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 .
Priority
This application 18/697,196 filed on 03/29/2024 is a national phase application under 35
U.S.C. § 371 that claims priority to International Application No. PCT/JP2022/036238 field on
09/28/2022, and claims priority of foreign application JP 2021-160065 filed on 09/29/2021.
A certified copy of foreign application JP 2021-160065 filed on 09/29/2021 has been
submitted of the record by Applicants on 03/29/2022. Receipt is acknowledged of certified
copies of papers required by 37 CFR 1.55.
No English translation of foreign application JP 2021-160065 filed on 09/29/2021 has
been provided. The priority date of claim set filed on 03/29/2024 is determined to be 09/28/2022,
the filing date of PCT/JP2022/036238.
Should applicant desire to obtain the benefit of foreign priority under 35 U.S.C. 119(a)-
(d) prior to declaration of an interference, a certified English translation of the foreign
application must be submitted in reply to this action. 37 CFR 41.154(b) and 41.202(e).
Failure to provide a certified translation may result in no benefit being accorded for the
non-English application.
Status of Claims
Claims 1-7 are pending.
Claims 1-7 are currently under examination.
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 1-7 are 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 1 recites “measuring a cell concentration in a sample” by “measuring the number of copies of a specific gene”, creating a calibration curve relating a normalized copy number value to a known cell concentration”, and “determining a cell concentration… from the normalized value.” The claim therefore requires that a measured number of gene copies be converted into a number of cells. That conversion is stated in step (4) of claim 1 where the “specific gene” is present at a known and a consistent number of copies per cell across both the standard samples and the unknown sample. Claim 1 places no limitation on the “specific gene” requiring a known or constant per cell copy number, and does not otherwise define the relationship by which the recited “number of copies of a specific gene” yields the recited “cell concentration” based on an unspecified “calibration curve” stated in step (2) of claim 1.
Because the recited determination is operative for some genes (e.g., an endogenous genomic gene present at a fixed copy number in every cell of the relevant lineage) but not for others (e.g., a sequence present at a variable copy number per cell, or one not uniformly present in every cell, such that a calibration relationship established from the standards does not transfer to unknown sample), one of ordinary skill could not ascertain with reasonable certainty which genes fall within the scope of “specific gene” for purposes of the claimed cell-concentration determination. The metes and bounds of the claim are accordingly unclear. See Nautilus, Inc. v. Biosig Instruments, Inc., 572 U.S. 898 (2014).
Claims 2-7 depend from claim 1.
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.
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, 3, 4, and 5 are rejected under 35 U.S.C. 103 as being unpatentable over Funakoshi et al. (2017 Sci. Rep. 7:13202) in view of Albayrak et al. (2016 Mol. Cell 61:914-924) and O’Connell et al (2017 Lab. Med. 48(4):332-338).
Regarding claim 1, claim 1 recites, “A method for measuring a cell concentration in a sample, the method comprising the following steps of:
(1) measuring the number of copies of a specific gene and a gene
of an external standard in a plurality of standard samples each having
a known cell concentration by using digital PCR (dPCR) ;
(2) normalizing the measured value of the specific gene measured
in the step (1) using the measured value of the external standard and
creating a calibration curve on the basis of the normalized value and
the known cell concentration;
(3) measuring the number of copies of the same specific gene and
gene of the external standard in a sample having an unknown cell
concentration by using dPCR; and
(4) normalizing the measured value of the specific gene measured
in the step (3) using the measured value of the external standard and
determining a cell concentration using the calibration curve created in
the step (2) from the normalized value.”
With respect to step (1), Funakoshi et al. teaches measuring the copy number of a human-specific multi-copy genomic element – Alu, a primate specific short interspersed element (SINE) present at more than one million copier per human genome, across a plurality of serially diluted human genome calibrators, which reads on measuring the number of copies of a “specific gene” in a plurality of standard samples (Abstract; p. 10, qPCR section; p. 6, 4th para).
Funakoshi et al. does not explicitly teach the following limitations of claim 1: (i) performing the copy number measurement by digital PCR (dPCR), instead employs real-time qPCR; (ii) measuring the number of copies of a gene of an external standard and normalizing the specific gene measurement using the external standard measurement, Funakoshi et al. does not employ an exogeneous spike in or any external standard recovery normalization; and (iii) constructing the calibration curve from a plurality of standard samples each having a known cell concentration on a cell number axis, Funakoshi et al. calibrates against human DNA amount (which it then converts to cell number) rather than against standards of directly known cell number.
Albayrak et al. teaches the dPCR readout (i) and the known cell number calibration (iii). As to (i), Albayrak performs absolute molecular counting by droplet digital PCR (ddPCR): the DNA to quantified is partitioned by limiting dilution into approximately 20,000 nanoliter-sized droplets (p. 916, col. 1), each containing zero or one DNA molecule; the molecules are amplified by PCR; and amplicon-bearing droplets are counted on a droplet reader to yield an absolute count, with a reported Poisson error of approximately 6-8% CV (p. 917, col. 1, Section: Direct and digital quantification of protein copy numbers in single cells) and a separately constructed daily calibration curve to bound day to day variation (p. 922, col. 1, Section: Protein quantification from mammalian cells). As to (iii), Albayrak et al. constructs calibration curves from standards containing known numbers of FACS-sorted cells (1, 2, 5, 10, and 100 cells per well) and regress the digital readout against the known per well cell number (Fig. 3.; p. 917, col. 1, Section: Direct and digital quantification of protein copy numbers in single cells).
The analytes Albayrak et al. itself quantifies are not copies of an endogenous genomic gene measured at the DNA level. The molecules Albayrak et al. partitions and counts are (a) protein-derived double stranded DNA amplicons generated by a digital proximity-ligation assay (digital PLA) and (b) reverse transcribed mRNA (cDNA) generated by RT-ddPCR. Albayrak et al. does not measure the copy number of a genomic “specific gene” at the DNA level. Accordingly, Albayrak et al. is relied upon not for the identity of the analyte, but for two target-independent teachings: first, the dPCR absolute counting readout itself, which operates on whatever DNA molecules are partitioned into the droplets and is independent of the identity or origin of that DNA; and second, the technique of constructing a calibration curve by regressing a digital readout against standards of known cell number. The genomic “specific gene” measured at the DNA level, Alu, is supplied by Funakoshi et al., which performs Alu copy number measurement on extracted genomic DNA. The combination thus applies Albayrak’s et al. dPCR readout and known cell number calibration to Funakoshi’s et al. genomic Alu target.
O’Connell et al. teaches the gene of an external standard and the normalization step (ii). O’Connell et al. spikes a fixed copy number of an exogenous oligonucleotide fragment (GFP605) into each specimen prior to nucleic acid extraction (p. 333, col. 2, Section: exogenous Spike in Oligonucleotide fragment; p. 333, col. 1, Section: experimental design, first para), measures the spike-in’s recovery downstream by PCR (Abstract, methods), and divides each specimen’s target signal by its co-extracted spike in signal before regression in order to correct specimen to specimen variation in extraction/recovery efficiency (abstract; p. 332, col. 2, last para). O’Connell reports that DNA extraction efficiency varied from 22.9% to 88.1% across plasma specimens (CV 28.9%) and that the spike in normalizes this variation (Abstract; p. 335, col. 2, last para; p. 336, col. 2, first para). O’Connell’s et al. exogenous spike-in corresponds to the recited “gene of an external standard”, and its signal ratio correction corresponds to the recited normalization of the specific gene measurement using the external standard measurement.
With respect to step (2) of claim 1, Albayrak et al. teaches constructing a calibration curve directly from standards each containing a known number of cells, regressing the digital readout against the FACS-sorted cell numbers on a per sorted cell basis (Fig 3B, 3D; p. 917, col. 1; p. 922, col. 2; Fig. 4A). O’Connell et al. teaches the normalization step, in which each standard’s specific gene signal is divided by its co-extracted external standard signal before regression (p. 333, col. 2; p. 335, col. 1). Funakoshi et al. teaches the human specific multi-copy genomic element analyte (Alu) with an established linear range (R^2.0.999) (p. 6; Abstract).
With respect to step (3) of claim 1, Funakoshi et al. teaches measuring Alu, the same specific gene, in a sample of unknown human cell content (Abstract; p. 7). O’Connell et al. teaches measuring the same exogenous external standard spike in that unknown specimen, the spike in having been added to the specimen prior to extraction (p. 333; p. 335 col. 2).
With respect to step (4) of claim 1, O’Connell et al. teaches dividing the unknown specimen’s specific gene signal by its co-extracted external standard signal to yield the recovery normalized value (p. 335, col. 1; p. 333). Albayrak et al. teaches determining the quantity of interest from the normalized digital readout by reference to the calibration curve constructed per limitation (b) (p. 916, col. 1; Fig. 2; p. 922, col. 1; Fig. 3). Funakoshi et al. teaches that an analyte to cell calibration curve is used to determine human cell number from the measured signal (p. 7 para 1; p. 10, para 10; Fig. 5).
The combined teachings of Funakoshi et al., Albayrak et al., and O’Connell et al. render claim 1 prima facie obvious. Funakoshi’s et al. Alu-based human-cell quantification scheme, Albayrak’s digital PCR absolute counting readout, and O’Connell’s et al. exogenous spike in recovery normalization control each occupy a recognized position in this art, and their combination in the manner contemplated by claim1 reflects nothing more than the predictable composition of recognized techniques to quantify cells by digital PCR against a calibration curve with external standard recovery normalization.
It would have been obvious to combine prior art elements according to known methods to yield predictable results. A POSITA applying Funakoshi’s Alu based cell quantification method would have been motivated (i) to move the readout to digital PCR to obtain absolute molecular counts with reduced dependence on amplification efficiency, improved precision, and superior day to day reproducibility; and (ii) to add O’Connell’s exogeneous spike in external standard to correct for the very error source Funakoshi et al. expressly identifies “loss of genomic DNA during our genome extraction procedure”. O’Connell’s affirmative demonstration that DNA recovery varies from 22.9% to 88.9% across plasma specimens, paired with its express recommendation to use a spike-in to normalize that variation, supplies particularized motivation to combine with a predictable result. Further, where the measurement objective is cell concentration rather than DNA mass, a POSITA would have been motivated to calibrate against samples of known cell number, as Albayrak et al. teaches by FACS-sorting 1 to 100 cells per well, because the calibration axis should correspond to the measurand. The combination is supported by MPEP 2143(I), rationales (B) (ddPCR for qPCR), (C) (applying O’Connell’s et al recovery normalizing external standard and Albayrak’s et al. ddPCR counting to Funakoshi’s et al. cell quantification scheme), and (G) (Funakoshi’s et al. acknowledgement of extraction loss combined with O’Connell’s et al. explicit recommendation of spike-in). See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 416 (2007).
A person of ordinary skill in the art would have had reasonable expectation of success in combining the cited references in the manner contemplated by claim 1. Funakoshi’s et al. Alu calibration achieves R^2 of at least 0.996 over seven orders of magnitude; Albayrak’s et al. ddPCR with daily calibration achieves Poisson error of approximately 6-8% CV; and O’Connell’s spike-in successfully normalizes recovery variability across more than 8- plasma specimens. A POSITA would therefore have had a reasonable expectation that the combined techniques would yield a working method for quantifying cells by dPCR with external standard recovery normalization against a calibration curve.
Regarding claim 3, claim 3 recites, “The method according to claim 1, wherein a matrix of each of the standard samples used for creating a calibration curve is different from a matrix of the sample used for measuring a cell concentration.” The combined method of claim 1 incorporates an exogenous external standard (O’Connell) specifically to normalize specimen by specimen DNA recovery and thereby to remove matrix dependent variability in the measured signal (p. 332, Results, col. 2; p. 336). Because the recovery normalizing external standard removed the very matrix/recovery dependence that would otherwise compel matched standard and sample matrices, it would have been obvious to a POSITA to construct the cell-concentration calibration curve from standard samples in one matrix and to measure unknowns in a different matrix, i.e., to operate with the matrix of the standard samples differing from the matrix of the unknown. O’Connell’s et al. demonstration that an exogeneous spike-in corrects recovery variation across differing sample compositions (DNA extraction efficiencies of 22.9%-88.1%, CV 28.9%). The motivation to combine and reasonable expectation of success are the same as fully articulated above for claim 1.
Regarding claim 4, claim 4 recites, “The method according to claim 1, wherein accuracy of the value of the cell concentration determined in the step (4) is within ±35%.” O’Connell et al. demonstrates that recovery varies from 22.9% to 88.1% across specimens (CV 28.9%) and that the spike-in normalizes this systematic under-recovery on a specimen by specimen basis (Abstract; p. 333, col. 1; p. 335; p. 226, col. 1). The motivation to combine and reasonable expectation of success are the same as fully articulated above for claim 1.
Regarding claim 5, claim 5 recites, “The method according to claim 1, wherein precision of the value of the cell concentration determined in the step (4) is within ±35%.” Albayrak et al. reports Poisson error of approximately CV across the digital readout’s operative range, with daily calibration curves bounding day to day reproducibility (p. 916, col. 1; p. 917, col. 1; Fig. 3-4; p. 922, col. 1). The motivation to combine and reasonable expectation of success are the same as fully articulated above for claim 1.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Funakoshi et al. (2017 Sci. Rep. 7:13202) in view of Albayrak et al. (2016 Mol. Cell 61:914-924) and O’Connell et al (2017 Lab. Med. 48(4):332-338) as applied to claims 1, 3, 4, and 5 above, and further in view of Findlay et al. (2016 PLoS One 11(4):e0153901).
The teachings of Funakoshi et al., Albayrak et al. and O’Connell et al. have been documented above in the rejection of claims 1, 3, 4, and 5 are rejected under 35 U.S.C. 103.
Regarding claim 2, claim 2 recites, ”The method according to claim 1, wherein in the step (1),
measurement of the number of copies of a specific gene and measurement of the number of copies of a gene of an external standard are simultaneously performed.” Findlay et al. establishes that two distinct DNA targets can be co-amplified and independently resolved in a single ddPCR reaction by assigning each its own spectrally distinct fluorophore (FAM and HEX) and resolving them on a two dimensional droplet plot, and that this duplexed configuration performs reliably on genomic DNA inputs (Findlay’s et al. target probe duplexed with the RPP30 genomic reference) (S1 Fig.; Fig. 2; p. 13, Droplet digital PCR). It would have been prima facie obvious to a POSITA to apply Findlay’s et al. duplexing technique so that the specific gene and the gene of the external standard are co-amplified in a single ddPCR reaction on separate fluorescent channels, i.e., “simultaneously performed”. That the reference channel in Findlay’s et al. worked example is an endogenous single-copy locus rather than an exogeneous spike-in does not alter the analysis: Findlay et al. teaches the channel-multiplexing mechanism, and applying a known technique to a method ready for improvement to yield a predictable result is obvious. Motivation includes (i) reducing regent consumption and per-reaction technical variation; (ii) eliminating between well variability as between the specific gene and external standard measurements, so that recovery normalization (per O’Connell) is performed on co-partitioned analytes; and (iii) Findlay’s et al. demonstration that duplexed ddPCR achieves high precision on genomic DNA inputs. MPEP 2143 (C); KSR, 550 U.S. at 416. The reasonable expectation of success is supplied by Findlay’s et al working two-channel duplex on genomic DNA; the motivation to combine is otherwise the same as fully articulated above for claim 1.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Funakoshi et al. (2017 Sci. Rep. 7:13202) in view of Albayrak et al. (2016 Mol. Cell 61:914-924) and O’Connell et al (2017 Lab. Med. 48(4):332-338) as applied to claims 1, 3, 4, and 5 above, and further in view of He et al. (2019, Sci. Rep. 9:5599).
The teachings of Funakoshi et al., Albayrak et al. and O’Connell et al. have been documented above in the rejection of claims 1, 3, 4, and 5 are rejected under 35 U.S.C. 103.
Regarding claim 6, claim 6 recites, “The method according to claim 1, wherein the specific gene is LINE-1 gene.” Funakoshi et al. in view of Albayrak et al. and O’Connell renders obvious the method of claim 1 for the reasons set forth in Rejection 1 above. Funakoshi et al., Albayrak et al. and O’Connell. do not, however, expressly identify LINE-1 as the “specific gene” being quantified. He et al. teaches the use of LINE-1 as a target sequence for absolute quantification of human DNA by droplet digital PCR (ddPCR). Specifically, He et al. develops a ddPCR assay targeting “repetitive nuclear genomic elements (LINE-1)” for “absolute quantification of host specific gene targets” in a heterogenous biological sample (Abstract; p. 2, para 2.). He et al. selects LINE-1 because it is human-specific (i.e., distinguishable from non-human genomes that may be present in the sample) and because it is present at high copy number per haploid genome, both of which are properties advantageous for human-cell quantification. He et al. confirms the human-specificity of the LINE-1 assay experimentally, demonstrating signal to noise ratios of greater than 25-fold against all tested non-human genomes (including bovine, E. coli, mouse, potato, rice, chicken, corn, and wheat) and demonstrating no detectable signal in water controls (Fig. 1B; p. 2, col. 2). He et al. further validates the LINE-1 ddPCR assay across 200 stool DNA extracts from healthy individuals and hospitalized patients, establishing the assay’s operability for absolute quantification of human cellular material in heterogeneous biological matrix containing PCR inhibitors and substantial non-human (microbial, dietary) DNA background (Abstract; p. 2, para 3.).
A person of ordinary skill in the art at the time the invention was made, it would have been prima facie obvious to select LINE-1, as taught by He et al., as the “specific gene” in the method rendered obvious by Funakoshi et al., Albayrak et al., and O’Connell. The skilled artisan implementing the Funakoshi/Albayrak/O’Connell method to quantify human cells in a biological sample would have been seeking a target gene that (i) is present in human cells, (ii) is specific to human DNA so as to avoid spurious amplification from non-human DNA that may be present in the sample (for example, from animal tissue in xenotransplatation contexts or from microbial DNA in other biological matrices), and (iii) has been validated as a functional ddPCR target.
He’s et al. express teaching of LINE-1 as a human specific ddPCR target for absolute quantification of human cellular material provides direct teaching, suggestion, and motivation for the selection under MPEP 214319(I)(G). The combination further represents the simple substitution of one known ddPCR target for another known ddPCR target (the LINE-1 element of He et al.) within an otherwise unchanged workflow, to obtain the predictable result of human cell quantification using a human specific target. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398 (2007).
Claim 7 is rejected under 35 U.S.C 103 as being unpatentable over Funakoshi et al. (2017 Sci. Rep. 7:13202) in view of Albayrak et al. (2016 Mol. Cell 61:914-924) and O’Connell et al (2017 Lab. Med. 48(4):332-338) as applied to claims 1, 3, 4, and 5 above, further in view of Walker et al. (2003, Anal. Biochem. 315:122-128), and Tyson et al. (2014, Hum. Genet. 22(4):458-463).
The teachings of Funakoshi et al., Albayrak et al. and O’Connell et al. have been documented above in the rejection of claims 1, 3, 4, and 5 are rejected under 35 U.S.C. 103.
Regarding claim 7, claim 7 recites, “The method according to claim 1, wherein the specific gene is REXO1L1 gene.” Funakoshi et al. in view of Albayrak et al. and O’Connell et al. renders obvious the method of claim 1 for the reasons set forth in rejection 1 above. Walker et al. teaches the use of multi-copy, human specific genomic elements as PCR analytes for sensitive quantification of human DNA in complex biological samples. Specifically, Walker et al. develops Alu element-based PCR assays for “rapid identification and quantification of human DNA” (Abstract). Walker et al. teaches that the advantage of Alu-based PCR for this purpose derives from two properties of the target: (i) human specificity, because “multicopy Alu elements include recently integrated subfamilies that are present in the human genome but are largely absent from nonhuman primate” (Abstract), and (ii) high per cell copy number because “the high copy number of subfamily specific Alu repeats in the human genome makes these assays human specific within a very sensitive linear range (Abstract). Walker et al, further contrast these multi-copy approaches with single copy nuclear DNA detection, noting that the latter “is limited as a result of the single copy” (p. 122, col. 1).
Tyson et al. teaches that REXO1L1 possesses the same two properties that Walker identifies as making Alu useful for human DNA quantification. Specifically, Tyson et al. teaches that the REXO1L1 gene cluster lies within “one of the largest variable number tandem repeat arrays in the human genome” at chromosome band 8q21.2 (Abstract; p. 459), confirming that REXO1L1 is present at high per-cell copy number (median diploid copy number of 166, ranging from 97 to 277 across 216 control individuals) (p. 462, col. 1; Fig. 3B). Tyson et al. further establishes that REXO1L1 is a defined human gene cluster with a sequence specific probe accessible for single molecule quantification (p. 459, col. 2), and validates the digital quantification against pulse field electrophoresis Southern blot with R^2 = 0.98 (p. 460, col. 1; Fig. 3a).
A person of ordinary skill in the art at the time the invention was made, it would have been prima facie obvious to select REXO1L1, as taught by Tyson et al. The skilled artisan, having been taught by Walker et al that multi-copy human specific genomic targets are selected for PCR based human DNA quantification specifically because of their human specificity and high per cell copy number, would have looked to the broader genetics literature characterizing such elements to identify additional suitable candidates. Tyson et al, identifies REXO1L1 as a candidate possessing both selection criteria: REXO1L1 lies within one of the largest tandem repeat arrays in the human genome (high per cell copy number) and is characterized as a human gene cluster (human-specificity).
The combination is supported by the simple substitution rationale of MPEP(I)(B). The ddPCR chemistry, duplex assay format, external standard normalization, cell-based calibration, and cells-per-unit-volume readout established by the Funakoshi/Albayrak/O’Connell combination are all preserved unchanged; only the identity of the “specific gene” is changed to the REXO1L1 element of Tyson et al. Walker et al. confirms that the biological properties underlying the operability of multi-copy human-specific PCR targets, human specificity and high per cell copy number are the relevant selection criteria within this class of analytes, supporting the substation of one such target for another that shares the same properties. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398 (2007).
A reasonable expectation of success accompanies the combination. Tyson et al. establishes that REXO1L1 yields a robust, quantitative signal in single-molecule detection (R^2=0.98 against an orthogonal method; Fig. 3A; p. 460, col. 2; Abstract). Walker et al. establishes the operability of human specific multi-copy PCR analytes in complex biological matrices including those containing non-human DNA (Fig. 4). A POSITA would have had a reasonable expectation that REXO1L1, when employed as the specific gene in the duplex ddPCR workflow of the Funakoshi/Albayrak/O’Connell combination, would yield operative quantification of human cells in a biological sample.
Conclusion
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/BREANNA MARIE TAVERNINI/Examiner, Art Unit 1682
/WU CHENG W SHEN/Supervisory Patent Examiner, Art Unit 1682
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