evol. 2018 Sep 1;35(9):2145-2158)
As applied to independent claim 37 (detailed above), Fähnrich et al. in view of Setliff et al. in view of Rivas et al. in view of Noell et al. teaches a method for visualizing multi-antigen binding capabilities of a set of clonotype groups.
Fähnrich et al. in view of Setliff et al. in view of Rivas et al. in view of Noell et al. does not explicitly teach the binding diagram includes a spatial arrangement of a collection of antigens that are of interest based on a matching of first human leukocyte antigen (HLA) alleles present in the collection of antigens to second HLA alleles expressed by immune cells in the clonotype group (claim 44).
In regards to the limitation of dependent claim 44, the binding diagram includes a spatial arrangement of a collection of antigens that are of interest based on a matching of first human leukocyte antigen (HLA) alleles present in the collection of antigens to second HLA alleles expressed by immune cells in the clonotype group, Pierini et al. teaches the relationship between HLA alleles and antigen binding. For all five human MHC genes, the genetic distance between two alleles of a heterozygous genotype was positively correlated with the total number of peptides bound by these two alleles. In accordance with the major antigen-presentation pathway of MHC class I molecules, HLA-B and HLA-C alleles showed particularly strong correlations for peptides derived from intracellular pathogens (abstract).
A person having or