DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Election/Restrictions
Claims 45-46 and 48 are withdrawn from further consideration pursuant to 37 CFR 1.142(b), as being drawn to a nonelected group, there being no allowable generic or linking claim. Applicant timely traversed the restriction (election) requirement in the reply filed on June 22, 2026.
Claim Status
Claims 45-46 and 48 are withdrawn.
Claims 1-13, 33-34, and 41-44 are pending.
Claims 1-13, 33-34, and 41-44 are rejected.
Priority
This application is a 371 of PCT/IL2021/050539, filed 05/11/2021, which claims benefit of application no. 63/022,912, filed 05/11/2020. The instant application has the effective filing date of 11 May 2020.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/13/2023 and 07/31/2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements have been considered by the examiner.
Drawings
The drawings, submitted on 11/14/2022, are accepted by the examiner.
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 1-13, 33-34, and 41-44 are rejected under U.S.C 101 because the claimed invention is directed to abstract ideas without significantly more, as detailed in the analysis below.
Eligibility Step 1: Subject matter eligibility evaluation in accordance with MPEP § 2106:
Claims 1-13 and 33-34 are directed to a statutory category (method).
Claims 41-44 are directed to a statutory category (system).
Therefore, in accordance with MPEP § 2106.03 all claims have patent eligible subject matter.
[Eligibility Step 1: YES]
Eligibility Step 2A: This step determines whether a claim is directed to a judicial exception in accordance with MPEP § 2106.
Eligibility Step 2A -- Prong One: Limitations are analyzed to determine if the claims recite any concepts that could equate to a judicial exception (i.e. abstract idea, law of nature, or natural phenomenon). Possible judicial exceptions are explored below.
Recitations of Judicial Exceptions:
Claims 1 and 41: constructing, per each particular type of adverse effect of one or more types of possible adverse effects of said NA editing procedure, a statistical model of occurrence of said type of adverse effect by the NA editing procedure, (mental process)
applying said statistical model to said sequencing data to statistically determine actual occurrence of said type of adverse effect by the NA editing procedure (mental process, mathematical concept)
Claim 2: utilizing the statistical model to quantify the types of adverse effects actually affected by the NA editing procedure by determining rates of occurrence thereof by the NA editing procedure, and a statistical confidence intervals for said rates. (mental process, mathematical concept)
Claim 3: wherein said one or more types of adverse effect are classified to one or more classes of adverse effects, each class being characterized by the one or two participating sites [Xm1,2], with which adverse effects of the class are associated, whereby each class belongs to one of two categories of adverse effects: - Category 1 (INDELs): adverse effects involving one site [nt=Amtn2] where ml=m2; and - Category 2(TRANSLOCATIONs): adverse effects involving two sites where m1n2; (mental process)
carrying out the following operations a. to d. for at least one of said two categories of adverse effects: b. processing the sequencing data according to the class of said particular type of adverse effect to determine or assess respective 'collective' counts Nxand NMc of reads of amplicons which are associated with the participating sites [Xm11,Xm2] of said class in the sequencing data of each of the edited and control collections; (mental process)
c. processing the sequencing data according to the particular type of adverse effect to determine or assess respective counts nrx and nMe of 'affected' reads of amplicons in which said particular type of adverse effect is observed; (mental process)
d. applying said template statistical model to the respective 'collective' counts NTx and NMc of reads of amplicons which are associated with the participating sites [%,m1t,Xtm2] in the edited and control collections and to the respective 'affected' counts rx and nMc of reads of amplicons in which said particular type of adverse effect is observed, from amongst the reads of amplicons which are associated with the edited and control collections; and thereby obtaining the said statistical determination of the occurrence of said particular type of adverse effect by the NA editing procedure (e.g. in tested cell types or in related samples and/or in clinical material). (mental process, mathematical concept)
Claim 5: wherein said processing includes a preliminary preprocessing of the sequencing data for adjusting said reads of said multiplexed amplifications' products/amplicans from each of the edited and control collections by carrying out at least one of the following: - trimming of sequencing adapters from said reads, - merging pair-end reads, and - filtering out low-quality reads. (mental process)
Claim 6: The method of any claim 3, adapted for determining at least one indel type T of said one or more of types of adverse effect of the NA editing procedure, which belong to the Category 1 of adverse effects that is associated with INDEL activity of said NA editing procedure, and which belong to at least one class of adverse effects associated with a respective site/locus of interest Xmi. (mental process)
Claim 7: b. utilizing a 'collective' count match condition of said template statistical model, to identify matched reads of the multiplexed amplifications products/amplicons that match the reference NA sequence of the site/locus of interest in the reference data; and thereby obtaining for the site of interest, Am respective collections and Lu(amt)of matched reads, in the sequencing data of the edited and control collections respectively. (mental process, mathematical concept)
Claim 8: wherein the 'collective ' count match condition of the template statistical model of Category 1 of adverse effects is satisfied for a read to be match in case the prefix and suffix and regions of the read match prefix PRS+mn and suffix PRS-m primer sequences (PRSrmi, PRS-mi) of the respective site of interest (mental process)
Claim 9: wherein sizes of said respective collections present said 'collective' counts NTx and NMc of reads of amplicons which are associated with said at least one class of adverse effects involving the site Xml observed in the sequencing data of the corresponding edited and control collections. (mental process)
Claim 10: wherein said processing of said sequencing data by includes segregating the collections of reads matching the site of interest X1.1, to form at two sub-collections Lr.(nmi,T) and LA(ni,T) of reads presenting a certain type T of indel observed in the matched reads from the sequencing data of the edited and control collections respectively; wherein each indel type T is characterized by at least one of:- a size/length t of bases introduced-to or deleted-from the matched read relative to the reference NA sequence of the site/locus of interest (mental process)
aligning the matched reads in the collections to the reference NA sequence for the site of interest; identifying gaps in the aligned matched reads whereby each gap representing an indel and at least one of a position i and a length z of the gap represents a type T of said indel; (mental process)
respectively aggregating the aligned matched reads of the collections Crx(mi) and L(Amt), to form the corresponding sub-collections of reads matching the site of interest X1.1, to form at two sub-collections of reads, respectively presenting observations of said certain type T of indel, in the aligned matched reads of the sequencing data of the corresponding edited and control collections, whereby said aggregating comprises matching the identified gaps in the aligned matched reads with properties of a gap representing said certain type T of indel based on an 'affected' count match condition of the template statistical model of Category 1 of adverse effects, whereby said 'affected' count match condition of the template statistical model of Category 1 is satisfied upon fulfillment of a predetermined set one or more of the following conditions:i) the position i of an identified gap in an aligned matched read is similar to a position i of the gap in said type T of indel;ii) a size - of the gap of an identified gap in an aligned matched read is similar to a size ^'[ of the gap in said type T of mdel;iii)a nucleotide base sequence in the gap of an identified gap in an aligned matched read has a degree of similarity with a nucleotide base sequence of said type T of indel above a certain threshold. (mental process)
Claim 11: wherein said indel type T is characterized by both said size/length ' of bases and said position i. (mental process)
Claim 12: wherein sizes of said respective sub-collections Lrr(ami ,T) and L'l(1.i,T) present said 'affected' counts nTx and nMc of reads of amplicons, in which said particular type T of adverse effect is observed. (mental process)
Claim 13: wherein the template statistical model provided for the INDEL activity of said NA editing procedure comprises a statistical classifier comprising a Maximum A Posteriori (MAP) estimator. (mathematical concept)
Claim 42: c. constructing a statistical model for said type of adverse effect based on said template statistical model and the reference data, by carrying out the following: processing said sequencing data of the first and second collection to determine or assess respective 'collective' counts reads of amplicons which are associated with the one or two sites participating in said particular type of adverse effect, by matching said amplicons to the reference NA sequences of said one or two sites according to a 'collective' count match condition designated by said template statistical model, (mental process, mathematical concept)
respectively counting the reads of amplicons of said first and second collections, which satisfy said 'collective' count match condition, to thereby determine or assess the respective 'collective' counts; (mental process)
processing said sequencing data of the first and second collection to determine or assess respective 'affected' counts and of reads of affected amplicons in which said particular type of adverse effect is observed, by matching said amplicons to the reference NA sequences of said one or two sites according to an 'affected' count match condition designated by said template statistical model, and respectively counting the reads of amplicons of said first and second collections, which satisfy said 'affected' count match condition, to thereby determine or assess the respective 'affected' counts. (mental process)
statistically determining whether said particular type of adverse effect occurs due to the NA editing procedure by utilizing a statistical classifier of the template statistical model; and classifying the occurrence of said particular type of adverse effect according to said statistical classifier based on said 'collective' counts and said 'affected' counts. (mental process, mathematical concept)
Claim 43: determining said probability of occurrence for adverse effects of one or both of the following categories: - Category 1 (INDELs): adverse effects involving one site; and Category 2(TRANSLOCATIONs): adverse effects involving two sites. (mathematical concept, mental process)
Step 2A – Prong One Analysis:
Analysis techniques such as making a statistical model to determine occurrence, characterizing, classifying, filtering, and/or separating data from other groups, requiring nothing more than the human mind and pen/paper, read on observations, evaluations, judgments, opinions, and fall under the mental process grouping of abstract ideas. Limitations that merely provide additional information regarding the data being analyzed in this manner are similarly categorized (claims 9, 11).
Analysis techniques such as statistical models that use classifiers, confidence intervals, Maximum A Posteriori (MAP) estimators, and other quantitative conclusions recite mathematical formulas, calculations, and/or relationships that fall under the mathematical concept grouping of abstract ideas.
Therefore, the claims appear to recite judicial exceptions.
[Eligibility Step 2A – Prong One: YES]
Eligibility Step 2A – Prong Two: 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. If the claim contains no additional claim elements beyond the abstract idea, the claim fails to integrate the abstract idea into a practical application (MPEP 2106.04(d)). Additional elements are recited, categorized, and analyzed below.
Data Gathering/Outputting Elements:
Claims 1 and 41: providing a first and second collections of NA sequences originated from the same NA source, whereby the first collection is an edited collection of NA sequences from said NA source to which a certain NA editing procedure was applied, and the second collection is a control (mock) collection of NA sequences of said NA source to which said NA editing procedure was not applied;
providing target data indicative of expected editing sites {xmiM of the NA editing procedure including at least one on-target site {X} and one or more off-target sites where m represents an off-target or on-target site indexed m and M is a number of the expected on-target and off-target sites;
outputting data indicative of the of whether said each type of adverse effect by actually occurs due to the NA editing procedure, to thereby enable determination of safety of the NA editing procedure.
Claim 3: a. providing a template statistical model corresponding to the category of said particular type of adverse effect;
Claim 7: a. providing reference data indicative of at least one reference NA sequence of the at least one respective site/locus of for which INDEL activity of said NA editing procedure is to be assessed;
Claim 42: a. retrieving from the reference data stored in said memory or section thereof, reference NA sequences of the one or two sites participating in said type of adverse effect; b. obtaining from said memory or section thereof, a template statistical model corresponding to said type of adverse effect;
Computer Components:
Claim 41: an input to receive sequencing data; a memory or a section thereof for storing; a processor for processing said sequencing data; and an output for outputting data
Claim 44: wherein said input is connectable to the sequencing utility for receiving said sequencing data therefrom
Sequencing Elements:
Claims 1 and 41: applying multiplexed amplifications to the edited and control collections respectively, and thereby obtaining respective amplified products/amplicons of said edited and control collections, whereby the multiplexed amplifications of the edited and control collections are conducted with similar primer molecule types;
sequencing the multiplexed amplifications products/amplicons of said edited and control collections to obtain sequencing data indicative of pluralities of reads, Rrx={rT" and RuG= {rfc},of said multiplexed amplifications' products/amplicons from each of the edited and control collections
Claim 4: wherein said multiplexed amplifications of the edited and control collections are conducted utilizing respective multiplex PCR processes with a similar selected set of primer molecule types{PRt}; and wherein the method includes providing the selected set of a plurality of primer molecule types {PRt} including primer molecule types selected according to said target data, such that the plurality of primer types {PRt} comprise, or constitutes of, matched pairs (PRM+m, PRM-m) of forward PRM+m and reverse PRM-m primer molecule types {(PRM+m,,, PRM-m,)}1Me {PRt} suitable for amplification of said on-target and off- target sites in the edited and control NA collections.
Claim 44: a sequencing utility capable of sequencing the multiplexed amplification products/amplicons of the first and second collections of NA sequences;
Step 2A – Prong Two Analysis:
The elements categorized as data gathering activities merely store, retrieve, and output information in memory necessary to complete the judicial exceptions. Such elements are categorized as insignificant extra-solution activities per MPEP 2106.05 (g) and Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) as they do not add a meaningful limitation to the process of completing the judicial exceptions.
The sequencing components, as instantly recited merely gather data necessary to complete the judicial exceptions are also categorized as insignificant extra-solution activities per MPEP 2106.05 (g).
Generic computer components and implementations provide mere instructions to implement the abstract ideas onto a technological environment per Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984.
As such, the additional elements, when viewed separately and in the context of a whole claimed invention, do not integrate the judicial exceptions into practical application.
[Eligibility Step 2A – Prong Two: NO]
Eligibility Step 2B: Claim elements are probed for inventive concept equating to significantly more than the judicial exception (MPEP 2106.04(II)).
Step 2B Analysis:
Storing and retrieving information in memory is found well-understood, routine, and conventional per Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; generic outputting is found well-understood, routine, and conventional per Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). This evidence is applicable to the data gathering and computer component elements.
The sequencing components are found well-understood, routine, and conventional per University of Utah Research Foundation v. Ambry Genetics, 774 F.3d 755, 764, 113 USPQ2d 1241, 1247 (Fed. Cir. 2014) for amplifying and sequencing nucleic acid sequences; and Genetic Techs. Ltd., 818 F.3d at 1377; 118 USPQ2d at 1546 for analyzing DNA to provide sequence information or detect allelic variants.
As such, the additional elements are further found to lack inventive concept.
[Eligibility Step 2B: NO]
Therefore, claims 1-13, 33-34, and 41-44 are directed to judicial exceptions without significantly more and are rejected under 35 U.S.C 101.
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, 4-5, 41, and 44 are rejected under 35 U.S.C. 103 as being unpatentable over Daher et al. (2021/0230548) in view of Tsai et al. (IDS ref, filed 02/13/2023; NPL; cite no. 8; 2015).
Daher et al. describes a method of engineering natural killer cells to express chimeric antigen receptors with immune checkpoint blockades.
Claims 1 and 41 are directed to a methods and systems that include: providing a first and second collections of NA sequences originated from the same NA source, whereby the first collection is an edited collection of NA sequences from said NA source to which a certain NA editing procedure was applied, and the second collection is a control (mock) collection of NA sequences of said NA source to which said NA editing procedure was not applied.
Daher et al. teaches nucleofecting the transduced NK cells with Cas9 alone, Cas9 control, or Cas9 pre-loaded with chemically synthesized crRNA:tracrRNA duplex targeting CISH exon 4 [0047]; and in this study, HEK293 cells that constitutively express the S pyogenes Cas9 nuclease (“HEK293-Cas9” cells) were the source of Cas9 [0308].
Claims 1 and 41 are further directed to providing target data indicative of expected editing sites of the NA editing procedure including at least one on-target and off-target site.
Daber et al. teaches total editing at the on- and off-target sites identified by GUIDE-Seq was measured using rhAmpSeq [0039]; and pie charts indicate the fractional percentage of the total unique, CRISPR-Cas9 specific read counts that are on-target and off-target [0039].
Claims 1 and 41 are further directed to applying multiplexed amplifications to the edited and control collections respectively, whereby the multiplexed amplifications of the edited and control collections are conducted with similar primer molecule types; and sequencing the multiplexed amplifications products/amplicons of said edited and control collections to obtain reads from each of the edited and control collections.
Daher et al. teaches to better quantify editing at off-target sites found using GUIDE-seq, multiplex PCR coupled to amplicon NGS was performed using rhPCR with blocked-cleavable primers [0309]; and PCR amplicons were sequenced on an Illumina MiSeq instrument [0309].
Claims 1 and 41 are further directed to processing the sequencing data by constructing a statistical model of occurrence of each type of adverse effect of the NA editing procedure; applying said statistical model to said sequencing data to statistically determine occurrence of said type of adverse effect by the NA editing procedure; and outputting data indicative of the of whether said each type of adverse effect occurs due to the NA editing procedure, intended to enable determination of safety of the NA editing procedure.
Daher et al. teaches data were analyzed using a custom-built pipeline [0309]; at each target, editing was calculated as the percentage of total reads containing an INDEL [0309]; noting higher frequencies off-target events with crRNA2 in FIGS. 12A-B [0281]; and that the identification of off-target INDELs, is crucial before this approach can be taken to the clinic; thus, GuideSeq and Rhampseq technologies were used to evaluate the off-target effects of the specific CISH guide RNAs used in the experiments [0281].
Claim 41 is further directed to an input adapted to receive the sequencing data, a memory for storing the sequencing data, a processor for processing the sequencing data, and an output for outputting the data.
Daher et al. teaches NGS library preparation, sequencing, and operation of the GUIDE-seq software was performed as previously described, except that Needleman-Wunch alignment was incorporated [0308]; and data were analyzed using a custom-built pipeline [0309].
Therefore, the method of Daher et al. inherently requires inputting data onto a computer that includes a memory and processor for storing and executing the software that enacts the method.
Claim 2 is directed to wherein said processing further comprising utilizing the statistical model to quantify the types of adverse effects affected by the NA editing procedure by determining rates of occurrence thereof by the NA editing procedure, and statistical confidence intervals for said rates.
Daher et al. teaches noting frequencies of off-target events with crRNA2 in FIGS. 12A-B [0281]; and presenting data within the claimed invention as mean ± 95% confidence interval [0310] and mean ± s.d [0310].
Claim 4 is directed to the method of claim 1, wherein said multiplexed amplifications of the edited and control collections are conducted utilizing respective multiplex PCR processes with a similar selected set of primer molecule types; and wherein the method includes providing the selected set of a plurality of primer molecule types including primer molecule types selected according to said target data, such that the plurality of primer types include at least, matched pairs of forward and reverse primer molecule types, suitable for amplification of said on-target and off- target sites in the edited and control NA collections.
Daher et al. teaches the PCR primers used for the amplification of the target locus were as follows [0290]: Exon 4 Forward Primer: CGTCTGGACTCCAACTGCTT (SEQ ID NO:7) [0291]; and Exon 4 Reverse Primer: GTACAAAGGGCTGCACCAGT (SEQ ID NO:8) [0292].
Claim 5 is directed to wherein said processing includes a preliminary preprocessing of the sequencing data for adjusting said reads of said multiplexed amplifications' products/amplicons from each of the edited and control collections by carrying out at least one of the following steps: trimming of sequencing adapters from said reads, merging pair-end reads, or filtering out low-quality reads.
Daher et al. teaches forward and reverse reads were merged into extended amplicons; and reads with any base quality score <10 were filtered out [0309].
Claim 44 is directed to the system of claims 41 that includes a sequencing utility capable of sequencing the multiplexed amplification products/amplicons of the first and second collections of NA sequences; and wherein said input is connectable to the sequencing utility for receiving said sequencing data therefrom.
Daher et al. teaches sequencing PCR amplicons on an Illumina MiSeq instrument [0309]; purified PCR products were sent for Sanger Sequencing at MD Anderson's core facility using both PCR primers, each sequence chromatogram was analyzed [0293]; and Sanger sequencing results show multiple peaks in the NT CISH KO and CAR CISH KO samples compared to their respective cas9 mock controls, which corresponds to CRISPR mediated events of NHEJ in fig. 7E [0034].
Therefore, the method inherently requires the use of a sequencer, connected to a computer by the transmission of results.
Daher et al. does not explicitly teach outputting data indicative of the of whether said each type of adverse effect occurs due to the NA editing procedure (claims 1 and 41); performing the entire method using both experimental and controls (claims 1 and 41); nor determining statistical confidence intervals for the adverse effect occurrence rates (claim 2).
Tsai et al. describes Guide-Seq, a software tool that enables genome-wide profiling of off-target cleavage by CRISPR-Cas nucleases.
Regarding claims 1 and 41, Tsai et al. teaches CRISPR-Cas RGNs are robust genome-editing reagents with a broad range of research and potential clinical applications (page 1, column 1); however, therapeutic use of RGNs in humans will require a comprehensive knowledge of their off-target effects to minimize the risk of deleterious outcomes (page 1, column 1); DNA cleavage by Streptococcus pyogenes Cas9 nuclease is directed by a programmable, guide RNA (page 1, column 1); GUIDE-seq experiments also revealed the existence of 30 unique, RGN-independent, DSB hotspots in the U2OS and HEK293 cells used for our studies (page 7, column 2); and we uncovered these when analyzing genomic DNA from control experiments with U2OS and HEK293 cells in which we transfected only the dsODN without RGN-encoding plasmids (page 7, column 2).
Tsai et al. further teaches the range of indel mutation frequencies ranged from 0.03% to 60.1% (page 5, column 2); notably, we observed positive linear correlations between GUIDE seq read counts and indel mutation frequencies for off-target sites of all five RGNs, as shown in Figs. 3b–f (page 5, column 2); thus, we conclude that GUIDE-seq read counts for a given site provide a quantitative measure of the cleavage efficiency of that sequence by an RGN (page 5, column 2).
Regarding claim 2, Tsai et al. shows the effects of wobble transition, non-wobble transition and transversion mismatches, estimated by linear regression analysis, with error bars representing 95% confidence intervals of the mean (page 4, fig. 3).
Therefore Daher et al. teaches a method of identifying and quantifying adverse effects of a nucleic acid procedure using Guide-Seq. Tsai et al. teaches the quantification of adverse effects provides a conclusion of whether the adverse effect occurred due to the RGNs, a crucial component to the nucleic editing procedure; and provides motivation for one of ordinary skill in the art to have certainty in the conclusion by using control data of which the editing procedure is not applied. As such it would be obvious to one of ordinary skill in the art to apply the methods of Tsai et al. to the method of Daher et al. with a reasonable expectation of success as both methods rely on the Guide-Seq software.
Furthermore, Daher et al. provides two methods of presenting analyzed data using techniques known in the art; and Tsai further teaches using confidence intervals to display adverse effect rates. As such, it would be obvious to one of ordinary skill in the art to optimize the occurrence rates using statistical confidence intervals with a reasonable expectation of success, as it is one of the finite number of techniques presented by Daher et al.
Claims 3, 6-7, and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Daher et al. (2021/0230548), in view of Tsai et al. (IDS ref, filed 02/13/2023; NPL; cite no. 8; 2015), as applied to claims 1, 4-5, 41, and 44 above, in view of Yin et al. (Cell Discovery; Vol. 5: 18; 2019).
Daher et al. in view of Tsai et al. teach a method of identifying and quantifying adverse effects, in the form of indels, and determining whether the adverse effects occur due to the nucleic acid editing process.
Claim 3 is directed to processing sequencing data for at least one category of adverse effects by: a. providing a template statistical model corresponding to the category of adverse effect; b. determining or assess counts of the experimental and mock control reads of amplicons associated with participating on-target and off-target sites of the class; c. determining or assessing counts of reads of amplicons in which a particular type of adverse effect is observed; applying the template statistical model to the counts; and obtaining the statistical determination of the occurrence of the particular type of adverse effect by the NA editing procedure.
Daher et al. teaches located at Fig. 12C, bar graphs shows INDEL formation at each targeted loci [0039]; pie charts indicate the fractional percentage of the total unique, CRISPR-Cas9 specific read counts that are on-target and off-target [0039]; data were analyzed using a custom-built pipeline [0309], statistical tests indicated were performed using Prism software [0310]; and at each target, editing was calculated as the percentage of total reads containing an INDEL within a 10 bp window of the cut site [0309].
Daher et al. does not explicitly teach classifying the adverse effects based on one or two participating sites associated with the adverse effect, where each class of adverse effect has two categories; Category 1 is drawn to indels, where the adverse effect only involves one site; and Category 2 is drawn to translocations, where the adverse effects involve two different sites (claim 3).
Yin et al. describes optimizing genome editing strategy.
Yin et al. teaches characterizing off-target sites as well as other abnormal chromosomal structures including small indels, large deletions, and genome-wide translocations of Cas9 (page 2, column 1).
Yin et al. further teaches analyzing the break-site and neighbor ±5 bp region for indels (page 9, column 2); also categorizing reads containing large deletions resulting from resection and rejoining in the break-site ±250 kb region as indels (I); and genome-wide translocation (T) was identified as before (page 9, column 2), in which translocation requires the joining of two separate double-stranded breaks (page 2, column 1).
Claim 6 is directed to the method of claim 3, adapted for determining at least one indel of said one or more of types of adverse effect of the NA editing procedure, which belong to the Category 1 of adverse effects that is associated with INDEL activity, and are associated with a respective site/locus of interest.
Daher et al. teaches at each target, editing was calculated as the percentage of total reads containing an INDEL within a 10 bp window of the cut site [0309].
Claim 7 is directed to wherein said processing of said sequencing data includes: a. providing reference data indicative of at least one reference NA sequence of the at least one respective site/locus of interest for which INDEL activity of said NA editing procedure is to be assessed; b. utilizing a 'collective' count match condition of said template statistical model, to identify matched reads of the multiplexed amplifications products/amplicons that match the reference NA sequence of the site/locus of interest in the reference data; and thereby obtaining for the site of interest, respective collections of matched reads, in the edited and control sequencing data.
Daher et al. teaches aligning reads against the GRCh38 genomic reference [0309]; assigning the reads to targets in the multiplex primer pool via bedtools tags v2.25 [0309]; performing Needleman-Wunch alignment [0309]; and employing the GUIDE-seq method for unbiased discovery of off-target editing events [0308].
Claim 9 is directed to the method of claim 7, wherein sizes of said respective collections represent said 'collective' counts of reads of amplicons which are associated with said at least one class of adverse effects involving the site observed in the sequencing data of the corresponding edited and control collections.
Yin et al. teaches performing reads mapping and translocation break point detection with the hg38 genome as reference (page 9, column 2); sensitively detecting CRISPR/Cas9 off-target sites through translocation capture and assessing their editing efficiency by quantifying imperfect Cas9-induced DSB repair products (page 2, column 1); characterizing off-target sites as well as other abnormal chromosomal structures including small indels, large deletions, and genome-wide translocations of Cas9 by PEM-seq (page 2, column 1); and displaying a scatter plot of Cas9:RAG1A off-target hotspots in 293T, HCT116, K562, and U2OS cells, in which the y Axis showed frequency of each hotspot per 100,000 editing events in the form of indels plus translocations (page 3, fig. 1d).
Claim 33 is directed to a method for determining effects of Nucleic Acid (NA) editing procedure that includes: receiving sequencing data resulting from sequencing of multiplexed amplifications products/amplicons of a first and second collections of NA sequences, such that the sequencing data is indicative of pluralities of reads, of the multiplexed amplifications' products/amplicons from each of the first and second collections, whereby: said first and second collections of NA sequences originate from the same NA source, such that the first collections of NA sequences is an edited collection of NA sequences from said NA source to which a certain NA editing procedure is applied, and the second collection is a control (mock) collection of NA sequences of said NA source to which said NA editing procedure is not applied; where the multiplexed amplifications of the edited and control collections are conducted with similar set of a plurality of primer molecule types; said set of a plurality of primer molecule types is designed to provide amplification of expected editing sites of the NA editing procedure, whereby the expected editing sites include at least one on-target site and one or more off target sites.
Daher et al. teaches nucleofecting the transduced NK cells with Cas9 alone, Cas9 control, or Cas9 pre-loaded with chemically synthesized crRNA:tracrRNA duplex targeting CISH exon 4 [0047]; and in this study, HEK293 cells that constitutively express the S pyogenes Cas9 nuclease (“HEK293-Cas9” cells) were the source of Cas9 [0308].
Daher et al. teaches to better quantify editing at off-target sites found using GUIDE-seq, multiplex PCR coupled to amplicon NGS was performed using rhPCR with blocked-cleavable primers [0309]; total editing at the on- and off-target sites identified by GUIDE-Seq was measured using rhAmpSeq, a multiplexed targeted enrichment approach for NGS [0039]; and PCR amplicons were sequenced on an Illumina MiSeq instrument [0309].
Claim 33 is further directed to processing said sequencing data for constructing, per each particular type of adverse effect of one or more types of possible adverse effects of said NA editing procedure, a statistical model of occurrence of said type of adverse effect by the NA editing procedure, and applying said statistical model to said sequencing data to statistically determine occurrence of said type of adverse effect by the NA editing procedure; and outputting data indicative of whether said each type of adverse effect occurs due to the NA editing procedure, to thereby enable determination of adverse effects of the NA editing procedure.
Daher et al. teaches data were analyzed using a custom-built pipeline [0309]; at each target, editing was calculated as the percentage of total reads containing an INDEL within a 10 bp window of the cut site [0309]; and the identification of off-target INDELs, is crucial before this approach can be taken to the clinic; thus, GuideSeq and Rhampseq technologies were used to evaluate the off-target effects of the specific CISH guide RNAs used in the experiments [0281]; and higher frequencies of off-target events were noted with crRNA2 in FIGS. 12A-B [0281].
Tsai et al. teaches the range of indel mutation frequencies ranged from 0.03% to 60.1% (page 5, column 2); notably, we observed positive linear correlations between GUIDE seq read counts and indel mutation frequencies for off-target sites of all five RGNs, as shown in Figs. 3b–f (page 5, column 2); thus, we conclude that GUIDE-seq read counts for a given site provide a quantitative measure of the cleavage efficiency of that sequence by an RGN (page 5, column 2).
Claim 33 is further directed to wherein said one or more types of adverse effect are classified to one or more classes of adverse effects, each class being characterized by the one or two involving sites , with which adverse effects of the class are involved, whereby each class belongs to one of two categories of adverse effects: Category 1 (INDELs): adverse effects involving one site; and Category 2 (TRANSLOCATIONs): adverse effects involving two sites.
Yin et al. teaches the break-site and neighbor ±5 bp region was analyzed for indels (page 9, column 2); reads containing large deletions resulting from resection and rejoining in the break-site ±250 kb region were also categorized as indels (I); and genome-wide translocation (T) was identified as before (page 9, column 2), in which translocation requires the joining of two separate double-stranded breaks (page 2, column 1).
Claim 33 is further directed to carrying out the following operations a. to d. for at least one of said two categories of adverse effects: a. providing a template statistical model corresponding to the category of said particular type of adverse effect; b. processing the sequencing data according to the class of said particular type of adverse effect to determine or assess respective 'collective' counts and of reads of amplicons which are associated with the involving sites of said class in the sequencing data of each of the edited and control collections; c. processing the sequencing data according to the particular type of adverse effect to determine or assess respective 'affected' counts and of reads of amplicons in which said particular type of adverse effect is observed; d. applying said template statistical model to the respective 'collective' counts and of reads of amplicons which are associated with the involving sites in the edited and control collections and to the respective 'affected' counts and of reads of amplicons in which said particular type of adverse effect is observed in the reads of amplicons which are associated with the edited and control collections; and thereby statistically determining whether said particular type of adverse effect is affected by the NA editing procedure.
Daher et al. teaches located at Fig. 12C, bar graphs shows INDEL formation at each targeted loci [0039]; pie charts indicate the fractional percentage of the total unique, CRISPR-Cas9 specific read counts that are on-target and off-target [0039]; data were analyzed using a custom-built pipeline [0309], statistical tests indicated were performed using Prism software [0310]; and at each target, editing was calculated as the percentage of total reads containing an INDEL within a 10 bp window of the cut site [0309].
Yin et al. further teaches LAM-HTGTS identifies CRISPR/Cas9 off-target sites via mapping genome-wide translocation with target cleavage site (page 2, column 1); and initiating with an 80-cycle linear amplification to generate multiple copies of the original DNA fragments, which makes it difficult to distinguish PCR duplicates from the original templates (page 2, column 2). Yin et al. further teaches to overcome this problem and fully assess CRISPR/Cas9, we developed PEM-seq (page 2, column 2).
Therefore Daher et al. in view of Tsai et al. teach a method of quantifying on-target, off-target, sites along with indel adverse effects by using PCR amplified sequences. Yin et al. teaches a method of further defining, quantifying, and analyzing the indels and translocations from an editing procedure that can be combined with the method of Daher et al., with each element merely performing the same function as they do separately. Furthermore Yin et al. provides a motivation for one of ordinary skill in the art to apply its method to a nucleic acid editing procedure that uses PCR amplified sequences in order to fully assess the effects of the editing procedure. As such, it would be obvious to one of ordinary skill in the art to combine the methods of Daher et al. in view of Tsai et al. with the method of Yin et al. with the results of the combination being predictable.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Daher et al. (2021/0230548), in view of Tsai et al. (IDS ref, filed 02/13/2023; NPL; cite no. 8; 2015), as applied to claims 1, 4-5, 41, and 44 previously, and in further view of Gottimukkala et al. (2019/0087539).
Daher et al. in view of Tsai et al. teach a method of identifying and quantifying adverse effects, in the form of indels, and determining whether the adverse effects occur due to the nucleic acid editing process, as described previously.
Claim 8 is directed to the method of claim 7, wherein the 'collective ' count match condition of the template statistical model of Category 1 of adverse effects is satisfied for a read to be match in case the prefix and suffix and regions of the read match prefix forward primer and suffix of the reverse primer sequences of the respective site of interest.
Daher et al. further teaches designing primers by an algorithm (IDT) for primer cross-comparison and selection based on compatibility with other primers in the multiplex; this amplification technology requires that the primer properly hybridize to a target site before amplification; and mismatches between target and primer prevent unblocking, thereby increasing specificity and eliminating primers dimers [0309].
Daher et al. does not teach considering a match as the prefix and suffix and regions of the read matching the prefix of forward primer and suffix of the reverse primer sequences (claim 8).
Gottimukkala et al. describes methods for detection of fusions using compressed molecular tagged nucleic acid sequence data.
Gottimukkala et al. teaches appending molecular tags to the 5′ primer and the 3′ primer, respectively, including a prefix tag appended to the 5′ primer and a suffix tag appended to the 3′ primer; individual polynucleotide molecules are labeled with unique molecular tags, amplified in a PCR reaction and sequenced generating fusion amplicons [0027]; and the use of barcodes allows for the detection and analysis of multiple samples, sources, tissues or populations of nucleic acid molecules per multiplex reaction [0023].
Gottimukkala et al. teaches a tag trimming method that may require that the sequence of bases in the tag portion of the sequence read match the known bases [0035]; and in some embodiments, using the tag trimming method to detect and correct sequencing error in the tag, such as insertions and deletions [0035].
Therefore Gottimukkala et al. provides a method matching tags to read sequences in order to identify indels that can be combined with the method of using primers suitable for detecting adverse effects in sequenced, multiplexed amplifications, as in Daher et al. As such, it would be obvious to one of ordinary skill in the art to combine the methods, with each element merely performing the same function as they do separately, with an expectation of predictable results in the form of the identification of indels.
Claims 10-12 are rejected under 35 U.S.C. 103 as being unpatentable over Daher et al. (2021/0230548) in view of Tsai et al. (IDS ref, filed 02/13/2023; NPL; cite no. 8; 2015) and Yin et al. (Cell Discovery; Vol. 5: 18; 2019), as applied to claims 3, 6-7, and 9 previously, and in further view of Fernandez et al. (2020/0190513).
Daher et al. in view of Tsai et al. and Yin et al. teach a method of identifying and quantifying adverse effects, in the form of indels and translocations, and determining whether the adverse effects occur due to the nucleic acid editing process, as described previously.
Claim 10 is directed to the method of claim 7, wherein said processing of said sequencing data by includes segregating the collections of reads matching the interest site to form two sub-collections of reads presenting certain type of indel from the sequencing data of the experimental and control collections.
Yin et al. teaches separating the composition of indels of Cas9:RAG1A libraries within ±20 bp around cleavage site to include: deletions, insertions, and deletions that also involved insertions (page 4, fig. 2e).
Daher et al. in view of Yin et al. do not teach characterizing each indel type by at least one of the following: a size/length (t) of bases introduced-to or deleted-from the matched read relative to the reference NA sequence of the site/locus of interest; or a position (i) along the site of interest at which said bases are introduced- to or deleted-from; and wherein segregating includes: (a) aligning the matched reads in the collections to the reference NA sequence of the site of interest; (b) identifying gaps in the aligned matched reads whereby each gap representing an indel; at least one of a position i and a length t of the gap represents a type T of said indel; and (c) respectively aggregating the aligned matched reads of the collections, to form the corresponding sub-collections of reads, respectively presenting observations of said certain type T of indel, in the aligned matched reads of the sequencing data of the corresponding edited and control collections (claim 10).
Fernandez et al. describes methods and systems for analyzing guide RNA molecules.
Fernandez et al. teaches the first step for data analysis involved aligning each sequencing read to a reference sequence [0232]; this step was followed by classifying and quantifying any bases from the read that did not align perfectly to the reference such as any bases that are considered mismatches or indels/gaps by the alignment algorithm [0232].
Fernandez et al. teaches the frequency with which individual bases and length variances occur at each position from the 5′ end of the molecule between a given read and the reference sequence was performed using the Needleman-Wunsch algorithm, although other global algorithms can be similarly used [0234]; if the alignment contained a gap character (or indel) in the reference sequence, it was counted as an inserted base in the read occurring at the position where the gap occurred [0234]; and if the gap character occurred in the read sequence, it was counted as a deletion in the gRNA sequence at the corresponding alignment position in the reference sequence [0234].
Fernandez et al. further teaches this assay showed a region of relatively high frequency of mismatches/indels at linkage site located at position 34 [0244].
Claim 10 is further directed to where aggregating includes matching the identified gaps in the aligned matched reads with properties of a gap representing said certain type T of indel based on an 'affected' count match condition of the template statistical model of Category 1 of adverse effects, whereby said 'affected' count match condition of the template statistical model of Category 1 is satisfied upon fulfillment of a predetermined set one or more of the following conditions: i) the position i of an identified gap in an aligned matched read is similar to a position i of the gap in said type T of indel; ii) a size t of the gap of an identified gap in an aligned matched read is similar to a size t of the gap in said type T of indel; iii) a nucleotide base sequence in the gap of an identified gap in an aligned matched read has a degree of similarity with a nucleotide base sequence of said type T of indel above a certain threshold.
Fernandez et al. teaches at each position in the reference sequence, determining the identity of the base from the read sequence aligned to that position; using it to generate a frequency table describing how often each base occurred at a given position [0234]; and finding indel/substitution profiles, based on the aligning positions [0234, 0246].
Claim 11 is directed to the method of claim 10, wherein said indel type T is characterized by both said size/length t of bases and said position i.
Fernandez et al. teaches quantifying any bases from the read that did not align perfectly to the reference such as any bases that are considered mismatches or indels/gaps by the alignment algorithm [0232]; and counting inserted/deleted bases in the read occurring at the position where the gap occurred [0234].
Claim 12 is directed to the method of claim 10 wherein sizes of said respective sub-collections present affected counts of reads of amplicons, in which said particular type of adverse effect is observed.
Fernandez et al. teaches methods and systems described herein can be used to count [0234] and characterize variants such as truncations, internal insertions or deletions, relative to a reference guide RNA sequence corresponding, for example, to a desired gRNA synthesis product [0077]; using a product nucleic acid as a template for second-strand synthesis and/or PCR amplification, such as for subsequent sequencing of the amplicons [0180]; and further subjecting a product nucleic acid to nucleic acid amplification conditions, which may include the addition of forward and reverse primers configured to amplify all or a desired portion of the product nucleic acid [0180].
Therefore Fernandez et al. teaches a method of counting and classifying indels using their position and size, based on a Needleman-Wunch alignment to a reference sequence. Daher et al. also teaches incorporating a Needleman-Wunch alignment into its off-target identification pipeline [0308]. Therefore, the method of Fernandez et al. is applicable to the method of Daher et al. As such, it would be obvious to one of ordinary skill in the art to combine the methods of Fernandez et al. to the method of Daher et al. with each element merely performing the same function as it does separately with a reasonable expectation of success.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Daher et al. (2021/0230548), in view of Tsai et al. (IDS ref, filed 02/13/2023; NPL; cite no. 8; 2015) and Yin et al. (Cell Discovery; Vol. 5: 18; 2019), as applied to claims 3, 6-7, and 9 previously, and in further view of Chen et al. (Genome Research; Vol. 17; 2007).
Daher et al. in view of Tsai et al. and Yin et al. teach a method of identifying and quantifying adverse effects, in the form of indels and translocations, and determining whether the adverse effects occur due to the nucleic acid editing process, as described previously.
Daher et al. does not teach the template statistical model provided for the indel activity of said NA editing procedure includes a statistical classifier with a maximum a postereior (MAP) estimator (claim 13).
Chen et al. describes PolyScan, an automatic indel and SNP detection approach to the analysis of human resequencing data.
Chen et al. teaches while significant advancements have been made for SNP discovery and detection in PCR-amplified genomic DNA samples, progress in indel detection and annotation has been rather limited (age 3, column 1); we have addressed this problem with a new algorithm and software implementation called PolyScan (page 3, column 1); and in particular, PolyScan is intended to provide de novo heterozygous indel detection functionality with high sensitivity and improved specificity that is adjustable, according to different needs (page 3, column 1).
Chen et al. teaches a single indel hypothesis is predicted from each pool of indel signatures through a maximum a posteriori (MAP) procedure (page 7, column 2); and the Bayesian probabilistic approach enables integration of various kinds of evidence into a single confidence score through an elegant probabilistic framework (page 5, column 2).
Therefore Chen et al. provides sufficient motivation for one of ordinary skill in the art to apply the maximum a posteriori approach to an indel detection system within a framework that uses PCR-amplified genomic sequences. As such, it would be obvious to one of ordinary skill in the art to apply the technique to the method of Daher et al. in view of Tsai et al. and Yin et al. with a reasonable expectation of success.
Claims 34 is rejected under 35 U.S.C. 103 as being unpatentable over Daher et al. (2021/0230548) in view of Tsai et al. (IDS ref, filed 02/13/2023; NPL; cite no. 8; 2015), and in further view of Frock et al. (IDS ref, filed 02/13/2023; NPL; cite no. 18; 2015).
Claim 34 is directed to a method for determining translocation adverse effects of Nucleic Acid (NA) editing procedure that includes: receiving sequencing data resulting from sequencing of multiplexed amplifications products/amplicons of a first and second collections of NA sequences, such that the sequencing data is indicative of pluralities of reads, of the multiplexed amplifications' products/amplicons from each of the first and second collections, whereby: said first and second collections of NA sequences originate from the same NA source, such that the first collections of NA sequences is an edited collection of NA sequences from said NA source to which a certain NA editing procedure is applied, and the second collection is a control (mock) collection of NA sequences of said NA source to which said NA editing procedure is not applied, wherein the multiplexed amplifications of the edited and control collections are conducted with similar set of a plurality of primer molecule types; said set of a plurality of primer molecule types is designed to provide amplification of expected editing sites of the NA editing procedure, whereby the expected editing sites include at least one on- target site and one or more off-target sites.
Daher et al. teaches nucleofecting the transduced NK cells with Cas9 alone, Cas9 control, or Cas9 pre-loaded with chemically synthesized crRNA:tracrRNA duplex targeting CISH exon 4 [0047]; and in this study, HEK293 cells that constitutively express the S pyogenes Cas9 nuclease (“HEK293-Cas9” cells) were the source of Cas9 [0308].
Daher et al. teaches to better quantify editing at off-target sites found using GUIDE-seq, multiplex PCR coupled to amplicon NGS was performed using rhPCR with blocked-cleavable primers [0309]; Total editing at the on- and off-target sites identified by GUIDE-Seq was measured using rhAmpSeq, a multiplexed targeted enrichment approach for NGS [0039]; and PCR amplicons were sequenced on an Illumina MiSeq instrument [0309].
Claim 34 is further directed to said set of the plurality of primer molecule types including at least match pairs of forward and reverse primer molecule types suitable for amplification of said on-target and off-target sites in the edited and control NA collections;
Daher et al. teaches the PCR primers used for the amplification of the target locus were as follows [0290]: Exon 4 Forward Primer: CGTCTGGACTCCAACTGCTT (SEQ ID NO:7) [0291]; and Exon 4 Reverse Primer: GTACAAAGGGCTGCACCAGT (SEQ ID NO:8) [0292].
Claim 34 is further directed to processing the sequencing data to identify at least one type or species of translocation adverse effect involving two different sites of the expected on-target and off-target sites of said NA editing procedure, whereby said processing includes: counting reads of pluralities of said reads of the edited and control collections which satisfy a single site partial match condition with respect to at least one of the two different sites and thereby assessing respective 'collective' counts of reads of the edit and control collection in which at least one of the two different sites is involved; counting reads of the pluralities of said reads of the edited and control collections which satisfy a double site match condition, associated with said type or species of the translocation adverse effect, to determine respective 'affected' counts of reads of the edit and control collection satisfying said double site partial match condition; and statistically determining whether the 'affected' count in the edit collection is observed due to said at least one type or species of translocation adverse effect occurring in the NA editing procedure, by applying a selected statistical distribution model to said 'collective' and 'affected' counts.
Frock et al. describes a linear amplification–mediated modification of a HTGTS method that robustly detects DNA double-stranded breaks (DSBs).
Frock et al. teaches chromosomal translocations can arise by fusion of the ends of two DNA DSBs lying on heterologous chromosomes or on separated regions of a homologous chromosome (page 1, column 2); off-target sites were defined as hotspots that contained genomic sequence differing from the on-target sequence by less than or equal to one-half the targeted sequence length (page 9, column 2); for each set of HTGTS libraries from a particular break-site or under particular conditions, using modified Circos plots to visualize overall junction patterns and key features (page 2, column 1), where in these plots, translocation hotspots, bioinformatically identified in an unbiased fashion (page 2, column 1) as focally enriched HTGTS junction clusters, are indicated by lines that connect the bait-site to a given hotspot (page 2, column 2).
Frock et al. further teaches HTGTS libraries were also generated using a modified protocol, which involved linear amplification-mediated (LAM)-PCR (page 9, column 1); LAM-PCR–based HTGTS is a versatile assay that goes beyond simply detecting nuclease off-target sites by also revealing collateral damage in the form of recurrent translocations between on-target DSBs and off-target DSBs, as well as translocations between different off-target DSBs (page 6, column 2).
Tsai et al. further teaches translocations, large deletions and inversions were identified using a custom algorithm based on split BWA-MEM alignments (page 12, column 2); chromosomal translocations can result from joining of on- and off-target, RGN-induced cleavage events (page 1, column 1); our method also identified RGN-independent, DNA breakpoint hotspots that can participate together with RGN-induced DSBs in higher-order genomic alterations such as translocations (page 2, column 1); and using statistical analysis to determine whether the large-scale structural alterations, such as translocations were induced by RGNs (page 6, fig 5) (page 1, column 1).
Tsai et al. further teaches GUIDE-seq experiments also revealed the existence of 30 unique, RGN-independent, DSB hotspots in the U2OS and HEK293 cells used for our studies (page 7, column 2); and we uncovered these when analyzing genomic DNA from control experiments with U2OS and HEK293 cells in which we transfected only the dsODN without RGN-encoding plasmids (page 7, column 2).
Daher et al. further teaches in some aspects, the double-stranded or single-stranded breaks undergo repair via a cellular repair process [0174] that can be error-prone and result in disruption of the gene [0174] such as inducing a deletion, mutation, and/or insertion [0174]; and in some aspects, the presence of an insertion, deletion, translocation, frameshift mutation, and/or a premature stop codon results in disruption of the expression, activity, and/or function of the gene [0174].
Therefore Frock et al. teaches using a method with amplified primers and statistical analysis to identify translocations from off and on target events that can be applied versatilely. Daher et al. provides motivation to explore translocations via the double-stranded breaks to explore gene disruptions related to the nucleic acid editing process; and Tsai et al. teaches using statistical analysis, within Guide-Seq, applicable to Daher et al., to determine whether the 'affected' count is observed due to a translocation adverse effect occurring within the editing procedure and confirm counts based on comparing experimental measurements to that of a control. As such, it would be would be obvious to one of ordinary skill in the art to combine the methods with each element merely performing the same function as they do separately, yielding predictable results in the form of the identification of translocations via two double stranded break sites.
Claims 42 is rejected under 35 U.S.C. 103 as being unpatentable over Daher et al. (2021/0230548), in view of Tsai et al. (IDS ref, filed 02/13/2023; NPL; cite no. 8; 2015), as applied to claim 41 previously, and of Frock et al. (IDS ref, filed 02/13/2023; NPL; cite no. 18; 2015) and in further view of Chapuy et al. (US 12/571,049).
Claim 42 is directed to the system of claim 41, wherein said processor is adapted to process said sequencing data for said type of adverse effect by carrying out the following: a. retrieving from the reference data stored in said memory or section thereof, reference NA sequences of the one or two sites participating in said type of adverse effect; b. obtaining from said memory or section thereof, a template statistical model corresponding to said type of adverse effect.
Daher et al. teaches aligning reads against the GRCh38 genomic reference [0309]; assigning the reads to targets in the multiplex primer pool via bedtools tags v2.25 [0309]; performing Needleman-Wunch alignment [0309]; and employing the GUIDE-seq method for unbiased discovery of off-target editing events [0308].
Daher et al. does not explicitly teach c. constructing a statistical model for said type of adverse effect based on said template statistical model and the reference data, by carrying out the following: or processing said sequencing data of the first and second collection to determine or assess respective 'collective' counts reads of amplicons which are associated with the one or two sites participating in said particular type of adverse effect, by matching said amplicons to the reference NA sequences of said one or two sites according to a 'collective' count match condition designated by said template statistical model, and respectively counting the reads of amplicons of said first and second collections, which satisfy said 'collective' count match condition, to thereby determine or assess the respective 'collective' counts; and processing said sequencing data of the first and second collection to determine or assess respective 'affected' counts and of reads of affected amplicons in which said particular type of adverse effect is observed, by matching said amplicons to the reference NA sequences of said one or two sites according to an 'affected' count match condition designated by said template statistical model, and respectively counting the reads of amplicons of said first and second collections, which satisfy said 'affected' count match condition, to thereby determine or assess the respective 'affected' counts (claim 42).
Frock et al. teaches mapping reads to the hg19 reference genome using Bowtie2 with the top 50 alignments reported that had an alignment score above 50, representing a perfect 25-nt local alignment (page 9, column 2); defining off-target sites as hotspots that contained genomic sequence differing from the on-target sequence by less than or equal to one-half the targeted sequence length (page 9, column 2); and for each set of HTGTS libraries from a particular break-site or under particular conditions, using modified Circos plots to visualize overall junction patterns and key features (page 2, column 1), where in these plots, translocation hotspots, bioinformatically identified in an unbiased fashion (page 2, column 1) as focally enriched HTGTS junction clusters, are indicated by lines that connect the bait-site to a given hotspot (page 2, column 2).
Frock et al. further teaches HTGTS libraries were also generated using a modified protocol, which involved linear amplification-mediated (LAM)-PCR (page 9, column 1); LAM-PCR–based HTGTS is a versatile assay that goes beyond simply detecting nuclease off-target sites by also revealing collateral damage in the form of recurrent translocations between on-target DSBs and off-target DSBs, as well as translocations between different off-target DSBs (page 6, column 2).
Claim 42 is further directed to statistically determining whether said particular type of adverse effect occurs due to the NA editing procedure by utilizing a statistical classifier of the template statistical model; and classifying the occurrence of said particular type of adverse effect according to said statistical classifier based on said 'collective' counts and said 'affected' counts.
Frock et al. teaches HTGTS confirmed that off-target activity of the RAG1A sgRNA was dramatically suppressed genome-wide by the Cas9 D10 nickase approach; but also revealed that this approach does not suppress translocations involving DSBs on both bait-site chromosomes (page 7, column 1).
Frock et al. further teaches chromosomal translocations can arise by fusion of the ends of two DNA DSBs lying on heterologous chromosomes or on separated regions of a homologous chromosome; The HTGTS and translocation-capture sequencing approaches were developed to identify translocations of yeast I-SceI meganuclease-generated 'bait' DSBs at target sites introduced into the genome of mouse cells to other 'prey' cellular DSBs genome-wide; and these methods also identified various classes of endogenous DSBs in primary and transformed B-lymphocyte lineage cells (page 1, column 2).
Therefore Frock et al. teaches determining whether the adverse effects occurred due to the nucleic acid, Cas9 D10 nickase, editing approach; and further classifying the adverse effects, based on the translocation capture-method that uses “collected” and “affected” counts.
Daher et al. in view of Frock et al. do not teach utilizing a statistical classifier of the template statistical model.
Chapuy et al. describes a diffuse large B-cell lymphoma (DLBCL) classifier that has identified at least five distinct classes of DLBCL cancer, each of which possesses distinct pathogenic mechanisms and outcomes (abstract).
Chapuy et al. teaches the methods and compositions described herein relate to identification of a new and clinically useful classifier for DLBCL (page 93, column 2); in certain aspects, the instant disclosure provides methods that involve and/or allow for assessment of the presence or absence of one or more sequence variants and/or mutations in a test subject, tissue, cell or sample, as compared to a corresponding reference sequence (page 93, column 2); and for the instantly exemplified classification, up to five alteration types were measured and can be used for the classifier, such as the prognostic classifier exemplified herein: 1.) Mutations, such as single nucleotide variants and/or InDels 2.) Copy number alterations, such as CN gain, amplifications, CN losses, Deletions 3.) Structural variants, such as chromosomal translocations, inversions, tandem duplications, etc. 4.) Genome doublings 5.) Mutational Signatures (page 93, column 2).
Therefore Chapuy et al. teaches a statistical classifier technique that uses adverse effects such as indels and translocations, and can be applied to the method designed for B-lymphocyte lineage cells. As such, it would be obvious to one of ordinary skill in the art that applying the known technique of Chapuy et al. to the technique of Frock et al. would yield predictable results and result in an improved system that is clinically useful.
Claim 43 is rejected under 35 U.S.C. 103 as being unpatentable over Daher et al. (2021/0230548), in view of Tsai et al. (IDS ref, filed 02/13/2023; NPL; cite no. 8; 2015), as applied to claim 41 previously, and in further view of Lunter et al. (Genome Research; Vol. 18; 2008).
Daher et al. teaches a method of identifying and quantifying adverse effects, in the form of indels, of a nucleic acid editing process, as described previously.
Claim 43 is directed to the system of claim 41, configured and operable for determining said probability of occurrence for adverse effects of one or both of the following categories: - Category 1 (INDELs): adverse effects involving one site; and Category 2(TRANSLOCATIONs): adverse effects involving two sites.
Daher et al. teaches incorporating a Needleman-Wunch alignment into its off-target identification pipeline [0308], though optimal alignment may be determined with the use of any suitable algorithm for aligning sequences [0202].
Daher et al. does not teach determining the probability of occurrence of indels or translocations.
Lunter et al. describes assessing and improving genomic sequence alignment.
Lunter et al. teaches parameters of the model include indel probability per aligned site (page 7, fig. 5); such probabilistic treatment is essential, both to improve alignment quality and to quantify the remaining uncertainty (page 2, column 1); and this nonheuristic algorithm for DNA sequence alignment shows robust improvements over the classic Needleman–Wunsch algorithm (page 2, column 1).
Therefore Daher et al. teaches aligning sequences and determining indels by a method based of the Needleman-Wunsch alignment algorithm, and further teaches the algorithm may be substituted with another algorithm capable of performing the task. Lunter et al. provides sufficient motivation for one of ordinary skill in the art to substitute the Needleman-Wunsch algorithm, with that of which provided in Lunter et al., that incorporates the probabilities of indel occurrences. As such, one of ordinary skill in the art could substitute the algorithms with a reasonable expectation of success and improvement to the system.
Conclusion
No claims are currently allowed.
Correspondence
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/M.K.T./Examiner, Art Unit 1687
/Karlheinz R. Skowronek/Supervisory Patent Examiner, Art Unit 1687
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