Methods and systems for assessing microsatellite instability

Abstract

The invention disclosed herein generally relates to methods for assessing microsatellite instability in a subject. In one aspect, the present disclosure provides a computer-implemented method for assessing microsatellite instability in a subject, the method comprising: obtaining quantitative measures of a plurality of microsatellite repeat elements from a blood sample of the subject; processing the plurality of quantitative measures to obtain a statistical measure of the deviation of the plurality of quantitative measures; and detecting the presence of microsatellite instability (MSI) in the subject when the statistical measure of the deviation of the plurality of quantitative measures meets a predetermined criterion, or detecting the absence of microsatellite instability (MSI) in the subject when the statistical measure of the deviation of the plurality of quantitative measures does not meet a predetermined criterion.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of U.S. Provisional Patent Application No. 62 / 731,718, filed on September 14, 2018, the entire contents of which are incorporated herein by reference. Background Art

[0003] Microsatellite instability (MSI) can generally refer to genetic susceptibility mutations caused by impaired DNA mismatch repair (MMR) in subjects. In subjects with MSI, cells with abnormal MMR function may accumulate errors during DNA replication, producing mutated microsatellite fragments or repeated DNA sequences. MSI may play an important role in many types of cancer, such as colon cancer, gastric cancer, endometrial cancer, ovarian cancer, hepatobiliary cancer, urinary tract cancer, brain cancer, and skin cancer. For example, MSI is a good marker for detecting hereditary non-polyposis colorectal cancer (HNPCC) or Lynch syndrome, an autosomal dominant genetic disease with a high risk of colon cancer and other types of cancer. In addition, microsatellite status can indicate the prognosis of a subject for cancer treatment. For example, MSI studies in patients with colon cancer have shown that patients with high MSI (MSI-H) have a better prognosis than patients with low MSI (MSI-L) or microsatellite stable (MSS) tumors. Summary of the invention

[0004] Provided herein are methods, systems and media for assessing the microsatellite instability (MSI) of a subject (e.g., a patient with cancer) by analyzing a blood sample of the subject. Microsatellite instability (MSI) can be assessed and / or monitored by analyzing the tumor DNA (e.g., from cell-free DNA) of the subject sample in a plurality of genetic loci corresponding to a microsatellite comprising mononucleotides and dinucleotides, and by measuring the average length of each of a plurality of microsatellite repeat elements from the blood sample of the subject based on the analysis of the tumor DNA. For example, the MSI of the subject can be assessed by identifying the presence or absence of MSI in the subject. The average insertion or deletion (indel) length of the measured microsatellite repeat elements, such as the deletion of two repeat units, can be based on, for example, a score of a group of microsatellite repeat elements (e.g., an insertion or deletion (indel) exceeding a certain size, or the average number of microsatellite lengths in the sequencing data of each microsatellite locus, from a group of selected repeat elements. The MSI state of the subject can indicate the diagnosis, prognosis or treatment selection of the subject.

[0005] In some embodiments, the MSI status can change (e.g., increase or decrease) over a period of time (e.g., at two or more different time points). In some embodiments, the duration can correspond to, for example, a course of treatment for a subject's cancer or a monitoring period after surgical resection or other therapy of a tumor (e.g., to detect recurrence of a tumor in a subject). In some embodiments, the generation of the MSI status can include generating a quantitative measure of cfDNA sequencing reads for each of a plurality of genetic loci corresponding to microsatellites. A plurality of genetic loci may include microsatellites, such as a whole set of microsatellite repeat sequences (or a subset thereof) in a human reference genome, a set of microsatellite repeat sequences (or a subset thereof) optimized to minimize noise in microsatellite stable (MSS) data, a set of microsatellite repeat sequences of the same class (e.g., all repeat sequences with a length of 1 for the repeat unit, or a subset thereof), a set of microsatellite repeat units within a certain size (e.g., length) range, wherein the sequencing data indicates a set of microsatellite repeat sequences (or a subset thereof) lacking promiscuous germline insertions or deletions (indels), a set of microsatellite repeat units (or a subset thereof) optimized to maximize algorithm performance for a given set of training data, or a union or intersection of a combination thereof. In some cases, a quantitative measure of cfDNA (e.g., sequencing reads) may include counts of sequencing reads aligned to each of a plurality of genetic loci. Alternatively, obtaining a quantitative measure of cfDNA may include performing a binding measurement of a plurality of cfDNA molecules on each of a plurality of microsatellite repeat elements. In some embodiments, the generation of an MSI state may include generating a comparison (e.g., a difference or ratio) of a quantitative measure for cfDNA (e.g., sequencing reads). By evaluating comparisons of sequencing read counts between loci corresponding to different sets of microsatellites, the methods provided herein can allow for the generation of an MSI status that is useful for diagnosis, prognosis, or treatment selection for a subject by non-invasive laboratory testing (e.g., a blood-based test).

[0006] In one aspect, the present disclosure provides a computer-implemented method for assessing microsatellite instability in a subject, the method comprising: obtaining quantitative measures of multiple microsatellite repeat elements from a blood sample of the subject; processing the multiple quantitative measures to obtain statistical measures of deviations of the multiple quantitative measures; and detecting the presence of microsatellite instability (MSI) in the subject when the statistical measures of the deviations of the multiple quantitative measures meet a predetermined criterion, or detecting the absence of microsatellite instability (MSI) in the subject when the statistical measures of the deviations of the multiple quantitative measures do not meet the predetermined criterion.

[0007] In some embodiments, the quantitative measure of multiple microsatellite repeat elements is selected from the average length of each (or a subset thereof) of multiple microsatellite repeat elements, the number, frequency or fraction of multiple microsatellite repeat elements (or a subset thereof) whose length falls within a predetermined size range, and the average insertion or deletion (indel) length of multiple microsatellite repeat elements (or their subelements). In some embodiments, the subject is diagnosed with cancer. In some embodiments, the subject is asymptomatic for cancer. In some embodiments, the subject has one or more cancer risk factors (e.g., age, sex, race, ethnicity, family history, smoking or drinking history, the presence of genetic variation or other clinical health characteristics). In some embodiments, multiple quantitative measures are measured from multiple cell-free DNA (cfDNA) molecules. In some embodiments, multiple quantitative measures are measured from a set of sequencing reads at each of multiple microsatellite repeat elements in multiple cfDNA molecules. In some embodiments, the method further includes sequencing multiple cfDNA molecules to generate the set of sequencing reads. In some embodiments, sequencing includes whole genome sequencing (WGS). In some embodiments, sequencing is performed at a depth of no more than about 50X, no more than about 48X, no more than about 46X, no more than about 44X, no more than about 42X, no more than about 40X, no more than about 38X, no more than about 36X, no more than about 34X, no more than about 32X, no more than about 30X, no more than about 28X, no more than about 24X, no more than about 22X, no more than about 20X, no more than about 18X, no more than about 16X, no more than about 14X, or no more than about 12X. In some embodiments, sequencing is performed at a depth of no more than about 10X. In some embodiments, sequencing is performed at a depth of no more than about 8X. In some embodiments, sequencing is performed at a depth of no more than about 6X. In some embodiments, sequencing is performed at a depth of no more than about 5X, no more than about 4X, no more than about 3X, no more than about 2X, or no more than about 1X. In some embodiments, measuring a plurality of quantitative measures comprises making binding measurements for a plurality of cfDNA molecules at each of a plurality of microsatellite repeat elements (or a subset thereof).

[0008] In some embodiments, the method further comprises, based on the presence or absence of microsatellite instability of the subject detected, identifying treatment for the subject and / or administering a therapeutically effective amount of treatment to the subject. In some embodiments, treatment is selected from chemotherapy, radiotherapy and immunotherapy. In some embodiments, treatment comprises immunotherapy. In some embodiments, immunotherapy comprises pembrolizumab. In some embodiments, the method further comprises enriching multiple cfDNA molecules for at least one subset of multiple microsatellite repeat elements. In some embodiments, enrichment comprises amplifying multiple cfDNA molecules. In some embodiments, amplification comprises selective amplification (e.g., targeted PCR or targeted enrichment, followed by universal or targeted PCR). In some embodiments, amplification comprises universal amplification (e.g., universal PCR). In some embodiments, enrichment comprises selectively separating at least a portion of multiple cfDNA molecules (e.g., targeted enrichment). In some embodiments, the at least portion comprises a mononucleotide. In some embodiments, the at least portion comprises a dinucleotide.

[0009] In some embodiments, the statistical measure of deviation is an average z score. In some embodiments, the statistical measure of deviation is an average z score relative to a reference blood sample. In some embodiments, a reference blood sample is obtained from a subject with microsatellite instability (e.g., an MSI positive subject). In some embodiments, a reference blood sample is obtained from a subject without microsatellite instability (e.g., an MSI negative or MSS subject). In some embodiments, the predetermined standard is that the absolute value of the average z score is greater than a predetermined number. In some embodiments, the predetermined number is about 1. In some embodiments, the predetermined number is about 2. In some embodiments, the predetermined number is about 3. In some embodiments, a plurality of microsatellite repeat elements comprise mononucleotides or dinucleotides. In some embodiments, a plurality of microsatellite repeat elements comprise mononucleotides and dinucleotides.

[0010] In some embodiments, the plurality of microsatellite repeat elements comprises at least about one million different microsatellite repeat elements. In some embodiments, the plurality of microsatellite repeat elements comprises at least about 5 million different microsatellite repeat elements. In some embodiments, the plurality of microsatellite repeat elements comprises at least about 10 million different microsatellite repeat elements. In some embodiments, the plurality of microsatellite repeat elements comprises at least about 20 million different microsatellite repeat elements.

[0011] In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 70%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 80%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 90%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 95%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 99%.

[0012] In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 70%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 80%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 90%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 95%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 99%.

[0013] In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 70%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 80%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 90%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 95%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 99%.

[0014] In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 70%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 80%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 90%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 95%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 99%.

[0015] In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.70. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.80. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.90. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.95. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.96, at least about 0.97, or at least about 0.98. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.99.

[0016] In some embodiments, the method further comprises: detecting the presence of microsatellite stability (MSS) of the subject when the statistical measure of the deviation of the multiple quantitative measurements does not meet a predetermined criterion, or detecting the absence of microsatellite stability (MSS) when the statistical measure of the deviation of the multiple quantitative measurements meets a predetermined criterion.

[0017] In some embodiments, the presence of microsatellite stability in a subject is detected with a sensitivity of at least about 70%. In some embodiments, the presence of microsatellite stability in a subject is detected with a sensitivity of at least about 80%. In some embodiments, the presence of microsatellite stability in a subject is detected with a sensitivity of at least about 90%. In some embodiments, the presence of microsatellite stability in a subject is detected with a sensitivity of at least about 95%. In some embodiments, the presence of microsatellite stability in a subject is detected with a sensitivity of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the presence of microsatellite stability in a subject is detected with a sensitivity of at least about 99%.

[0018] In some embodiments, the absence of microsatellite stability in a subject is detected with a specificity of at least about 70%. In some embodiments, the absence of microsatellite stability in a subject is detected with a specificity of at least about 80%. In some embodiments, the absence of microsatellite stability in a subject is detected with a specificity of at least about 90%. In some embodiments, the absence of microsatellite stability in a subject is detected with a specificity of at least about 95%. In some embodiments, the absence of microsatellite stability in a subject is detected with a specificity of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the absence of microsatellite stability in a subject is detected with a specificity of at least about 99%.

[0019] In some embodiments, the presence of microsatellite stability of a subject is detected with a positive predictive value (PPV) of at least about 70%. In some embodiments, the presence of microsatellite stability of a subject is detected with a positive predictive value (PPV) of at least about 80%. In some embodiments, the presence of microsatellite stability of a subject is detected with a positive predictive value (PPV) of at least about 90%. In some embodiments, the presence of microsatellite stability of a subject is detected with a positive predictive value (PPV) of at least about 95%. In some embodiments, the presence of microsatellite stability of a subject is detected with a positive predictive value (PPV) of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the presence of microsatellite stability of a subject is detected with a positive predictive value (PPV) of at least about 99%.

[0020] In some embodiments, the absence of microsatellite stability of a subject is detected with a negative predictive value (NPV) of at least about 70%. In some embodiments, the absence of microsatellite stability of a subject is detected with a negative predictive value (NPV) of at least about 80%. In some embodiments, the absence of microsatellite stability of a subject is detected with a negative predictive value (NPV) of at least about 90%. In some embodiments, the absence of microsatellite stability of a subject is detected with a negative predictive value (NPV) of at least about 95%. In some embodiments, the absence of microsatellite stability of a subject is detected with a negative predictive value (NPV) of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the absence of microsatellite stability of a subject is detected with a negative predictive value (NPV) of at least about 99%.

[0021] In some embodiments, the presence or absence of microsatellite stability of a subject is detected with an area under the curve (AUC) of at least about 0.70. In some embodiments, the presence or absence of microsatellite stability of a subject is detected with an area under the curve (AUC) of at least about 0.80. In some embodiments, the presence or absence of microsatellite stability of a subject is detected with an area under the curve (AUC) of at least about 0.90. In some embodiments, the presence or absence of microsatellite stability of a subject is detected with an area under the curve (AUC) of at least about 0.95. In some embodiments, the presence or absence of microsatellite stability of a subject is detected with an area under the curve (AUC) of at least about 0.96, at least about 0.97, or at least about 0.98. In some embodiments, the presence or absence of microsatellite stability of a subject is detected with an area under the curve (AUC) of at least about 0.99.

[0022] In another aspect, the present disclosure provides a system comprising a controller comprising or capable of accessing a non-transitory computer-readable medium comprising machine-executable instructions, which when executed by one or more computer processors perform a method for assessing microsatellite instability in a subject, the method comprising: obtaining quantitative measures of multiple microsatellite repeat elements from a blood sample of the subject; processing the multiple quantitative measures to obtain statistical measures of deviations of the multiple quantitative measures; and when the statistical measures of the deviations of the multiple quantitative measures meet a predetermined criterion, detecting the presence of microsatellite instability (MSI) in the subject; or when the statistical measures of the deviations of the multiple quantitative measures do not meet the predetermined criterion, detecting the absence of microsatellite instability (MSI) in the subject.

[0023] In some embodiments, the quantitative measure of multiple microsatellite repeat elements is selected from the average length of each (or a subset thereof) of multiple microsatellite repeat elements, the number, frequency or fraction of multiple microsatellite repeat elements (or a subset thereof) whose length falls within a predetermined size range, and the average insertion or deletion (indel) length of each of multiple microsatellite repeat elements (or their subelements). In some embodiments, the subject is diagnosed with cancer. In some embodiments, the subject is asymptomatic for cancer. In some embodiments, the subject has one or more cancer risk factors (e.g., age, sex, race, ethnicity, family history, smoking or drinking history, the presence of genetic variation or other clinical health characteristics). In some embodiments, multiple quantitative measures are measured from multiple cell-free DNA (cfDNA) molecules. In some embodiments, multiple quantitative measures are measured from a set of sequencing reads at each of multiple microsatellite repeat elements in multiple cfDNA molecules. In some embodiments, the method of the system also includes sequencing multiple cfDNA molecules to produce a group of sequencing reads. In some embodiments, sequencing includes whole genome sequencing (WGS). In some embodiments, sequencing is performed at a depth of no more than about 50X, no more than about 48X, no more than about 46X, no more than about 44X, no more than about 42X, no more than about 40X, no more than about 38X, no more than about 36X, no more than about 34X, no more than about 32X, no more than about 30X, no more than about 28X, no more than about 24X, no more than about 22X, no more than about 20X, no more than about 18X, no more than about 16X, no more than about 14X, or no more than about 12X. In some embodiments, sequencing is performed at a depth of no more than about 10X. In some embodiments, sequencing is performed at a depth of no more than about 8X. In some embodiments, sequencing is performed at a depth of no more than about 6X. In some embodiments, sequencing is performed at a depth of no more than about 5X, no more than about 4X, no more than about 3X, no more than about 2X, or no more than about 1X. In some embodiments, measuring a plurality of quantitative measures comprises making binding measurements for a plurality of cfDNA molecules at each of a plurality of microsatellite repeat elements (or a subset thereof).

[0024] In some embodiments, the method of the system also includes, based on the presence or absence of microsatellite instability in the subject detected, identifying treatment for the subject or a therapeutically effective amount of treatment to be administered to the subject. In some embodiments, treatment is selected from chemotherapy, radiotherapy and immunotherapy. In some embodiments, treatment includes immunotherapy. In some embodiments, immunotherapy includes pembrolizumab. In some embodiments, the method of the system also includes guiding the enrichment of multiple cfDNA molecules for at least one subset of multiple microsatellite repeat elements. In some embodiments, enrichment includes amplifying multiple cfDNA molecules. In some embodiments, amplification includes selective amplification (e.g., targeted PCR or targeted enrichment, followed by universal or targeted PCR). In some embodiments, amplification includes universal amplification (e.g., universal PCR). In some embodiments, enrichment includes selectively separating at least a portion of multiple cfDNA molecules (e.g., targeted enrichment). In some embodiments, the at least portion comprises a mononucleotide. In some embodiments, the at least portion comprises a dinucleotide.

[0025] In some embodiments, the statistical measure of deviation is an average z score. In some embodiments, the statistical measure of deviation is an average z score relative to a reference blood sample. In some embodiments, a reference blood sample is obtained from a subject with microsatellite instability (e.g., an MSI positive subject). In some embodiments, a reference blood sample is obtained from a subject without microsatellite instability (e.g., an MSI negative or MSS subject). In some embodiments, the predetermined standard is that the absolute value of the average z score is greater than a predetermined number. In some embodiments, the predetermined number is about 1. In some embodiments, the predetermined number is about 2. In some embodiments, the predetermined number is about 3. In some embodiments, a plurality of microsatellite repeat elements comprise mononucleotides or dinucleotides. In some embodiments, a plurality of microsatellite repeat elements comprise mononucleotides and dinucleotides.

[0026] In some embodiments, the plurality of microsatellite repeat elements comprises at least about one million different microsatellite repeat elements. In some embodiments, the plurality of microsatellite repeat elements comprises at least about 5 million different microsatellite repeat elements. In some embodiments, the plurality of microsatellite repeat elements comprises at least about 10 million different microsatellite repeat elements. In some embodiments, the plurality of microsatellite repeat elements comprises at least about 20 million different microsatellite repeat elements.

[0027] In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 70%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 80%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 90%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 95%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 99%.

[0028] In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 70%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 80%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 90%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 95%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 99%.

[0029] In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 70%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 80%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 90%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 95%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 99%.

[0030] In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 70%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 80%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 90%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 95%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 99%.

[0031] In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.70. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.80. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.90. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.95. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.96, at least about 0.97, or at least about 0.98. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.99.

[0032] In some embodiments, the method of the system also includes: detecting the presence of microsatellite stability (MSS) of the subject when the statistical measure of the deviation of the multiple quantitative measurements does not meet a predetermined standard; or detecting the absence of microsatellite stability (MSS) of the subject when the statistical measure of the deviation of the multiple quantitative measurements meets a predetermined standard.

[0033] In another aspect, the present disclosure provides a non-transitory computer-readable medium comprising machine executable code, which, when executed by one or more computer processors, performs a method for assessing microsatellite instability in a subject, the method comprising: obtaining quantitative measures of multiple microsatellite repeat elements from a blood sample of the subject; processing the multiple quantitative measures to obtain statistical measures of deviations of the multiple quantitative measures; and when the statistical measures of deviations of the multiple quantitative measures meet predetermined criteria, detecting the presence of microsatellite instability (MSI) in the subject; or when the statistical measures of deviations of the multiple quantitative measures do not meet predetermined criteria, detecting the absence of microsatellite instability (MSI) in the subject.

[0034] In some embodiments, the quantitative measure of multiple microsatellite repeat elements is selected from the average length of each (or a subset thereof) of multiple microsatellite repeat elements, the number, frequency or fraction of multiple microsatellite repeat elements (or a subset thereof) whose length falls within a predetermined size range, and the average insertion or deletion (indel) length of each of multiple microsatellite repeat elements (or their subelements). In some embodiments, the subject is diagnosed with cancer. In some embodiments, the subject is asymptomatic for cancer. In some embodiments, the subject has one or more cancer risk factors (e.g., age, sex, race, ethnicity, family history, smoking or drinking history, the presence of genetic variation or other clinical health characteristics). In some embodiments, multiple quantitative measures are measured from multiple cell-free DNA (cfDNA) molecules. In some embodiments, multiple quantitative measures are measured from a set of sequencing reads at each of multiple microsatellite repeat elements in multiple cfDNA molecules. In some embodiments, the method of a non-transitory computer-readable medium also includes sequencing multiple cfDNA molecules to produce a group of sequencing reads. In some embodiments, sequencing includes whole genome sequencing (WGS). In some embodiments, sequencing is performed at a depth of no more than about 50X, no more than about 48X, no more than about 46X, no more than about 44X, no more than about 42X, no more than about 40X, no more than about 38X, no more than about 36X, no more than about 34X, no more than about 32X, no more than about 30X, no more than about 28X, no more than about 24X, no more than about 22X, no more than about 20X, no more than about 18X, no more than about 16X, no more than about 14X, or no more than about 12X. In some embodiments, sequencing is performed at a depth of no more than about 10X. In some embodiments, sequencing is performed at a depth of no more than about 8X. In some embodiments, sequencing is performed at a depth of no more than about 6X. In some embodiments, sequencing is performed at a depth of no more than about 5X, no more than about 4X, no more than about 3X, no more than about 2X, or no more than about 1X. In some embodiments, measuring a plurality of quantitative measures comprises performing binding measurements on a plurality of cfDNA molecules at each of a plurality of microsatellite repeat elements (or a subset thereof).

[0035] In some embodiments, the method of the non-transitory computer-readable medium further comprises, based on the presence or absence of microsatellite instability of the subject detected, identifying a treatment for the subject or a treatment to be administered to the subject in a therapeutically effective amount. In some embodiments, the treatment is selected from chemotherapy, radiotherapy and immunotherapy. In some embodiments, the treatment comprises immunotherapy. In some embodiments, immunotherapy comprises pembrolizumab. In some embodiments, the method of the non-transitory computer-readable medium further comprises guiding the enrichment of multiple cfDNA molecules for at least one subset of multiple microsatellite repeat elements. In some embodiments, enrichment comprises amplifying multiple cfDNA molecules. In some embodiments, amplification comprises selective amplification (e.g., targeted PCR or targeted enrichment, followed by universal or targeted PCR). In some embodiments, amplification comprises universal amplification (e.g., universal PCR). In some embodiments, enrichment comprises selectively separating at least a portion of multiple cfDNA molecules (e.g., targeted enrichment). In some embodiments, the at least portion comprises a mononucleotide. In some embodiments, the at least portion comprises a dinucleotide.

[0036] In some embodiments, the statistical measure of deviation is an average z score. In some embodiments, the statistical measure of deviation is an average z score relative to a reference blood sample. In some embodiments, a reference blood sample is obtained from a subject with microsatellite instability (e.g., an MSI positive subject). In some embodiments, a reference blood sample is obtained from a subject without microsatellite instability (e.g., an MSI negative or MSS subject). In some embodiments, the predetermined standard is that the absolute value of the average z score is greater than a predetermined number. In some embodiments, the predetermined number is about 1. In some embodiments, the predetermined number is about 2. In some embodiments, the predetermined number is about 3. In some embodiments, a plurality of microsatellite repeat elements comprise mononucleotides or dinucleotides. In some embodiments, a plurality of microsatellite repeat elements comprise mononucleotides and dinucleotides.

[0037] In some embodiments, the plurality of microsatellite repeat elements comprises at least about one million different microsatellite repeat elements. In some embodiments, the plurality of microsatellite repeat elements comprises at least about 5 million different microsatellite repeat elements. In some embodiments, the plurality of microsatellite repeat elements comprises at least about 10 million different microsatellite repeat elements. In some embodiments, the plurality of microsatellite repeat elements comprises at least about 20 million different microsatellite repeat elements.

[0038] In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 70%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 80%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 90%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 95%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the presence of microsatellite instability in a subject is detected with a sensitivity of at least about 99%.

[0039] In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 70%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 80%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 90%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 95%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the absence of microsatellite instability in a subject is detected with a specificity of at least about 99%.

[0040] In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 70%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 80%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 90%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 95%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the presence of microsatellite instability in a subject is detected with a positive predictive value (PPV) of at least about 99%.

[0041] In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 70%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 80%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 90%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 95%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 96%, at least about 97%, or at least about 98%. In some embodiments, the absence of microsatellite instability in a subject is detected with a negative predictive value (NPV) of at least about 99%.

[0042] In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.70. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.80. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.90. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.95. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.96, at least about 0.97, or at least about 0.98. In some embodiments, the presence or absence of microsatellite instability in a subject is detected with an area under the curve (AUC) of at least about 0.99.

[0043] In some embodiments, the method of non-transitory computer-readable medium also includes: detecting the presence of microsatellite stability (MSS) of the subject when the statistical measure of the deviation of the multiple quantitative measurements does not meet a predetermined standard, or detecting the absence of microsatellite stability (MSS) of the subject when the statistical measure of the deviation of the multiple quantitative measurements meets a predetermined standard.

[0044] Another aspect of the present disclosure provides a non-transitory computer-readable medium comprising machine-executable code that, when executed by one or more computer processors, implements any of the methods herein above or elsewhere herein.

[0045] Another aspect of the present disclosure provides a system comprising one or more computer processors and a computer memory coupled thereto. The computer memory comprises machine executable code, which implements any method described above or elsewhere herein when executed by one or more computer processors.

[0046] Other aspects and advantages of the present disclosure will become apparent to those skilled in the art through the following detailed description, wherein only illustrative embodiments of the present disclosure are shown and described. It will be appreciated that the present disclosure is capable of other and different embodiments, and that its several details are capable of modification in various obvious respects, all without departing from the present disclosure. Therefore, the drawings and description are to be regarded as illustrative in nature, and not restrictive.

[0047] Incorporated by Reference

[0048] All publications, patents, and patent applications mentioned in this specification are incorporated herein by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference. In the event that publications and patents or patent applications incorporated by reference conflict with the disclosure contained in this specification, this specification is intended to supersede and / or take precedence over any such conflicting material. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The patent or application file contains at least one drawing printed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.

[0050] The novel features of the present invention are particularly set forth in the appended claims. The features and advantages of the present invention may be better understood by reference to the following detailed description and accompanying drawings (also referred to herein as "Figures" and "FIG.") which set forth illustrative embodiments in which the principles of the present invention are utilized, wherein:

[0051] Figure 1 Example methods of assessing microsatellite instability in a subject according to some embodiments are shown.

[0052] Figure 2Plots showing the cumulative density function (CDF, ​​y-axis) versus microsatellite insertion or deletion (indel) length (x-axis) for four different patient cohorts: tumor TCGA-A6-A566-01A-11D-A28G, microsatellite stable (MSS) (upper left); tumor TCGA-A6-A566-01A-11D-A28G, microsatellite instability-high (MSI-H) (upper right); tumor TCGA-D7-55, microsatellite stable (MSS) (lower left); and tumor TCGA-D7-55, microsatellite instability-high (MSI-H) (lower right).

[0053] Figure 3 Shown are box plots representing the average insertion or deletion (indel) length of a panel of microsatellites determined from microsatellite stable (MSS) patients (left, blue) and microsatellite instability-high (MSI-H) patients (right, red).

[0054] Figure 4 Shown are box plots representing the average insertion or deletion (indel) length of a panel of microsatellites determined from microsatellite stable (MSS) patients (left, blue) and microsatellite instability-high (MSI-H) patients (right, red).

[0055] Figure 5 A computer system is shown that is programmed or otherwise configured to implement the methods provided herein. DETAILED DESCRIPTION

[0056] Although various embodiments of the present invention have been shown and described herein, it will be apparent to those skilled in the art that these embodiments are provided by way of example only. Without departing from the present invention, those skilled in the art may conceive of many variations, changes and substitutions. It should be understood that various alternatives to the embodiments of the present invention described herein may be employed.

[0057] As used in the specification and claims, the singular forms "a", "an" (or a noun without the article), and "the" include plural referents unless the context clearly dictates otherwise. For example, the term "nucleic acid" includes a plurality of nucleic acids, including mixtures thereof.

[0058] As used herein, the term "nucleic acid" or "polynucleotide" generally refers to a molecule comprising one or more nucleic acid subunits or nucleotides. Nucleic acids can include one or more nucleotides selected from adenosine (A), cytosine (C), guanine (G), thymine (T) and uracil (U) or variants thereof. Nucleotides generally include nucleosides and at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more phosphate radicals (PO3). Nucleotides can include nucleobases, pentoses (ribose or deoxyribose) and one or more phosphate radicals, individually or in combination.

[0059] Ribonucleotides are nucleotides in which sugar is ribose. Deoxyribonucleotides are nucleotides in which sugar is deoxyribose. Nucleotides can be nucleoside monophosphates or nucleoside polyphosphates. Nucleotides can be forms that are easy to incorporate, such as deoxyribonucleoside polyphosphates, such as deoxyribonucleoside triphosphates (dNTPs), which can be selected from deoxyadenosine triphosphate (dATP), deoxycytidine triphosphate (dCTP), deoxyguanosine triphosphate (dGTP), uridine triphosphate (dUTP) and deoxythymidine triphosphate (dTTP) dNTP, which include detectable labels, such as luminescent labels or labels (e.g., fluorophores). Nucleotides can include any subunit that can be incorporated into the growing nucleic acid chain. Such subunits can be A, C, G, T or U, or any other subunits that are unique to one or more complementary A, C, G, T or U, or any other subunits that are complementary to purine (e.g., A or G, or variants thereof) or pyrimidine (e.g., C, T or U, or variants thereof). In some examples, the nucleic acid is deoxyribonucleic acid (DNA), ribonucleic acid (RNA), or a derivative or variant thereof. The nucleic acid can be single-stranded or double-stranded. The nucleic acid molecule can be linear, curved or circular or any combination thereof.

[0060] As used herein, the terms "nucleic acid molecule," "nucleic acid sequence," "nucleic acid fragment," "oligonucleotide" and "polynucleotide" generally refer to polynucleotides that can be of various lengths, such as deoxyribonucleotides or ribonucleotides (RNA) or analogs thereof. A nucleic acid molecule can have a length of at least about 5 bases, 10 bases, 20 bases, 30 bases, 40 bases, 50 bases, 60 bases, 70 bases, 80 bases, 90, 100 bases, 110 bases, 120 bases, 130 bases, 140 bases, 150 bases, 160 bases, 170 bases, 180 bases, 190 bases, 200 bases, 300 bases, 400 bases, 500 bases, 1 kilobase (kb), 2 kb, 3 kb, 4 kb, 5 kb, 10 kb, or 50 kb, or it can have any number of bases between the above two values. Oligonucleotides are generally composed of a specific sequence of four nucleotide bases: adenine (A); cytosine (C); guanine (G); and thymine (T) (when the polynucleotide is RNA, uracil (U) is used for thymine (T). Therefore, the terms "nucleic acid molecule", "nucleic acid sequence", "nucleic acid fragment", "oligonucleotide" and "polynucleotide" are intended at least in part to be alphabetic representations of polynucleotide molecules. Alternatively, the terms can be applied to the polynucleotide molecules themselves. The alphabetic representation can be entered into a database in a computer with a central processing unit and / or used for bioinformatics applications such as functional genomics and homology searches. Oligonucleotides can include one or more non-standard nucleotides, nucleotide analogs and / or modified nucleotides.

[0061] As used herein, the term "sample" generally refers to a biological sample. Examples of biological samples include nucleic acid molecules, amino acids, polypeptides, proteins, carbohydrates, fats or viruses. In one example, a biological sample is a nucleic acid sample including one or more nucleic acid molecules. Nucleic acid molecules can be cell-free or cell-free nucleic acid molecules, such as cell-free DNA (cfDNA) or cell-free RNA (cfRNA). Nucleic acid molecules can be derived from a variety of sources, including humans, mammals, non-human mammals, apes, monkeys, chimpanzees, reptiles, amphibians or avian sources. In addition, samples can be extracted from various animal body fluids containing cell-free sequences, and these animal body fluids include but are not limited to blood, serum, plasma, vitreous, sputum, urine, tears, sweat, saliva, semen, mucosal excretions, mucus, spinal fluid, amniotic fluid, lymph fluid, etc. Cell-free polynucleotides (e.g., cfDNA) can be fetal-derived (via liquid obtained from a pregnant subject), or can be derived from the subject's own tissue.

[0062] As used herein, the term "subject" generally refers to an individual with a biological sample being processed or analyzed. The subject can be an animal or a plant. The subject can be a mammal, such as a human, dog, cat, horse, pig, or rodent. The subject can be a patient, such as suffering from or suspected of having a disease, such as one or more cancers (e.g., brain cancer, breast cancer, cervical cancer, colorectal cancer, endometrial cancer, esophageal cancer, gastric cancer, hepatobiliary cancer, leukemia, liver cancer, lung cancer, lymphoma, ovarian cancer, pancreatic cancer, skin cancer, urinary tract cancer), one or more infectious diseases, one or more hereditary diseases, or one or more tumors or any combination thereof. For a subject suffering from or suspected of having one or more tumors, the tumor can be one or more types.

[0063] As used herein, the term "whole blood" generally refers to a blood sample that has not yet been separated into subcomponents (e.g., by centrifugation). The whole blood of a blood sample may contain cfDNA and / or germline DNA. Whole blood DNA (which may contain cfDNA and / or germline DNA) can be extracted from a blood sample. Whole blood DNA sequencing reads (which may contain cfDNA sequencing reads and / or germline DNA sequencing reads) can be extracted from whole blood DNA.

[0064] Microsatellite instability (MSI) can generally refer to genetic susceptibility mutations caused by impaired DNA mismatch repair (MMR) in subjects. In such subjects, cells with abnormal MMR function may accumulate errors during DNA replication, resulting in mutated microsatellite fragments or repeated DNA sequences. MSI may play an important role in many types of cancer, such as colon cancer, gastric cancer, endometrial cancer, ovarian cancer, hepatobiliary cancer, urinary tract cancer, brain cancer and skin cancer. For example, MSI is a good marker for detecting hereditary non-polyposis colorectal cancer (HNPCC) or Lynch syndrome (an autosomal dominant genetic disorder with a high risk of colon cancer and other types of cancer). In addition, microsatellite status can indicate the prognosis of cancer treatment in subjects. For example, MSI studies conducted in patients with colon cancer have shown that patients with MSI-high (MSI-H) have a better prognosis than patients with low MSI (MSI-L) or microsatellite stable (MSS) tumors.

[0065] MSI status can be determined according to a method established by the National Cancer Institute (NCI), which can use five microsatellite markers to indicate the presence of MSI: two mononucleotides (BAT25 and BAT26) and three dinucleotide repeats (D2S123, D5S346, and D17S250). Those with an MSI greater than about 30% of the unstable MSI biomarker can be referred to as MSI-H tumors, while those with an MSI less than about 30% of the unstable MSI biomarker can be referred to as MSI-L tumors.

[0066] MSI-L tumors can be classified as tumors of other etiologies. Studies may show that MSI-H patients respond best to surgery alone, rather than chemotherapy and surgery combined. Accurate identification of MSI-H status may prevent the administration of potentially ineffective treatments such as chemotherapy to patients.

[0067] Additionally, cancer treatments can be developed and administered to patients based at least in part on the identification of MSI in the patient. TM (pembrolizumab) for adult and pediatric patients with unresectable or metastatic solid tumors characterized by high microsatellite instability or mismatch repair deficiency who have progressed on alternative medicines. Accurate identification of MSI status can allow for accurate clinical decisions, such as initiating and administering targeted therapies such as Keytruda to patients. TM (pembrolizumab).

[0068] Methods for determining MSI status in a patient may include tissue analysis. For example, polymerase chain reaction (PCR) and fragment analysis of paired normal and tumor tissue samples may be performed at each locus in a set of genetic loci (e.g., a standard set of five NCI-recommended loci) to determine microsatellite instability (MSI). Tissue analysis may produce a reported positive test result as MSI high (indicating that at least two markers are unstable) or a reported negative test result as MSI low (indicating that one marker is unstable). Such methods for MSI status determination may require obtaining tumor tissue for analysis. In some cases, obtaining tumor tissue may present challenges. Obtaining tissue may be time-consuming and expensive and require coordination with a pathologist. Obtaining biopsy tissue may be difficult, expensive, and involve painful procedures, if not impossible to obtain, and may have low to moderate clinical relevance due to underlying cancer genome evolution. In some cases, it may be necessary to wait until several years after the initial cancer diagnosis to determine whether a patient is eligible for Keytruda. TM Therefore, liquid biopsy tests for determining MSI status may offer the advantage of an earlier, less invasive, and lower-cost alternative to tumor biopsy.

[0069] Assessment of microsatellite instability in DNA sequence data from subjects

[0070] When a significant portion (e.g., greater than about 50%, about 60%, about 70%, about 80%, or about 90%) of a sample obtained from a subject is from or derived from tumor cells, the assessment of microsatellite instability (MSI) status may be relatively simple. However, in the preparation of cell-free DNA (cfDNA) from subject plasma derived from a blood sample, detecting tumor DNA from cfDNA and thereby assessing microsatellite instability (MSI) status may be an insensitive and noisy process. Due to the overwhelming signal from non-tumor DNA (e.g., germline DNA from germline cells of non-tumor origin), it may be challenging to detect tumor DNA and assess microsatellite instability (MSI) status from such insensitive and / or noisy signals. The present disclosure provides methods, systems, and media for assessing microsatellite instability (MSI) status from combined measurements of cell-free DNA (cfDNA) sequence data (e.g., cfDNA sequencing reads) or cfDNA molecules derived from subject samples. Once cfDNA sequence data is obtained from analysis of a sample from a subject, one or more bioinformatics processes can be used to assess the microsatellite instability (MSI) status of the subject.

[0071] In one aspect, the present disclosure provides a computer-implemented method for assessing microsatellite instability in a subject, the method comprising: obtaining quantitative measures of multiple microsatellite repeat elements from a blood sample of the subject; processing the multiple quantitative measures to obtain statistical measures of deviations of the multiple quantitative measures; and detecting the presence of microsatellite instability (MSI) in the subject when the statistical measures of the deviations of the multiple quantitative measures meet a predetermined criterion, or detecting the absence of microsatellite instability (MSI) in the subject when the statistical measures of the deviations of the multiple quantitative measures do not meet the predetermined criterion.

[0072] Figure 1 An example method of assessing microsatellite instability in a subject according to some embodiments is shown. In some embodiments, a quantitative measure (e.g., a plurality of average lengths) is measured from a plurality of cell-free DNA (cfDNA) molecules (e.g., in 105). In some embodiments, measuring the plurality of average lengths comprises sequencing the plurality of cfDNA molecules to generate sequencing reads at each of a plurality of microsatellite repeat elements in the plurality of cfDNA molecules (e.g., in 110).

[0073] For example, any suitable sequencing method can be used to generate sequencing reads from cfDNA. The sequencing method can be a first generation sequencing method, such as Maxam-Gilbert or Sanger sequencing, or a high-throughput sequencing (e.g., next generation sequencing or NGS) method. High-throughput sequencing methods can simultaneously (or substantially simultaneously) sequence at least about 10,000, about 100,000, about 1 million, about 10 million, about 100 million, about 100 million, about 1 billion or more than about 1 billion polynucleotide molecules. The sequencing method can include but is not limited to: pyrophosphate sequencing, synthetic sequencing, single molecule sequencing, nanopore sequencing, semiconductor sequencing, connection sequencing, hybrid sequencing, digital gene expression (Helicos), massively parallel sequencing, such as Helicos, cloning single molecule arrays (Solexa / Illumina), using PacBio, SOLiD, Ion Torrent or Nanopore platform sequencing.

[0074] In some embodiments, sequencing includes whole genome sequencing (WGS). Sequencing can be carried out at a depth sufficient to assess the microsatellite instability in a subject with a desired performance (e.g., accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) or receiver operator characteristic (ROC) curve area (AUC)). In some embodiments, sequencing is performed in a "low-pass" manner, such as a depth of not more than about 12X, not more than about 11X, not more than about 10X, not more than about 9X, not more than about 8X, not more than about 7X, not more than about 6X, not more than about 5X, not more than about 4X, not more than about 3X, or not more than about 2X.

[0075] In some embodiments, assessing microsatellite instability in a subject may include comparing cfDNA sequencing reads to a reference genome. A reference genome may include at least a portion of a genome (e.g., a human genome). A reference genome may include an entire genome (e.g., an entire human genome). A reference genome may include a database comprising a plurality of genomic regions corresponding to coding and / or non-coding genomic regions of a genome. The database may include a plurality of genomic regions corresponding to coding and / or non-coding genomic regions of a genome associated with cancer (or tumor associated), such as cancer driver gene mutations (e.g., single nucleotide variants (SNVs), copy number variations (CNVs), insertions or deletions (indels), fusion genes, and microsatellite repeat elements (e.g., mononucleotides and / or dinucleotides)). For example, alignment may be performed using the Burrows-Wheeler algorithm or any other suitable alignment algorithm.

[0076] In some embodiments, assessing microsatellite instability in a subject can include generating a quantitative measure of cfDNA sequencing reads for each of a plurality of genetic loci. A quantitative measure of cfDNA sequencing reads may be generated, such as a count of DNA sequencing reads aligned to a given locus (e.g., a microsatellite repeat element). CfDNA sequencing reads with some or all sequencing reads aligned to a given microsatellite repeat element can be counted in the quantitative measure of the microsatellite repeat element.

[0077] In some embodiments, a plurality of microsatellite repeat elements are selected from the entire set of microsatellite repeat sequences (or a subset thereof) in a human reference genome, a set of microsatellite repeat sequences (or a subset thereof) optimized to minimize noise in MSS data, a set of microsatellite repeat sequences of the same class (e.g., all repeat sequences with a repeat unit length of 1), a set of microsatellite repeat units within a certain size (e.g., length) range, a set of microsatellite repeat sequences in which sequencing data indicates the lack of promiscuous germline indels, a set of microsatellite repeat units (or a subset thereof) optimized to maximize algorithm performance for a given set of training data, or a union or intersection of a combination thereof. The pattern of specific and non-specific microsatellite repeat elements may indicate a microsatellite instability (MSI) state or a microsatellite stability (MSS) state. Changes in the pattern of these microsatellite repeat elements over time may indicate changes in a microsatellite instability (MSI) state or a microsatellite stability (MSS) state.

[0078] In some embodiments, measuring multiple average lengths includes performing a combined measurement of multiple cfDNA molecules on each of multiple microsatellite repeat elements. In some embodiments, performing a combined measurement includes analyzing multiple cfDNA molecules using a probe that is selective for at least a portion of multiple microsatellite repeat elements in multiple cfDNA molecules. In some embodiments, the probe is a nucleic acid molecule with sequence complementarity to the nucleic acid sequence of multiple microsatellite repeat elements. In some embodiments, these nucleic acid molecules are primers or enrichment sequences. In some embodiments, the determination includes using array hybridization or polymerase chain reaction (PCR) or nucleic acid sequencing.

[0079] In some embodiments, the method further comprises a plurality of cfDNA molecules enriched for at least a portion of a plurality of microsatellite repeat elements. In some embodiments, enrichment comprises amplifying a plurality of cfDNA molecules. For example, a plurality of cfDNA molecules may be amplified by selective amplification (e.g., by using a set of primers or probes comprising nucleic acid molecules having sequence complementarity with nucleic acid sequences of a plurality of microsatellite repeat elements). Alternatively or in combination, a plurality of cfDNA molecules may be amplified by universal amplification (e.g., by using universal primers). In some embodiments, enrichment comprises selectively isolating at least a portion (e.g., mononucleotides and / or dinucleotides) of a plurality of cfDNA molecules.

[0080] In some embodiments, a method for assessing microsatellite instability in a subject comprises processing a plurality of average lengths to obtain a quantitative measure (e.g., a statistical measure) of the deviation of the average length (e.g., as in 115). In some embodiments, the statistical measure of the deviation is an average z-score relative to one or more reference blood samples. A reference blood sample can be obtained from a subject with microsatellite instability and / or from a subject without microsatellite instability. A reference blood sample can be obtained from a subject with cancer or from a subject without cancer (e.g., breast cancer, cervical cancer, colorectal cancer, endometrial cancer, esophageal cancer, gastric cancer, hepatobiliary tract cancer, leukemia, liver cancer, lung cancer, lymphoma, ovarian cancer, pancreatic cancer, skin cancer, urinary tract cancer).

[0081] In some embodiments, the method for assessing microsatellite instability in a subject also includes: when the statistical measure of the deviation of the average length meets the predetermined standard, determine the microsatellite instability (MSI) of the subject (as in 120). The statistical measure of the deviation can be an average z score or an average z score relative to a reference sample or a reference value. In some embodiments, the predetermined standard is that the absolute value of the average z score is greater than a predetermined number. The predetermined number can be about 0.1, about 0.2, about 0.3, about 0.4, about 0.5, about 0.6, about 0.7, about 0.8, about 0.9, about 1, about 1.5, about 2, about 2.5, about 3, about 3.5, about 4, about 4.5, about 5, or greater than about 5.

[0082] In some embodiments, the plurality of microsatellite repeat elements comprises mononucleotides and / or dinucleotides. The plurality of microsatellite repeat elements may include at least about 10 different microsatellite repeat elements, at least about 50 different microsatellite repeat elements, at least about 100 different microsatellite repeat elements, at least about 500 different microsatellite repeat elements, at least about 1000 different microsatellite repeat elements, at least about 5000 different microsatellite repeat elements, at least about 10,000 different microsatellite repeat elements, at least about 50,000 different microsatellite repeat elements, at least about 100,000 different microsatellite repeat elements, at least about 500,000 different microsatellite repeat elements, at least about 100,000 different microsatellite repeat elements, at least about 500,000 different microsatellite repeat elements, at least about 1 million different microsatellite repeat elements. satellite repeat elements, at least about 2 million different microsatellite repeat elements, at least about 3 million different microsatellite repeat elements, at least about 4 million different microsatellite repeat elements, at least about 5 million different microsatellite repeat elements, at least about 10 million different microsatellite repeat elements, at least about 15 million different microsatellite repeat elements, at least about 20 million different microsatellite repeat elements, at least about 25 million different microsatellite repeat elements, at least about 30 million different microsatellite repeat elements, or more than 30 million different microsatellite repeat elements.

[0083] In some embodiments, the presence of microsatellite instability (MSI) in the subject is detected with a sensitivity of at least about 10%, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0084] In some embodiments, the absence of microsatellite instability (MSI) in the subject is detected with a specificity of at least about 10%, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0085] In some embodiments, the presence of microsatellite instability (MSI) in the subject is detected with a positive predictive value (PPV) of at least about 10%, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0086] In some embodiments, the absence of microsatellite instability (MSI) in a subject is detected with a negative predictive value (NPV) of at least about 10%, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0087] In some embodiments, microsatellite instability (MSI) in a subject is detected with an area under the curve (AUC) of a receiver operator characteristic (ROC) of at least about 0.50, at least about 0.55, at least about 0.60, at least about 0.65, at least about 0.70, at least about 0.75, at least about 0.80, at least about 0.85, at least about 0.90, at least about 0.95, at least about 0.96, at least about 0.97, at least about 0.98, or at least about 0.99.

[0088] In some embodiments, the method of assessing microsatellite instability in a subject further comprises determining the presence of microsatellite stability (MSS) in the subject when the statistical measure of the deviation from the mean length does not meet a predetermined criterion, or determining the absence of microsatellite stability (MSS) in the subject when the statistical measure of the deviation from the mean length meets a predetermined criterion.

[0089] In some embodiments, the presence of microsatellite stability (MSS) in the subject is detected with a sensitivity of at least about 10%, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0090] In some embodiments, the absence of microsatellite stability (MSS) in the subject is detected with a specificity of at least about 10%, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0091] In some embodiments, the presence of microsatellite stability (MSS) in the subject is detected with a positive predictive value (PPV) of at least about 10%, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0092] In some embodiments, the absence of microsatellite stability (MSS) in a subject is detected with a negative predictive value (NPV) of at least about 10%, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0093] In some embodiments, the absence of microsatellite stability (MSS) in the subject is detected with an area under the curve (AUC) of a receiver operator characteristic (ROC) of at least about 0.50, at least about 0.55, at least about 0.60, at least about 0.65, at least about 0.70, at least about 0.75, at least about 0.80, at least about 0.85, at least about 0.90, at least about 0.95, at least about 0.96, at least about 0.97, at least about 0.98, or at least about 0.99.

[0094] In some embodiments, the subject has been diagnosed with cancer. For example, the cancer can be one or more types including: brain cancer, breast cancer, cervical cancer, colorectal cancer, endometrial cancer, esophageal cancer, gastric cancer, hepatobiliary tract cancer, leukemia, liver cancer, lung cancer, lymphoma, ovarian cancer, pancreatic cancer, skin cancer, or urinary tract cancer.

[0095] In some embodiments, the method further comprises administering a therapeutically effective amount of a therapy and / or identifying a therapy to treat microsatellite instability in the subject based on the determined presence or absence of microsatellite instability in the subject. In some embodiments, the therapy comprises chemotherapy, radiation therapy, or immunotherapy. For example, the therapy may comprise immunotherapy, such as Keytruda TM (pembrolizumab).

[0096] The microsatellite instability (MSI) or microsatellite stability (MSS) of the subject can be assessed to determine the signs of cancer diagnosis, cancer prognosis or tumor progression or regression in the subject. In addition, one or more clinical results can be assigned based on microsatellite instability (MSI) or microsatellite stability (MSS) assessment or monitoring (e.g., microsatellite instability (MSI) or microsatellite stability (MSS) status differences between two or more time points). Such clinical results can include diagnosing a subject with a cancer including one or more types of tumors, diagnosing a subject with a cancer including one or more types and stages of tumors, predicting a subject with cancer (e.g., indicating a clinical course of treatment (e.g., surgery, chemotherapy, radiotherapy, immunotherapy or other treatments), indicating another clinical course of action (e.g., no treatment, continuing to monitor on a prescribed time interval basis, stopping current treatment, switching to another treatment), or indicating the expected survival time of the subject.

[0097] In some embodiments, the method for assessing the microsatellite instability (MSI) of a subject also includes determining whether the microsatellite instability (MSI) or microsatellite stability (MSS) is greater than a predetermined threshold. A predetermined threshold can be generated by assessing a microsatellite instability (MSI) or microsatellite stability (MSS) and identifying a suitable predetermined threshold based on the microsatellite instability (MSI) or microsatellite stability (MSS) assessment of one or more samples from one or more control subjects (e.g., a patient known to have a certain tumor type, a patient known to have a certain tumor type at a certain stage, or a healthy subject not showing any cancer).

[0098] The predetermined threshold can be adjusted based on the accuracy of the microsatellite instability (MSI) or microsatellite stability (MSS) state of the expected sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) or assessment of the subject. For example, if the high sensitivity of the microsatellite instability (MSI) or microsatellite stability (MSS) state of the subject is expected to be assessed, the predetermined threshold can be adjusted to be lower. Alternatively, if the high specificity of the microsatellite instability (MSI) or microsatellite stability (MSS) state of the subject is expected to be assessed, the predetermined threshold can be adjusted to be higher. The predetermined threshold can be adjusted to maximize the area under the curve (AUC) of the receiver operator characteristic (ROC) of the control sample obtained from the control subject. The predetermined threshold can be adjusted to achieve a desired balance between the false positive (FP) and the false negative (FN) in the microsatellite instability (MSI) or microsatellite stability (MSS) of the cancer of the tumor comprising one or more types of assessment.

[0099] In some embodiments, the method of assessing microsatellite instability (MSI) or microsatellite stability (MSS) also includes repeating the assessment at a second later time point. The second time point can be selected to perform an appropriate comparison of microsatellite instability (MSI) or microsatellite stability (MSS) assessment relative to the first time point. An example of a second time point can correspond to the time after surgical resection, the time to monitor the effectiveness of treatment during or after treatment is administered to treat cancer in a subject, or the time to monitor residual disease or cancer recurrence in a subject after cancer cannot be detected in the subject after treatment.

[0100] In some embodiments, the method for assessing microsatellite instability (MSI) or microsatellite stability (MSS) also includes determining a difference between a first microsatellite instability (MSI) or microsatellite stability (MSS) state and a second microsatellite instability (MSI) or microsatellite stability (MSS) state, the difference indicating the progression or regression of a tumor in a subject. Alternatively or in combination, the method may also include generating by a computer processor a graph of a first microsatellite instability (MSI) or microsatellite stability (MSS) state and a second microsatellite instability (MSI) or microsatellite stability (MSS) state varying with a first time point and a second time point, the graph indicating the progression or regression of a tumor in a subject. For example, a computer processor may generate a graph of a time corresponding to the collection time of data corresponding to two or more microsatellite instability (MSI) or microsatellite stability (MSS) states on the y-axis relative to the two or more microsatellite instability (MSI) or microsatellite stability (MSS) states on the x-axis.

[0101] The determined difference or a graph illustrating the difference between a first microsatellite instability (MSI) or microsatellite stability (MSS) state and a second microsatellite instability (MSI) or microsatellite stability (MSS) state may indicate progression or regression of a tumor in a subject. If the second microsatellite instability (MSI) or microsatellite stability (MSS) state is greater than the first microsatellite instability (MSI) or microsatellite stability (MSS) state, the difference may indicate, for example, tumor progression, ineffectiveness of treatment of a tumor in a subject, resistance of a tumor to ongoing treatment, metastasis of a tumor to other sites in a subject, or residual disease or cancer recurrence in a subject. If the second microsatellite instability (MSI) or microsatellite stability (MSS) state is less than the first microsatellite instability (MSI) or microsatellite stability (MSS) state, the difference may indicate, for example, tumor regression, effectiveness of surgical resection of a tumor in a subject, efficacy of treatment of a tumor in a subject, or absence of residual disease or cancer recurrence in a subject.

[0102] After assessing and / or monitoring microsatellite instability (MSI) or microsatellite stability (MSS) status, one or more clinical outcomes may be assigned based on the microsatellite instability (MSI) or microsatellite stability (MSS) status assessment or monitoring (e.g., microsatellite instability (MSI) or microsatellite stability (MSS) status difference between two or more time points). Such clinical outcomes may include diagnosing a subject with a cancer comprising one or more types of tumors, diagnosing a subject with a cancer comprising one or more types and stages of tumors, predicting a subject with cancer (e.g., indicating a clinical course of treatment (e.g., surgery, chemotherapy, radiation therapy, immunotherapy, or other treatment), indicating another clinical course of action (e.g., no treatment, continue monitoring on a specified time interval basis, stop current treatment, switch to another treatment), or indicating the expected survival time of the subject.

[0103] Example

[0104] Example 1: Determination of MSI from patient normal-tumor paired samples by whole genome sequencing

[0105] Whole genome sequencing data is collected from about 500 groups of normal-tumor paired tissue samples obtained from subjects of cancer patients. A group of 1.3 million genetic loci corresponding to the microsatellites assessed are enriched for short repeat units (e.g., mononucleotides and dinucleotides). In MSI-H tumors, mononucleotide repeats may be abundant and have a higher mutation frequency. For each microsatellite, the average length of each normal-tumor paired tissue sample is measured, and the difference in average length is calculated. Since MSI-H normal-tumor pairing has more deletions in microsatellites, while microsatellite stable (MSS) tumors do not, the average length of the measurement of each microsatellite of normal-tumor pairing is analyzed to determine the MSI status of the subject.

[0106] Figure 2 Cumulative density function (CDF, ​​y-axis) versus microsatellite insertion or deletion (indel) length (x-axis) for each of 4 different cohorts of patients is shown: tumor TCGA-A6-A566-01A-11D-A28G, microsatellite stable (MSS) (upper left); tumor TCGA-A6-A566-01A-11D-A28G, microsatellite instability high (MSI-H) (upper right); tumor TCGA-D7-55, microsatellite stable (MSS) (lower left); and tumor TCGA-D7-55, microsatellite instability high (MSI-H) (lower right). Figure 2 As shown, for two cohorts of patients with MSS status, the measured cumulative density function (CDF) shows that the indel length of most microsatellites measured is about zero in the measured tumor tissue and normal tissue samples. This result indicates that the MSS normal-tumor pairing has substantially the same microsatellite length. In contrast, for two cohorts of patients with MSI-H status, the measured cumulative density function (CDF) shows that most of the measured microsatellites have a negative indel length of about zero (a range of about -6 to about 0) in the measured tumor tissue samples. This result shows that the MSI-H normal-tumor pairing has a statistically significant portion of microsatellites with different microsatellite lengths.

[0107] Figure 3 Box plots showing the average insertion or deletion (indel) length of a panel of microsatellites determined from microsatellite stable (MSS) patients (left, blue) and microsatellite instability-high (MSI-H) patients (right, red) are shown. Figure 3As shown, for patients in MSS status, the measured average indel length has a distribution centered around a median of about zero, with a small standard deviation. In contrast, for patients in MSI-H status, the measured average indel length has a distribution centered around a median of about 0.5, with a significantly larger standard deviation. In particular, almost all of the absolute values ​​of the average indel lengths are significantly greater than zero. If the z-score of the average indel length of a sample is less than about -3 (e.g., having an absolute value greater than a predetermined threshold of about 3), it is considered to be MSI-H. The MSI status of a patient is determined based on next-generation sequencing (NGS) data obtained by whole genome sequencing (WGS) of a tissue with a high sensitivity of about 98.9% and a high specificity of 93.1%.

[0108] Example 2: MSI determination from patient blood samples by whole genome sequencing

[0109] Whole genome sequencing data is collected from about several groups of blood samples obtained from subjects of cancer patients. Blood samples are collected from patients to analyze cell-free DNA (cfDNA) to determine the microsatellite instability status of circulating tumor DNA (ctDNA). A group of 1.3 million genetic loci corresponding to the microsatellites evaluated are enriched for short repeat units (such as mononucleotides and dinucleotides). In MSI-H tumors, mononucleotide repeat sequences may be abundant and have a higher mutation frequency. For each microsatellite, the average length of each blood sample is measured. Since MSI-H normal-tumor pairings have more deletions in microsatellites, while microsatellite stable (MSS) tumors do not, the measured average length of each microsatellite in the blood sample can be analyzed to determine the MSI status of the subject.

[0110] Whole genome sequencing data obtained by performing next generation sequencing (NGS) on blood samples obtained from patients were simulated by computer simulation of 1% sequencing reads obtained from tumor tissue spiked into patient-matched normal background reads (e.g., sequencing reads obtained from normal tissue of a normal-tumor paired sample of the subject). Differences in microsatellite length were observed even at low tumor fractions (e.g., such as those that tend to be observed in blood), enabling differentiation of MSI-H and MSS status in subjects.

[0111] Figure 4 Box plots showing the average insertion or deletion (indel) length of a panel of microsatellites determined from microsatellite stable (MSS) patients (left, blue) and microsatellite instability-high (MSI-H) patients (right, red) are shown. Figure 4As shown, for patients in MSS status, the measured average indel length has a distribution centered around a median of about zero, with a small standard deviation. In contrast, for patients in MSI-H status, the measured average indel length has a distribution centered around a median of about 0.01, with a significantly larger standard deviation. In particular, almost all of the absolute values ​​of the average indel lengths are significantly greater than zero. If the absolute value of the z-score of the average indel length of a sample is greater than a predetermined threshold, it is considered to be MSI-H. With a high sensitivity of 95.7%, a high specificity of 99.1%, and a classification gap of 1.7, the MSI status of the patient was determined based on computer simulated sequencing data measured from a blood sample with a low 1% tumor fraction.

[0112] Computer Systems

[0113] The present disclosure provides a computer system programmed to implement the method of the present disclosure. Figure 5 A computer system 501 is shown, which is programmed or otherwise configured to obtain, for example, a quantitative measure of microsatellite repeat elements from a blood sample of a subject, process the quantitative measure to obtain a statistical measure of the deviation of the quantitative measure, and when the statistical measure of the deviation of the quantitative measure meets a predetermined criterion, detect the presence of microsatellite instability (MSI) in the subject, or when the statistical measure of the deviation of the quantitative measure does not meet the predetermined criterion, detect the absence of microsatellite instability (MSI) in the subject. The computer system 501 can adjust various aspects of the analysis, calculation, and generation of the present disclosure, for example, to obtain a quantitative measure of microsatellite repeat elements from a blood sample of a subject, process the quantitative measure to obtain a statistical measure of the deviation of the quantitative measure, and when the statistical measure of the deviation of the quantitative measure meets the predetermined criterion, detect the presence of microsatellite instability (MSI) in the subject, or when the statistical measure of the deviation of the multiple quantitative measures does not meet the predetermined criterion, detect the absence of microsatellite instability (MSI) in the subject. The computer system 501 may be a user's electronic device or a computer system located remotely from the electronic device. The electronic device may be a mobile electronic device.

[0114] Computer system 501 includes a central processing unit (CPU, also referred to herein as a "processor" and "computer processor") 505, which may be a single-core or multi-core processor, or multiple processors for parallel processing. Computer system 501 also includes memory or memory location 510 (e.g., random access memory, read-only memory, flash memory), an electronic storage unit 515 (e.g., a hard disk), a communication interface 520 (e.g., a network adapter) for communicating with one or more other systems, and peripherals 525, such as cache, other memory, data storage, and / or an electronic display adapter. Memory 510, storage unit 515, interface 520, and peripherals 525 communicate with CPU 505 via a communication bus (solid lines) such as a motherboard. Storage unit 515 may be a data storage unit (or data repository) for storing data. Computer system 501 may be operatively coupled to a computer network ("network") 530 by means of communication interface 520. Network 530 may be the Internet, the Internet and / or an extranet, or an intranet and / or an extranet in communication with the Internet. In some cases, network 530 is a telecommunications and / or data network. Network 530 can include one or more computer servers, which can enable distributed computing, such as cloud computing. For example, one or more computer servers can enable cloud computing (" cloud ") on network 530 to perform the analysis, calculation and various aspects of generation of the present disclosure, such as obtaining the quantitative measurement of microsatellite repeat elements from the blood sample of the experimenter, processing the quantitative measurement to obtain the statistical measurement of the deviation of the quantitative measurement, and when the statistical measurement of the deviation of the quantitative measurement meets the predetermined standard, determine the microsatellite instability of the experimenter. Such cloud computing can be provided by cloud computing platforms such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform and IBM Cloud. Network 530 can realize peer-to-peer network by means of computer system 501 in some cases, and the peer-to-peer network can enable the device coupled to computer system 501 to act as client or server.

[0115] The CPU 505 may execute a series of machine-readable instructions that may be implemented in a program or software. The instructions may be stored in a memory location such as the memory 510. The instructions may be directed to the CPU 505, which may then program or otherwise configure the CPU 505 to implement the methods of the present disclosure. Examples of operations performed by the CPU 505 may include fetching, decoding, executing, and writing back.

[0116] CPU 505 may be part of a circuit such as an integrated circuit. One or more other components of system 501 may be included in the circuit. In some cases, the circuit is an application specific integrated circuit (ASIC).

[0117] Storage unit 515 can store files, such as drivers, libraries, and saved programs. Storage unit 515 can store user data, such as user preferences and user programs. In some cases, computer system 501 may include one or more other data storage units located external to computer system 501, such as on a remote server that communicates with computer system 501 via an intranet or the Internet.

[0118] Computer system 501 can communicate with one or more remote computer systems via network 530. For example, computer system 501 can communicate with a remote computer system of a user (e.g., a physician, nurse, caregiver, patient, or subject). Examples of remote computer systems include a personal computer (e.g., a portable PC), a tablet or tablet computer (e.g., iPad, Galaxy Tab), phones, smartphones (e.g. iPhone, Android-supported devices, ) or a personal digital assistant. A user can access the computer system 501 through a network 530.

[0119] The methods described herein may be implemented by machine (e.g., computer processor) executable code stored in an electronic storage location of the computer system 501, such as in the memory 510 or the electronic storage unit 515. The machine executable or machine readable code may be provided in the form of software. During use, the code may be executed by the processor 505. In some cases, the code may be retrieved from the storage unit 515 and stored in the memory 510 for access by the processor 505 at any time. In some cases, the electronic storage unit 515 may be excluded and the machine executable instructions may be stored in the memory 510.

[0120] The code may be precompiled and configured for use with a machine having a processor suitable for executing the code, or may be compiled during runtime. The code may be provided in a programming language that may be selected so that the code can be executed in a precompiled or compile-time manner.

[0121] Various aspects of the systems and methods (e.g., computer system 501) provided herein can be embodied in programming. Various aspects of the technology can be viewed as "products" or "articles" in the form of machine (or processor) executable code and / or associated data, which are usually carried or embodied in the type of machine-readable media. Machine executable code can be stored in an electronic storage unit, such as a memory (e.g., read-only memory, random access memory, flash memory) or a hard disk. "Storage" type media can include any or all tangible memories of a computer, processor, etc., or its related modules, such as various semiconductor memories, tape drives, disk drives, etc. that can provide non-temporary storage at any time for software programming. All or part of the software can sometimes communicate through the Internet or other various telecommunications networks. For example, such communication can enable software to be loaded from one computer or processor to another computer or processor, such as from a management server or host computer to a computer platform of an application server. Therefore, another type of medium that can carry software elements includes, for example, light waves, radio waves, and electromagnetic waves used by physical interfaces between local devices through wired and optical landline networks and through various air links. Physical elements that carry such waves, such as wired or wireless links, optical links, etc., can also be considered as media that carry the software. As used herein, unless limited to non-transitory, tangible "storage" media, terms such as computer or machine "readable media" refer to any medium that participates in providing instructions to a processor for execution.

[0122] Therefore, machine-readable media, such as computer executable code, can take many forms, including but not limited to tangible storage media, carrier media, or physical transmission media. Non-volatile storage media include, for example, optical or magnetic disks, such as any storage device in any computer, etc., such as can be used to implement the database shown in the accompanying drawings, etc. Volatile storage media include dynamic memory, such as the main memory of such a computer platform. Tangible transmission media include coaxial cables; copper wires and optical fibers, including wires that constitute the bus within a computer system. Carrier transmission media can take the form of electrical or electromagnetic signals or sound or light waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. Therefore, common forms of computer-readable media include: floppy disks, floppy disks, hard disks, magnetic tapes, any other magnetic media, CD-ROMs, DVDs or DVD-ROMs, any other optical media, punched card tapes, any other physical storage media with hole patterns, RAM, ROM, PROM and EPROM, FLASH-EPROM, any other memory chip or cassette, carriers for transmitting data or instructions, cables or links for transmitting such carriers, or any other medium from which a computer can read programming code and / or data. Many of these forms of computer readable media may be involved in carrying one or more sequences of one or more instructions to a processor for execution.

[0123] The computer system 501 may include or communicate with an electronic display 535 that includes a user interface (UI) 540 for providing, for example, a measured average length of microsatellite repeat elements from a blood sample of a subject, a statistical measure of the deviation from the average length, and the presence or absence of microsatellite instability (MSI) or microsatellite stability (MSS) detected for the subject. Examples of UIs include, but are not limited to, graphical user interfaces (GUIs) and web-based user interfaces.

[0124] The methods, systems, and media of the present disclosure may be implemented by one or more algorithms. The algorithm may be implemented by software when executed by the central processing unit 505. The algorithm may, for example, obtain a quantitative measure of microsatellite repeat elements from a blood sample of a subject, process the quantitative measure to obtain a statistical measure of the deviation of the quantitative measure, and when the statistical measure of the deviation of the quantitative measure meets a predetermined criterion, detect the presence of microsatellite instability (MSI) in the subject, or when the statistical measure of the deviation of the multiple quantitative measures does not meet a predetermined criterion, detect the absence of microsatellite instability (MSI) in the subject.

[0125] Although preferred embodiments of the present invention have been shown and described herein, it is obvious to those skilled in the art that such embodiments are provided by way of example only. It is not intended to limit the present invention by the specific embodiments provided in the specification. Although the present invention has been described with reference to the foregoing description, the description and illustration of the embodiments herein are not meant to be interpreted in a restrictive sense. Without departing from the present invention, those skilled in the art will now think of many variations, changes and substitutions. In addition, it should be understood that all aspects of the present invention are not limited to the specific description, configuration or relative proportions set forth herein, which depend on various conditions and variables. It should be understood that various alternatives to the embodiments of the present invention described herein may be used to implement the present invention. Therefore, it is contemplated that the present invention will also encompass any such substitution, modification, variation or equivalent. It is intended that the appended claims define the scope of the present invention, and thus encompass methods and structures and their equivalents within the scope of these claims.

Claims

1. A computer-implemented method for assessing microsatellite instability in a subject, the method comprising: A computer processor receives a quantified measure of a plurality of microsatellite repetitive elements of a plurality of tumor-derived cell-free DNA (cfDNA) molecules obtained from a blood sample of the subject, wherein the quantified measure of the plurality of microsatellite repetitive elements comprises an average length of each of the plurality of microsatellite repetitive elements, a number or fraction of the plurality of microsatellite repetitive elements whose lengths fall within a predetermined size range, or an average insertion or deletion (indel) length of each of the plurality of microsatellite repetitive elements; the computer processor processing the plurality of quantitative measures to obtain a statistical measure of deviation of the plurality of quantitative measures, wherein the statistical measure of deviation is a mean z-score; and The computer processor detects the presence of microsatellite instability (MSI) in the subject when the absolute value of the average z-score is greater than a predetermined number, or detects the absence of microsatellite instability (MSI) in the subject when the absolute value of the average z-score is not greater than a predetermined number.

2. The method of claim 1, wherein the subject is diagnosed with cancer.

3. The method of claim 1, wherein the plurality of quantitative measurements are measured from a set of sequencing reads at each of the plurality of microsatellite repeat elements in the plurality of cfDNA molecules.

4. The method of claim 3, further comprising sequencing the plurality of cfDNA molecules to generate the set of sequencing reads.

5. The method of claim 3 or 4, wherein the sequencing comprises whole genome sequencing (WGS).

6. The method of claim 5, wherein the sequencing is performed at a depth of no greater than 10X.

7. The method of claim 5, wherein the sequencing is performed at a depth of no greater than 8X.

8. The method of claim 5, wherein the sequencing is performed at a depth of no greater than 6X.

9. The method of claim 1, wherein measuring the plurality of quantitative measurements comprises performing binding measurements of the plurality of cfDNA molecules at each of the plurality of microsatellite repeat elements.

10. The method of claim 1, further comprising enriching the plurality of cfDNA molecules for at least a subset of the plurality of microsatellite repeat elements.

11. The method of claim 10, wherein the enrichment comprises amplifying the plurality of cfDNA molecules.

12. The method of claim 11, wherein the amplification comprises selective amplification. The method of claim 11 , wherein the amplifying comprises universal amplification.

14. The method of claim 10, wherein the enrichment comprises selectively isolating at least a portion of the plurality of cfDNA molecules for targeted enrichment.

15. The method of claim 14, wherein the at least one portion comprises a single nucleotide.

16. The method of claim 14, wherein the at least one portion comprises a dinucleotide.

17. The method of claim 1, wherein the statistical measure of the deviation is the mean z-score relative to a reference blood sample.

18. The method of claim 17, wherein the reference blood sample is obtained from a subject having microsatellite instability.

19. The method of claim 17, wherein the reference blood sample is obtained from a subject without microsatellite instability.

20. The method of claim 1, wherein the predetermined number is three.

21. The method of claim 1, wherein the plurality of microsatellite repeat elements comprises mononucleotides or dinucleotides.

22. The method of claim 21, wherein the plurality of microsatellite repeat elements comprises mononucleotides and dinucleotides.

23. The method of claim 1, wherein the plurality of microsatellite repeat elements comprises at least one million different microsatellite repeat elements.

24. The method of claim 1, wherein the plurality of microsatellite repeat elements comprises at least 5 million different microsatellite repeat elements.

25. The method of claim 1, wherein the plurality of microsatellite repeat elements comprises at least 10 million different microsatellite repeat elements.

26. The method of claim 1, wherein the plurality of microsatellite repeat elements comprises at least 20 million different microsatellite repeat elements.

27. The method of claim 1, wherein the presence of microsatellite instability in the subject is detected with a sensitivity of at least 90%.

28. The method of claim 1, wherein the presence of microsatellite instability in the subject is detected with a sensitivity of at least 95%.

29. The method of claim 1, wherein the presence of microsatellite instability in the subject is detected with a sensitivity of at least 99%.

30. The method of claim 1, wherein the absence of microsatellite instability in the subject is detected with a specificity of at least 90%.

31. The method of claim 1, wherein the absence of microsatellite instability in the subject is detected with a specificity of at least 95%.

32. The method of claim 1, wherein the absence of microsatellite instability in the subject is detected with a specificity of at least 99%.

33. The method of claim 1, wherein the presence of microsatellite instability in the subject is detected with a positive predictive value (PPV) of at least 90%.

34. The method of claim 1, wherein the presence or absence of microsatellite instability in the subject is detected with an area under the curve (AUC) of at least 0.

90.

35. The method of claim 1, further comprising: When the absolute value of the average z-score is not greater than a predetermined number, the presence of microsatellite stability (MSS) of the subject is detected.

36. A system comprising a controller comprising or having access to a non-transitory computer readable medium comprising machine executable instructions that, when executed by one or more computer processors, perform a method for assessing microsatellite instability in a subject, the method comprising: receiving a quantified measure of a plurality of microsatellite repetitive elements of a plurality of tumor-derived cell-free DNA (cfDNA) molecules obtained from a blood sample of the subject, wherein the quantified measure of the plurality of microsatellite repetitive elements comprises an average length of each of the plurality of microsatellite repetitive elements, a number or fraction of the plurality of microsatellite repetitive elements having lengths falling within a predetermined size range, or an average insertion or deletion (indel) length of each of the plurality of microsatellite repetitive elements; processing the plurality of quantitative measures to obtain a statistical measure of deviation of the plurality of quantitative measures, wherein the statistical measure of deviation is a mean z-score; and When the absolute value of the average z-score is greater than a predetermined number, the presence of microsatellite instability (MSI) in the subject is detected, or when the absolute value of the average z-score is not greater than a predetermined number, the absence of microsatellite instability (MSI) in the subject is detected.

37. The system of claim 36, wherein the subject is diagnosed with cancer.

38. The system of claim 36, wherein the plurality of quantitative measurements are measured from a set of sequencing reads at each of the plurality of microsatellite repeat elements in the plurality of cfDNA molecules.

39. The system of claim 38, wherein the method further comprises sequencing the plurality of cfDNA molecules to generate the set of sequencing reads.

40. The system of claim 38 or 39, wherein the sequencing comprises whole genome sequencing (WGS).

41. The system of claim 40, wherein the sequencing is performed at a depth of no greater than 10X.

42. The system of claim 40, wherein the sequencing is performed at a depth of no greater than 8X.

43. The system of claim 40, wherein the sequencing is performed at a depth of no greater than 6X.

44. The system of claim 36, wherein measuring the plurality of quantitative measurements comprises performing binding measurements of the plurality of cfDNA molecules at each of the plurality of microsatellite repeat elements.

45. The system of claim 36, wherein the method further comprises identifying a treatment for the subject or a therapeutically effective amount of a treatment to be administered to the subject based on the detected microsatellite instability in the subject.

46. ​​The system of claim 45, wherein the treatment is selected from chemotherapy, radiation therapy, and immunotherapy.

47. The system of claim 46, wherein the treatment comprises immunotherapy.

48. The system of claim 47, wherein the immunotherapy comprises pembrolizumab.

49. The system of claim 36, wherein the method further comprises directing enrichment of the plurality of cfDNA molecules for at least a subset of the plurality of microsatellite repeat elements.

50. The system of claim 49, wherein the enrichment comprises amplifying the plurality of cfDNA molecules.

51. The system of claim 50, wherein the amplification comprises selective amplification.

52. The system of claim 50, wherein the amplification comprises universal amplification.

53. A system according to claim 49, wherein the enrichment includes selectively isolating at least a portion of the multiple cfDNA molecules for targeted enrichment.

54. The system of claim 53, wherein the at least a portion comprises a single nucleotide.

55. The system of claim 53, wherein the at least a portion comprises a dinucleotide.

56. The system of claim 36, wherein the statistical measure of the deviation is a mean z-score relative to a reference blood sample.

57. The system of claim 56, wherein the reference blood sample is obtained from a subject having microsatellite instability.

58. The system of claim 56, wherein the reference blood sample is obtained from a subject without microsatellite instability.

59. The system of claim 36, wherein the predetermined number is 3.

60. The system of claim 36, wherein the plurality of microsatellite repeat elements comprises mononucleotides or dinucleotides.

61. The system of claim 60, wherein the plurality of microsatellite repeat elements comprises mononucleotides and dinucleotides.

62. The system of claim 36, wherein the plurality of microsatellite repeat elements comprises at least one million different microsatellite repeat elements.

63. The system of claim 36, wherein the plurality of microsatellite repeat elements comprises at least 5 million different microsatellite repeat elements.

64. The system of claim 36, wherein the plurality of microsatellite repeat elements comprises at least 10 million different microsatellite repeat elements.

65. The system of claim 36, wherein the plurality of microsatellite repeat elements comprises at least 20 million different microsatellite repeat elements.

66. The system of claim 36, wherein the presence of microsatellite instability in the subject is detected with a sensitivity of at least 90%.

67. The system of claim 36, wherein the presence of microsatellite instability in the subject is detected with a sensitivity of at least 95%.

68. The system of claim 36, wherein the presence of microsatellite instability in the subject is detected with a sensitivity of at least 99%.

69. The system of claim 36, wherein the absence of microsatellite instability in the subject is detected with a specificity of at least 90%.

70. The system of claim 36, wherein the absence of microsatellite instability in the subject is detected with a specificity of at least 95%.

71. The system of claim 36, wherein the absence of microsatellite instability in the subject is detected with a specificity of at least 99%.

72. The system of claim 36, wherein the presence of microsatellite instability in the subject is detected with a positive predictive value (PPV) of at least 90%.

73. The system of claim 36, wherein the presence or absence of microsatellite instability in the subject is detected with an area under the curve (AUC) of at least 0.

90.

74. The system of claim 36, wherein the method further comprises: When the absolute value of the average z-score is not greater than a predetermined number, the presence of microsatellite stability (MSS) of the subject is detected, or when the absolute value of the average z-score is greater than a predetermined number, the absence of microsatellite stability (MSS) of the subject is detected.

75. A non-transitory computer readable medium comprising machine executable code which, upon execution by one or more computer processors, performs a method for assessing microsatellite instability in a subject, the method comprising: receiving a quantified measure of a plurality of microsatellite repetitive elements of a plurality of tumor-derived cell-free DNA (cfDNA) molecules obtained from a blood sample of the subject, wherein the quantified measure of the plurality of microsatellite repetitive elements comprises an average length of each of the plurality of microsatellite repetitive elements, a number or fraction of the plurality of microsatellite repetitive elements having lengths falling within a predetermined size range, or an average insertion or deletion (indel) length of each of the plurality of microsatellite repetitive elements; processing the plurality of quantitative measures to obtain a statistical measure of deviation of the plurality of quantitative measures, wherein the statistical measure of deviation is a mean z-score; and When the absolute value of the average z-score is greater than a predetermined number, the presence of microsatellite instability (MSI) in the subject is detected, or when the absolute value of the average z-score is not greater than a predetermined number, the absence of microsatellite instability (MSI) in the subject is detected.

76. The non-transitory computer readable medium of claim 75, wherein the subject is diagnosed with cancer.

77. The non-transitory computer-readable medium of claim 75, wherein the plurality of quantitative measurements are measured from a set of sequencing reads at each of the plurality of microsatellite repeat elements in the plurality of cfDNA molecules.

78. The non-transitory computer-readable medium of claim 77, wherein the method further comprises sequencing the plurality of cfDNA molecules to generate the set of sequencing reads.

79. The non-transitory computer readable medium of claim 77 or 78, wherein the sequencing comprises whole genome sequencing (WGS).

80. The non-transitory computer readable medium of claim 79, wherein the sequencing is performed at a depth of no greater than 10X.

81. The non-transitory computer readable medium of claim 79, wherein the sequencing is performed at a depth of no greater than 8X.

82. The non-transitory computer readable medium of claim 79, wherein the sequencing is performed at a depth of no greater than 6X.

83. The non-transitory computer-readable medium of claim 75, wherein measuring the plurality of quantitative measurements comprises performing binding measurements of the plurality of cfDNA molecules at each of the plurality of microsatellite repeat elements.

84. The non-transitory computer-readable medium of claim 75, wherein the method further comprises identifying a treatment for the subject or a therapeutically effective amount of a treatment to be administered to the subject based on the detected presence or absence of microsatellite instability in the subject.

85. The non-transitory computer readable medium of claim 84, wherein the treatment is selected from chemotherapy, radiation therapy, and immunotherapy.

86. The non-transitory computer readable medium of claim 85, wherein the treatment comprises immunotherapy.

87. The non-transitory computer readable medium of claim 86, wherein the immunotherapy comprises pembrolizumab.

88. The non-transitory computer-readable medium of claim 75, wherein the method further comprises directing enrichment of the plurality of cfDNA molecules for at least a subset of the plurality of microsatellite repeat elements.

89. The non-transitory computer-readable medium of claim 88, wherein the enrichment comprises amplifying the plurality of cfDNA molecules.

90. The non-transitory computer-readable medium of claim 89, wherein the amplifying comprises selective amplification.

91. The non-transitory computer-readable medium of claim 89, wherein the amplification comprises a universal amplification.

92. The non-transitory computer-readable medium of claim 88, wherein the enrichment comprises selectively isolating at least a portion of the plurality of cfDNA molecules for targeted enrichment.

93. The non-transitory computer readable medium of claim 92, wherein the at least a portion comprises a single nucleotide.

94. The non-transitory computer readable medium of claim 92, wherein the at least a portion comprises a dinucleotide.

95. The non-transitory computer readable medium of claim 75, wherein the statistical measure of the deviation is a mean z-score relative to a reference blood sample.

96. The non-transitory computer-readable medium of claim 95, wherein the reference blood sample is obtained from a subject having microsatellite instability.

97. The non-transitory computer-readable medium of claim 95, wherein the reference blood sample is obtained from a subject without microsatellite instability.

98. The non-transitory computer-readable medium of claim 75, wherein the predetermined number is 3.

99. The non-transitory computer readable medium of claim 75, wherein the plurality of microsatellite repeat elements comprises mononucleotides or dinucleotides.

100. The non-transitory computer readable medium of claim 99, wherein the plurality of microsatellite repeat elements comprises mononucleotides and dinucleotides.

101. The non-transitory computer readable medium of claim 75, wherein the plurality of microsatellite repeat elements comprises at least one million different microsatellite repeat elements.

102. The non-transitory computer readable medium of claim 75, wherein the plurality of microsatellite repeat elements comprises at least 5 million different microsatellite repeat elements.

103. The non-transitory computer readable medium of claim 75, wherein the plurality of microsatellite repeat elements comprises at least 10 million different microsatellite repeat elements.

104. The non-transitory computer readable medium of claim 75, wherein the plurality of microsatellite repeat elements comprises at least 20 million different microsatellite repeat elements.

105. The non-transitory computer-readable medium of claim 75, wherein the presence of microsatellite instability in the subject is detected with a sensitivity of at least 90%.

106. The non-transitory computer-readable medium of claim 75, wherein the presence of microsatellite instability in the subject is detected with a sensitivity of at least 95%.

107. The non-transitory computer-readable medium of claim 75, wherein the presence of microsatellite instability in the subject is detected with a sensitivity of at least 99%.

108. The non-transitory computer-readable medium of claim 75, wherein the absence of microsatellite instability in the subject is detected with a specificity of at least 90%.

109. The non-transitory computer-readable medium of claim 75, wherein the absence of microsatellite instability in the subject is detected with a specificity of at least 95%.

110. The non-transitory computer-readable medium of claim 75, wherein the absence of microsatellite instability in the subject is detected with a specificity of at least 99%.

111. The non-transitory computer readable medium of claim 75, wherein the presence of microsatellite instability in the subject is detected with a positive predictive value (PPV) of at least 90%.

112. The non-transitory computer readable medium of claim 75, wherein the presence or absence of microsatellite instability in the subject is detected with an area under the curve (AUC) of at least 0.

90.

113. The non-transitory computer readable medium of claim 75, wherein the method further comprises: When the absolute value of the average z-score is not greater than a predetermined number, the presence of microsatellite stability (MSS) of the subject is detected, or when the absolute value of the average z-score is greater than a predetermined number, the absence of microsatellite stability (MSS) of the subject is detected.

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