DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Application
This action is in reply to the correspondence received through September 17, 2025.
Claims 1-20 are pending.
Information Disclosure Statement
The information disclosure statement submitted September 17, 2025 and its contents have been considered.
Claim Rejections - 35 U.S.C. § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 7 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 7 specifies that only a result of the flagged probe of interest is extracted and analyzed, but in the claims on which it depends, other information is required to be extracted and analyzed that is not a result of the flagged probe.
Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Rejections - 35 U.S.C. § 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 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to non-statutory subject matter. Claims 1-20 are directed to an abstract idea without significantly more as required by the Alice test as discussed below.
Step 1
Claims 1-20 are directed to a process, machine, manufacture, or composition of matter.
Step 2A
Claims 1-20 are directed to abstract ideas, as explained below.
Prong one of the Step 2A analysis requires identifying the specific limitation(s) in the claim under examination that the examiner believes recites an abstract idea; and determining whether the identified limitation(s) falls within at least one of the groupings of abstract ideas of mathematical concepts, mental processes, and certain methods of organizing human activity.
The claims recite the following limitations that are directed to abstract ideas. Claim 16 recites acquiring information regarding an examination of a tumor tissue and chronological examinations of blood, integrating the information from the information acquiring section to generate data regarding the tumor, and outputting the data generated by the integrating section, storing the data output from the outputting section, outputting a result of the examination of the tumor tissue; and outputting a result of the examinations of the blood. Claims 1 and 17 recite similar features as claim 1. Claims 2-15 and 18-20 further specify features of the identified abstract ideas or characteristics of the data used thereby.
These limitations describe abstract ideas that correspond to concepts identified as abstract ideas by the courts as mental processes—such as concepts performed in the human mind (including an observation, evaluation, judgment, or opinion)—because the claimed features identified above are concepts performed in the human mind (including an observation, evaluation, judgment, or opinion).
These limitations describe abstract ideas that correspond to concepts identified as abstract ideas by the courts as certain methods of organizing human activity—such as fundamental economic principles or practices (including hedging, insurance, mitigating risk), commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations), managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)—because the claimed features identified above manage personal behavior or relationships or interactions between people including following rules or instructions.
Thus, the concepts set forth in claims 1-20 recite abstract ideas.
Prong two of the Step 2A requires identifying whether there are any additional elements recited in the claim beyond the judicial exception(s), and evaluating those additional elements to determine whether they integrate the exception into a practical application of the exception. “Integration into a practical application” requires an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. Further, “integration into a practical application” uses the considerations laid out by the Supreme Court and the Federal Circuit to evaluate whether the judicial exception is integrated into a practical application, such as considerations discussed in M.P.E.P. § 2106.05(a)-(h).
The claims recite the following additional elements beyond those identified above as being directed to an abstract idea. Claim 16 recites parts of an information processing apparatus include a controller, sections, sub apparatuses, displaying the data output, and presenting the data output from the outputting section onto a network.
The identified judicial exception(s) are not integrated into a practical application for the following reasons.
First, evaluated individually, the additional elements do not integrate the identified abstract ideas into a practical application. The additional computer elements identified above—the apparatuses, controller, sections, and network—are recited at a high level of generality. Inclusion of these elements amounts to mere instructions to implement the identified abstract ideas on a computer. See M.P.E.P. § 2106.05(f). The use of conventional computer elements to display the data output and present the data output from the outputting section onto a network is the insignificant, extra-solution activity of mere data gathering or outputting in conjunction with a law of nature or abstract idea. See M.P.E.P. § 2106.05(g). To the extent that the claims transform data, the mere manipulation of data is not a transformation. See M.P.E.P. § 2106.05(c). Inclusion of computing system in the claims amounts to generally linking the use of the judicial exception to a particular technological environment or field of use. See M.P.E.P. § 2106.05(h). Thus, taken alone, the additional elements do not amount to significantly more than a judicial exception.
Second, evaluating the claim limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. See M.P.E.P. § 2106.05(a). Their collective functions merely provide an implementation of the identified abstract ideas on a computer system in the general field of use of tumor analysis. See M.P.E.P. § 2106.05(h).
Thus, claims 1-20 recite mathematical concepts, mental processes, or certain methods of organizing human activity without including additional elements that integrate the exception into a practical application of the exception.
Accordingly, claims 1-20 are directed to abstract ideas.
Step 2B
Claims 1-20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered both individually and as an ordered combination, do not amount to significantly more than the abstract idea.
The analysis above describes how the claims recite the additional elements beyond those identified above as being directed to an abstract idea, as well as why identified judicial exception(s) are not integrated into a practical application. These findings are hereby incorporated into the analysis of the additional elements when considered both individually and in combination. Additional features of these analyses are discussed below.
Evaluated individually, the additional elements do not amount to significantly more than a judicial exception. In addition to the factors discussed regarding Step 2A, prong two, these additional computer elements also provide conventional computer functions that do not add meaningful limits to practicing the abstract idea. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. The use of generic computer components to display the data output and present the data output from the outputting section onto a network is likewise the well-understood, routine, and conventional computer functions of receiving or transmitting data over a network, e.g., the Internet, and does not impose any meaningful limit on the computer implementation of the identified abstract ideas. See M.P.E.P. § 2106.05(d)(II). Thus, taken alone, the additional elements do not amount to significantly more than a judicial exception.
Evaluating the claim limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. In addition to the factors discussed regarding Step 2A, prong two, there is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely amount to mere instructions to implement the identified abstract ideas on a computer.
Thus, claims 1-20, taken individually and as an ordered combination of elements, are not directed to eligible subject matter since they are directed to an abstract idea without significantly more.
Claim Rejections - 35 U.S.C. § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. § 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-13 and 17-20 are rejected under 35 U.S.C. § 102(a)(1)-(2) as being anticipated by Swanton et al. (U.S. Pub. No. 2020/0248266 A1) (hereinafter “Swanton”).
Claim 1: Swanton, as shown, discloses the following limitations:
acquiring information regarding a tumor by using an examination of a tumor tissue and chronological examinations of blood (see at least ¶ [0044]: the clonal and/or subclonal mutations identified in the tumour, that are used to determine whether the tumour has recurred in the patient, are mutations previously determined to be present in the tumour resected or biopsied from the individual subject; see also at least ¶ [0046]: The method of the invention detects the recurrence of a tumour in the specific subject or patient by detecting the presence and/or rise of clonal and/or subclonal mutations that are characteristic of the patient's tumour in the cell free DNA (cfDNA). It will be appreciated that the term “clonal mutation” may include an early clonal mutation(s) and/or a clonal mutation(s). The clonal and/or subclonal mutations are characteristic of the specific tumour from the individual patient. The clonal and/or subclonal mutations characteristic of the patient's tumour are defined by sequencing all or part of the whole genome and/or exome of DNA from the tumour, typically after the tumour has been resected from the patient. Using a set of reagents designed or defined to detect the presence of DNA from the tumour via the presence of the specific clonal and/or subclonal mutations identified for the specific subject of interest, the presence and/or rise of clonal and/or subclonal mutations in cfDNA obtained from the patient is analysed; see also at least ¶ [0056]: the tumour sample may be a blood sample. For example the blood sample may comprise cfDNA, circulating tumour DNA, circulating tumour cells or exosomes comprising tumour DNA; see also at least ¶ [0110]: the cfDNA sample analysis is carried out on multiple occasions over a period of time, for example at regular intervals).
Claim 2: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
acquiring mutational information regarding genes of the tumor tissue, in reference to the examination of the tumor tissue (see at least ¶ [0046]: the method of the invention detects the recurrence of a tumour in the specific subject or patient by detecting the presence and/or rise of clonal and/or subclonal mutations that are characteristic of the patient's tumour in the cell free DNA (cfDNA). It will be appreciated that the term “clonal mutation” may include an early clonal mutation(s) and/or a clonal mutation(s). The clonal and/or subclonal mutations are characteristic of the specific tumour from the individual patient. The clonal and/or subclonal mutations characteristic of the patient's tumour are defined by sequencing all or part of the whole genome and/or exome of DNA from the tumour, typically after the tumour has been resected from the patient. Using a set of reagents designed or defined to detect the presence of DNA from the tumour via the presence of the specific clonal and/or subclonal mutations identified for the specific subject of interest, the presence and/or rise of clonal and/or subclonal mutations in cfDNA obtained from the patient is analysed; see also at least ¶ [0060]: a ‘mutation’ refers to a difference in a nucleotide sequence (e.g. DNA or RNA) in a tumour cell compared to a healthy cell from the same individual. The difference in the nucleotide sequence can result in the expression of a protein which is not expressed by a healthy cell from the same individual; see also at least ¶¶ [0050]-[0051]).
Claim 3: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
listing information concerning one or multiple genetic mutations, in reference to the mutational information (see at least ¶ [0130]: the standard assay design pipeline was used to design Right and Left PCR primers for all given SNVs. We refer to a pair of Right and Left PCR primers targeting a SNV as an assay for that particular SNV. Note that it is possible for one assay to cover more than 1 target SNV, if they were in close proximity For every pair of assays, the probability of forming primer-dimer was calculated using the standard pipeline. The SNV allele-fraction data in each tumour was used to reconstruct phylogenetic trees using LICHeE (Lineage Inference for Cancer Heterogeneity and Evolution). The list of assays for each sample were filtered to remove primers that were predicted to form primer dimers while giving strong priority to assays covering driver 1 and 2 SNVs. The remaining assays were used to create 5 balanced pools, each containing assays of 10 patients; see also ¶ [0071]: determining a truncal mutation is subject to statistical analysis and threshold. As such, a mutation may be identified as truncal if it is determined to have 5 a CCF 95% confidence interval <=0.75, for example 0.80, 0.85, 0.90, 0.95, 1.00 or >1.00. Conversely, a mutation may be identified as branched if it is determined to have a CCF 95% confidence interval <=0.75, for example 0.70, 0.65, 0.60, 0.55, 0.50, 0.45, 0.40, 0.35, 0.30, 0.25, 0.20, 0.15, 0.10, 0.05, 0.01 in any sample analysed. It will be appreciated that the accuracy of a method for identifying truncal mutations is increased by identifying clonal mutations for more than one sample isolated from the tumour; see also at least ¶ [0128]: PyClone was used to identify clusters of SNVs, and calculate their cancer-cell fraction. This was used to categorize SNVs as either clonal or subclonal. The driver category of each SNV was determined and provided as the driver category (1-4, where 1 is most likely to be a driver mutation, and 4 is the least likely). For each patient, up to 108 SNVs, spanning all driver categories and including clonal and subclonal mutations, were identified. The detected allele fractions of each SNV in each tumour subsection, lymph node and matched normal DNA sample along with PyClone clonal/subclonal cluster information were also identified.
The collection of identified mutations is a listing).
Claim 4: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
acquiring chronological information regarding the one or multiple genetic mutations by the chronological examinations of blood (see also at least ¶ [0056]: the tumour sample may be a blood sample. For example the blood sample may comprise cfDNA, circulating tumour DNA, circulating tumour cells or exosomes comprising tumour DNA; see also at least ¶ [0110]: the cfDNA sample analysis is carried out on multiple occasions over a period of time, for example at regular intervals; see also at least ¶ [0100]).
Claim 5: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
selecting a probe of interest by referring to a database generated in reference to the mutational information (see at least ¶ [0099]: for example, a set of reagents may be a set of reagents for carrying out the CAPP-SEQ assay or a set of reagents for carrying out a digital PCR assay. In a preferred embodiment, the set of reagents is a set of reagents comprising probes and/or primers. Such probes and/or primers may be produced by known and routine techniques used in the art. Typically, the probes and/or primers will be for multiplex PCR. In a preferred embodiment, the set of reagents is a set of multiplex PCR probes and/or primers. The set of reagents for performing multiplex PCR is known to the person skilled in the art; see also at least ¶ [0101]: the set of detection reagents is capable of detecting one or more mutations. The set of detection reagents may be capable of detecting at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, at least fifteen, at least twenty, at least twenty-five, at least thirty, at least thirty five, at least forty, at least forty five, at least fifty, at least one hundred, at least one hundred and fifty, at least two hundred, at least two hundred and fifty, at least three hundred, at least three hundred and fifty, at least four hundred, at least four hundred and fifty, at least or up to 500 mutations characteristic of each subsection of the tumour; see also at least ¶¶ [0105], [0200], and [0204]).
Claim 6: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
flagging the probe of interest (see at least ¶ [0099]: for example, a set of reagents may be a set of reagents for carrying out the CAPP-SEQ assay or a set of reagents for carrying out a digital PCR assay. In a preferred embodiment, the set of reagents is a set of reagents comprising probes and/or primers. Such probes and/or primers may be produced by known and routine techniques used in the art. Typically, the probes and/or primers will be for multiplex PCR. In a preferred embodiment, the set of reagents is a set of multiplex PCR probes and/or primers. The set of reagents for performing multiplex PCR is known to the person skilled in the art; see also at least ¶¶ [0101], [0105], [0200], and [0204]).
Claim 7: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
extracting and analyzing only a result of the flagged probe of interest (see at least ¶ [0099]: for example, a set of reagents may be a set of reagents for carrying out the CAPP-SEQ assay or a set of reagents for carrying out a digital PCR assay. In a preferred embodiment, the set of reagents is a set of reagents comprising probes and/or primers. Such probes and/or primers may be produced by known and routine techniques used in the art. Typically, the probes and/or primers will be for multiplex PCR. In a preferred embodiment, the set of reagents is a set of multiplex PCR probes and/or primers. The set of reagents for performing multiplex PCR is known to the person skilled in the art; see also at least ¶¶ [0101], [0105], [0200], and [0204]).
Claim 8: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
establishing one or multiple regions for the examination of the tumor tissue (see at least ¶ [0096]: whole or part of the genome and/or exome is sequenced from the whole tumour or from subsections of the tumour. It will be appreciated that a subsection of the tumour refers to a resected section of the whole tumour resected from the patient. Whole or part of the exome may be sequenced from one or more tumour subsections. Whole or part of the exome may be sequenced from at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least or up to ten subsections; see also at least ¶ [0101]: the early clonal, clonal and/or subclonal mutations are defined based on which mutations occur in which tumour subsections. For example, early clonal, clonal and/or subclonal mutations may be defined on mutations occurring in the same tumour subsection or subsections and/or a different tumour subsection or subsections. In a preferred embodiment, early clonal, clonal and/or subclonal mutations in the tumour are defined from one or more tumour subsections. Early clonal, clonal and/or subclonal mutations in the tumour may be defined from at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least or up to ten subsections. In some embodiments of the invention, the set of detection reagents is capable of detecting one or more mutations. The set of detection reagents may be capable of detecting at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, at least fifteen, at least twenty, at least twenty-five, at least thirty, at least thirty five, at least forty, at least forty five, at least fifty, at least one hundred, at least one hundred and fifty, at least two hundred, at least two hundred and fifty, at least three hundred, at least three hundred and fifty, at least four hundred, at least four hundred and fifty, at least or up to 500 mutations characteristic of each subsection of the tumour; see also at least ¶ [0125]); and
coupling biomarkers in the an examination of blood to the regions (see at least ¶¶ [0096], [0101], and [0125] and the analysis above; see also at least ¶ [0127]: the mutation profile, which included single nucleotide variants (SNVs) for each tumour subsection, was determined using whole exome sequencing. The full mutation profile of each tumour was used to reconstruct the phylogenetic tree of each tumour; see also at least ¶ [0128]: PyClone was used to identify clusters of SNVs, and calculate their cancer-cell fraction. This was used to categorize SNVs as either clonal or subclonal. The driver category of each SNV was determined and provided as the driver category (1-4, where 1 is most likely to be a driver mutation, and 4 is the least likely). For each patient, up to 108 SNVs, spanning all driver categories and including clonal and subclonal mutations, were identified. The detected allele fractions of each SNV in each tumour subsection, lymph node and matched normal DNA sample along with PyClone clonal/subclonal cluster information were also identified; see also at least ¶ [0130]).
Claim 9: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
predicting states of the tumor in the regions by using the coupled biomarkers (see at least ¶ [0176]: the most important predictor of whether a particular tumour was detected in the plasma appeared to be histological type: 100% of the squamous cell carcinomas (SQCC) were detected in plasma, whereas only 52% (15/29) of the adenocarcinomas (ADC) were detected (FIG. 9); see also at least ¶ [0179]: A regression analysis was performed to determine the variables that can be used to predict detection of mutations in plasma. More specifically, a binary response variable was used to annotate the mutations as ‘called’ or ‘not called’. Mean VAF in tumour refers to the average mutation VAF among all tumour regions. Clonal/subclonal information was determined using PyClone; see also at least ¶¶ [0196]: based on multi-regional whole exome sequencing data, subclonal deconstruction and phylogenetic tree analysis, clonal and subclonal variant clusters are identified. Unpublished data shows that NSCLC relapse may be monoclonal and originate from an early truncal clone or specific-subclone, or that relapse may be polyclonal originating from multiple subclones. Through barcoding all variant clusters present in the phylogenetic trees (i.e. having SNVs private to individual clusters represented within a primer assay pool) it has been demonstrated that cfDNA can predict which “part” of the tumour and therefore subclonal population gives rise to the relapse. For example, if the SNVs detected in plasma corresponds to specific subclonal clusters in one branch of the original phylogenetic tree, then it can be inferred that this branch is “seeding” disease relapse; see also at least ¶ [0196]).
Claim 10: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
performing the chronological examinations of the blood with regard to a particular biomarker of the one or multiple biomarkers that is selected according to the examination of the tumor tissue (see also at least ¶ [0056]: the tumour sample may be a blood sample. For example the blood sample may comprise cfDNA, circulating tumour DNA, circulating tumour cells or exosomes comprising tumour DNA; see also at least ¶ [0110]: the cfDNA sample analysis is carried out on multiple occasions over a period of time, for example at regular intervals; see also at least ¶¶ [0096], [0100]-[0101], and [0125]).
Claim 11: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
wherein the particular biomarker is a biomarker that has fallen out of determination standards for an administration target in a first or second or subsequent examination (see at least ¶ [0130]: the standard assay design pipeline was used to design Right and Left PCR primers for all given SNVs. We refer to a pair of Right and Left PCR primers targeting a SNV as an assay for that particular SNV. Note that it is possible for one assay to cover more than 1 target SNV, if they were in close proximity For every pair of assays, the probability of forming primer-dimer was calculated using the standard pipeline. The SNV allele-fraction data in each tumour was used to reconstruct phylogenetic trees using LICHeE (Lineage Inference for Cancer Heterogeneity and Evolution). The list of assays for each sample were filtered to remove primers that were predicted to form primer dimers while giving strong priority to assays covering driver 1 and 2 SNV; see also at least ¶ [0152]: Natera’s standard assay design pipeline was used to design forward and reverse PCR primers for all SNVs detected in tumour samples; each pair targeting an SNV comprises the assay for that SNV. If two SNVs were in close proximity, a single assay could cover more than 1 target SNV. For some SNVs, it was not possible to design an assay. When creating assay pools, the probability of every pairing of two assays to form primer-dimers was calculated. For each patient sample, an optimal list of assays with no predicted primer-dimer was selected, while giving strong priority to assays covering driver SNVs. These remaining assays were used to create 10 balanced pools, each containing the assays for 10 patients' SNVs and on average 20 assays per each patient. Assays were always chosen such that, 1) assays covering driver SNVs had highest priority, and 2) there was uniform sampling of SNVs from branches in the reconstructed phylogeny tree. The final design for baseline cohort consisted of 1835 assays, equally distributed among the 10 pools, and contained 15-20 assays for each sample).
Claim 12: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
calculating a data set of clusters and features in reference to an information group regarding one or multiple biomarkers linked to tumor tissues and blood (see at least ¶ [0128]: PyClone was used to identify clusters of SNVs, and calculate their cancer-cell fraction. This was used to categorize SNVs as either clonal or subclonal. The driver category of each SNV was determined and provided as the driver category (1-4, where 1 is most likely to be a driver mutation, and 4 is the least likely). For each patient, up to 108 SNVs, spanning all driver categories and including clonal and subclonal mutations, were identified. The detected allele fractions of each SNV in each tumour subsection, lymph node and matched normal DNA sample along with PyClone clonal/subclonal cluster information were also identified; see also at least ¶¶ [0140]-[0143]).
Claim 13: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
estimating information regarding missing one or multiple biomarkers, in reference to the data set (see at least ¶ [0143]: individual mutations (SNVs, DNVs and indels) were timed as clonal or subclonal through PyClone clustering as described above. For clonal timing, the values from phyloCCF were used. Clonal mutations were then further timed as early, late or untimed clonal. This was performed first within each tumor region relative to overlapping copy number events as previously described. In brief, mutations in parts of the genome with at least two copies of the major allele were preliminarily classified as early if the mutation copy number (described above) was >1, and late if it was <=1. Temporal analysis was then performed across all regions. Mutations classified as clonal were called as “clonal early” if a given mutation was early across all regions, or, if the mutation was early in the majority of regions. A clonal mutation was called as “clonal late” if it was called as late across all regions, or if it was late across the majority of regions. Any clonal mutations that could not be timed as either early or late, was classified as “clonal untimed”; see also at least ¶ [0200]: the primary and metastatic setting a single biopsy may not provide insight into the breadth of actionable alterations, neo-antigens or potential resistance mechanisms present within the bulk of a patient's disease. Clonal alterations may be lost in a specific tumour region due to copy number events and subclonal alterations may not be represented in a single biopsy. Utilisation of a generic ctDNA driver panel, generic ctDNA resistance mechanism panel or generic ctDNA neoantigen encoding variant panel to probe ctDNA may be performed to identify therapeutically relevant mutations not represented in a single tumour biopsy. The bespoke early-clonal barcode could act as a companion diagnostic tool to determine the therapeutic value of variants not represented in tissue, but identified in plasma by a generic panel).
Claim 17: Swanton, as shown, discloses the following limitations:
using an examination of a tumor tissue and chronological examinations of blood and having the examinations intervene in each other to integrally analyze data from the examinations, thereby generating data regarding the tumor (see at least ¶ [0044]: the clonal and/or subclonal mutations identified in the tumour, that are used to determine whether the tumour has recurred in the patient, are mutations previously determined to be present in the tumour resected or biopsied from the individual subject; see also at least ¶ [0046]: The method of the invention detects the recurrence of a tumour in the specific subject or patient by detecting the presence and/or rise of clonal and/or subclonal mutations that are characteristic of the patient's tumour in the cell free DNA (cfDNA). It will be appreciated that the term “clonal mutation” may include an early clonal mutation(s) and/or a clonal mutation(s). The clonal and/or subclonal mutations are characteristic of the specific tumour from the individual patient. The clonal and/or subclonal mutations characteristic of the patient's tumour are defined by sequencing all or part of the whole genome and/or exome of DNA from the tumour, typically after the tumour has been resected from the patient. Using a set of reagents designed or defined to detect the presence of DNA from the tumour via the presence of the specific clonal and/or subclonal mutations identified for the specific subject of interest, the presence and/or rise of clonal and/or subclonal mutations in cfDNA obtained from the patient is analysed; see also at least ¶ [0056]: the tumour sample may be a blood sample. For example the blood sample may comprise cfDNA, circulating tumour DNA, circulating tumour cells or exosomes comprising tumour DNA; see also at least ¶ [0110]: the cfDNA sample analysis is carried out on multiple occasions over a period of time, for example at regular intervals).
Claim 18: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
acquiring mutational information regarding genes of the tumor tissue in reference to the examination of the tumor tissue (see at least ¶ [0046]: the method of the invention detects the recurrence of a tumour in the specific subject or patient by detecting the presence and/or rise of clonal and/or subclonal mutations that are characteristic of the patient's tumour in the cell free DNA (cfDNA). It will be appreciated that the term “clonal mutation” may include an early clonal mutation(s) and/or a clonal mutation(s). The clonal and/or subclonal mutations are characteristic of the specific tumour from the individual patient. The clonal and/or subclonal mutations characteristic of the patient's tumour are defined by sequencing all or part of the whole genome and/or exome of DNA from the tumour, typically after the tumour has been resected from the patient. Using a set of reagents designed or defined to detect the presence of DNA from the tumour via the presence of the specific clonal and/or subclonal mutations identified for the specific subject of interest, the presence and/or rise of clonal and/or subclonal mutations in cfDNA obtained from the patient is analysed; see also at least ¶ [0060]: a ‘mutation’ refers to a difference in a nucleotide sequence (e.g. DNA or RNA) in a tumour cell compared to a healthy cell from the same individual. The difference in the nucleotide sequence can result in the expression of a protein which is not expressed by a healthy cell from the same individual; see also at least ¶¶ [0050]-[0051]); and
listing information concerning one or multiple genetic mutations in reference to the mutational information (see at least ¶ [0130]: the standard assay design pipeline was used to design Right and Left PCR primers for all given SNVs. We refer to a pair of Right and Left PCR primers targeting a SNV as an assay for that particular SNV. Note that it is possible for one assay to cover more than 1 target SNV, if they were in close proximity For every pair of assays, the probability of forming primer-dimer was calculated using the standard pipeline. The SNV allele-fraction data in each tumour was used to reconstruct phylogenetic trees using LICHeE (Lineage Inference for Cancer Heterogeneity and Evolution). The list of assays for each sample were filtered to remove primers that were predicted to form primer dimers while giving strong priority to assays covering driver 1 and 2 SNVs. The remaining assays were used to create 5 balanced pools, each containing assays of 10 patients; see also ¶ [0071]: determining a truncal mutation is subject to statistical analysis and threshold. As such, a mutation may be identified as truncal if it is determined to have 5 a CCF 95% confidence interval <=0.75, for example 0.80, 0.85, 0.90, 0.95, 1.00 or >1.00. Conversely, a mutation may be identified as branched if it is determined to have a CCF 95% confidence interval <=0.75, for example 0.70, 0.65, 0.60, 0.55, 0.50, 0.45, 0.40, 0.35, 0.30, 0.25, 0.20, 0.15, 0.10, 0.05, 0.01 in any sample analysed. It will be appreciated that the accuracy of a method for identifying truncal mutations is increased by identifying clonal mutations for more than one sample isolated from the tumour; see also at least ¶ [0128]: PyClone was used to identify clusters of SNVs, and calculate their cancer-cell fraction. This was used to categorize SNVs as either clonal or subclonal. The driver category of each SNV was determined and provided as the driver category (1-4, where 1 is most likely to be a driver mutation, and 4 is the least likely). For each patient, up to 108 SNVs, spanning all driver categories and including clonal and subclonal mutations, were identified. The detected allele fractions of each SNV in each tumour subsection, lymph node and matched normal DNA sample along with PyClone clonal/subclonal cluster information were also identified.
The collection of identified mutations is a listing).
Claim 19: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
establishing one or multiple regions for the examination of the tumor tissue (see at least ¶ [0096]: whole or part of the genome and/or exome is sequenced from the whole tumour or from subsections of the tumour. It will be appreciated that a subsection of the tumour refers to a resected section of the whole tumour resected from the patient. Whole or part of the exome may be sequenced from one or more tumour subsections. Whole or part of the exome may be sequenced from at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least or up to ten subsections; see also at least ¶ [0101]: the early clonal, clonal and/or subclonal mutations are defined based on which mutations occur in which tumour subsections. For example, early clonal, clonal and/or subclonal mutations may be defined on mutations occurring in the same tumour subsection or subsections and/or a different tumour subsection or subsections. In a preferred embodiment, early clonal, clonal and/or subclonal mutations in the tumour are defined from one or more tumour subsections. Early clonal, clonal and/or subclonal mutations in the tumour may be defined from at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least or up to ten subsections. In some embodiments of the invention, the set of detection reagents is capable of detecting one or more mutations. The set of detection reagents may be capable of detecting at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, at least fifteen, at least twenty, at least twenty-five, at least thirty, at least thirty five, at least forty, at least forty five, at least fifty, at least one hundred, at least one hundred and fifty, at least two hundred, at least two hundred and fifty, at least three hundred, at least three hundred and fifty, at least four hundred, at least four hundred and fifty, at least or up to 500 mutations characteristic of each subsection of the tumour; see also at least ¶ [0125]);
coupling biomarkers in an examination of blood to the regions (see at least ¶¶ [0096], [0101], and [0125] and the analysis above; see also at least ¶ [0127]: the mutation profile, which included single nucleotide variants (SNVs) for each tumour subsection, was determined using whole exome sequencing. The full mutation profile of each tumour was used to reconstruct the phylogenetic tree of each tumour; see also at least ¶ [0128]: PyClone was used to identify clusters of SNVs, and calculate their cancer-cell fraction. This was used to categorize SNVs as either clonal or subclonal. The driver category of each SNV was determined and provided as the driver category (1-4, where 1 is most likely to be a driver mutation, and 4 is the least likely). For each patient, up to 108 SNVs, spanning all driver categories and including clonal and subclonal mutations, were identified. The detected allele fractions of each SNV in each tumour subsection, lymph node and matched normal DNA sample along with PyClone clonal/subclonal cluster information were also identified; see also at least ¶ [0130]); and
predicting states of the tumor in the regions by using the coupled biomarkers (see at least ¶ [0176]: the most important predictor of whether a particular tumour was detected in the plasma appeared to be histological type: 100% of the squamous cell carcinomas (SQCC) were detected in plasma, whereas only 52% (15/29) of the adenocarcinomas (ADC) were detected (FIG. 9); see also at least ¶ [0179]: A regression analysis was performed to determine the variables that can be used to predict detection of mutations in plasma. More specifically, a binary response variable was used to annotate the mutations as ‘called’ or ‘not called’. Mean VAF in tumour refers to the average mutation VAF among all tumour regions. Clonal/subclonal information was determined using PyClone; see also at least ¶¶ [0196]: based on multi-regional whole exome sequencing data, subclonal deconstruction and phylogenetic tree analysis, clonal and subclonal variant clusters are identified. Unpublished data shows that NSCLC relapse may be monoclonal and originate from an early truncal clone or specific-subclone, or that relapse may be polyclonal originating from multiple subclones. Through barcoding all variant clusters present in the phylogenetic trees (i.e. having SNVs private to individual clusters represented within a primer assay pool) it has been demonstrated that cfDNA can predict which “part” of the tumour and therefore subclonal population gives rise to the relapse. For example, if the SNVs detected in plasma corresponds to specific subclonal clusters in one branch of the original phylogenetic tree, then it can be inferred that this branch is “seeding” disease relapse; see also at least ¶ [0196]).
Claim 20: Swanton discloses the limitations as shown in the rejections above. Further, Swanton, as shown, discloses the following limitations:
calculating a data set of clusters and features in reference to an information group regarding one or multiple biomarkers linked to tumor tissues and blood (see at least ¶ [0128]: PyClone was used to identify clusters of SNVs, and calculate their cancer-cell fraction. This was used to categorize SNVs as either clonal or subclonal. The driver category of each SNV was determined and provided as the driver category (1-4, where 1 is most likely to be a driver mutation, and 4 is the least likely). For each patient, up to 108 SNVs, spanning all driver categories and including clonal and subclonal mutations, were identified. The detected allele fractions of each SNV in each tumour subsection, lymph node and matched normal DNA sample along with PyClone clonal/subclonal cluster information were also identified; see also at least ¶¶ [0140]-[0143]); and
estimating information regarding missing one or multiple biomarkers in reference to the data set (see at least ¶ [0143]: individual mutations (SNVs, DNVs and indels) were timed as clonal or subclonal through PyClone clustering as described above. For clonal timing, the values from phyloCCF were used. Clonal mutations were then further timed as early, late or untimed clonal. This was performed first within each tumor region relative to overlapping copy number events as previously described. In brief, mutations in parts of the genome with at least two copies of the major allele were preliminarily classified as early if the mutation copy number (described above) was >1, and late if it was <=1. Temporal analysis was then performed across all regions. Mutations classified as clonal were called as “clonal early” if a given mutation was early across all regions, or, if the mutation was early in the majority of regions. A clonal mutation was called as “clonal late” if it was called as late across all regions, or if it was late across the majority of regions. Any clonal mutations that could not be timed as either early or late, was classified as “clonal untimed”; see also at least ¶ [0200]: the primary and metastatic setting a single biopsy may not provide insight into the breadth of actionable alterations, neo-antigens or potential resistance mechanisms present within the bulk of a patient's disease. Clonal alterations may be lost in a specific tumour region due to copy number events and subclonal alterations may not be represented in a single biopsy. Utilisation of a generic ctDNA driver panel, generic ctDNA resistance mechanism panel or generic ctDNA neoantigen encoding variant panel to probe ctDNA may be performed to identify therapeutically relevant mutations not represented in a single tumour biopsy. The bespoke early-clonal barcode could act as a companion diagnostic tool to determine the therapeutic value of variants not represented in tissue, but identified in plasma by a generic panel).
Claim Rejections - 35 U.S.C. § 103
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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. § 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 14 and 15 are rejected under AIA 35 U.S.C. § 103 as being unpatentable over Swanton et al. (U.S. Pub. No. 2020/0248266 A1) (hereinafter “Swanton”) in view of Wherry et al. (U.S. Pub. No. 2024/0264151 A1) (hereinafter “Wherry”).
Claim 14: Swanton discloses the limitations as shown in the rejections above.
Swanton does not explicitly disclose, but Wherry, as shown, discloses the following limitations:
constructing a database of mutation-TCR, in reference to the examination of the tumor tissue and the chronological examinations of the blood (see at least ¶ [0113]: FIGS. 32A-32F are a series of images depicting that tumor-infiltrating T-cell clones in responding peripheral blood CD8 T-cell population and blood Ki67+ CD8 T-cell response correlates with tumor burden. FIGS. 32A-32C depict TCR sequencing on CD8 T cells (see materials & methods under Experimental Examples, “Cell Sorting”); see also at least ¶ [0387]: amplification and sequencing of TCRB CDR3 was performed at a survey level resolution using the immunoSEQ Platform (Adaptive Biotechnologies); see also at least ¶¶ [0395], [0401], and [0416]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the medical analysis techniques taught by Wherry with the tumor detection systems disclosed by Swanton, because Wherry teaches at ¶ [0007] that “There remains a need for identifying and tracking T cells that are associated with a disease. There also remains a need for methods of treating and monitoring disease progression that utilize methods of identifying and tracking T cells and collections of T cells in a subject” and its techniques address this need. See M.P.E.P. § 2143(I)(G).
Moreover, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the medical analysis techniques taught by Wherry with the tumor detection systems disclosed by Swanton, because the claimed invention is merely a combination of old elements (the medical analysis techniques taught by Wherry and the tumor detection systems disclosed by Swanton), in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. See M.P.E.P. § 2143(I)(A).
Claim 15: Swanton discloses the limitations as shown in the rejections above.
Swanton does not explicitly disclose, but Wherry, as shown, discloses the following limitations:
acquiring information concerning at least closed chromatin regions, in reference to the examination of the tumor tissue and the chronological examinations of the blood (see at least ¶ [0321]: the enhancer state of the cell refers to a specific pattern of open and closed chromatin regions that define an exhausted, naïve, effector or memory T cell).
The rationales to modify/combine the teachings of Swanton to include the teachings of Wherry are presented above regarding claim 14 and incorporated herein.
Claim 16 is rejected under AIA 35 U.S.C. § 103 as being unpatentable over Swanton et al. (U.S. Pub. No. 2020/0248266 A1) (hereinafter “Swanton”) in view of Landau et al. (U.S. Pub. No. 2021/0002728 A1) (hereinafter “Landau”).
Claim 16: Swanton, as shown, discloses the following limitations:
an information processing apparatus that includes a controller including an information acquiring section for acquiring information regarding an examination of a tumor tissue and chronological examinations of blood (see at least ¶ [0044]: the clonal and/or subclonal mutations identified in the tumour, that are used to determine whether the tumour has recurred in the patient, are mutations previously determined to be present in the tumour resected or biopsied from the individual subject; see also at least ¶ [0046]: The method of the invention detects the recurrence of a tumour in the specific subject or patient by detecting the presence and/or rise of clonal and/or subclonal mutations that are characteristic of the patient's tumour in the cell free DNA (cfDNA). It will be appreciated that the term “clonal mutation” may include an early clonal mutation(s) and/or a clonal mutation(s). The clonal and/or subclonal mutations are characteristic of the specific tumour from the individual patient. The clonal and/or subclonal mutations characteristic of the patient's tumour are defined by sequencing all or part of the whole genome and/or exome of DNA from the tumour, typically after the tumour has been resected from the patient. Using a set of reagents designed or defined to detect the presence of DNA from the tumour via the presence of the specific clonal and/or subclonal mutations identified for the specific subject of interest, the presence and/or rise of clonal and/or subclonal mutations in cfDNA obtained from the patient is analysed; see also at least ¶ [0056]: the tumour sample may be a blood sample. For example the blood sample may comprise cfDNA, circulating tumour DNA, circulating tumour cells or exosomes comprising tumour DNA; see also at least ¶ [0110]: the cfDNA sample analysis is carried out on multiple occasions over a period of time, for example at regular intervals),
an integrating section for integrating the information from the information acquiring section to generate data regarding the tumor (see at least ¶ [0046]: the method of the invention detects the recurrence of a tumour in the specific subject or patient by detecting the presence and/or rise of clonal and/or subclonal mutations that are characteristic of the patient's tumour in the cell free DNA (cfDNA). It will be appreciated that the term “clonal mutation” may include an early clonal mutation(s) and/or a clonal mutation(s). The clonal and/or subclonal mutations are characteristic of the specific tumour from the individual patient. The clonal and/or subclonal mutations characteristic of the patient's tumour are defined by sequencing all or part of the whole genome and/or exome of DNA from the tumour, typically after the tumour has been resected from the patient. Using a set of reagents designed or defined to detect the presence of DNA from the tumour via the presence of the specific clonal and/or subclonal mutations identified for the specific subject of interest, the presence and/or rise of clonal and/or subclonal mutations in cfDNA obtained from the patient is analysed; see also at least ¶ [0060]: a ‘mutation’ refers to a difference in a nucleotide sequence (e.g. DNA or RNA) in a tumour cell compared to a healthy cell from the same individual. The difference in the nucleotide sequence can result in the expression of a protein which is not expressed by a healthy cell from the same individual; see also at least ¶¶ [0050]-[0051]), and
an outputting section for outputting the data generated by the integrating section (see at least ¶ [0130]: the standard assay design pipeline was used to design Right and Left PCR primers for all given SNVs. We refer to a pair of Right and Left PCR primers targeting a SNV as an assay for that particular SNV. Note that it is possible for one assay to cover more than 1 target SNV, if they were in close proximity For every pair of assays, the probability of forming primer-dimer was calculated using the standard pipeline. The SNV allele-fraction data in each tumour was used to reconstruct phylogenetic trees using LICHeE (Lineage Inference for Cancer Heterogeneity and Evolution). The list of assays for each sample were filtered to remove primers that were predicted to form primer dimers while giving strong priority to assays covering driver 1 and 2 SNVs. The remaining assays were used to create 5 balanced pools, each containing assays of 10 patients; see also ¶ [0071]: determining a truncal mutation is subject to statistical analysis and threshold. As such, a mutation may be identified as truncal if it is determined to have 5 a CCF 95% confidence interval <=0.75, for example 0.80, 0.85, 0.90, 0.95, 1.00 or >1.00. Conversely, a mutation may be identified as branched if it is determined to have a CCF 95% confidence interval <=0.75, for example 0.70, 0.65, 0.60, 0.55, 0.50, 0.45, 0.40, 0.35, 0.30, 0.25, 0.20, 0.15, 0.10, 0.05, 0.01 in any sample analysed. It will be appreciated that the accuracy of a method for identifying truncal mutations is increased by identifying clonal mutations for more than one sample isolated from the tumour; see also at least ¶ [0128]: PyClone was used to identify clusters of SNVs, and calculate their cancer-cell fraction. This was used to categorize SNVs as either clonal or subclonal. The driver category of each SNV was determined and provided as the driver category (1-4, where 1 is most likely to be a driver mutation, and 4 is the least likely). For each patient, up to 108 SNVs, spanning all driver categories and including clonal and subclonal mutations, were identified. The detected allele fractions of each SNV in each tumour subsection, lymph node and matched normal DNA sample along with PyClone clonal/subclonal cluster information were also identified),
a storing section for storing the data output from the outputting section (see at least ¶¶ [0071], [0128], [0130] and the analysis above),
a tumor tissue examination result outputting apparatus for outputting a result of the examination of the tumor tissue (see at least ¶¶ [0096], [0101], and [0125] and the analysis above; see also at least ¶ [0127]: the mutation profile, which included single nucleotide variants (SNVs) for each tumour subsection, was determined using whole exome sequencing. The full mutation profile of each tumour was used to reconstruct the phylogenetic tree of each tumour; see also at least ¶ [0128]: PyClone was used to identify clusters of SNVs, and calculate their cancer-cell fraction. This was used to categorize SNVs as either clonal or subclonal. The driver category of each SNV was determined and provided as the driver category (1-4, where 1 is most likely to be a driver mutation, and 4 is the least likely). For each patient, up to 108 SNVs, spanning all driver categories and including clonal and subclonal mutations, were identified. The detected allele fractions of each SNV in each tumour subsection, lymph node and matched normal DNA sample along with PyClone clonal/subclonal cluster information were also identified; see also at least ¶¶ [0130] and [0199]); and
a blood examination result outputting apparatus for outputting a result of the examinations of the blood (see at least ¶ [0110]: the cfDNA sample analysis is carried out on multiple occasions over a period of time, for example at regular intervals; see also at least ¶ [0099]: for example, a set of reagents may be a set of reagents for carrying out the CAPP-SEQ assay or a set of reagents for carrying out a digital PCR assay. In a preferred embodiment, the set of reagents is a set of reagents comprising probes and/or primers. Such probes and/or primers may be produced by known and routine techniques used in the art. Typically, the probes and/or primers will be for multiplex PCR. In a preferred embodiment, the set of reagents is a set of multiplex PCR probes and/or primers. The set of reagents for performing multiplex PCR is known to the person skilled in the art; see also at least ¶¶ [0101], [0105], [0200], and [0204]).
Swanton does not explicitly disclose, but Landau, as shown, teaches the following limitations:
a displaying section for displaying the data output from the outputting section (see at least ¶ [0247]: the system comprises a computing unit 530 comprising computer-executable instructions, which, when executed by a processor, cause the processor to carry out a method or a set of steps for estimating tumor fraction (eTF) based on one or more of the aforementioned mathematical models for computing eTF; and a diagnosing unit that makes a qualified diagnosis based on the computed eTF (e.g., if eTF≥2 std above a noise-threshold, then a positive diagnosis is made). The system may further comprise a display 540 for outputting data and receiving user input via an associated input device (e.g., mouse). In some embodiments, the results may be displayed on display 540 in the form of a binary output (i.e., “+ve for MRD” or “−ve for MRD”) or an ordinal score, e.g., in a scale of 1 to 5; wherein a score of 1 indicates that it is unlikely that the subject has MRD and a score of 5 indicates that it is likely that the subject has MRD), and
a communicating section for presenting the data output from the outputting section onto a network (see at least ¶ [0266]: system 100 can also include display 160, as illustrated in FIG. 7C. The display can be configured and arranged to receive output from computing unit 150. Output can include data related to detection of residual disease in the subject/user. Alternatively, system 100 may exclude a display and can instead send data output from computing unit 150 to any form of storage or display device or location external to system 100. As also discussed herein, the components of system 100 can be integrated into one single unit or can be split up into more separate physical units than that which is illustrated in FIG. 7C. Moreover, system 100 can be part of a distributed network of systems each performing substantially similar tasks and transmit data from each system to a hub; see also at least ¶ [0247]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the data management techniques taught by Landau with the tumor detection systems disclosed by Swanton, because Landau teaches that at ¶ [0007] that “there is an urgent but unmet need for minimally invasive systems and methods that allow detection of tumors, particularly, in the context of diagnosis of minimal residual disease (MRD) with limited input material” it its techniques address these needs. See M.P.E.P. § 2143(I)(G).
Moreover, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the data management techniques taught by Landau with the tumor detection systems disclosed by Swanton, because the claimed invention is merely a combination of old elements (the data management techniques taught by Landau and the tumor detection systems disclosed by Swanton), in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. See M.P.E.P. § 2143(I)(A).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. The following references have been cited to further show the state of the art with respect to analyzing tumors.
Senapathy et al. (U.S. Pub. No. 2022/0310274 A1) (precision medicine portal for human diseases);
Leshchiner et al. (“Comprehensive analysis of tumour initiation, spatial and temporal progression under multiple lines of treatment.” BioRxiv (2018): 508127).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Christopher Tokarczyk, whose telephone number is 571-272-9594. The examiner can normally be reached Monday-Thursday between 6:00 AM and 4:00 PM Eastern.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mamon Obeid, can be reached at 571-270-1813. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHRISTOPHER B TOKARCZYK/ Primary Examiner, Art Unit 3687
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