System and assay for assessing microsatellite instability

Abstract

This invention describes systems, primers, kits, and methods for detecting microsatellite instabilities in biological samples. Signal data is received from a capillary electrophoresis genetic analysis instrument, wherein the signal data is determined based on the fluorescence of fragments comprising nucleic acid sequences amplified from the biological sample by polymerase chain reaction (PCR). The nucleic acid sequences correspond to multiple different microsatellite loci and are obtained using multiple PCR primers configured to side-join the multiple microsatellite loci of the biological sample. When the PCR primers are combined with the biological sample and subjected to PCR amplification, fluorescently labeled DNA fragments comprising the multiple microsatellite loci are generated. The microsatellite instabilities of the biological sample are classified using the fluorescence data obtained from the multiple fluorescently labeled microsatellite loci.

Description

[0001] This application is a divisional application, with its parent application number being 202080083538.7, filed on November 6, 2020, and entitled "System and Measurement for Evaluating Microsatellite Instability".

[0002] Cross-references to related applications

[0003] This application claims priority to U.S. Provisional Application No. 62 / 932,910, filed November 8, 2019, pursuant to 35 USC §119(e), which is jointly owned with this application and is hereby incorporated herein by reference in its entirety as if fully set forth herein.

[0004] sequence list

[0005] This application contains a sequence list, which has been electronically submitted in ASCII format and is incorporated herein by reference in its entirety. The ASCII copy, created on November 2, 2020, is named LT01514PCT_SL.txt and is 8,464 bytes in size. Background Technology

[0006] This disclosure generally relates to DNA fragment analysis.

[0007] Disruptions to the biomolecular mechanisms that repair DNA are considered a contributing factor to cancer. During cell replication, DNA repair mechanisms are crucial for the integrity of the replicating cell. When these mechanisms break down, errors can accumulate in the DNA carried by the resulting cell. Anticancer drugs exist that can exploit this breakdown to identify and destroy tumors. These drugs are most effective when tumors exhibit a high mutation rate, which in turn is associated with a high degree of failure in the DNA repair biomolecular mechanisms. One way to detect when a drug is most effective is to examine the degree to which the DNA deviates from its normal state at loci composed of many repetitive subsequences. These subsequences are called microsatellites.

[0008] Microsatellites, also known as short tandem repeats (STRs), are polymorphic DNA loci composed of short nucleotide sequences, typically 1-6 base repeats. These motifs comprise approximately 3% of the human genome. During DNA replication, these sequences are susceptible to errors, which can lead to deletions and insertions. When defects exist in the DNA MMR system, microsatellite replication errors accumulate in the genome. This phenomenon is commonly referred to as microsatellite instability (MSI). In typical microsatellite analysis, microsatellite loci are amplified using polymerase chain reaction (PCR) with fluorescently labeled forward primers and unlabeled reverse primers. PCR amplicon are separated by size using electrophoresis. Applications include: linkage mapping; animal breeding; human, animal, and plant typing; pathogen subtyping; genetic diversity; microsatellite instability; loss of heterozygosity (LOH); simple sequence repeat intervals (ISSRs); multilocular variant analysis (MLVA); and companion diagnostics for cancer treatment. Summary of the Invention

[0009] This technology generally relates to methods, systems, compositions, and kits for detecting microsatellite instability (MSI) in DNA samples. A microsatellite locus is considered microsatellite unstable (MSU) when the number of microsatellites at a given DNA locus deviates significantly from normal values. A DNA sample is considered to have high microsatellite instability (high MSI) when many microsatellite loci exhibit instability. A DNA sample is considered to have low MSI when only a few microsatellite loci exhibit instability. A DNA sample is considered microsatellite stable (MSS) when no microsatellite loci exhibit instability.

[0010] On one hand, a method for detecting microsatellite instability (MSI) in a DNA sample is provided, the method comprising: a) co-amplifying a plurality of microsatellite loci of the DNA sample to produce an amplified fragment (e.g., a DNA fragment) comprising a nucleic acid sequence from each locus; b) determining the size of the amplified fragment from each locus; and c) comparing the size of the amplified fragment from each locus with the size of a corresponding amplified fragment from a control. In an embodiment, the plurality of loci comprises at least one locus selected from: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In an embodiment, the size difference between one or more amplified fragments between the sample and the control indicates the presence of MSI at the corresponding locus in the DNA sample.

[0011] On the other hand, a method is provided for analyzing a DNA sample to determine microsatellite instability (MSI) in the DNA sample, the method comprising: a) co-amplifying a plurality of microsatellite loci of the DNA sample to produce an amplified fragment (e.g., a DNA fragment) comprising a nucleic acid sequence from each locus; b) determining the size of the amplified fragment from each locus; c) comparing the size of the amplified fragment from each locus with the size of a corresponding amplified fragment from a control, wherein a size difference between one or more amplified fragments between the sample and the control indicates the presence of MSI in the DNA sample; and d) assigning an MSI degree to the DNA sample, thereby determining the MSI state of the DNA sample. In embodiments, the plurality of loci include at least one locus selected from: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19.

[0012] On the other hand, a method for diagnosing the presence of cancerous tissue in a biological sample is provided, the method comprising: a) co-amplifying a plurality of microsatellite loci of a DNA sample to produce an amplified fragment (e.g., a DNA fragment) comprising a nucleic acid sequence from each locus; b) determining the size of the amplified fragment from each locus; and c) comparing the size of the amplified fragment from each locus with the size of a corresponding amplified fragment from a control. In embodiments, the plurality of loci comprises at least one locus selected from the group consisting of BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In embodiments, a size difference between one or more amplified fragments between a sample and a control indicates the presence of microsatellite instability (MSI) at a corresponding locus in the DNA sample, wherein the presence of MSI in the DNA sample indicates that the biological sample contains cancerous tissue.

[0013] In an embodiment, the method further includes assigning an MSI level to the DNA sample. In an embodiment, if more than about 30% of the loci in the DNA sample are determined to have MSI, the DNA sample is assigned a high MSI level (high microsatellite instability). In an embodiment, if less than about 30% but more than about 1% of the loci in the DNA sample are determined to have MSI, the DNA sample is assigned a low MSI level (low microsatellite instability). In an embodiment, if no loci in the DNA sample are determined to have MSI, the DNA sample is assigned a stable level (microsatellite stable).

[0014] On the other hand, a method for diagnosing cancer in a subject who has or is suspected of having cancer is provided, the method comprising: a) co-amplifying a plurality of microsatellite loci of a DNA sample to produce an amplified fragment (e.g., a DNA fragment) comprising a nucleic acid sequence from each locus; b) determining the size of the amplified fragment from each locus; and c) comparing the size of the amplified fragment from each locus with the size of a corresponding amplified fragment from a control, wherein a size difference between one or more amplified fragments between the sample and the control indicates the presence of microsatellite instability (MSI) at the corresponding locus in the DNA sample. In an embodiment, the presence of MSI in the DNA sample indicates that the subject has cancer. In an embodiment, the plurality of loci comprises at least one locus selected from the group consisting of BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19.

[0015] On the other hand, a method for treating cancer in a subject who has or is suspected of having cancer is provided, the method comprising: a) co-amplifying a plurality of microsatellite loci of a DNA sample to produce an amplified fragment (e.g., a DNA fragment) comprising a nucleic acid sequence from each locus; b) determining the size of the amplified fragment from each locus; c) comparing the size of the amplified fragment from each locus with the size of a corresponding amplified fragment from a control; and d) administering an anticancer agent to the subject with cancer. In an embodiment, a size difference between one or more amplified fragments between samples indicates the presence of microsatellite instability (MSI) in the DNA sample. In an embodiment, the presence of MSI in the DNA sample indicates that the subject has cancer. In an embodiment, the plurality of loci comprise at least one locus selected from the group consisting of BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19.

[0016] On the other hand, a method is provided for analyzing amplified fragments (e.g., DNA fragments) comprising nucleic acid sequences to determine microsatellite instability (MSI), the method comprising: a) providing amplified fragments (e.g., DNA fragments) comprising nucleic acid sequences amplified from a plurality of microsatellite loci in a DNA sample; b) determining the size of the amplified fragment; c) comparing the size of the amplified fragment in step b) with the size of corresponding amplified fragments from paired normal DNA samples, wherein size differences between one or more fragments between the samples indicate the presence of MSI in the DNA sample; and d) assigning an MSI degree to the DNA sample, thereby determining the MSI state of the DNA sample. In an embodiment, the amplified fragment contains a modification. In an embodiment, the modification contains a detectable biomarker. In an embodiment, the plurality of loci comprise at least one locus selected from the group consisting of BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19.

[0017] In an embodiment, the method further includes co-amplifying one or more identification markers in step a). In an embodiment, the one or more identification markers include PENTAD and / or TH01.

[0018] In one embodiment, the plurality of loci comprises at least two, three, four, five, six, or seven loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In another embodiment, the plurality of loci comprises at least eight, nine, ten, eleven, or twelve loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In the embodiments, the plurality of loci includes each of the following loci: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19.

[0019] In this embodiment, the DNA sample is derived from tumor cells, suspected cancerous cells, or other suspected cancerous biological material. In this embodiment, the control is a paired normal DNA sample, a DNA sample from non-cancerous tissue, DNA from a blood sample, or a value based on the average or median of a normal (non-cancerous) population.

[0020] In the embodiments, one or more primers selected from SEQ ID NO.: 1-26 were used to co-amplify microsatellite loci. In an embodiment, the microsatellite locus is co-amplified using a primer pair comprising a first primer and a second primer, wherein the polynucleotide sequences of the first primer and the second primer comprise one of the following pairs: SEQ ID NO.: 1 and SEQ ID NO.: 2; SEQ ID NO.: 3 and SEQ ID NO.: 4; SEQ ID NO.: 5 and SEQ ID NO.: 6; SEQ ID NO.: 7 and SEQ ID NO.: 8; SEQ ID NO.: 9 and SEQ ID NO.: 10; SEQ ID NO.: 11 and SEQ ID NO.: 12; SEQ ID NO.: 13 and SEQ ID NO.: 14; SEQ ID NO.: 15 and SEQ ID NO.: 16; SEQ ID NO.: 17 and SEQ ID NO.: 18; SEQ ID NO.: 18; SEQ ID NO.: 19 and SEQ ID NO.: 10; SEQ ID NO.: 11 and SEQ ID NO.: 12; SEQ ID NO.: 13 and SEQ ID NO.: 14; SEQ ID NO.: 15 and SEQ ID NO.: 16; SEQ ID NO.: 17 and SEQ ID NO.: 18; SEQ ID NO.: 19 and SEQ ID NO.: 10; SEQ ID NO.: 19 and SEQ ID NO.: 10; SEQ ID NO.: 10 and SEQ ID NO.: 1 ...2; SEQ ID NO.: 19 and SEQ ID NO.: 10; SEQ ID NO.: 19 and SEQ ID NO.: 10; SEQ ID NO.: 19 and SEQ ID NO.: 10; The polynucleotide sequences of SEQ ID NO.: 19 and SEQ ID NO.: 20; the polynucleotide sequences of SEQ ID NO.: 21 and SEQ ID NO.: 22; the polynucleotide sequences of SEQ ID NO.: 23 and SEQ ID NO.: 24; the polynucleotide sequences of SEQ ID NO.: 25 and SEQ ID NO.: 26.

[0021] In this embodiment, the plurality of microsatellite loci are amplified using thermal cycling, and analyzed by fragment analysis, Sanger sequencing, ion semiconductor sequencing, or high-resolution melt flow analysis. In this embodiment, the Sanger sequencing is capillary electrophoresis Sanger sequencing. In this embodiment, the DNA sample and the paired normal DNA sample are from the same individual. In this embodiment, the paired normal DNA sample is control DNA from non-cancerous tissue. In this embodiment, the DNA sample and the paired normal DNA sample are from the same type of tissue. In this embodiment, the cancer is colorectal cancer, gastric cancer, adrenocortical carcinoma, cervical cancer, mesothelioma, or endometrial cancer. In this embodiment, each locus is amplified using primer pairs, and further, at least one primer in the primer pair contains a modification. In this embodiment, the modification contains a detectable biomarker.

[0022] On the other hand, a primer set is provided, the primer set comprising one or more primer pairs, each primer pair comprising a first primer and a second primer, wherein the polynucleotide sequences of the first primer and the second primer comprise one of the following pairs: SEQ ID NO.: 1 and SEQ ID NO.: 2; SEQ ID NO.: 3 and SEQ ID NO.: 4; SEQ ID NO.: 5 and SEQ ID NO.: 6; SEQ ID NO.: 7 and SEQ ID NO.: 8; SEQ ID NO.: 9 and SEQ ID NO.: 10; SEQ ID NO.: 11 and SEQ ID NO.: 12; SEQ ID NO.: 13 and SEQ ID NO.: 14; SEQ ID NO.: 15 and SEQ ID NO.: 16; SEQ ID NO.: 17 and SEQ ID NO.: 18. The polynucleotide sequences are as follows: SEQ ID NO. 18; SEQ ID NO. 19 and SEQ ID NO. 20; SEQ ID NO. 21 and SEQ ID NO. 22; SEQ ID NO. 23 and SEQ ID NO. 24; SEQ ID NO. 25 and SEQ ID NO. 26. In some embodiments, at least one primer contains a modification. In some embodiments, the modification contains a detectable marker.

[0023] On the other hand, a composition is provided comprising a primer set of any one of the previously described primer sets, as described in the examples. In the examples, the primer set comprises at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, or at least 12 primer pairs. In the examples, the composition comprises 13 primer pairs, the primer pairs comprising the polynucleotide sequence of SEQ ID NO.: 1-26. In the examples, at least one primer is modified. In the examples, the modification comprises a detectable marker. In the examples, the composition further comprises a polymerase. In the examples, the composition further comprises a plurality of deoxyribonucleotide triphosphates. In the examples, the composition further comprises a DNA sample. In the examples, the composition further comprises one or more salts.

[0024] On the other hand, a system is provided comprising the composition as previously described, including embodiments, and a first device configured to perform DNA amplification. In embodiments, the first device is configured to perform Sanger sequencing, ion semiconductor sequencing, capillary electrophoresis, or high-resolution melt analysis. In embodiments, the system further comprises a second device configured to compare and / or analyze nucleic acid fragments generated by amplifying DNA using primers.

[0025] On the other hand, a kit is provided comprising a buffer and at least one primer pair for amplifying microsatellite loci, said primer pair comprising a first primer and a second primer. In embodiments, the microsatellite loci comprise BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B and / or ABI-19.

[0026] In embodiments, the at least one primer pair comprises at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, or at least 12 or at least 13 primer pairs. In embodiments, the at least one primer pair comprises at least one primer having a polynucleotide sequence having any one of SEQ ID NO.: 1-26. In embodiments, the at least one primer pair comprises 13 primer pairs having a polynucleotide sequence having each of SEQ ID NO.: 1-26. In embodiments, the kit further comprises primer pairs for amplifying an identification marker. In embodiments, the identification marker comprises PENTAD and / or TH01.

[0027] In the embodiments, the polynucleotide sequences of the first primer and the second primer comprise one of the following pairs: SEQ ID NO.: 1 and SEQ ID NO.: 2; SEQ ID NO.: 3 and SEQ ID NO.: 4; SEQ ID NO.: 5 and SEQ ID NO.: 6; SEQ ID NO.: 7 and SEQ ID NO.: 8; SEQ ID NO.: 9 and SEQ ID NO.: 10; SEQ ID NO.: 11 and SEQ ID NO.: 12; SEQ ID NO.: 13 and SEQ ID NO.: 14; SEQ ID NO.: 15 and SEQ ID NO.: 16; SEQ ID NO.: 17 and SEQ ID NO.: 18; SEQ ID NO.: 19 and SEQ ID NO.: 18. The polynucleotide sequences of SEQ ID NO. 20; SEQ ID NO. 21 and SEQ ID NO. 22; SEQ ID NO. 23 and SEQ ID NO. 24; SEQ ID NO. 25 and SEQ ID NO. 26.

[0028] In an embodiment, all primers of the primer pair are contained in the same container. In an embodiment, the kit contains primers having a polynucleotide sequence containing each of SEQ ID NO.: 1-26. In an embodiment, the kit further contains a polymerase and / or multiple deoxynucleoside triphosphates. In an embodiment, the buffer is a PCR buffer. In an embodiment, at least one primer from the primer set contains a modification. In an embodiment, the modification is a detectable marker. In an embodiment, the kit further contains a computer program for identifying microsatellite instability in biological samples.

[0029] Embodiments of the present invention for detecting microsatellite instability in biological samples are disclosed. Signal data is received from a capillary electrophoresis genetic analysis instrument, wherein the signal data is determined based on the fluorescence of fragments comprising nucleic acid sequences amplified from the biological sample by polymerase chain reaction. The nucleic acid sequences correspond to multiple different microsatellite loci. Different loci can exhibit different signal characteristics. At a specific locus, a hierarchical structure of analytical methods can be applied, which may also be specific to the characteristics of the signal data at that locus. For example, a three-level hierarchical structure can be described as follows: A first processing algorithm is implemented to obtain a first determination of instability of one or more first microsatellite loci among multiple different microsatellite loci based on the signal data. A second processing algorithm is implemented to obtain a second determination of instability of one or more second microsatellite loci among multiple different microsatellite loci based on the signal data. Then a third processing algorithm is implemented to measure the microsatellite instability of the biological sample based at least on the first determination and the second determination.

[0030] Embodiments of the present invention describe a set of methods for analyzing CE data to determine whether a given DNA locus is abnormal and to determine whether the overall genetic profile (combining results from all loci) can be considered high MSI, low MSI, or MSS. The methods described herein provide a way to automate the invocation process. The described methods can also be used, for example, to assign confidence scores to invocation scores by reporting how close the calculated results are to a decision threshold, which can further be used to focus manual review work on cases where the automated MSI assessment has low confidence.

[0031] The embodiments of the invention disclosed herein describe heterogeneous analysis methods, ranging from simple thresholding to the utilization of deep learning techniques. This is because assigning the overall genetic map to high MSI, low MSI, or stable MSI may involve a single microsatellite locus in the DNA, or even many microsatellite loci within the DNA. The complexity of the analysis algorithm depends on the nature of the DNA replication pattern at the selected locus. Different loci can be selected for different cancers because certain loci may be more sensitive to a given cancer type compared to other cancer types, and / or combinations with other loci may produce more sensitive and / or specific tests for MSI status, and / or the DNA may be amplified more reliably. Attached Figure Description

[0032] Figure 1 A system according to an embodiment of the present invention is shown;

[0033] Figure 2 Exemplary capillary electrophoresis processes used in some embodiments of the present invention are shown;

[0034] Figure 3Exemplary genetic analyzer instruments used in some embodiments of the present invention are shown;

[0035] Figure 4 Shown in Figure 3 An exemplary integrated cylinder used in an exemplary genetic analyzer instrument;

[0036] Figure 5 Exemplary screen snapshots show the user interface display used in some embodiments of the present invention;

[0037] Figure 6 Shown in Figure 3 A flowchart illustrating the cloud integration process of an exemplary genetic analyzer instrument;

[0038] Figure 7 A flowchart illustrating a method according to some embodiments of the present invention is shown;

[0039] Figure 8 A flowchart illustrating alternative methods according to some embodiments of the present invention is provided;

[0040] Figure 9 A block diagram of a distributed computer system that can implement one or more aspects of embodiments of the present invention is shown; and

[0041] Figure 10 A block diagram of an electronic device is shown that can implement one or more aspects of embodiments of the present invention.

[0042] Figure 11 This image shows representative electrophoresis results from 15-fold assays of DNA samples from colorectal cancer (left) or normal tissue (right), with markers spaced apart in the channels. The top row shows results from amplification of loci BAT25, NR24, and NR21. The second row shows results from amplification of loci TH01, BAT40, and CAT25. The third row shows results from amplification of loci NR22, NR27, ABI19, and ABI20B. The fourth row shows results from amplification of loci PentaD. The bottom row shows results from amplification of loci ABI17, ABI16, BAT26, and ABI20A. Loci are represented by gray bars on each trace, and the division between each trace is indicated by red triangles on the X-axis.

[0043] Figure 12A This table compares the results of the MSI assay described herein with those of a competitor (ProMega) on endometrial cancer samples.

[0044] Figure 12BThe trace profiles show a clear offset across different types of markers: 20bp (ABI-20A and ABI-20B) versus 40bp (BAT-40) homopolymers.

[0045] Figure 13 A synthetic construct that reveals the complexity of the detection is shown.

[0046] Figure 14 This is a graph of tumor-only analysis with >98% specificity and >90% sensitivity at 5 bpd.

[0047] Figure 15 This is a graph of tumor-normal analysis with >95% specificity and sensitivity at ≥3 bdp.

[0048] Figure 16 This is an ABI MSI software diagram showing the automatic recall and reporting of normal and tumor colon samples at BAT-25, NR-24, and NR-21 (top) and all 15 loci (bottom).

[0049] Although the invention has been described with reference to the above figures, the figures are intended to be illustrative, and other embodiments are consistent with the spirit of the invention and are within the scope of the invention. Detailed Implementation

[0050] After reading this specification, it will become apparent to those skilled in the art how this disclosure can be implemented in various alternative embodiments and applications. However, not all embodiments of the invention will be described herein. It will be understood that the embodiments presented herein are given by way of example only and not by way of limitation. Thus, this detailed description of the various alternative embodiments should not be construed as limiting the scope or breadth of the disclosure as set forth herein.

[0051] Before disclosing and describing the technology of this invention, it should be understood that the aspects described below are not limited to specific compositions, methods of preparing such compositions, or their uses, and therefore these aspects are naturally subject to variation. It should also be understood that the terminology used herein is for the purpose of describing particular aspects only and is not intended to be limiting.

[0052] The detailed description has been divided into sections for the reader's convenience only, and disclosures found in any section may be combined with disclosures in another section. Headings or subheadings may be used in the specification for the reader's convenience, and are not intended to affect the scope of this disclosure.

[0053] definition

[0054] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. In this specification and the following embodiments, reference will be made to several terms, which shall be defined as having the following meanings:

[0055] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a” and “the” are intended to include the plural forms as used herein.

[0056] "Optional" or "optionally" means that the event or situation described below may or may not occur, and the description includes instances where the event or situation occurs as well as instances where the event or situation does not occur.

[0057] When used before numerical specifications encompassing ranges, such as temperature, time, amount, concentration, and others, the term "about" indicates an approximate value that can vary (+) or (-) 10%, 5%, 1%, or any subrange or subvalue within that range. Preferably, when used with respect to dosage, the term "about" means that the dosage can vary by + / - 10%.

[0058] The terms "comprising" or "comprises" are intended to mean that a composition and method includes the described elements but does not exclude other elements. When used to define compositions and methods, "consisting essentially of" should mean excluding other elements that are of any significance to the combination for the stated purpose. Therefore, a composition consisting essentially of elements as defined herein will not exclude other materials or steps that do not materially affect the essential and novel characteristics of the claimed invention. "Consisting of" should mean excluding other components in greater quantities than trace amounts and numerous method steps. Examples defined by each of these transitional terms are within the scope of this disclosure.

[0059] As used herein, the term "cancer" refers to all types of cancer, tumors, or malignant tumors found in mammals (e.g., humans), including leukemia, lymphoma, carcinoma, and sarcoma. Exemplary cancers that can be treated with the compounds or methods provided herein include brain cancer, glioma, glioblastoma, neuroblastoma, prostate cancer, colorectal cancer, pancreatic cancer, medulloblastoma, melanoma, cervical cancer, gastric cancer, ovarian cancer, lung cancer, head cancer, Hodgkin's disease, and non-Hodgkin's lymphomas. Exemplary cancers that can be treated with the compounds or methods provided herein include thyroid cancer, endocrine system cancer, brain cancer, breast cancer, cervical cancer, colon cancer, head and neck cancer, liver cancer, kidney cancer, lung cancer, ovarian cancer, pancreatic cancer, rectal cancer, gastric cancer, and uterine cancer. Other examples include thyroid cancer, bile duct cancer, pancreatic cancer, malignant melanoma of the skin, colonic adenocarcinoma, rectal adenocarcinoma, gastric adenocarcinoma, esophageal cancer, squamous cell carcinoma of the head and neck, invasive breast cancer, lung adenocarcinoma, squamous cell carcinoma of the lung, non-small cell lung cancer, mesothelioma, multiple myeloma, neuroblastoma, glioma, glioblastoma multiforme, ovarian cancer, rhabdomyosarcoma, essential thrombocytosis, essential macroglobulinemia, primary brain tumor, malignant pancreatic islet tumor, malignant carcinoid tumor, urobladder cancer, precancerous skin lesions, testicular cancer, thyroid cancer, neuroblastoma, esophageal cancer, urogenital tract cancer, malignant hypercalcemia, endometrial cancer, adrenocortical carcinoma, endocrine or exocrine pancreatic tumors, medullary thyroid cancer, medullary thyroid carcinoma, melanoma, colorectal cancer, papillary thyroid carcinoma, hepatocellular carcinoma, or prostate cancer.

[0060] The term “leukemia” broadly refers to a progressive malignant disease of the blood-forming organs and is typically characterized by abnormal proliferation and development of leukocytes and their precursors in the blood and bone marrow. Leukemia is usually classified clinically based on the following: (1) the duration and characteristics of the acute or chronic disease; (2) the type of cells involved; myeloid, lymphoid, or monocytic; and (3) an increase or non-increase in the number of abnormal cells in the blood – leukemic or non-leukemic (subleukemic). Exemplary leukemias that can be treated with the compounds or methods provided herein include, for example, acute non-lymphocytic leukemia, chronic lymphocytic leukemia, acute myeloid leukemia, chronic myeloid leukemia, acute promyelocytic leukemia, adult T-cell leukemia, aleukemic leukemia, leukocytic leukemia, basophilic leukemia, blastic leukemia, bovine leukemia, chronic myeloid leukemia, cutaneous leukemia, embryonal leukemia, eosinophilic leukemia, Gross' leukemia, hairy cell leukemia, hemoblastic leukemia, and hemocytoblastic leukemia. Leukemia, histiocytic leukemia, stem cell leukemia, acute monocytic leukemia, leukopenic leukemia, lymphocytic leukemia, lymphoblastic leukemia, lymphocytic leukemia, lymphogenous leukemia, lymphoid leukemia, lymphosarcoma cell leukemia, mast cell leukemia, megakaryocytic leukemia, micromyeloblastic leukemia, monocytic leukemia, myeloid leukemia, myeloid granulocytic leukemia, myelomonocytic leukemia, Naegeli leukemia, plasma cell leukemia, multiple myeloma, plasma cell leukemia, promyelocytic leukemia, Rieder cell leukemia, Schilling's leukemia Leukemia, stem cell leukemia, subleukemic leukemia, and undifferentiated cell leukemia.

[0061] As used herein, the term "lymphoma" refers to a group of cancers that affect hematopoietic and lymphatic tissues. It begins in lymphocytes (blood cells primarily found in lymph nodes, spleen, thymus, and bone marrow). The two main types of lymphoma are non-Hodgkin's lymphoma and Hodgkin's disease. Hodgkin's disease accounts for approximately 15% of all diagnosed lymphomas. This is a cancer associated with Reed-Sternberg malignant B lymphocytes. Non-Hodgkin's lymphoma (NHL) can be classified based on the cancer's growth rate and the cell types involved. Aggressive (high-grade) and indolent (low-grade) types of NHL exist. Based on the cell types involved, there are B-cell and T-cell NHL. Exemplary B-cell lymphomas that can be treated with the compounds or methods provided herein include, but are not limited to, small lymphocytic lymphoma, mantle cell lymphoma, follicular lymphoma, marginal zone lymphoma, extranodal (MALT) lymphoma, nodular (monocyte-like B-cell) lymphoma, splenic lymphoma, diffuse large cell B-cell lymphoma, Burkitt's lymphoma, lymphoblastic lymphoma, immunoblastic large cell lymphoma, or precursor B-cell lymphoblastic lymphoma. Exemplary T-cell lymphomas that can be treated with the compounds or methods provided herein include, but are not limited to, cunateous T-cell lymphoma, peripheral T-cell lymphoma, anaplastic large cell lymphoma, mycosis fungoides, and precursor T-cell lymphoblastic lymphoma.

[0062] The term "sarcoma" generally refers to a tumor composed of material similar to embryonic connective tissue and typically consists of tightly packed cells embedded in filamentous or homogeneous material. Sarcomas that can be treated with the compounds or methods provided in this article include chondrosarcoma, fibrosarcoma, lymphosarcoma, melanosarcoma, myxosarcoma, osteosarcoma, Abemethy's sarcoma, liposarcoma, liposarcoma, alveolar soft tissue sarcoma, ameloblastic sarcoma, botryoid sarcoma, green carcinosarcoma, choriocarcinoma, embryonal sarcoma, Wilms' tumor sarcoma, endometrial sarcoma, stromal sarcoma, Ewing's sarcoma, fascial sarcoma, fibroblastic sarcoma, giant cell sarcoma, granulocytic sarcoma, Hodgkin's sarcoma, idiopathic multiple pigmented hemorrhagic sarcoma, B-cell immunoblastic sarcoma, lymphoma, T-cell immunoblastic sarcoma, Jensen's sarcoma, and Kaposi's sarcoma. Sarcoma, Kupffer cell sarcoma, angiosarcoma, leukemic sarcoma, malignant stromal sarcoma, extraperiosteal sarcoma, reticulum cell sarcoma, Rous sarcoma, serocystic sarcoma, synovial sarcoma, or capillary dilatational sarcoma.

[0063] The term "melanoma" refers to a tumor caused by the melanocyte system of the skin and other organs. Melanomas that can be treated with the compounds or methods provided herein include, for example, acral lentigines melanoma, amelanoma, benign juvenile melanoma, Cloudman's melanoma, S91 melanoma, Harding-Passey melanoma, juvenile melanoma, malignant lentigines, malignant melanoma, nodular melanoma, subungual melanoma, or superficial diffuse melanoma.

[0064] The term "cancer" refers to a malignant new growth composed of epithelial cells that tend to infiltrate surrounding tissues and cause metastasis. Exemplary cancers that can be treated with the compounds or methods provided herein include, for example, medullary thyroid carcinoma, familial medullary thyroid carcinoma, acinar carcinoma, acinar carcinoma, adenoid cystic carcinoma, adenocarcinoma, adrenocortical carcinoma, alveolar carcinoma, alveolar cell carcinoma, basal cell carcinoma, basoid cell tumor, basal cell-like carcinoma, basal squamous cell carcinoma, bronchioloalveolar carcinoma, bronchiolar carcinoma, bronchial carcinoma, brain carcinoma, cholangiocarcinoma, choriocarcinoma, colloid carcinoma, comedo carcinoma, uterine endometrial cancer, cribriform carcinoma, armored carcinoma, carcinoma cutaneum, columnar carcinoma, columnar cell carcinoma, tubular carcinoma, sclerosing carcinoma, embryonal carcinoma, medullary carcinoma, epidermoid carcinoma, adenoid epithelial cell carcinoma, explant carcinoma, ulcerative carcinoma, fibrocarcinoma, colloid carcinoma, and gelatinous carcinoma. Carcinoma, giant cell carcinoma, adenocarcinoma, granular cell carcinoma, hair-matrix carcinoma, hematoid carcinoma, hepatocellular carcinoma, Hurthle cell carcinoma, hyaline carcinoma, adrenal carcinoma, naive embryonal carcinoma, carcinoma in situ, intraepithelial carcinoma, intraepithelial carcinoma, Krompecher's carcinoma, Kulchitzky-cell carcinoma, large cell carcinoma, lenticular carcinoma, carcinoma lenticulare, lipomatous carcinoma, lymphoepithelial carcinoma, medullary carcinoma, medullary carcinoma Carcinoma, melanoma, soft carcinoma, mucinous carcinoma, mucinous carcinoma, mucocellular carcinoma, mucoepidermoid carcinoma, mucinous mucosum, mucinous carcinoma, myxomatous carcinoma, nasopharyngeal carcinoma, oat cell carcinoma, ossificans carcinoma, osteoid carcinoma, papillary carcinoma, periportal carcinoma, preinvasive carcinoma, acanthosis nigra, pultaceous carcinoma, renal cell carcinoma, reserve cell carcinoma, sarcomatoid carcinoma, Schneider's carcinoma.Carcinoma, scleroderma, scrotal carcinoma, signet ring cell carcinoma, simple carcinoma, small cell carcinoma, potato carcinoma, spherical cell carcinoma, spindle cell carcinoma, medullary carcinoma, squamous cell carcinoma, ligamentous carcinoma, angiomyodermal carcinoma, telangiectodes carcinoma, transitional cell carcinoma, tuberosum carcinoma, tuberous carcinoma, verrucous carcinoma, or villous carcinoma.

[0065] As used herein, the terms “metastasis,” “metastatic,” and “metastatic cancer” are used interchangeably and refer to the spread of a proliferative disease or condition (e.g., cancer) from one organ to another non-adjacent organ or body part. “Metastatic cancer” is also referred to as “stage IV cancer.” Cancer begins at a site of origin (e.g., the breast), which is called the primary tumor, such as primary breast cancer. Some cancer cells in the primary tumor or site of origin acquire the ability to penetrate and infiltrate the surrounding normal tissue and / or penetrate the walls of the lymphatic or vascular systems that circulate systemically to other parts and tissues in the body. A second, clinically detectable tumor formed from cancer cells of the primary tumor is called a metastatic or secondary tumor. When cancer cells metastasize, it is presumed that the metastatic tumor and its cells resemble the primary tumor. Therefore, if lung cancer metastasizes to the breast, the secondary tumor in the breast site consists of abnormal lung cells rather than abnormal breast cells. A secondary tumor in the breast refers to metastatic lung cancer. Therefore, the phrase metastatic cancer refers to a disease in which a subject has or has had a primary tumor and has one or more secondary tumors. The phrase "non-metastatic cancer" or "an individual with non-metastatic cancer" refers to a disease in which an individual has a primary tumor but no one or more secondary tumors. For example, metastatic lung cancer refers to a disease in an individual who has a primary lung tumor or a history of a primary lung tumor and has one or more secondary tumors in a second or more locations (e.g., in the breast).

[0066] The term "treating" or "treatment" refers to any indicator of successful treatment or improvement of an injury, disease, pathology, or symptom, including any objective or subjective parameters such as relief; alleviation; reduction of symptoms or making the injury, pathology, or symptom more tolerable for the patient; slowing the rate of degeneration or decline; or reducing the final point of degeneration; or improving the patient's physical or mental health. Treatment or improvement of symptoms can be based on objective or subjective parameters; and may include the results of physical examination, neuropsychiatric examination, and / or psychiatric evaluation. The term "treatment" and its adjuncts can include prevention of injury, pathology, symptom, or disease. In this embodiment, treatment is prevention. In this embodiment, treatment does not include prevention.

[0067] As used herein (and as fully understood in the art), “treatment” or “curative action” also broadly includes any method used to obtain a beneficial or desired outcome (including clinical outcomes) in a subject’s condition. Beneficial or desired clinical outcomes may include, but are not limited to: relief or improvement of one or more symptoms or conditions; reduction of the severity of the disease; stabilization (i.e., non-deterioration) of the disease state; prevention of the spread or diffusion of the disease; delay or slowing the progression of the disease; improvement or remission of the disease state; reduction of disease recurrence; and remission, whether partial or complete, and whether detectable or undetectable. In other words, as used herein, “treatment” includes any cure, improvement, or prevention of a disease. Treatment may prevent the onset of disease; inhibit the spread of disease; relieve the symptoms of disease; completely or partially eliminate the root cause of disease; shorten the duration of disease; or a combination of these.

[0068] "Patient" or "subject in need" means a living organism that suffers from or is susceptible to a disease or symptom that can be treated by administration of the pharmaceutical compositions provided herein. Non-limiting examples include humans, other mammals, bovine animals, rats, mice, dogs, monkeys, goats, sheep, cattle, deer, and other non-mammals. In some embodiments, the patient is a human.

[0069] "Effective amount" is the amount of a compound sufficient to achieve its stated purpose (e.g., to achieve its applied effect, treat a disease, reduce enzyme activity, increase enzyme activity, reduce signal transduction pathways, or reduce one or more symptoms of a disease or condition) relative to the absence of the compound. Examples of "effective amount" are amounts sufficient to induce treatment, prevention, or reduction of one or more symptoms of a disease; this amount may also be referred to as a "therapeutic effective amount." "Reduction" of one or more symptoms (and its grammatical equivalent) means a reduction in the severity or frequency of one or more symptoms, or the elimination of one or more symptoms. A "preventive effective amount" of a drug is the amount of drug that, when administered to a subject, will have the intended preventive effect, such as preventing or delaying the onset (or recurrence) of an injury, disease, pathology, or condition, or reducing the likelihood of the onset (or recurrence) of an injury, disease, pathology, or condition or its symptoms. A complete preventive effect does not necessarily occur with a single dose and can occur after only a series of doses. Therefore, a preventive effective amount can be administered in the form of a single or multiple doses. As used herein, "activity-reducing amount" refers to the amount of antagonist required to reduce enzyme activity relative to the absence of an antagonist. As used herein, “functionally disruptive amount” refers to the amount of antagonist required to disrupt the function of an enzyme or protein, relative to the absence of an antagonist. The precise amount will depend on the therapeutic purpose and will be determined by a person skilled in the art using known techniques (see, for example, Lieberman, Pharmaceutical Dosage Forms). Pharmaceutical Dosage Forms ) (Volumes 1-3, 1992); Lloyd, The Art, Science and Technique of Pharmaceutical Mixing ( The Art, Science and Technology of Pharmaceutical Compounding (1999); Pickar, "Dosage Calculation ( Dosage Calculations (1999); and Remington: Medical Science and Practice ( Remington: The Science and Practice of Pharmacy ( ), 20th edition, 2003, edited by Gennaro, Lippincott Williams Lippincott, Williams & Wilkins.

[0070] As used herein, the term "therapeutic effective dose" refers to an amount of therapeutic agent sufficient to improve the condition, as described above. For example, for a given parameter, the therapeutic effective dose will show an increase or decrease of at least 5%, 10%, 15%, 20%, 25%, 40%, 50%, 60%, 75%, 80%, 90%, or at least 100%. Therapeutic efficacy can also be expressed as an increase or decrease in "multiples." For example, the therapeutic effective dose may have an effect of at least 1.2 times, 1.5 times, 2 times, 5 times, or more compared to the control.

[0071] Dosage can vary depending on the patient's and the compound's requirements. In the context of this disclosure, the dose administered to the patient should be sufficient to produce a beneficial therapeutic response over time. The magnitude of the dose will also be determined by the presence, nature, and extent of any adverse side effects. The determination of the appropriate dose for a particular situation is within the skill of a practicing physician. Treatment typically begins with a smaller dose than the optimal dose of the compound. Thereafter, the dose is increased in small increments until optimal efficacy is achieved in multiple situations. The amount and interval of administration can be individually adjusted to provide a level of efficacy of the administered compound for the specific clinical indication being treated. This will provide a treatment regimen commensurate with the severity of the individual's disease state.

[0072] As used herein, the term "administration" means oral administration to a subject, administration in suppository form, local contact, intravenous, parenteral, intraperitoneal, intramuscular, intralesional, intrathecal, intrathecal, intranasal, or subcutaneous administration, or administration via implantation of a slow-release device (e.g., a microosmotic pump). Administration via any route includes parenteral and transmucosal (e.g., buccal, sublingual, palatal, gingival, nasal, vaginal, rectal, or percutaneous) administration. Parenteral administration includes, for example, intravenous, intramuscular, intraarterial, intradermal, subcutaneous, intraperitoneal, intravenous, and intracranial administration. Other delivery modalities include, but are not limited to, the use of liposome formulations, intravenous infusion, percutaneous patches, etc. In the embodiments, administration does not include the administration of any active agent other than the described active agents.

[0073] As may be used herein, the terms “nucleic acid,” “nucleic acid molecule,” “nucleic acid oligomer,” “oligonucleotide,” “nucleic acid sequence,” “nucleic acid fragment,” and “polynucleotide” are used interchangeably and are intended to include, but not limited to, polymeric forms of nucleotides covalently linked together, which may have various lengths and are deoxyribonucleotides or ribonucleotides or analogs, derivatives, or modifications thereof. Different polynucleotides may have different three-dimensional structures and may perform a variety of known or unknown functions. Non-limiting examples of polynucleotides include genes, gene fragments, exons, introns, intergenic DNA (including but not limited to heterochromatic DNA), messenger RNA (mRNA), transfer RNA, ribosomal RNA, ribozymes, cDNA, recombinant polynucleotides, branched-chain polynucleotides, plasmids, vectors, sequence-isolated DNA, sequence-isolated RNA, nucleic acid probes, and primers. Polynucleotides that may be used in the methods of this disclosure may include natural nucleic acid sequences and their variants, artificial nucleic acid sequences, or combinations of such sequences.

[0074] Polynucleotides are typically composed of a specific sequence of four nucleotide bases: adenine (A); cytosine (C); guanine (G); and thymine (T) (uracil (U) for thymine (T) when the polynucleotide is RNA). Therefore, the term "polynucleotide sequence" is a letter representation of a polynucleotide molecule; alternatively, the term can be applied to the polynucleotide molecule itself. This letter representation can be entered into a database in a computer with a central processing unit and used for bioinformatics applications such as functional genomics and homology searches. Polynucleotides may optionally contain one or more non-standard nucleotides, one or more nucleotide analogs, and / or modified nucleotides.

[0075] As used herein, the terms “amplified DNA fragment” or “amplified fragment including nucleic acid sequence” refer to a polynucleotide sequence produced by in vitro amplification methods, such as polymerase chain reaction (PCR), isothermal amplification, strand displacement amplification, or any other DNA amplification method.

[0076] The term "microsatellite locus" or "microsatellite loci" refers to a locus in the genome of an organism containing microsatellites. A microsatellite is a repetitive segment of DNA in which certain DNA motifs (usually one to six or more base pairs) are repeated, typically 5 to 50 times. Microsatellites occur at thousands of locations in the genome of an organism.

[0077] As used herein, the term "identification marker" refers to a locus that can be used to identify a DNA sample. An identification marker can be any locus that exhibits allelic variability in a population, such that the allelic variability can be distinguished by the amplification used. Typically, such identification markers are short tandem repeat (STR) polymorphisms, and these polymorphisms can be distinguished based on the length of the STR. For example, an identification marker can be any locus used in forensic DNA profiling, paternity testing, or similar methods. Such identification markers include, but are not limited to, amelogenin, CSF1PO, D13S317, D16S539, D18S51, D21S11, D3S1358, D5S818, D7S820, D8S1179, FGA, PentaD, PentaE, TH01, TPOX, and vWA. In this embodiment, the identification marker is a single nucleotide polymorphism (SNP). In the embodiments, the length of the fragments including the nucleic acid sequences amplified from the identification markers does not change or shows a small degree of change in cancers exhibiting MSI.

[0078] MSI testing

[0079] Clinical researchers are increasingly using MSI assessments for a variety of purposes, including: 1) evaluating the effectiveness of cancer immunotherapy options; and 2) providing information for the diagnosis of a neoplastic genetic syndrome known as Lynch Syndrome (Vaksman and Garner, 2015). Users indicate that current market solutions are insufficient for testing multiple cancer types, are slow to analyze, and have cumbersome data reporting. The proposed microsatellite instability assay aims to address these issues by developing products sensitive to multiple cancer types and simplifying data analysis through automated genotyping.

[0080] MSI status has been used as a predictive biomarker for cancer immunotherapy. Microsatellite instability is found at varying frequencies in many cancer types due to hereditary germline mutations in mismatch repair genes or epigenetic inactivation of these genes. Tumors with the highest rates of MSI include endometrial cancer of the uterine corpus, colorectal adenocarcinoma, and gastric adenocarcinoma (Cortes-Ciriano et al., 2017).

[0081] Lynch syndrome is the most common hereditary susceptibility syndrome for colorectal cancer (CRC). It accounts for approximately 3-5% of newly diagnosed CRC cases and 2-3% of endometrial cancer cases. The American Society of Clinical Oncology recommends tumor testing for Lynch syndrome in all individuals diagnosed with colorectal cancer. Recent guidelines recommend the same for all endometrial cancers. Screening tests can be performed on tumor tissue to determine the likelihood of Lynch syndrome. One testing approach is to analyze MSI (Mean Sequencing Indication). The results of MSI testing can indicate whether more specific genetic testing should be considered. Recent results indicate that 16% of all cancers classified as MSI-H (high MSI) are associated with Lynch syndrome, and broader MSI testing is needed regardless of tumor type or family history (Latham et al., 2019).

[0082] Fragment analysis is commonly used to assess MSI status. Fragment analysis applications are those that use dye-labeled primers designed for a specific query task to generate fluorescent DNA fragments via PCR. These fragments are then separated using capillary electrophoresis and their size is determined by comparison with size standards. MSI analysis via fragment analysis follows the same paradigm; fluorescently labeled primers are used to amplify the microsatellite loci of interest via PCR. The labeled PCR products are then analyzed by capillary electrophoresis (CE) or electrophoresis to separate alleles by size.

[0083] When the proportion of DNA with microsatellites that differ from normal molecules is low, it is difficult to detect the presence of abnormal DNA molecules. More accurate methods are needed to analyze CE data to resolve uncertainties sufficiently to reliably distinguish between high and stable MSI at a given DNA locus and to determine whether the overall genetic map can be considered high or low MSI.

[0084] There are possible alternatives to using CE fragment analysis. In a simple example, sequencing technology can be used to sequence the DNA loci of interest and assign MSI states through sequence analysis (e.g., counting the number of microsatellites in the sequence). However, using sequencing technologies or similar methods other than CE fragment analysis can be disadvantageous. For example, DNA sequence analysis has limited capacity for multiplexing data. Additionally, DNA sequence analysis is time-consuming and more prone to errors.

[0085] On one hand, a method for detecting microsatellite instability (MSI) in a DNA sample is provided. On the other hand, a method for analyzing a DNA sample to determine the microsatellite instability (MSI) in the DNA sample is provided. On another hand, a method for diagnosing the presence of cancerous tissue in a biological sample is provided. On yet another hand, a method for treating cancer in a subject who has or is suspected of having cancer is provided. On yet another hand, a method for diagnosing cancer in a subject who has or is suspected of having cancer is provided.

[0086] In an embodiment, the method comprises: a) co-amplifying multiple microsatellite loci of a DNA sample to generate an amplified fragment comprising a nucleic acid sequence from each locus; b) determining the size of the amplified fragment from each locus; and c) comparing the size of the amplified fragment from each locus with the size of a corresponding amplified fragment from a control. In an embodiment, the multiple loci comprise at least one locus selected from the group consisting of BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In an embodiment, the size difference between one or more amplified fragments between a sample and a control indicates the presence of MSI at the corresponding locus in the DNA sample or biological sample.

[0087] On the other hand, a method is provided for analyzing amplified fragments comprising nucleic acid sequences to determine microsatellite instability (MSI), the method comprising: a) providing amplified fragments amplified from multiple microsatellite loci in a DNA sample or a biological sample; b) determining the size of the amplified fragments; c) comparing the size of the amplified fragments in step b) with the size of corresponding amplified fragments from paired normal DNA samples or paired normal biological samples, wherein size differences between one or more amplified fragments between the samples indicate the presence of MSI in the DNA sample; and d) assigning an MSI degree to the DNA sample, thereby determining the MSI state of the DNA sample.

[0088] In this embodiment, the size difference between one or more amplified fragments between a sample and a control indicates the presence of microsatellite instability (MSI) at the corresponding locus in the DNA sample. In this embodiment, the presence of MSI in the DNA sample indicates that the biological sample from which the DNA sample originated contains cancerous tissue.

[0089] In an embodiment, the method further comprises assigning an MSI level to the DNA sample. In an embodiment, if more than about 30% of the loci in the DNA sample are found to have MSI, the DNA sample is assigned a high MSI level (high microsatellite instability). In an embodiment, if less than about 30% but more than about 1% of the loci in the DNA sample are found to have MSI, the DNA sample is assigned a low MSI level (low microsatellite instability). In an embodiment, if no loci in the DNA sample are found to have MSI, the DNA sample is assigned a stable level (microsatellite stable). For example, when a total of 13 loci are amplified, DNA samples in which at least 4 (or at least 3) loci are found to have MSI are assigned a high MSI level (i.e., MSI-high); DNA samples in which at least 1 but less than 4 (or less than 3) loci are found to have MSI are assigned a low MSI level (i.e., MSI-low); and DNA samples in which 0 loci are found to have MSI are assigned a stable MSI level (i.e., MSI-stable).

[0090] In one embodiment, the presence of MSI in a DNA sample indicates that the subject has cancer. In another embodiment, the method includes administering an anticancer agent to the subject with cancer.

[0091] In this embodiment, the primers used to amplify the loci contain modifications. In this embodiment, each locus is amplified using primer pairs, and at least one primer in the primer pairs contains a modification. In this embodiment, the modification may be a migration modifier, such as polyethylene glycol (PEG), locked nucleic acid (LNA), a 3'-minor groove binding agent, or the addition of a non-specific nucleic acid to one end of the primer sequence. In this embodiment, the amplified fragment contains modifications. In this embodiment, the modification contains a detectable biomarker. Detectable biomarkers include, but are not limited to, fluorescent biomarkers / dyes and radioactive biomarkers. Fluorescent labels / dyes are well known in the art and include, but are not limited to, fluorescein, FAM (carboxyfluorescein) (e.g., 5-FAM, 6-FAM), TET, VIC (2'-chloro-7'-phenyl-1,4-dichloro-6-carboxyfluorescein), HEX, NED, PET, JOE, TET, Cal FluorOrange 560, TAMRA, QUASAR® 570, Cal Fluor Red, ROX™, Texas Red®, Quasar 670, LCRed 640, LC Red 705, SID, TAZ, YY, rhodamine (or derivatives), coumarin (or derivatives), and cyanin (or derivatives, such as Cy2, Cy3, Cy3B, Cy3.5, Cy5, Cy5.5, Cy7) or derivatives of any of these molecules.

[0092] In an embodiment, the method further includes co-amplifying one or more identification biomarkers in step a). In an embodiment, the one or more identification biomarkers include amelogenin, CSF1PO, D13S317, D16S539, D18S51, D21S11, D3S1358, D5S818, D7S820, D8S1179, FGA, PentaD, PentaE, TH01, TPOX, and / or vWA. In an embodiment, the one or more identification biomarkers include PENTAD. In an embodiment, the one or more identification biomarkers include TH01. In an embodiment, the one or more identification biomarkers include both PENTAD and TH01.

[0093] In this embodiment, the term "size comparison" refers to comparing the size or size distribution of nucleic acid fragments. Comparisons can be made by any method, such as gel electrophoresis, capillary electrophoresis, DNA sequencing, microscopic visualization (e.g., adsorption grid electron microscopy visualization or Kleinschmidt electron microscopy visualization), etc. Comparisons can be performed, for example, by visualization of fragment sizes and / or by computer-implemented programs.

[0094] In one embodiment, the plurality of loci comprise at least two loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In another embodiment, the plurality of loci comprise at least three loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In one embodiment, the plurality of loci comprise at least four loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In another embodiment, the plurality of loci comprise at least five loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In one embodiment, the plurality of loci comprise at least six loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In another embodiment, the plurality of loci comprise at least seven loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In one embodiment, the plurality of loci comprise at least eight loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In another embodiment, the plurality of loci comprise at least nine loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In the embodiments, the plurality of loci include at least 10 loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B and ABI-19.In one embodiment, the multiple loci comprise at least 11 loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In another embodiment, the multiple loci comprise at least 12 loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19. In yet another embodiment, the multiple loci comprise BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19.

[0095] In one embodiment, multiple loci include BAT25. In one embodiment, multiple loci include BAT26. In one embodiment, multiple loci include BAT40. In one embodiment, multiple loci include CAT25. In one embodiment, multiple loci include NR21. In one embodiment, multiple loci include NR22. In one embodiment, multiple loci include NR24. In one embodiment, multiple loci include NR27. In one embodiment, multiple loci include ABI-20A. In one embodiment, multiple loci include ABI-17. In one embodiment, multiple loci include ABI-16. In one embodiment, multiple loci include ABI-20B. In one embodiment, multiple loci include ABI-19.

[0096] In this embodiment, the DNA sample is derived from a biological sample. In this embodiment, the biological sample comprises tumor cells, suspected cancerous cells, or other suspected cancerous or cancerous biological material.

[0097] In this embodiment, the control is a paired normal DNA sample, a DNA sample from non-cancerous tissue, DNA from a blood sample, or a value based on the mean or median of a normal population. In this embodiment, the term "normal" refers to a DNA sample from non-cancerous tissue. In this embodiment, the term "normal" refers to a DNA sample from non-cancerous tissue adjacent to cancerous tissue.

[0098] In this embodiment, one or more primers selected from SEQ ID NO.: 1-26 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 1 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 2 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 3 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 4 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 5 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 6 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 7 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 8 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 9 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 10 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 11 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 12 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 13 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 14 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 15 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 16 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 17 are used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 18 were used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 19 were used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 20 were used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 21 were used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 22 were used to co-amplify the microsatellite locus.In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 23 were used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 24 were used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 25 were used to co-amplify the microsatellite locus. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 26 were used to co-amplify the microsatellite locus.

[0099] In this embodiment, a primer pair containing a first primer and a second primer is used to co-amplify the microsatellite locus. In the embodiments, the polynucleotide sequences of the first primer and the second primer (each) comprise one of the following pairs: SEQ ID NO.: 1 and SEQ ID NO.: 2; SEQ ID NO.: 3 and SEQ ID NO.: 4; SEQ ID NO.: 5 and SEQ ID NO.: 6; SEQ ID NO.: 7 and SEQ ID NO.: 8; SEQ ID NO.: 9 and SEQ ID NO.: 10; SEQ ID NO.: 11 and SEQ ID NO.: 12; SEQ ID NO.: 13 and SEQ ID NO.: 14; SEQ ID NO.: 15 and SEQ ID NO.: 16; SEQ ID NO.: 17 and SEQ ID NO.: 18; SEQ ID NO.: 19 and SEQ ID NO.: 19. The polynucleotide sequences of SEQ ID NO. 20; SEQ ID NO. 21 and SEQ ID NO. 22; SEQ ID NO. 23 and SEQ ID NO. 24; SEQ ID NO. 25 and SEQ ID NO. 26.

[0100] In this embodiment, one or more primers selected from SEQ ID NO.: 27-31 are used for co-amplification identification of the biomarker. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 27 are used for co-amplification identification of the biomarker. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 28 are used for co-amplification identification of the biomarker. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 29 are used for co-amplification identification of the biomarker. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 30 are used for co-amplification identification of the biomarker. In this embodiment, primers containing the nucleotide sequence of SEQ ID NO.: 31 are used for co-amplification identification of the biomarker.

[0101] In this embodiment, multiple microsatellite loci are amplified using thermal cycling. In this embodiment, the obtained nucleic acid fragments are analyzed by fragment analysis, Sanger sequencing, ion semiconductor sequencing, or high-resolution melt flow analysis. In this embodiment, the Sanger sequencing is capillary electrophoresis Sanger sequencing.

[0102] In one embodiment, the DNA sample and the paired normal DNA sample are from the same individual. In another embodiment, the paired normal DNA sample is control DNA from non-cancerous tissue. In yet another embodiment, the DNA sample and the paired normal DNA sample are from the same type of tissue.

[0103] The cancer can be any type of cancer. In particular, the cancer can be any cancer associated with MSI. In the embodiments, the cancer is colorectal cancer, gastric cancer, adrenocortical carcinoma, cervical cancer, mesothelioma, or endometrial cancer.

[0104] At a given microsatellite locus, capillary electrophoresis (CE) can be used to measure the number of microsatellites by using fragment analysis. Compared to other methods such as agarose or polyacrylamide gel electrophoresis, automated CE uses fluorescent dyes and performs separation with higher resolution and greater accuracy.

[0105] To perform fragment analysis on a CE system, probes and primers can be designed to side-patch the region of interest. This can be done by attaching a fluorescent dye to primers or probes used with polymerase chain reaction (PCR) to amplify the DNA locus of interest prior to electrophoresis and submit the amplicon to CE. Set-size standards are also available, which are a set of fragments of known size labeled with a different color than the test fragment. The labeled PCR product and the set-size standards are then electrically injected into a capillary. During electrophoresis, when a high voltage is applied between the electrodes, the negatively charged DNA fragment moves from the cathode through the polymer-filled capillary toward the positively charged anode.

[0106] DNA fragment analysis using CE allows for multiplexing, meaning multiple fragments pass through the same capillary in the reaction wells. Smaller fragments typically run faster, while larger fragments run slower. Shortly before reaching the anode, the fluorescently labeled DNA fragments, separated by size, move through the path of a laser beam. This laser beam causes the dye on the fragments to fluoresce at different emission wavelengths. A CCD camera detects the fluorescence, and the fluorescence intensity is digitized, color-coded, and displayed as peaks in the electrophoresis chart. Longer fragments, relative to the shorter ones, will appear in the data later.

[0107] Reagents and kits

[0108] On the other hand, a primer set is provided. The primer set may contain one or more primer pairs, each primer pair containing a first primer and a second primer (e.g., forward and reverse primers). In the embodiments, the polynucleotide sequences of the first primer and the second primer comprise one of the following pairs: SEQ ID NO.: 1 and SEQ ID NO.: 2; SEQ ID NO.: 3 and SEQ ID NO.: 4; SEQ ID NO.: 5 and SEQ ID NO.: 6; SEQ ID NO.: 7 and SEQ ID NO.: 8; SEQ ID NO.: 9 and SEQ ID NO.: 10; SEQ ID NO.: 11 and SEQ ID NO.: 12; SEQ ID NO.: 13 and SEQ ID NO.: 14; SEQ ID NO.: 15 and SEQ ID NO.: 16; SEQ ID NO.: 17 and SEQ ID NO.: 18; SEQ ID NO.: 19 and SEQ ID NO.: 18. The polynucleotide sequences of SEQ ID NO.: 20; SEQ ID NO.: 21 and SEQ ID NO.: 22; SEQ ID NO.: 23 and SEQ ID NO.: 24; SEQ ID NO.: 25 and SEQ ID NO.: 26.

[0109] In an embodiment, at least one primer includes a modification. In an embodiment, at least one primer in each primer pair includes a modification. In an embodiment, the modification includes a detectable marker.

[0110] On the other hand, a composition is provided comprising a primer set of any of the previously described primer sets, including the embodiments described. In the embodiments, the primer set comprises at least 2 primer pairs. In the embodiments, the primer set comprises at least 3 primer pairs. In the embodiments, the primer set comprises at least 4 primer pairs. In the embodiments, the primer set comprises at least 5 primer pairs. In the embodiments, the primer set comprises at least 6 primer pairs. In the embodiments, the primer set comprises at least 7 primer pairs. In the embodiments, the primer set comprises at least 8 primer pairs. In the embodiments, the primer set comprises at least 9 primer pairs. In the embodiments, the primer set comprises at least 10 primer pairs. In the embodiments, the primer set comprises at least 11 primer pairs. In the embodiments, the primer set comprises at least 12 primer pairs. In the embodiments, the composition comprises at least 13 primer pairs.

[0111] In this embodiment, the primer pair comprises one or more polynucleotide sequences of SEQ ID NO.: 1-26. In this embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 1. In this embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 2. In this embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 3. In this embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 4. In this embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 5. In this embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 6. In this embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 7. In this embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 8. In this embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 9. In this embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 10. In this embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 11. In this embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 12. In this embodiment, the primer pair contains the polynucleotide sequence of SEQ ID NO.: 13. In this embodiment, the primer pair contains the polynucleotide sequence of SEQ ID NO.: 14. In this embodiment, the primer pair contains the polynucleotide sequence of SEQ ID NO.: 15. In this embodiment, the primer pair contains the polynucleotide sequence of SEQ ID NO.: 16. In this embodiment, the primer pair contains the polynucleotide sequence of SEQ ID NO.: 17. In this embodiment, the primer pair contains the polynucleotide sequence of SEQ ID NO.: 18. In this embodiment, the primer pair contains the polynucleotide sequence of SEQ ID NO.: 19. In this embodiment, the primer pair contains the polynucleotide sequence of SEQ ID NO.: 20. In this embodiment, the primer pair contains the polynucleotide sequence of SEQ ID NO.: 21. In this embodiment, the primer pair contains the polynucleotide sequence of SEQ ID NO.: 22. In this embodiment, the primer pair contains the polynucleotide sequence of SEQ ID NO.: 23. In this embodiment, the primer pair contains the polynucleotide sequence of SEQ ID NO.: 24. In one embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 25. In another embodiment, the primer pair comprises the polynucleotide sequence of SEQ ID NO.: 26.

[0112] In an embodiment, the primer set further comprises primer pairs for amplifying the identification marker. In an embodiment, the identification marker comprises PENTAD and / or TH01. In an embodiment, the identification marker comprises TH01. In an embodiment, the identification marker comprises PENTAD and TH01. In an embodiment, the primer pair for amplifying PENTAD comprises primers containing one or more polynucleotide sequences of SEQ ID NO.: 27-29. In an embodiment, the primer pair for amplifying TH01 comprises primers containing one or more polynucleotide sequences of SEQ ID NO.: 30-31. In an embodiment, the primers comprise primers containing the nucleotide sequence of SEQ ID NO.: 27. In an embodiment, the primers comprise primers containing the nucleotide sequence of SEQ ID NO.: 28. In an embodiment, the primers comprise primers containing the nucleotide sequence of SEQ ID NO.: 29. In an embodiment, the primers comprise primers containing the nucleotide sequence of SEQ ID NO.: 30. In an embodiment, the primers comprise primers containing the nucleotide sequence of SEQ ID NO.: 31.

[0113] In some embodiments, at least one primer is modified. In some embodiments, the modification includes a detectable marker. In some embodiments, the composition further includes a polymerase. In some embodiments, the composition further includes a plurality of deoxyribonucleotide triphosphates. In some embodiments, the composition further includes a DNA sample. In some embodiments, the composition further includes one or more salts.

[0114] On the other hand, a kit is provided comprising a buffer and a primer set containing at least one primer pair for amplifying microsatellite loci, said primer pair comprising a first primer and a second primer. In embodiments, the microsatellite loci comprise BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and / or ABI-19.

[0115] In some embodiments, the primer set contains at least two primer pairs. In some embodiments, the primer set contains at least three primer pairs. In some embodiments, the primer set contains at least four primer pairs. In some embodiments, the primer set contains at least five primer pairs. In some embodiments, the primer set contains at least six primer pairs. In some embodiments, the primer set contains at least seven primer pairs. In some embodiments, the primer set contains at least eight primer pairs. In some embodiments, the primer set contains at least nine primer pairs. In some embodiments, the primer set contains at least ten primer pairs. In some embodiments, the primer set contains at least eleven primer pairs. In some embodiments, the primer set contains at least twelve primer pairs. In some embodiments, the primer set contains at least thirteen primer pairs. In some embodiments, the primer set contains at least fourteen primer pairs. In some embodiments, the primer set contains at least fourteen primer pairs. In some embodiments, the primer set contains at least one primer having a polynucleotide sequence having any one of SEQ ID NO.: 1-26. In this embodiment, the primer set comprises 13 primer pairs, each primer having a polynucleotide sequence of each of SEQ ID NO.: 1-26. In this embodiment, the primer set is as described above.

[0116] In an embodiment, the primer set further comprises primer pairs for amplifying the identification marker. In an embodiment, the identification marker comprises PENTAD. In an embodiment, the identification marker comprises TH01. In an embodiment, the identification marker comprises both PENTAD and TH01. In an embodiment, the primer set comprises primers having any one or more polynucleotide sequences of SEQ ID NO.: 27-31.

[0117] In the embodiments, the polynucleotide sequences of the first primer and the second primer comprise one of the following pairs: SEQ ID NO.: 1 and SEQ ID NO.: 2; SEQ ID NO.: 3 and SEQ ID NO.: 4; SEQ ID NO.: 5 and SEQ ID NO.: 6; SEQ ID NO.: 7 and SEQ ID NO.: 8; SEQ ID NO.: 9 and SEQ ID NO.: 10; SEQ ID NO.: 11 and SEQ ID NO.: 12; SEQ ID NO.: 13 and SEQ ID NO.: 14; SEQ ID NO.: 15 and SEQ ID NO.: 16; SEQ ID NO.: 17 and SEQ ID NO.: 18; SEQ ID NO.: 19 and SEQ ID NO.: 18. The polynucleotide sequences of SEQ ID NO. 20; SEQ ID NO. 21 and SEQ ID NO. 22; SEQ ID NO. 23 and SEQ ID NO. 24; SEQ ID NO. 25 and SEQ ID NO. 26.

[0118] In an embodiment, one or more primers in the primer set are modified. In an embodiment, at least one primer in each primer pair of the primer set is modified. In an embodiment, the modification includes a detectable marker.

[0119] In this embodiment, all primers in the primer set are contained in the same container. In this embodiment, the kit further comprises a polymerase. In this embodiment, the kit further comprises multiple deoxynucleoside triphosphates. In this embodiment, the buffer is a PCR buffer. In this embodiment, the kit further comprises a computer program for identifying microsatellite instability in biological samples.

[0120] Systems and analytical methods

[0121] On the other hand, a system is provided comprising the composition as previously described, including embodiments, and a first device configured to perform DNA amplification. In embodiments, the first device is configured to perform Sanger sequencing, ion semiconductor sequencing, capillary electrophoresis, or high-resolution melt analysis. In embodiments, the system further comprises a second device configured to compare and / or analyze nucleic acid fragments generated by amplifying DNA using primers.

[0122] On the other hand, a system comprising the composition as previously described, including embodiments, and means configured to compare and / or analyze nucleic acid fragments generated by amplifying DNA using primers is provided.

[0123] Existing solutions involving manual inspection of CE fragment analysis data for MSI state invocation tend to be quite time-consuming and inefficient for limited manual inspection time. The embodiments of the invention discussed herein provide a reasonable method for automating MSI state invocations with very broad coverage in many situations. The described method can also be used, for example, to configure confidence metrics for invocation scores by reporting how close the calculated results are to a decision threshold, which can further be used to focus manual review efforts on cases where the confidence level of the automated MSI assessment is low.

[0124] Various embodiments will now be described more fully below with reference to the accompanying drawings, which form part of the invention and serve as illustrations of specific examples of practical embodiments. However, this specification may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this specification will be thorough and complete, and that these embodiments will fully convey the scope of the invention to those skilled in the art. Furthermore, this specification may embody a method or apparatus. Therefore, any of the various embodiments described herein may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Therefore, the following description should not be considered limiting.

[0125] Figure 1A system 1000 according to an exemplary embodiment of the present invention is illustrated. The DNA fragment analysis process described in embodiments of the invention begins with the extraction of DNA from a tissue sample. Multiple microsatellite DNA loci of interest in one or more nucleic acid samples 111 under investigation can be amplified in a PCR reaction performed in an amplification instrument 112 (e.g., a thermal cycler). Exemplary thermal cyclers used in some embodiments of the invention include the Applied Biosystems ProFlex PCR system, the SimpliAmp thermal cycler, and other thermal cycler systems manufactured by Thermo Fisher Scientific. PCR reactions are performed using a wet chemistry kit 110 containing specially designed fluorescently labeled primers for lateralizing microsatellite loci of interest, such as those described herein. System 1000 includes a capillary electrophoresis-based genetic analyzer instrument (e.g., a sequencer) 101, one or more computers 103, and a user device 108. Exemplary genetic analyzer instruments used in some embodiments of the present invention include the Applied Biosystems SeqStudio genetic analyzer, Models 3500, 3720 and 3130 from Thermo Fisher Scientific, as well as similar capillary electrophoresis-based genetic analyzers manufactured by Thermo Fisher Scientific and other companies.

[0126] like Figure 2 As illustrated in the exemplary process, capillary electrophoresis (CE) is a process 200 for separating ionic fragments by size. In the Thermo Fisher Scientific CE instrument used in some embodiments of the invention, electroinjection is used to inject DNA fragments from solution into each capillary of a capillary array 201 comprising one or more capillaries. During capillary electrophoresis, extension products of the PCR reaction (as well as any other negatively charged molecules, such as salts or unincorporated primers and nucleotides) enter the capillary due to electroinjection. A high voltage applied to the sample forces the negatively charged fragments into the capillary. The extension products are separated by size according to their total charge. The electrophoretic mobility of the sample can be affected by the following operating conditions: buffer type, concentration, and pH; operating temperature; amount of voltage applied; and type of polymer used.

[0127] Shortly before reaching the anode, the size-separated fluorescently labeled DNA fragments move through the path of laser beam 202. The laser beam causes the dye attached to the fragments to fluoresce. The dye signal is separated by diffraction system 203, and the fluorescence is detected by a CCD camera, as shown in 204. Because each dye emits light at a different wavelength when excited by the laser, all colors can be detected and distinguished in a single capillary injection, and thus loci can be detected and differentiated. The fluorescence signal is converted into digital data, which is then stored in a file format compatible with analysis software applications.

[0128] Typically, data from CE instruments presents as a series of fluorescence peaks, rather than a single peak at the precise size of the amplicon expected for a given number of microsatellites. This is due to subtle variations in the amplification of the DNA of interest; the “stuttering” of the involved biomolecular mechanisms can result in amplicon production where the number of microsatellites is slightly more or less than the actual number. Because of this “stuttering,” some uncertainty may exist in determining the number of microsatellites and / or whether the determined number differs from the expected number in normal, non-cancerous tissue.

[0129] In addition to the complexity of the signal received from the CE instrument, a single dye can be used with several different PCR primers targeting different DNA loci. This is because the instrument imposes a limit on the number of different dyes that can be used, and the number of DNA loci of interest may exceed the maximum number of dyes that can be used. If there is a significant difference in amplicon size between a group of loci using the same dye on their respective PCR primers, the fluorescence peaks associated with each locus within those loci will be well separated in the data generated by the CE instrument.

[0130] For implementation Figure 1 The instructions of the CE data analysis algorithm 102 shown reside in a computer program product 104 stored in storage device 105, and these instructions are executable by processor 106. While processor 106 is executing the instructions of computer program product 104, the instructions, or portions thereof, are typically loaded into working memory 109, from which processor 106 can easily access the instructions. In the illustrated embodiment, computer program product 104 is stored in storage device 105 or other non-transitory computer-readable medium (which may comprise a media distribution across different devices and locations). In alternative embodiments, the storage medium is transient.

[0131] In one embodiment, processor 106 actually includes multiple processors, which may include additional working memory (the additional processors and memory are not shown separately), and a graphics processing unit (GPU) including at least several thousand arithmetic logic units supporting massively parallel computing. GPUs are commonly used in deep learning applications because they can perform relevant processing tasks more efficiently than typical general-purpose processors (CPUs). Other embodiments include one or more dedicated processing units that include systolic arrays and / or other hardware arrangements supporting efficient parallel processing. In some embodiments, such dedicated hardware works in conjunction with a CPU and / or a GPU to perform the various processes described herein. In some embodiments, such dedicated hardware includes application-specific integrated circuits (ASICs, which may refer to a portion of an application-specific integrated circuit), field-programmable gate arrays, and combinations thereof. However, in some embodiments, processors such as processor 106 may be implemented as one or more general-purpose processors (preferably having multiple cores) without departing from the spirit and scope of the invention.

[0132] Figure 3 It shows that it can be used Figure 1 The exemplary genetic analyzer instrument system 300 used in the system. In some embodiments of the invention, the exemplary genetic analyzer instrument system 300 includes the Applied Biosystems™ SeqStudio™ genetic analyzer instrument system manufactured by Thermo Fisher Scientific, although other genetic analyzer instrument systems similarly capable of performing capillary electrophoresis may be used.

[0133] System 300 includes a genetic analyzer instrument 310, an integrated cartridge 320, and a cathode buffer 330. Built into the genetic analyzer instrument 310 are a touchscreen display 340 and a USB port 350. In some embodiments of the invention, the genetic analyzer system 300 allows multiple fragment analyses and / or sequencing to be run on the same plate. The genetic analyzer system 300 is easy to use with the integrated cartridge-based system 320 and allows researchers to access and monitor experimental runs and view data on the integrated touchscreen display 340 or remotely. The fully connected genetic analyzer and simple cartridge design allow for easy sharing by multiple researchers in a laboratory or facility.

[0134] In some embodiments of the invention, the instrument's easy-to-use core functionality includes a cylindrical design that helps maximize efficiency and convenience. For example, the SeqStudio genetic analyzer mentioned above uses... Figure 4The integrated cartridge 320, shown in more detail, includes a capillary array 440, a polymer reservoir 410, a polymer delivery system 420, and an anode buffer 430. In some embodiments of cartridge 320, a laser detection window may also be provided. Cartridge 320 is removable and can be stored on the instrument for up to four months. In some embodiments of the invention, each cartridge contains a novel polymer unique to the SeqStudio system, which allows Sanger sequencing and fragment analysis to be performed without reconfiguration. In one embodiment of the invention, the cartridge has four capillaries and can handle samples from standard 96-well plates or 8-well tubes. In some embodiments of the invention, the cartridge and cathode buffer container include radio frequency identification (RFID) tags that track the number of injections (cartridges) and the length of time spent on the instrument (cathode buffer container). This allows scientists to maintain their own cartridges using the same instrument.

[0135] The Genetic Analyzer Instrument System 300 allows for real-time monitoring of the SeqStudio genetic analyzer's operation. For example... Figure 5 As shown, instrument 300 displays the results 510 for each capillary in real time. Once injection is complete, several quality checks are calculated and displayed in an exemplary screen display 520. If the injection produces poor trace amounts or poor QC values, these samples can be re-injected, and the injection parameters can be changed (if necessary). An exemplary screen snapshot 530 from off-site computer monitoring shows the progress of the run. In an exemplary screen snapshot 540 used in some embodiments of the invention, the run set up in the PlateManager user interface can be directly uploaded to the instrument. PlateManager allows researchers to allocate multiple sequencing and fragment analysis runs on the same plate, utilizing a universal polymer in the tube and using that universal polymer only when needed, thus providing another level of flexibility. Figure 5 As shown in user interface screenshots 510-540, the maintenance of the SeqStudio genetic analyzer used in some embodiments of the invention is simple and straightforward for the user, and instrument calibration used in the genetic analyzer instrument used in the exemplary embodiments of the invention described herein can be automated by leveraging advancements in imaging and algorithmic tools.

[0136] like Figure 6 As shown in the figure, by integrating wireless connectivity into Figure 3 The exemplary genetic analyzer instrument shown in the figure can add another level of convenience. Figure 6The SeqStudio genetic analyzer instrument is shown to be accessible to users in several different ways: via an onboard interface, a remote computer, or a mobile device app. In some embodiments of the invention, assays or experimental runs can be set up using an onboard computer or by using PlateManager (standalone software running within Thermo Fisher Connect or on a separate computer), as shown in 610. Run settings, plate plots, run conditions, and analysis settings can be accessed immediately from anywhere with internet access using web browser-based software. Injection conditions, re-injections, and injection reordering can all be monitored and modified during the run, as shown in 620, thereby maximizing the ability to collect quality data from each plate. After data collection, a web browser-based application suite, including an application for measuring microsatellite instability, allows accessible analysis in some embodiments of the invention. Upon completion of the run, assays for DNA sequence variants, alignment, and fragment analysis are immediately available in analysis step 630. Finally, cloud connectivity 650 enables collaborators in different locations to monitor, access, share data, and quickly analyze the same dataset at any time after the run in step 640.

[0137] The SeqStudio genetic analyzer offers touchscreen availability via the instrument itself or through smartphones, tablets, or other user devices, allowing researchers to collaborate and analyze data with the same efficiency, both remotely and in the field. The exemplary genetic analyzer systems discussed herein, as used in some embodiments of the invention, are designed for both new and experienced users who require simple and affordable Sanger sequencing and fragment analysis without compromising performance or quality.

[0138] Figure 7 A flowchart of a method 700 for determining the MSI status of a biological sample in some embodiments of the present invention is shown. In step 710, one or more DNA loci of the biological sample are selected to study tumors exhibiting high mutation rates and therefore high microsatellite instability.

[0139] Microsatellite instability (MSI) is a form of genomic instability caused by reduced fidelity during DNA replication; this is thought to be caused by defects in DNA repair mechanisms. Defects in this biomolecular mechanism are most readily observed by examining the location of a single nucleotide (one of four possible nucleotides) repeated multiple times (homopolymer) within the DNA; for example, GGGGGGGGGG (SEQ ID NO: 32) is an 11-base repeat sequence of guanine. Extending this example, in cases where impaired DNA repair mechanisms are frequently observed in tumor cells, a DNA portion containing an 11-base repeat sequence of guanine can be replicated as, for example, 10 bases, 5 bases, or 13 bases, instead of the normal 11 bases. Microsatellite instability analysis involves chemicals designed to examine several different regions within the DNA where homopolymers are present. These chemicals select and amplify the DNA portion containing each homopolymer of interest (an amplified fragment of DNA at a specific DNA locus). Therefore, again based on the example of 11-base guanine, the size of the DNA fragment amplified at this locus would typically be, for example, 20 bases (some numbers selected by chemicals are greater than 11). However, if the DNA replication repair mechanism is impaired, the replicated DNA may, for example, have only 10 bases instead of the usual 11 guanines, and thus the size of the amplified fragment would be 19 instead of 20. There are two ways to detect this situation using the techniques that are the subject of this disclosure: 1) analyzing and comparing DNA from tumor and normal tissues from the same person, or 2) analyzing DNA from tumor tissue and comparing it with the DNA typically expected at each DNA locus of interest, provided that the DNA repair mechanism is not impaired. Note that these concepts, as well as the invention described in this disclosure, also apply to non-homogeneous portions of DNA consisting of simple repeating nucleotide sequences, such as ACACACAC or TATTGTATGTATGTAGT (SEQ ID NO: 33), etc.

[0140] Therefore, in step 710, a specific DNA locus can be selected based on the sensitivity of the locus to the cancer type under study compared to other cancer types. A specific DNA locus (also referred to as a biomarker) can also be selected based on the reliability of DNA amplification at the specific locus.

[0141] In step 720, each DNA locus is examined, and one or more algorithms can be selected for each locus to determine whether a given locus is a microsatellite unstable (MSU) or a microsatellite stable (MSS). Embodiments of the invention utilize multiple algorithms to determine whether a given DNA locus is an MSU or an MSS, including algorithms 1 to 11 described below. In step 730, the selected algorithm is executed for each selected DNA locus. In step 740, the overall MSI status of the biological sample is determined by combining the MSI results of each selected DNA locus.

[0142] Figure 8 Another embodiment of a method for assessing microsatellite instability in biological samples is shown, the method first described above and Figure 7 It is described in the text. Figure 8 The embodiments shown in the figure provide detailed descriptions. Figure 7 Further details and alternative data analysis approaches for embodiments of the microsatellite instability assessment method shown in the diagram. From Figure 8 Beginning at step 810, CE fragment analysis data for all DNA loci across the biological sample are obtained. As shown in step 805, each DNA locus or biomarker can be analyzed individually. Alternatively, as... Figure 8 As shown in step 815, markers can be analyzed together. If markers are to be analyzed individually in step 805, one or more signal features can be extracted for each marker in step 820, and one or more classification functions, such as the exemplary classification functions described below, can be applied to the extracted signal features in step 830 to determine the MSI state of each marker.

[0143] 1. Simple Size Threshold: Any fluorescence peak below the fragment size threshold (or above the fragment size threshold, depending on the location in the MSS case) is considered an MSU. This is appropriate if a given dye covers only one DNA locus and the number of nucleotides differs significantly between the MSU and MSS DNA molecular cases.

[0144] 2. Fragment Size Range: If any fluorescence peak appears within a given fragment size range (the range on the DNA fragment size axis of the data), the DNA locus is considered to be an MSU. This assumes that there is no overlap between the size ranges of all DNA loci covered with the same dye, and that the fluorescence peaks associated with MSU and MSS cases are well separated.

[0145] 3. Peak count within a given size interval: If the number of significant fluorescent peaks (significance is determined by peak size) is above a threshold, the locus is considered an MSU. This assumes no overlap between size intervals covering all DNA loci using the same dye.

[0146] 4. Relevant peak count within a given size interval: If the number of significant fluorescent peaks (significance determined by peak size) deviates significantly from the expected MSS, the locus is considered an MSU. This assumes no overlap between size intervals covering all DNA loci using the same dye.

[0147] 5. Peak envelope peaks within a given size interval: If the number of envelope peaks is two or more, the locus is considered MSI-high. This assumes that there is no overlap between size intervals covering all DNA loci using the same dye.

[0148] 6. Peak envelope separation within a given size interval: If the separation between the two largest envelope peaks deviates significantly from the separation of an MSI-stable sample, the locus is considered MSI-high. This assumes that there is no overlap between the size intervals of all DNA loci covered by the same dye.

[0149] 7. Peaking Mode: The peaking mode can consist of two or more of the following values: peak amplitude and / or position along the segment size axis; peak amplitude and / or position relative to the maximum peak; peak envelope peak amplitude, position, and / or width; peak metric relative to the peak envelope metric.

[0150] 8. Peak patterns deviate from normal values: the peak patterns of these patterns relative to those from normal tissue samples as described in (7) above;

[0151] 9. Peak patterns deviate from the peak patterns of normal (non-cancer) populations: The peak patterns mentioned above (7) are relative to the nominal values ​​from these patterns, such as the mean, median, z-score, etc. of the non-cancer population.

[0152] 10. Deviation from peak patterns relative to normal values ​​relative to population: a combination of (8) and (9) above, where the measure of (8) is compared to the nominal values ​​of these patterns in a non-cancer population.

[0153] 11. Differential Signal Patterns: When data from a given individual is available from both normal and tumor tissues, the signal patterns described above can be calculated based on the differences between standardized data from tumor and normal tissues. Additionally, other measures derived from differential signals can be used to characterize the differential signal at each locus. For example, the asymmetry of the differential signal can be characterized by the difference between the centroids of the positive peaks of the differential signal compared to the negative peaks. Other examples include the relative positions of the maximum and minimum values ​​of the differential signal, the root mean square (RMS) value of the positive peak compared to the negative peak, the overall RMS value of the differential signal, etc.

[0154] For items (7) through (11), the algorithm used to determine whether a DNA locus is an MSS or an MSU will consist of a suitable classification function capable of handling multidimensional vectors. For example, discriminant functions, multilayer artificial neural networks, vector machines, etc., are typical examples of machine learning methods that can be applied. Alternatively, instead of the pre-specified signal features outlined in items (7) through (10), deep learning methods can be applied to automatically learn the optimal signal features to distinguish between MSU and MSS by using a large number of CE fragment analysis data samples located within the size range of the fragment of interest.

[0155] In order to Figure 7 In step 740 or from Figure 8 Step 810 begins an overall assessment of the MSI status. In step 840, the MSI results for each DNA locus can be combined across all biomarkers in the nucleic acid sample under investigation to assign an overall MSI status call. The following is an exemplary method for performing this operation when using two or more DNA loci:

[0156] 12. Fixed percentage level: If the percentage of DNA loci for MSU is higher than the selected threshold, the overall allocation is MSI-high (or if the percentage of DNA loci for MSU is lower than the first selected threshold but higher than the second predetermined threshold, it is MSI-low), and if the percentage of DNA loci for MSU is lower than both of these thresholds, it is MSS.

[0157] 13. Weighted Summation: In one embodiment of the invention, a weighted sum across DNA loci can be calculated after assigning an exemplary value of 1 to the MSU locus and an exemplary value of 0 to the MSS locus; if the weighted sum across loci exceeds a threshold, an MSI-high can be assigned to the overall assessment. A linear discriminant function is an exemplary way to determine the weights.

[0158] 14. Nonlinear classification: such as Figure 8 As shown in steps 820 and 830, the MSI results across DNA loci can alternatively be combined in a nonlinear manner to determine the overall assessment of the MSI state in step 840. An exemplary way to determine the nonlinear classification function is to train a multi-layer artificial neural network for assignment.

[0159] It has been found that a standard 3-layer artificial neural network trained with conventional backpropagation techniques known in the art to minimize cross-entropy provides sufficient accuracy in distinguishing between MSU and MSS.

[0160] 15. Targeted Overall Assessment: Instead of pre-assessing the MSI state of each DNA locus as in step 805, biomarkers can be analyzed together in step 815, and the signal features expressed in items (7) through (11) can be combined across DNA loci, as shown in step 860, and used to generate one or more classification functions that directly assign the overall MSI state, such as... Figure 8 As shown in step 870. For example, suppose marker A uses 3 signal features to determine whether it is an MSU or MSS, and marker B uses 4 features for this purpose. In one embodiment of the invention, features from the two markers can be combined into a 7-dimensional feature vector to be fed into an AI-generated classifier, such as an artificial neural network trained to map this vector to the overall MSI state call. Instead of an explicit algorithm to combine information across markers, the combination of information becomes inherent in the training of this artificial neural network classifier. Alternatively, the AI-generated classifier can be implemented using deep learning methods, which can be used as described above, except after analyzing the markers separately in step 805 or, as shown in step 815, to combine data across DNA loci in the analysis. Signal features are fed directly into a deep learning neural network for direct mapping to the MSI state call, such as Figure 8 As shown in step 850. For example, at step 880, signals from each locus can be concatenated into a large signal vector and fed into the deep learning network to map it to the overall MSI state call.

[0161] Some embodiments of the present invention include methods for treating cancer patients with one or more anti-tumor drugs. In a particular embodiment, one or more methods, computer program products, systems, or kits disclosed herein are used to determine the microsatellite instability of tumor cells in a biological sample obtained from a patient. If the determined microsatellite instability is high, one or more anti-tumor drugs are then administered to the patient to treat the tumor.

[0162] The systems, apparatus, and methods described herein can be implemented using a computer program product tangibly embodied in an information carrier (e.g., a non-transitory machine-readable storage device) for execution by a programmable processor; and the steps of the methods described herein can be implemented using one or more computer programs executed by such a processor, including... Figure 6 , Figure 7 and Figure 8And one or more of the steps in the method in alternative embodiments. A computer program is a set of computer program instructions that can be used directly or indirectly in a computer to perform an activity or produce a result. A computer program can be written in any form of programming language, including compiled or interpreted languages, and the computer program can be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0163] Figure 9 Components of one embodiment of an environment 900 in which the invention can be practiced are shown. Practicing the invention may not require all components, and the arrangement and type of components can be varied without departing from the spirit or scope of the invention. As shown, system 900 includes one or more local area networks (“LANs”) / wide area networks (“WANs”) 912, one or more wireless networks 910, one or more wired or wireless client devices 906, mobile or other wireless client devices 902-906, servers 907-909, and may include or communicate with one or more data stores or databases. Each client device 902-906 may include, for example, a desktop computer, laptop computer, set-top box, tablet computer, display, mobile phone, smartphone, or a device for interacting with or viewing dashboards or analyses related to the genetic analysis-related system or entity. Servers 907-909 may include, for example, one or more application servers, content servers, search servers, database servers, database management or SQL servers, other servers related to the genetic analysis-related system, etc.

[0164] Figure 10 A block diagram of an electronic device 1100, which can implement one or more aspects of genetic analysis-related systems and methods according to embodiments of the present invention, is shown. Examples of the electronic device 1100 may include servers, such as servers 907-909, and client devices, such as client devices 902-906.

[0165] Figure 11 An example of computer system 1100 is shown, one or more of which can provide... Figure 1 One or more components or alternatives of the parts or alternatives of computer 103. Computer system 1100 executes instruction code contained in computer program product 1122, which includes genetic analyzer program 1123 (e.g., the computer program product may include...). Figure 1The computer program product 102 of the embodiment includes a CE data analyzer program 104. The computer program product 1122 includes executable code in an electronically readable medium that can instruct one or more computers (such as computer system 1100) to perform processing to complete the exemplary method steps performed by the embodiments mentioned herein. The electronically readable medium can be any non-transitory medium that stores information electronically and can be accessed locally or remotely, for example, via a network connection. In alternative embodiments, the medium can be transient. The medium may comprise multiple geographically dispersed media, each configured to store different portions of the executable code in different locations and / or at different times. The executable instruction code in the electronically readable medium instructs the illustrated computer system 1100 to perform the various exemplary tasks described herein. Executable code for instructing the performance of the tasks described herein will typically be implemented in software. However, those skilled in the art will understand that computers or other electronic devices can utilize code implemented in hardware to perform many or all of the identified tasks without departing from the invention. Those skilled in the art will understand that many variations of the executable code implementing the exemplary methods within the spirit and scope of the invention can be found.

[0166] The code or a copy of the code contained in the computer program product 1100 may reside in one or more persistent storage media (not shown separately) communicatively coupled to the system 1100 for loading and storage in the persistent storage device. Typically, the electronic device 1100 may include a processor / CPU 1102, memory 1130, power supply 1106, and input / output (I / O) components / devices 1140, such as a microphone, speaker, display, touch screen, keyboard, mouse, keypad, microscope, GPS component, etc., which may be operable for example, to provide a graphical user interface, dashboard, etc.

[0167] A user can provide input via the touchscreen of electronic device 1100. The touchscreen can determine whether the user is providing input by, for example, determining whether the user is touching the touchscreen with a part of the user's body (such as his or her finger). Electronic device 1100 may also include a communication bus 1104 connecting the aforementioned elements of electronic device 1100. Network interface 1114 may include a receiver and a transmitter (or transceiver), and one or more antennas for wireless communication.

[0168] Processor 1102 may include one or more processing devices of any type, such as a central processing unit (CPU) and a graphics processing unit (GPU). Similarly, for example, the processor may be central processing logic or other logic, and may include hardware, firmware, software, or a combination thereof to perform one or more functions or actions, or to cause one or more functions or actions from one or more other components. Likewise, depending on the desired application or need, the central processing logic or other logic may include, for example, a software-controlled microprocessor, discrete logic such as an application-specific integrated circuit (ASIC), a programmable / programmable logic device, a memory device containing instructions, or combinational logic embodied in hardware. Furthermore, the logic may also be entirely embodied in software.

[0169] The memory 1130, which may include random access memory (RAM) 1112 and read-only memory (ROM) 1132, can be enabled by one or more memory devices of any type, such as primary (directly accessed by the CPU) or secondary (indirectly accessed by the CPU) storage devices (e.g., flash memory, disk, optical disk, etc.). ROM 1132 may also include the basic input / output system (BIOS) 1120 of the electronic device.

[0170] RAM may contain an operating system 1121, a data storage device 1124 that may contain one or more databases, and programs and / or applications 1122 and a genetic analyzer program 1123. The genetic analyzer program 1123 is intended to broadly include all programming, applications, algorithms, software, and other tools required to implement or facilitate the methods and systems according to embodiments of the present invention. Elements of the genetic analyzer program 1123 may reside on a single server computer or be distributed among multiple computers, servers, devices, entities, or sites. Furthermore, those skilled in the art will understand that, in addition to storing the computer program product 1122 for performing the processes described herein, memory 1130 may be configured to store various data elements mentioned and shown herein.

[0171] The power supply 1106 contains one or more electrical components and facilitates the power supply and management of the electronic device 1100.

[0172] The input / output component including input / output (I / O) interface 1140 may include interfaces for facilitating communication between any component of electronic device 1100, components of external devices (e.g., components of other devices in network or system 1100), and the end user. For example, such a component may include a network interface card (NIC) that may be a receiver, transmitter, transceiver, and one or more input / output interfaces. The NIC may, for example, facilitate wired or wireless communication with other devices in the network. In the case of wireless communication, an antenna may facilitate such communication. Similarly, some of the input / output interface 1140 and bus 1104 may facilitate communication between components of electronic device 1100 and, in one instance, may simplify processing performed by processor 1102.

[0173] In the case where electronic device 1100 is a server, the electronic device may include a computing device that is capable of transmitting or receiving signals, for example, via a wired or wireless network, or of processing or storing signals as physical memory states, for example, in a memory. The server may be an application server containing configurations for providing one or more applications.

[0174] Any computing device capable of sending, receiving, and processing data via wired and / or wireless networks can act as a server, such as in facilitating the implementation of genetic analyzer-related systems and methods according to embodiments of the present invention. Devices acting as servers may include devices such as dedicated rack servers, desktop computers, laptop computers, set-top boxes, integrated devices combining one or more of the foregoing.

[0175] Servers may vary greatly in configuration and functionality, but they typically include one or more central processing units, memory, large data storage devices, power supply, wired or wireless network interfaces, input / output interfaces, and operating systems such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc.

[0176] A server may include, for example, means configured to or include means configured to provide data or content to another device via one or more networks, as in aspects of facilitating systems and methods according to embodiments of the invention. One or more servers may, for example, be used to host websites used in embodiments of the invention. One or more servers may host various sites, such as commercial sites, information sites, social networking sites, educational sites, wikis, financial sites, government sites, personal sites, etc.

[0177] The server can also provide various services, such as web services, third-party services, audio services, video services, email services, HTTP or HTTPS services, instant messaging (IM) services, short message service (SMS) services, multimedia message service (MMS) services, file transfer protocol (FTP) services, voice over IP (VoIP) services, calendar services, telephone services, etc., all of which can work in conjunction with exemplary aspects of the systems and methods according to embodiments of the present invention. Content can include, for example, text, images, audio, video, etc.

[0178] In an example aspect of the genetic analyzer system and method according to embodiments of the present invention, the client device may include, for example, any computing device capable of sending and receiving data via wired and / or wireless networks. Such client devices may include desktop computers and portable devices such as mobile phones, smartphones, display pagers, radio frequency (RF) devices, infrared (IR) devices, personal digital assistants (PDAs), handheld computers, GPS-enabled devices, tablet computers, displays, sensor-equipped devices, laptop computers, set-top boxes, wearable computers, integrated devices combining one or more of the foregoing devices, etc.

[0179] Client devices can vary widely in terms of functionality and features. For example, a mobile phone, smartphone, or tablet computer may have a numeric keypad and a few lines of monochrome liquid crystal display (LCD) screen on which only text can be displayed. In another example, a web-enabled client device may have a physical or virtual keyboard, a data storage device (such as flash memory or an SD card), an accelerometer, a gyroscope, GPS or other location-aware capabilities, and a 2D or 3D color touchscreen on top that can display both text and graphics.

[0180] For example, client devices such as client devices 1002-1006, which can be used in the example systems and methods according to embodiments of the present invention, can run various operating systems, including personal computer operating systems such as Windows, iOS, or Linux, and mobile operating systems such as iOS, Android, Windows Mobile, etc. The client device can be used to run one or more applications configured to send or receive data from another computing device. The client applications can provide and receive text content, multimedia information, etc. The client applications can perform actions such as viewing or interacting with analytics or dashboards, interacting with genetic analyzer instruments, methods, or systems used in embodiments of the present invention, browsing web pages, using web search engines, interacting with various apps stored on a smartphone, sending and receiving messages via email, SMS, or MMS, playing games, receiving advertisements, watching locally stored or streamed videos, or participating in social networks. In an example aspect of the genetic analyzer system and method according to embodiments of the present invention, one or more networks, such as network 1010 or 1012, can, for example, couple servers and client devices to other computing devices, including from wireless networks to client devices. This allows the network to use any form of computer-readable medium for transmitting information from one electronic device to another. In addition to Local Area Networks (LANs), Wide Area Networks (WANs), and direct connections, networks can also include the Internet, such as via a Universal Serial Bus (USB) port, other forms of computer-readable media, or any combination thereof. On a set of interconnected LANs, including LANs based on different architectures and protocols, routers act as links between LANs, enabling data to be sent from one LAN to another.

[0181] Communication links within a LAN can include twisted-pair or coaxial cables, while communication links between networks can use analog telephone lines, electrical cables, optical lines, full or partial dedicated digital lines including T1, T2, T3, and T4, Integrated Services Digital Network (ISDN), Digital Subscriber Line (DSL), wireless links including satellite links, fiber optic links, or other communication links known to those skilled in the art. Furthermore, remote computers and other related electronic devices can be remotely connected to the LAN or WAN via modems and telephone links.

[0182] Wireless networks, such as wireless network 1010, can couple devices to a network, as in the example genetic analysis-related systems and methods according to embodiments of the present invention. Wireless networks can be standalone self-organizing networks, mesh networks, wireless LAN (WLAN) networks, cellular networks, etc.

[0183] Wireless networks can further comprise autonomous systems of terminals, gateways, routers, etc., connected via radio links. These connectors can be configured to move freely and randomly and organize themselves arbitrarily, allowing the topology of the wireless network to change rapidly. Wireless networks can further employ various access technologies, including 2G, 3G, 4G, LTE radio access for cellular systems, WLAN, and wireless router (WR) meshes. Access technologies such as 2G, 2.5G, 3G, 4G, 5G, and future access networks enable wide-area coverage of client devices, such as those with varying degrees of mobility. For example, wireless networks can achieve radio connectivity through radio network access technologies such as GSM, UMTS, GPRS, EDGE, LTE, LTE-Advanced Wideband Code Division Multiple Access (WCDMA), Bluetooth, and 802.11b / g / n. A wireless network can actually include any wireless communication mechanism through which information can travel between a client device and another computing device, network, etc.

[0184] The Internet Protocol (IP) is used to transmit data communication packets over networks participating in digital communication networks, and can include protocols such as TCP / IP, UDP, DECnet, NetBEUI, IPX, and AppleTalk. Versions of the Internet Protocol include IPv4 and IPv6. The Internet includes Local Area Networks (LANs), Wide Area Networks (WANs), wireless networks, and long-distance public networks that allow packet transmission between LANs. Packets can be transmitted between nodes in the network to stations, each of which has a unique local network address. Data communication packets can be sent from a user station through an access node connected to the Internet. Packets can be forwarded by network nodes to any destination station connected to the network, provided that the destination station's address is included in the packet header. Each packet transmitted over the Internet can be routed via a path determined by gateways and servers, which switch packets to connect to a destination station based on the availability of the destination address and network path.

[0185] The packet header may include, for example, source port (16 bits), destination port (16 bits), sequence number (32 bits), acknowledgment number (32 bits), data offset (4 bits), reserved (6 bits), checksum (16 bits), urgent pointer (16 bits), options (variable bit length, a multiple of 8 bits), and padding (which may consist of all zeros and include bits to end the header on a 32-bit boundary). The bit length of each of these items can also be higher or lower.

[0186] As may be used in the example systems and methods according to embodiments of the present invention, a "content delivery network" or "content distribution network" (CDN) generally refers to a distributed computer system comprising a collection of autonomous computers linked through one or more networks, and software, systems, protocols, and technologies designed to facilitate various services such as storing, caching, or transmitting content, streaming media, and applications on behalf of content providers. Such services may utilize ancillary technologies, including but not limited to "cloud computing," distributed storage, DNS request processing, provisioning, data monitoring and reporting, content targeting, personalization, and business intelligence. A CDN can also enable entities to operate and / or manage, in whole or in part, the website infrastructure of third parties.

[0187] Peer-to-peer (P2P) computer networks rely primarily on the computing power and bandwidth of the participants in the network, rather than concentrating them on a given set of dedicated servers. P2P networks are typically used to connect nodes through a large number of self-organized connections. Pure peer-to-peer networks do not have the concept of clients or servers, but only peer nodes that simultaneously act as both "clients" and "servers" for other nodes on the network.

[0188] One embodiment of the present invention includes a system, method, and a non-transitory computer-readable storage medium or a medium that tangibly stores computer program logic executable by a computer processor.

[0189] Those skilled in the art will understand that computer system 1100 is merely one example of a system in which a computer program product according to embodiments of the present invention can be implemented. For the sake of reference to only one example of an alternative embodiment, the execution of instructions contained in a computer program product according to embodiments of the present invention may be distributed across multiple computers, such as, for example, computers in a distributed computer network.

[0190] It should be understood that the examples and embodiments described herein are for illustrative purposes only, and various modifications or changes made thereto will inspire those skilled in the art and will be included within the spirit and scope of this application and the appended embodiments. All publications, patents, and patent applications cited herein are hereby incorporated in their entirety for all purposes.

[0191] Example

[0192] Those skilled in the art will understand that the description of the preparation and use of particles described herein is for illustrative purposes only, and this disclosure is not limited to such description.

[0193] Example 1. DNA isolation and microsatellite instability analysis

[0194] FFPE tissue sections (10 μm) were collected from formalin-fixed paraffin-embedded (FFPE) blocks using a Microm HM 355S rotary microtome. DNA was isolated from the FFPE sections using the RecoverAll™ Total Nucleic Acid Isolation Kit, and the concentration was measured using the Qubit™ dsDNA HS assay kit on an Invitrogen Qubit 4 Fluorimeter. The extracted FFPE DNA was diluted to 1 ng / μl in 1× low-EDTA TE buffer. Microsatellite instability in the tissue samples was assessed using the ABI MSI assay. The ABI MSI amplification mixture consisted of 4 μl of multiplex PCR MasterMix, 4 μl of 1× low-EDTA TE buffer, and 2 μl of DNA at 1 ng / μl. PCR was performed in the Applied Biosystems ProFlex PCR system in GeneAmp™ PCR System 9700 simulation mode under the following conditions: 95°C for 11 min; 29 denaturation cycles at 94°C for 20 sec followed by adhesion at 59°C for 2 min; and a final extension at 60°C for 25 min. The amplified PCR product was denatured in a 20 μl reaction volume at 95°C for 3 min, consisting of 17 μl Hi-Di™ formamide, 1 μl GeneScan™ 600 LIZ™ dye (size standard v2.0), and 2 μl of PCR product. The denatured amplified PCR product was then analyzed by fragment analysis on an ABI 3500 (xL) or SeqStudio™ genetic analyzer.

[0195] PCR primers, containing associated markers, are shown in Table 1. The forward primers in each group are labeled with a specified dye at the 5' end, except for ABI-16, which is labeled at the 5' end of the reverse primer. The markers are attached via C3 linkers.

[0196] Table 1. Primers used for ABI-MSI amplification.

[0197]

[0198] Example 2. Assessment of MSI in colorectal cancer and normal tissue

[0199] DNA was isolated from FFPE sections of colorectal cancer (“tumor”) or normal tissue (“normal”) and PCR was performed as described in Example 1. Normal tissue was typically a matched normal control (tissue from the same patient). Figure 11 The signals in the electrophoresis images clearly show the difference between the tumor and normal samples. The signals are clear and easy to interpret, and the signal intensity is consistent.

[0200] Example 3. Comparison of ABI-MSI with other MSI measurements

[0201] Endometrial cancer is notoriously difficult to detect because standard MSI assays struggle to resolve small deletions. DNA samples from endometrial cancer are amplified and analyzed using the PROMEGA™ MSI analysis system, as described in Example 1 (“ABI-MSI”), or using a manufacturer-supplied protocol. The PROMEGA™ system amplifies DNA from five loci (NR21, BAT26, BAT25, NR24, and MONO27) and includes two controls (PentaC and PentaD). Figure 12A As shown, the ABI-MSI determination identified one sample that would be identified as MSI-Low (MSI-L) by the PROMEGA™ system as MSI-High (MSI-H), and five samples that would be identified as MSI-Stable (MSS) by the PROMEGA™ system as MSI-Low. Figure 12B The study shows a clear shift in several loci between normal (blue) and tumor (green) samples.

[0202] Example 4. Development of an Extended Microsatellite Instability Panel Using Automated Data Analysis

[0203] In 2017, the Food and Drug Administration (FDA) approved pembrolizumab for any patient with a solid tumor harboring MSI or mismatch repair deficiency. This led to an increase in research utilizing MSI as a predictive biomarker for the effectiveness of immune checkpoint inhibition. However, current solutions for detecting MSI are few and limited, including an inadequacy of biomarkers for application across multiple tumor types and cumbersome data analysis.

[0204] To improve upon standard MSI detection panels and workflows, an MSI assay was developed featuring a rapid, simple workflow, low sample input (2 ng FFPE DNA), expanded capabilities, automated analysis, interpretable results, and tumor-only analysis. The assay takes only 3.5 hours from DNA to response: 15 minutes for PCR sample preparation, 2 hours for fluorescent PCR, 15 minutes for fragment analysis sample preparation, 55 minutes for CE-based fragment analysis, and 5 minutes for data analysis.

[0205] Figure 13 This demonstrates how synthetic constructs reveal the complexity of detection. The detection of instability involves a complex interaction between deletion size and the presence of mutated alleles in the sample. Synthetic constructs are generated to: 1) understand the peak morphology of difficult-to-assess MSI samples, and 2) train the algorithm with various allele frequencies and variable deletion sizes for each homopolymer.

[0206] Figure 14Tumor-only analysis was shown with >98% specificity and >90% sensitivity at 5 bpd. High sensitivity will be observed for tumor-only analysis of cancer types with large deletions, such as colon and gastric cancer.

[0207] Figure 15 Tumor-normal analysis with >95% specificity and sensitivity at ≥3 bdp is shown. Adjustable algorithm parameters allow maximizing the sensitivity and specificity of the Applied Biosystems™ 3500 and SeqStudio™ genetic analyzer systems.

[0208] Figure 16 The ABI MSI software (top) and a sample MSI report (bottom) are showcased. This software provides an automated genotyping solution for simplified analysis and reporting, saving customers the time and effort currently required for manual analysis.

[0209] ABI MSI assays enable reliable identification of microsatellite instability across multiple cancer types with low sample input. Furthermore, the MSI analysis software offers fast analysis speed and can include automated sensitivity and specificity invocations.

[0210] References

[0211] 1. Vaksman, Zlaman, and Harold R. Garner. “Somatic microsatellite variability as a predictivemarker for colorectal cancer and liver cancer progression.” Oncotarget 6.8 (2015): 5760.

[0212] 2. Le, Dung T. et al. "PD-1 blockade intumors with mismatch-repair deficiency." New England Journal of Medicine 372.26 (2015): 2509-2520.

[0213] 3. Cortes-Ciriano, Isidro et al. “Amolecular portrait of microsatellite instability across multiple cancers.” Nature Communications 8 (2017): 15180.

[0214] Latham et al., 2019

[0215] This disclosure also includes the following implementation plan:

[0216] 1. A method for detecting microsatellite instability (MSI) in a DNA sample, the method comprising:

[0217] a) Co-amplify multiple microsatellite loci of the DNA sample to produce an amplified fragment comprising a nucleic acid sequence from each locus, the multiple loci including at least one selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B and ABI-19;

[0218] b) Determine the size of the amplified fragment from each locus; and

[0219] c) The size of the amplified fragment from each locus is compared with the size of the corresponding amplified fragment from the control, and the size difference between one or more amplified fragments between the sample and the control indicates the presence of MSI in the DNA sample.

[0220] 2. A method for analyzing a DNA sample to determine microsatellite instability (MSI) in the DNA sample, the method comprising:

[0221] a) Co-amplify multiple microsatellite loci of the DNA sample to produce an amplified fragment comprising a nucleic acid sequence from each locus, the multiple loci including at least one selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B and ABI-19;

[0222] b) Determine the size of the amplified fragment from each locus;

[0223] c) Compare the size of the amplified fragment from each locus with the size of the corresponding amplified fragment from the control, wherein the size difference between one or more amplified fragments between the sample and the control indicates the presence of MSI in the DNA sample; and

[0224] d) Assign MSI levels to the DNA sample, thereby determining the MSI status of the DNA sample.

[0225] 3. A method for diagnosing cancerous tissue in a biological sample, the method comprising:

[0226] a) Co-amplify multiple microsatellite loci from the biological sample to produce an amplified fragment comprising a nucleic acid sequence from each locus, the multiple loci including at least one selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B and ABI-19;

[0227] b) Determine the size of the amplified fragment from each locus; and

[0228] c) The size of the amplified fragment from each locus is compared with the size of the corresponding amplified fragment from the control, wherein the size difference between the sample and the control between one or more amplified fragments from one or more loci indicates the presence of microsatellite instability (MSI) in the biological sample, and the presence of MSI in the biological sample indicates that the biological sample contains cancerous tissue.

[0229] 4. A method for diagnosing cancer in a subject who has or is suspected of having cancer, the method comprising:

[0230] a) Obtain biological samples from the subject;

[0231] b) Co-amplify multiple microsatellite loci of the biological sample to produce an amplified fragment comprising a nucleic acid sequence, wherein the multiple loci include at least one selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B and ABI-19;

[0232] c) Determine the size of the amplified fragment; and

[0233] d) Compare the size of the amplified fragment from step b) with the size of the corresponding amplified fragment from the control, wherein the size difference between one or more amplified fragments between the sample and the control indicates the presence of microsatellite instability (MSI) in the biological sample, and the presence of MSI in the biological sample indicates that the subject has cancer.

[0234] 5. A method for treating cancer in a subject who has or is suspected of having cancer, the method comprising:

[0235] a) Obtain biological samples from the subject;

[0236] b) Co-amplify multiple microsatellite loci of a DNA sample to produce an amplified fragment comprising a nucleic acid sequence, wherein the multiple loci include at least one selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B, and ABI-19;

[0237] c) Determine the size of the amplified fragment;

[0238] d) Compare the size of the amplified fragment from step b) with the size of the corresponding amplified fragment from the control, wherein the size difference between one or more amplified fragments between the samples indicates the presence of microsatellite instability (MSI) in the biological sample, and the presence of MSI in the biological sample indicates that the subject has cancer; and

[0239] e) Administering anticancer agents to the subjects who have cancer.

[0240] 6. The method according to any one of embodiments 3 to 5, wherein DNA is isolated from the biological sample prior to co-amplification.

[0241] 7. A method for detecting microsatellite instability (MSI) in a DNA sample, the method comprising:

[0242] a) Co-amplify multiple microsatellite loci of the DNA sample to produce an amplified fragment comprising a nucleic acid sequence from each locus, the multiple loci including at least one selected from the following: ABI-20A, ABI-17, ABI-16, ABI-20B and ABI-19;

[0243] b) Determine the size of the amplified fragment from each locus; and

[0244] c) The size of the amplified fragment from each locus is compared with the size of the corresponding amplified fragment from the control, and the size difference between one or more amplified fragments between the sample and the control indicates the presence of MSI in the DNA sample.

[0245] 8. A method for analyzing amplified fragments comprising nucleic acid sequences to determine microsatellite instability (MSI), the method comprising:

[0246] a) Provides an amplified fragment comprising a nucleic acid sequence amplified from a plurality of microsatellite loci in a DNA sample, said plurality of loci including at least one selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B and ABI-19;

[0247] b) Determine the size of the amplified fragment from each locus;

[0248] c) Compare the size of the amplified fragment from each locus with the size of the corresponding amplified fragment from the control, wherein the size difference between one or more amplified fragments between the sample and the control indicates the presence of MSI in the DNA sample; and

[0249] d) Assign MSI levels to the DNA sample, thereby determining the MSI status of the DNA sample.

[0250] 9. The method according to any one of embodiments 3 to 7, further comprising distributing the biological sample or the DNA sample as having high microsatellite instability, low microsatellite instability, or stable microsatellite instability.

[0251] 10. The method according to embodiment 2, 8 or 9, wherein if more than about 30% of the loci amplified from the DNA sample are determined to have MSI, the DNA sample is assigned high microsatellite instability.

[0252] 11. The method according to any one of embodiments 2, 8, 9 or 10, wherein if less than about 30% but more than about 1% of the loci amplified from the DNA sample are determined to have MSI, the DNA sample is assigned low microsatellite instability.

[0253] 12. The method according to embodiment 2 or any one of 8 to 11, wherein the DNA sample is assigned microsatellite stabilization if none of the loci amplified from the DNA sample are determined to have MSI.

[0254] 13. The method according to any one of embodiments 1 to 12, further comprising co-amplifying one or more identification markers in the co-amplification step.

[0255] 14. The method according to embodiment 13, wherein the one or more identification markers include PENTAD and / or TH01.

[0256] 15. The method according to any one of embodiments 1 to 14, wherein the plurality of loci include at least two loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B and ABI-19.

[0257] 16. The method according to embodiment 15, wherein the plurality of loci include at least eight loci selected from the following: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B and ABI-19.

[0258] 17. The method according to embodiment 15, wherein the plurality of loci include each of the following loci: BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B and ABI-19.

[0259] 18. The method according to any one of embodiments 1 to 17, wherein the DNA sample or the biological sample is derived from tumor cells, suspected cancerous cells, or other suspected cancerous biological material.

[0260] 19. The method according to any one of embodiments 1 to 18, wherein the control is a pair of normal samples, a sample from non-cancerous tissue, a blood sample, or an average value based on a normal population.

[0261] 20. The method according to any one of embodiments 1 to 19, wherein the microsatellite locus is co-amplified using one or more primers selected from SEQ ID NO. 1-26.

[0262] 21. The method according to embodiment 20, wherein the microsatellite locus is co-amplified using a primer pair comprising a first primer and a second primer, wherein the polynucleotide sequences of the first primer and the second primer comprise one of the following pairs: SEQ ID NO.: 1 and SEQ ID NO.: 2; SEQ ID NO.: 3 and SEQ ID NO.: 4; SEQ ID NO.: 5 and SEQ ID NO.: 6; SEQ ID NO.: 7 and SEQ ID NO.: 8; SEQ ID NO.: 9 and SEQ ID NO.: 10; SEQ ID NO.: 11 and SEQ ID NO.: 12; SEQ ID NO.: 13 and SEQ ID NO.: 14; SEQ ID NO.: 15 and SEQ ID NO.: 16; SEQ ID NO.: 17 and SEQ ID NO.: 18. The polynucleotide sequences of SEQ ID NO.:18; SEQ ID NO.:19 and SEQ ID NO.:20; SEQ ID NO.:21 and SEQ ID NO.:22; SEQ ID NO.:23 and SEQ ID NO.:24; and / or SEQ ID NO.:25 and SEQ ID NO.:26.

[0263] 22. The method according to embodiment 20 or 21, wherein at least one primer includes a modification.

[0264] 23. The method according to embodiment 22, wherein the modification includes a detectable marker.

[0265] 24. The method according to embodiment 23, wherein the detectable marker is a fluorescent marker.

[0266] 25. The method according to any one of embodiments 22 to 24, wherein the amplified fragment from each locus includes modifications different from those at each other locus.

[0267] 26. The method according to any one of embodiments 1 to 25, wherein the plurality of microsatellite loci are amplified using thermal cycling and analyzed by fragment analysis, Sanger sequencing, ion semiconductor sequencing or high-resolution melt flow analysis.

[0268] 27. The method according to embodiment 26, wherein the Sanger sequencing is capillary electrophoresis Sanger sequencing.

[0269] 28. The method according to any one of embodiments 1 to 27, wherein the DNA sample and the paired normal DNA sample are from the same individual.

[0270] 29. The method according to any one of embodiments 1 to 27, wherein the paired normal DNA samples are control DNA from non-cancerous tissue.

[0271] 30. The method according to any one of embodiments 1 to 29, wherein the DNA sample and the paired normal DNA sample are derived from the same type of tissue.

[0272] 31. The method according to any one of embodiments 1 to 30, wherein the cancer is colorectal cancer, gastric cancer, adrenocortical carcinoma, cervical cancer, mesothelioma, or endometrial cancer.

[0273] 32. The method according to any one of embodiments 1 to 31, wherein each locus is amplified using primer pairs, and further wherein at least one primer in the primer pairs comprises a modification.

[0274] 33. The method according to embodiment 32, wherein the modification includes a detectable marker.

[0275] 34. The method according to any one of embodiments 1 to 33, wherein each amplified fragment includes a fluorescent label, and wherein determining the size of said amplified fragment from each locus includes:

[0276] Multiple signals are obtained by detecting the fluorescence of the amplified fragment, wherein each signal corresponds to an amplified fragment from one of multiple different microsatellite loci; and

[0277] Determine one or more signal characteristics for each of the plurality of signals.

[0278] 35. The method according to embodiment 34, comprising applying one or more classifiers to one or more signal features of the plurality of microsatellite loci to identify whether the biological sample is characterized as having high microsatellite instability, low microsatellite instability, or stable microsatellites.

[0279] 36. The method according to any one of embodiments 1 to 33, wherein each amplified fragment includes a fluorescent label, and wherein determining the size of said amplified fragment from each locus comprises:

[0280] Multiple signals are obtained by detecting the fluorescence of the amplified fragment, wherein the nucleic acid sequence corresponds to multiple different microsatellite loci, and each signal corresponds to one of the multiple different microsatellite loci.

[0281] 37. The method according to embodiment 36 further includes using one or more classifiers to analyze the plurality of signals to identify whether the biological sample has high microsatellite instability, low microsatellite instability, or is microsatellite stable.

[0282] 38. A primer set comprising one or more primer pairs, each primer pair comprising a first primer and a second primer, wherein the polynucleotide sequences of the first primer and the second primer comprise one of the following pairs: SEQ ID NO.: 1 and SEQ ID NO.: 2; SEQ ID NO.: 3 and SEQ ID NO.: 4; SEQ ID NO.: 5 and SEQ ID NO.: 6; SEQ ID NO.: 7 and SEQ ID NO.: 8; SEQ ID NO.: 9 and SEQ ID NO.: 10; SEQ ID NO.: 11 and SEQ ID NO.: 12; SEQ ID NO.: 13 and SEQ ID NO.: 14; SEQ ID NO.: 15 and SEQ ID NO.: 16; SEQ ID NO.: 17 and SEQ ID NO.: 18. The polynucleotide sequences of SEQ ID NO.: 18; SEQ ID NO.: 19 and SEQ ID NO.: 20; SEQ ID NO.: 21 and SEQ ID NO.: 22; SEQ ID NO.: 23 and SEQ ID NO.: 24; and / or SEQ ID NO.: 25 and SEQ ID NO.: 26.

[0283] 39. The primer set according to embodiment 38, wherein at least one primer includes a modification.

[0284] 40. The primer set according to embodiment 39, wherein the modification includes a detectable marker.

[0285] 41. The primer set according to embodiment 40, wherein the detectable marker is a fluorescent marker.

[0286] 42. The primer set according to any one of embodiments 39 to 41, wherein each primer pair includes modifications different from those of each other primer pair.

[0287] 43. A composition comprising a set of primers according to any one of embodiments 38 to 42.

[0288] 44. The composition according to embodiment 43, wherein the primer set comprises at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, or at least 12 primer pairs.

[0289] 45. The composition according to embodiment 43 or 44, comprising 13 primer pairs, said primer pairs comprising polynucleotide sequences of SEQ ID NO.: 1-26.

[0290] 46. ​​The composition according to any one of embodiments 43 to 45, wherein at least one primer is modified.

[0291] 47. The composition according to embodiment 46, wherein the modification includes a detectable marker.

[0292] 48. The composition according to any one of embodiments 43 to 47, further comprising a polymerase.

[0293] 49. The composition according to any one of embodiments 43 to 48, further comprising a plurality of deoxyribonucleoside triphosphates.

[0294] 50. The composition according to any one of embodiments 43 to 49, further comprising a DNA sample.

[0295] 51. The composition according to any one of embodiments 43 to 50, further comprising one or more salts.

[0296] 52. A system comprising a composition according to any one of embodiments 43 to 51 and a first device configured to perform DNA amplification.

[0297] 53. The system according to embodiment 52, wherein the first device is configured to perform Sanger sequencing, ion semiconductor sequencing, capillary electrophoresis, or high-resolution melt analysis.

[0298] 54. The system according to embodiment 52 or 53, further comprising a second device configured to compare and / or analyze fragments generated by DNA amplification using the primers.

[0299] 55. A kit comprising a buffer and at least one primer pair for amplifying a microsatellite locus, said primer pair comprising a first primer and a second primer, and said microsatellite locus comprising BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B and / or ABI-19.

[0300] 56. The kit according to embodiment 55, wherein the at least one primer pair comprises at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, or at least 12 or at least 13 primer pairs.

[0301] 57. The kit according to embodiment 55 or 56, wherein the at least one primer pair comprises at least one primer having a polynucleotide sequence having any one of SEQ ID NO.: 1-26.

[0302] 58. The kit according to embodiment 57, wherein the at least one primer pair comprises 13 primer pairs having a polynucleotide sequence of any one of SEQ ID NO.: 1-26.

[0303] 59. The kit according to any one of embodiments 55 to 58, further comprising primer pairs for amplifying the identification marker.

[0304] 60. The kit according to embodiment 59, wherein the identification markers include PENTAD and / or TH01.

[0305] 61. The kit according to any one of embodiments 55 to 60, wherein the polynucleotide sequences of the first primer and the second primer comprise one of the following pairs: SEQ ID NO.: 1 and SEQ ID NO.: 2; SEQ ID NO.: 3 and SEQ ID NO.: 4; SEQ ID NO.: 5 and SEQ ID NO.: 6; SEQ ID NO.: 7 and SEQ ID NO.: 8; SEQ ID NO.: 9 and SEQ ID NO.: 10; SEQ ID NO.: 11 and SEQ ID NO.: 12; SEQ ID NO.: 13 and SEQ ID NO.: 14; SEQ ID NO.: 15 and SEQ ID NO.: 16; SEQ ID NO.: 17 and SEQ ID NO.: 18; SEQ ID NO.: The polynucleotide sequences of SEQ ID NO.: 19 and SEQ ID NO.: 20; the polynucleotide sequences of SEQ ID NO.: 21 and SEQ ID NO.: 22; the polynucleotide sequences of SEQ ID NO.: 23 and SEQ ID NO.: 24; and / or the polynucleotide sequences of SEQ ID NO.: 25 and SEQ ID NO.: 26.

[0306] 62. The kit according to any one of embodiments 55 to 61, wherein all primers in the primer pair are present in the same container.

[0307] 63. The kit according to any one of embodiments 55 to 62, comprising primers comprising the polynucleotide sequence of each of SEQ ID NO.: 1-26.

[0308] 64. The kit according to any one of embodiments 55 to 63, further comprising a polymerase and / or multiple deoxynucleoside triphosphates.

[0309] 65. The kit according to any one of embodiments 55 to 64, wherein the buffer is a PCR buffer.

[0310] 66. The kit according to any one of embodiments 55 to 65, wherein at least one primer from the primer set includes a modification.

[0311] 67. The kit according to embodiment 66, wherein the modification is a detectable marker.

[0312] 68. The kit according to embodiment 67, wherein the detectable marker is a fluorescent marker.

[0313] 69. The kit according to any one of embodiments 66 to 68, wherein each primer pair includes modifications different from those of each other primer pair.

[0314] 70. The kit according to any one of embodiments 55 to 69, further comprising a computer program for identifying microsatellite instability in biological samples.

[0315] 71. The kit according to embodiment 70, wherein each primer pair includes a fluorescent label such that when the primer pair is combined with a biological sample and subjected to an amplification process, a fluorescently labeled DNA fragment is generated; and wherein the computer program is a computer program product embedded in a non-transitory computer-readable medium, the computer program product including executable instruction code that, when executed by one or more processors, causes the one or more processors to perform processing, the processing including:

[0316] The microsatellite instabilities of the biological samples were classified using fluorescence data obtained from the fluorescently labeled DNA fragments.

[0317] 72. The kit according to embodiment 71, wherein execution of the executable instruction code causes the one or more processors to perform processing, the processing including:

[0318] One or more locus-specific algorithms are applied to the fluorescence data to generate locus-specific results, thereby classifying the microsatellite instabilities of corresponding specific loci of the plurality of microsatellite loci; and

[0319] The microsatellite instabilities of the biological samples were classified using locus-specific results.

[0320] 73. A method for identifying microsatellite instability in a biological sample, the method comprising:

[0321] Multiple signals are obtained by detecting the fluorescence of a fragment comprising a nucleic acid sequence obtained using the biological sample, wherein each signal corresponds to one of multiple different microsatellite loci;

[0322] Determine one or more signal characteristics for each of the plurality of signals; and

[0323] One or more classifiers are applied to one or more of the signal features of the plurality of microsatellite loci to identify whether the biological sample is characterized as having high microsatellite instability, low microsatellite instability, or stable microsatellite instability.

[0324] 74. The method according to embodiment 35 or 73, further comprising: applying one or more classifiers to one or more signal features of a signal corresponding to each individual microsatellite locus among the plurality of different microsatellite loci to identify whether each individual microsatellite locus is microsatellite unstable or microsatellite stable; and combining these determinations across loci to determine the microsatellite state of the biological sample.

[0325] 75. The method according to embodiments 35, 73 or 74, wherein the application of one or more classifiers includes comparing signal features derived from the biological sample with signal features derived from one or more non-cancer tissue samples.

[0326] 76. The method according to embodiments 35, 73 or 74, wherein at least one classifier includes a fragment size threshold.

[0327] 77. The method according to embodiments 35, 73 or 74, wherein at least one classifier includes a fragment size range.

[0328] 78. The method according to embodiments 35, 73 or 74, wherein applying the one or more classifiers includes evaluating peak counts within a specified size interval.

[0329] 79. The method according to embodiments 35, 73 or 74, wherein applying the one or more classifiers includes evaluating the relative peak counts between tumor and normal tissue within a specified size interval.

[0330] 80. The method according to embodiments 35, 73 or 74, wherein applying the one or more classifiers includes evaluating peak envelope counts within a specified size interval.

[0331] 81. The method according to embodiments 35, 73 or 74, wherein applying the one or more classifiers includes evaluating peak envelope separation within a specified size interval.

[0332] 82. The method according to embodiments 35, 73 or 74, wherein applying the one or more classifiers includes evaluating peak envelope separation within a specified size interval.

[0333] 83. The method according to embodiments 35, 73 or 74, wherein applying the one or more classifiers includes evaluating the offset of one or more peak locations within a specified size interval.

[0334] 84. The method according to embodiments 35, 73 or 74, wherein applying the one or more classifiers includes analyzing peak pattern input.

[0335] 85. The method according to embodiment 84, wherein the peak mode input includes two or more of the following values: peak amplitude along the segment size axis, peak position along the segment size axis; peak amplitude relative to the maximum peak, peak position relative to the maximum peak, peak envelope peak amplitude, peak envelope peak position, peak envelope peak width, or peak measure relative to the peak envelope measure.

[0336] 86. The method according to embodiment 74, further comprising:

[0337] When the percentage of microsatellite loci determined to be microsatellite unstable is higher than a first predetermined threshold, the biological sample is assigned a high microsatellite instability state; if the percentage of microsatellite loci determined to be microsatellite unstable is higher than a second predetermined threshold but lower than the first predetermined threshold, the biological sample is assigned a low microsatellite instability state; or if the percentage of microsatellite loci determined to be microsatellite unstable is lower than the second predetermined threshold, the biological sample is assigned a microsatellite stable state.

[0338] 87. The method according to embodiment 74, further comprising:

[0339] The signal characteristics are analyzed to assign stable or unstable values ​​to each microsatellite locus in the microsatellite locus;

[0340] A weighted sum is calculated for the assigned stable and unstable values ​​across the microsatellite loci; and

[0341] If the weighted sum across the microsatellite loci exceeds a first predetermined threshold, the biological sample is assigned a high microsatellite instability state; if the weighted sum across the microsatellite loci exceeds a second predetermined threshold but does not exceed the first predetermined threshold, the biological sample is assigned a low microsatellite instability state; or if the weighted sum across the microsatellite loci is less than the second predetermined threshold, the biological sample is assigned a microsatellite stable state.

[0342] 88. The method according to embodiment 87, wherein the weighted sum is calculated using one or more classification functions, the one or more classification functions mapping the plurality of signal features to three different output values.

[0343] 89. A method for identifying microsatellite instabilities in biological samples, the method comprising:

[0344] Multiple signals are obtained by detecting the fluorescence of a fragment comprising a nucleic acid sequence amplified from the biological sample, the nucleic acid sequence corresponding to multiple different microsatellite loci, wherein each signal corresponds to one of the multiple different microsatellite loci; and

[0345] One or more classifiers are used to analyze the multiple signals to identify whether the biological sample has high microsatellite instability, low microsatellite instability, or is microsatellite stable.

[0346] 90. The method according to embodiment 37 or 89, wherein the classifier comprises a nonlinear classification function.

[0347] 91. The method according to embodiment 90, wherein the nonlinear classification function comprises a multilayer artificial neural network.

[0348] 92. The method according to embodiment 37 or 89, wherein the classifier comprises a deep learning neural network.

[0349] 93. A computer program product comprising executable code stored in a non-transitory computer-readable medium, the executable code being executable on one or more computer processors to identify microsatellite instabilities in a biological sample, the executable code including one or more computer-readable instructions for performing:

[0350] Multiple signals are obtained from a capillary electrophoresis genetic analysis instrument, wherein the signals are detected based on the fluorescence of fragments comprising nucleic acid sequences amplified from the biological sample by polymerase chain reaction, the nucleic acid sequences corresponding to multiple different microsatellite loci, wherein each signal corresponds to one of the multiple different microsatellite loci; and

[0351] Each of the plurality of signals is analyzed using one or more classifiers to identify whether the biological sample is in a state of high microsatellite instability, low microsatellite instability, or stable microsatellite state.

[0352] 94. The computer program product according to embodiment 93, wherein at least one classifier includes an artificial intelligence-generated classifier.

[0353] 95. A system for identifying microsatellite instabilities in biological samples using a capillary electrophoresis genetic analysis instrument, the system comprising:

[0354] One or more computer processors, the one or more computer processors being connected to a non-transitory computer-readable medium storing one or more computer-readable instructions, the one or more computer-readable instructions being executed by the one or more computer processors as follows:

[0355] Multiple signals are obtained from a capillary electrophoresis genetic analysis instrument, wherein the signals are detected based on the fluorescence of fragments comprising nucleic acid sequences amplified from the biological sample by polymerase chain reaction, the nucleic acid sequences corresponding to multiple different microsatellite loci, wherein each signal corresponds to one of the multiple different microsatellite loci; and

[0356] One or more classifiers are used to analyze each of the plurality of signals to identify whether the biological sample has a high microsatellite instability, a low microsatellite instability, or a stable microsatellite state.

[0357] A memory, connected to at least one of the one or more processors, for storing one or more of the signal features; and

[0358] User device display, connected to the memory and configured to display one or more of the signal features.

[0359] 96. The system according to embodiment 95, wherein at least one classifier includes an artificial intelligence-generated classifier.

[0360] 97. A kit for identifying microsatellite instability in biological samples, the kit comprising:

[0361] A plurality of polymerase chain reaction (PCR) primers, the plurality of PCR primers being configured to side-join a plurality of microsatellite loci of a biological sample, such that when the PCR primers are combined with the biological sample and subjected to an amplification process, fluorescently labeled DNA fragments comprising the plurality of microsatellite loci are generated, wherein at least some of the plurality of microsatellite loci are different from the other microsatellite loci; and

[0362] A computer program product embedded in a non-transitory computer-readable medium, the computer program product comprising executable instruction code that, when executed by one or more processors, causes the one or more processors to perform processing, the processing including:

[0363] Microsatellite instabilities in the biological samples were classified using fluorescence data obtained from multiple fluorescently labeled microsatellite loci.

[0364] 98. The kit according to embodiment 97, wherein execution of the executable instruction code causes the one or more processors to perform a process, the process including:

[0365] One or more locus-specific algorithms are applied to the fluorescence data to generate locus-specific results, thereby classifying the microsatellite instabilities of corresponding specific loci of the plurality of microsatellite loci; and

[0366] The microsatellite instabilities of the biological samples were classified using locus-specific results.

[0367] 99. A method of treating a patient with a tumor with an antitumor drug, wherein the antitumor drug is more likely to be effective when the tumor cells exhibit high microsatellite instability, the method comprising:

[0368] Biological samples were obtained from the patient, the biological samples including cells from the tumor;

[0369] The method according to any one of embodiments 73 to 92 is used to determine whether the cells of the tumor exhibit high microsatellite instability; and

[0370] If the microsatellite instability of the cells of the tumor is found to be high, the antitumor drug is administered to the patient to treat the tumor.

[0371] 100. A method of treating a patient with a tumor with an antitumor drug, wherein the antitumor drug is more likely to be effective when the tumor cells exhibit high microsatellite instability, the method comprising:

[0372] Biological samples were obtained from the patient, the biological samples including cells from the tumor;

[0373] The computer program product according to any one of embodiments 93 to 94 is used to determine whether the cells of the tumor exhibit high microsatellite instability; and

[0374] If the microsatellite instability of the cells of the tumor is found to be high, the antitumor drug is administered to the patient to treat the tumor.

[0375] 101. A method of treating a patient with a tumor with an antitumor drug, wherein the antitumor drug is more likely to be effective when the tumor cells exhibit high microsatellite instability, the method comprising:

[0376] Biological samples were obtained from the patient, the biological samples including cells from the tumor;

[0377] The system according to any one of embodiments 95 to 96 is used to determine whether the cells of the tumor exhibit high microsatellite instability; and

[0378] If the microsatellite instability of the cells of the tumor is found to be high, the antitumor drug is administered to the patient to treat the tumor.

[0379] 102. A method of treating a patient with a tumor with an antitumor drug, wherein the antitumor drug is more likely to be effective when the tumor cells exhibit high microsatellite instability, the method comprising:

[0380] Biological samples were obtained from the patient, the biological samples including cells from the tumor;

[0381] The tumor cells were determined to exhibit high microsatellite instability using a kit according to any one of embodiments 97 to 98; and

[0382] If the microsatellite instability of the cells of the tumor is found to be high, the antitumor drug is administered to the patient to treat the tumor.

Claims

1. A primer set comprising one or more primer pairs, each primer pair comprising a first primer and a second primer, wherein the polynucleotide sequences of the first primer and the second primer comprise one of the following pairs: SEQ ID NO.: 1 and SEQ ID NO.: 2; SEQ ID NO.: 3 and SEQ ID NO.: 4; SEQ ID NO.: 5 and SEQ ID NO.: 6; SEQ ID NO.: 7 and SEQ ID NO.: 8; SEQ ID NO.: 9 and SEQ ID NO.: 10; SEQ ID NO.: 11 and SEQ ID NO.: 12; SEQ ID NO.: 13 and SEQ ID NO.: 14; SEQ ID NO.: 15 and SEQ ID NO.: 16; SEQ ID NO.: 17 and SEQ ID NO.:

18. The polynucleotide sequences of SEQ ID NO.: 18; SEQ ID NO.: 19 and SEQ ID NO.: 20; SEQ ID NO.: 21 and SEQ ID NO.: 22; SEQ ID NO.: 23 and SEQ ID NO.: 24; and / or SEQ ID NO.: 25 and SEQ ID NO.:

26.

2. The primer set according to claim 1, wherein at least one primer includes a modification.

3. The primer set according to claim 2, wherein the modification includes a detectable marker.

4. The primer set according to claim 3, wherein the detectable marker is a fluorescent marker.

5. The primer set according to any one of claims 2 to 4, wherein each primer pair includes modifications different from those of each other primer pair.

6. A composition comprising the primer set according to any one of claims 1 to 5.

7. The composition according to claim 6, wherein the primer set comprises at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, or at least 12 primer pairs.

8. The composition according to claim 6 or 7, comprising 13 primer pairs, said primer pairs comprising the polynucleotide sequences of SEQ ID NO.:1-26.

9. The composition according to any one of claims 6 to 8, wherein at least one primer is modified.

10. The composition of claim 9, wherein the modification comprises a detectable marker.

11. The composition according to any one of claims 6 to 10, further comprising a polymerase.

12. The composition according to any one of claims 6 to 11, further comprising a plurality of deoxyribonucleoside triphosphates.

13. The composition according to any one of claims 6 to 12, further comprising a DNA sample.

14. The composition according to any one of claims 6 to 13, further comprising one or more salts.

15. A system comprising the composition according to any one of claims 6 to 14 and a first device configured to perform DNA amplification.

16. The system of claim 15, wherein the first device is configured to perform Sanger sequencing, ion semiconductor sequencing, capillary electrophoresis, or high-resolution melt analysis.

17. The system of claim 15 or 16, further comprising a second means configured to compare and / or analyze fragments generated by DNA amplification using the primers.

18. A kit comprising a buffer and at least one primer pair for amplification of a microsatellite locus, said primer pair comprising a first primer and a second primer, and said microsatellite locus comprising BAT25, BAT26, BAT40, CAT25, NR21, NR22, NR24, NR27, ABI-20A, ABI-17, ABI-16, ABI-20B and / or ABI-19.

19. The kit of claim 18, wherein the at least one primer pair comprises at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, or at least 12 or at least 13 primer pairs.

20. The kit according to claim 18 or 19, wherein the at least one primer pair comprises at least one primer having a polynucleotide sequence having any one of SEQ ID NO.: 1-26.

21. The kit according to claim 20, wherein the at least one primer pair comprises 13 primer pairs, the primers having a polynucleotide sequence of any one of SEQ ID NO.: 1-26.

22. The kit according to any one of claims 18 to 21, further comprising primer pairs for amplifying the identification marker.

23. The kit according to claim 22, wherein the identification markers include PENTAD and / or TH01.

24. The kit according to any one of claims 18 to 23, wherein the polynucleotide sequences of the first primer and the second primer comprise one of the following pairs: SEQ ID NO.: 1 and SEQ ID NO.: 2; SEQ ID NO.: 3 and SEQ ID NO.: 4; SEQ ID NO.: 5 and SEQ ID NO.: 6; SEQ ID NO.: 7 and SEQ ID NO.: 8; SEQ ID NO.: 9 and SEQ ID NO.: 10; SEQ ID NO.: 11 and SEQ ID NO.: 12; SEQ ID NO.: 13 and SEQ ID NO.: 14; SEQ ID NO.: 15 and SEQ ID NO.: 16; SEQ ID NO.: 17 and SEQ ID NO.: 18; SEQ ID NO.: The polynucleotide sequences of SEQ ID NO.: 19 and SEQ ID NO.: 20; the polynucleotide sequences of SEQ ID NO.: 21 and SEQ ID NO.: 22; the polynucleotide sequences of SEQ ID NO.: 23 and SEQ ID NO.: 24; and / or the polynucleotide sequences of SEQ ID NO.: 25 and SEQ ID NO.:

26.

25. The kit according to any one of claims 18 to 24, wherein all primers in the primer pair are present in the same container.

26. The kit according to any one of claims 18 to 25, comprising primers comprising the polynucleotide sequence of each of SEQ ID NO.: 1-26.

27. The kit according to any one of claims 18 to 26, further comprising polymerase and / or multiple deoxynucleoside triphosphates.

28. The kit according to any one of claims 18 to 27, wherein the buffer is a PCR buffer.

29. The kit according to any one of claims 18 to 28, wherein at least one primer from the primer set comprises a modification.

30. The kit of claim 29, wherein the modification is a detectable marker.

31. The kit of claim 30, wherein the detectable marker is a fluorescent marker.

32. The kit according to any one of claims 29 to 31, wherein each primer pair includes modifications different from those of each other primer pair.

33. The kit according to any one of claims 18 to 32, further comprising a computer program for identifying microsatellite instability in biological samples.

34. The kit of claim 33, wherein each primer pair includes a fluorescent label such that when the primer pair is combined with a biological sample and subjected to an amplification process, a fluorescently labeled DNA fragment is generated; and wherein the computer program is a computer program product embedded in a non-transitory computer-readable medium, the computer program product including executable instruction code that, when executed by one or more processors, causes the one or more processors to perform processing, the processing including: The microsatellite instabilities of the biological samples were classified using fluorescence data obtained from the fluorescently labeled DNA fragments.

35. The kit of claim 34, wherein execution of the executable instruction code causes the one or more processors to perform a process, the process comprising: One or more locus-specific algorithms are applied to the fluorescence data to generate locus-specific results, thereby classifying the microsatellite instabilities of the corresponding specific loci of the multiple microsatellite loci. as well as The microsatellite instabilities of the biological samples were classified using locus-specific results.

36. A method for identifying microsatellite instabilities in biological samples, the method comprising: Multiple signals are obtained by detecting the fluorescence of a fragment comprising a nucleic acid sequence obtained using the biological sample, wherein each signal corresponds to one of multiple different microsatellite loci; Determine one or more signal characteristics for each of the plurality of signals; as well as One or more classifiers are applied to one or more of the signal features of the plurality of microsatellite loci to identify whether the biological sample is characterized as having high microsatellite instability, low microsatellite instability, or stable microsatellite instability.

37. The method of claim 36, further comprising: One or more classifiers are applied to one or more signal features of the signal corresponding to each individual microsatellite locus among the plurality of different microsatellite loci to identify whether each individual microsatellite locus is microsatellite unstable or microsatellite stable. And these measurements, combined across loci, are used to determine the microsatellite status of the biological sample.

38. The method of claim 36 or 37, wherein applying one or more classifiers includes comparing signal features derived from the biological sample with signal features derived from one or more non-cancer tissue samples.

39. The method of claim 36 or 37, wherein at least one classifier includes a fragment size threshold.

40. The method of claim 36 or 37, wherein at least one classifier includes a fragment size range.

41. The method of claim 36 or 37, wherein applying the one or more classifiers includes evaluating peak counts within a specified size interval.

42. The method of claim 36 or 37, wherein applying the one or more classifiers includes evaluating the relative peak counts between tumor and normal tissue within a specified size interval.

43. The method of claim 36 or 37, wherein applying the one or more classifiers includes evaluating peak envelope counts within a specified size interval.

44. The method of claim 36 or 37, wherein applying the one or more classifiers includes evaluating peak envelope separation within a specified size interval.

45. The method of claim 36 or 37, wherein applying the one or more classifiers includes evaluating peak envelope separation within a specified size interval.

46. ​​The method of claim 36 or 37, wherein applying the one or more classifiers includes evaluating the offset of one or more peak locations within a specified size interval.

47. The method of claim 36 or 37, wherein applying the one or more classifiers includes analyzing peak pattern input.

48. The method of claim 47, wherein the peak mode input includes two or more of the following values: peak amplitude along the segment size axis, peak position along the segment size axis; peak amplitude relative to the maximum peak, peak position relative to the maximum peak, peak envelope peak amplitude, peak envelope peak position, peak envelope peak width, or peak measure relative to the peak envelope measure.

49. The method of claim 37, further comprising: When the percentage of the microsatellite loci determined to be microsatellite unstable is higher than a first predetermined threshold, the biological sample is assigned a high microsatellite instability state. If the percentage of microsatellite loci determined to be microsatellite unstable is higher than a second predetermined threshold but lower than the first predetermined threshold, then the biological sample is assigned a low microsatellite instability state. Alternatively, if the percentage of microsatellite loci determined to be microsatellite unstable is below the second predetermined threshold, then the biological sample is assigned a microsatellite stable state.

50. The method of claim 37, further comprising: The signal characteristics are analyzed to assign stable or unstable values ​​to each microsatellite locus in the microsatellite locus; A weighted sum is calculated for the assigned stable and unstable values ​​across the microsatellite loci; as well as If the weighted sum across the microsatellite loci exceeds a first predetermined threshold, the biological sample is assigned a high microsatellite instability state; if the weighted sum across the microsatellite loci exceeds a second predetermined threshold but does not exceed the first predetermined threshold, the biological sample is assigned a low microsatellite instability state. Alternatively, if the weighted sum across the microsatellite loci is less than the second predetermined threshold, a microsatellite stable state is assigned to the biological sample.

51. The method of claim 50, wherein the weighted sum is calculated using one or more classification functions, the one or more classification functions mapping the plurality of signal features to three different output values.

52. A method for identifying microsatellite instabilities in biological samples, the method comprising: Multiple signals are obtained by detecting the fluorescence of a fragment comprising a nucleic acid sequence amplified from the biological sample, the nucleic acid sequence corresponding to multiple different microsatellite loci, wherein each signal corresponds to one of multiple different microsatellite loci; as well as One or more classifiers are used to analyze the multiple signals to identify whether the biological sample has high microsatellite instability, low microsatellite instability, or is microsatellite stable.

53. The method of claim 52, wherein the classifier comprises a nonlinear classification function.

54. The method of claim 53, wherein the nonlinear classification function comprises a multilayer artificial neural network.

55. The method of claim 52, wherein the classifier comprises a deep learning neural network.

56. A computer program product comprising executable code stored in a non-transitory computer-readable medium, the executable code being executable on one or more computer processors to identify microsatellite instabilities in a biological sample, the executable code including one or more computer-readable instructions for performing: Multiple signals are obtained from a capillary electrophoresis genetic analysis instrument, wherein the signals are detected based on the fluorescence of fragments comprising nucleic acid sequences amplified from the biological sample by polymerase chain reaction, the nucleic acid sequences corresponding to multiple different microsatellite loci, wherein each signal corresponds to one of the multiple different microsatellite loci; and Each of the plurality of signals is analyzed using one or more classifiers to identify whether the biological sample is in a state of high microsatellite instability, low microsatellite instability, or stable microsatellite state.

57. The computer program product of claim 56, wherein at least one classifier comprises an artificial intelligence-generated classifier.

58. A system for identifying microsatellite instabilities in biological samples using a capillary electrophoresis genetic analysis instrument, the system comprising: One or more computer processors, the one or more computer processors being connected to a non-transitory computer-readable medium storing one or more computer-readable instructions, the one or more computer-readable instructions being executed by the one or more computer processors as follows: Multiple signals are obtained from a capillary electrophoresis genetic analysis instrument, wherein the signals are detected based on the fluorescence of fragments comprising nucleic acid sequences amplified from the biological sample by polymerase chain reaction, the nucleic acid sequences corresponding to multiple different microsatellite loci, wherein each signal corresponds to one of multiple different microsatellite loci; as well as One or more classifiers are used to analyze each of the plurality of signals to identify whether the biological sample has a high microsatellite instability, a low microsatellite instability, or a stable microsatellite state. A memory connected to at least one of the one or more processors to store one or more signal features; as well as User device display, connected to the memory and configured to display one or more of the signal features.

59. The system of claim 58, wherein at least one classifier comprises an artificial intelligence-generated classifier.

60. A kit for identifying microsatellite instability in biological samples, the kit comprising: Multiple polymerase chain reaction (PCR) primers are configured to side-connect multiple microsatellite loci of a biological sample, such that when the PCR primers are combined with the biological sample and subjected to an amplification process, fluorescently labeled DNA fragments comprising the multiple microsatellite loci are generated, wherein at least some of the multiple microsatellite loci are different from the other microsatellite loci. as well as A computer program product embedded in a non-transitory computer-readable medium, the computer program product comprising executable instruction code that, when executed by one or more processors, causes the one or more processors to perform processing, the processing including: Microsatellite instabilities in the biological samples were classified using fluorescence data obtained from multiple fluorescently labeled microsatellite loci.

61. The kit of claim 60, wherein execution of the executable instruction code causes the one or more processors to perform a process, the process comprising: One or more locus-specific algorithms are applied to the fluorescence data to generate locus-specific results, thereby classifying the microsatellite instabilities of the corresponding specific loci of the multiple microsatellite loci. as well as The microsatellite instabilities of the biological samples were classified using locus-specific results.

62. A method of treating a patient with a tumor with an antitumor drug, wherein the antitumor drug is more likely to be effective when the tumor cells exhibit high microsatellite instability, the method comprising: Biological samples were obtained from the patient, the biological samples including cells from the tumor; The method according to any one of claims 36 to 55 is used to determine whether the cells of the tumor exhibit high microsatellite instability; and If the microsatellite instability of the cells of the tumor is found to be high, the antitumor drug is administered to the patient to treat the tumor.

63. A method of treating a patient with a tumor with an antitumor drug, wherein the antitumor drug is more likely to be effective when the tumor cells exhibit high microsatellite instability, the method comprising: Biological samples were obtained from the patient, the biological samples including cells from the tumor; The computer program product according to any one of claims 56 to 57 is used to determine whether the cells of the tumor exhibit high microsatellite instability; and If the microsatellite instability of the cells of the tumor is found to be high, the antitumor drug is administered to the patient to treat the tumor.

64. A method of treating a patient with a tumor with an antitumor drug, wherein the antitumor drug is more likely to be effective when the tumor cells exhibit high microsatellite instability, the method comprising: Biological samples were obtained from the patient, the biological samples including cells from the tumor; The system according to any one of claims 58 to 59 is used to determine whether the cells of the tumor exhibit high microsatellite instability; and If the microsatellite instability of the cells of the tumor is found to be high, the antitumor drug is administered to the patient to treat the tumor.

65. A method of treating a patient with a tumor with an antitumor drug, wherein the antitumor drug is more likely to be effective when the tumor cells exhibit high microsatellite instability, the method comprising: Biological samples were obtained from the patient, the biological samples including cells from the tumor; The tumor cells were determined to exhibit high microsatellite instability using the kit according to any one of claims 60 to 61; and If the microsatellite instability of the cells of the tumor is found to be high, the antitumor drug is administered to the patient to treat the tumor.

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