Compositions and methods for evaluation of leiomyosarcoma

Abstract

The present disclosure relates to characterizing a sample from a subject having or suspected of having leiomyosarcoma (LMS). In particular, the present disclosure provides compositions and methods for determining a methylation profile of a sample from a subject having or suspected of having LMS, which can be used to evaluate and inform treatment options.

Description

COMPOSITIONS AND METHODS FOR EVALUATION OF LEIOMYOSARCOMAFIELD

[0001] The present disclosure relates to characterizing a sample from a subject having or suspected of having leiomyosarcoma (LMS). In particular’, the present disclosure provides compositions and methods for determining a methylation profile of a sample from a subject having or suspected of having LMS, which can be used to evaluate and inform treatment options.CROSS REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of U.S. Provisional Application Nos. 63 / 668,519, filed July 8, 2024, and 63 / 674,077, filed July 22, 2024, the contents of which are herein incorporated by reference in their entirety.BACKGROUND

[0003] Leiomyosarcoma (LMS) is an aggressive disease and clinical challenges in evaluation of response to treatment contribute to poor clinical outcome of patients with this disease. Surgery remains the cornerstone of LMS management and currently there are no clear guidelines whether or when to initiate treatment. In patients with no detectable metastasis or with asymptomatic small lung nodules, active surveillance is often favored over initiation of therapy. However, approximately half of all LMS patients develop a local recurrence or distant metastases within five years of diagnosis. The distinction between uterine LMS and its benign counterpart uterine leiomyoma (LM) is particularly difficult. Currently the distinction is based on clinical symptoms and imaging, which may result in inadequate choice of surgical treatment and dissemination of an unexpected malignancy when surgery is performed for a presumed benign lesion. In addition, this can also lead to a delayed treatment of a LMS that clinically is presumed to be benign. As such, there is a need for improved methods of diagnosing LMS to guide treatment for patients.SUMMARY

[0004] Embodiments of the present disclosure include methods for characterizing a biological sample. In some embodiments, the methods comprise treating the biological sample from the subject with a reagent that modifies DNA in a methylation-specific manner and determining the methylation profile for at least one CpG site (e.g., presence or absence of methylation of at leastone CpG site) present in the DNA (e.g., in one or more genes or chromosome locations) using a methylation- specific assay.

[0005] In some embodiments, the one or more genes or chromosome locations are selected from: APOLD1; SLC12A4; CCNE2; chr8.40057011; EFNA5; ABL1; chrl4.31698967;CDKN2A; SPRR2C; PVT1; ADM; chrl6.10956460; chr5.159602480; KIFC2; TWIST1;NPAS4; chr7.26416987; SPEG; GLI2; and THEM7P.

[0006] Tn some embodiments, the methods comprise determining a methylation profile for at least one CpG site in two genes or chromosome locations, three genes or chromosome locations, four genes or chromosome locations, five genes or chromosome locations, six genes or chromosome locations, seven genes or chromosome locations, eight genes or chromosome locations, nine genes or chromosome locations, ten genes or chromosome locations, eleven genes or chromosome locations, or twelve genes or chromosome locations.

[0007] In some embodiments, the one or more CpG sites are selected from: cg24579851; cgl5006175; cg25228422; cgl4699728; cg24755163; cg24496841; cg00803453; cg23032184; and cg06619621 and / or cg27423445; cg00420526; cgl4001824; cg08900470; cg22009908; cgl4471330; cgl0348234; cg23322868; cg07804289; cgl 1201447; cg26955482; cg01085454; and cg04102657, as referenced in the Illumina CpG loci database with CpG loci IDs. In some embodiments, the one or more CpG sites are selected from: cg24579851; cgl5006175; cg25228422; cgl4699728; cg24755163; cg24496841; cg00803453; cg23032184; and cg06619621. In some embodiments, the one or more CpG sites are selected from: cg27423445; cg00420526; cgl4001824; cg08900470; cg22009908; cgl4471330; cgl0348234; cg23322868; cg07804289; cgl 1201447; cg26955482; cg01085454; and cg04102657.

[0008] In some embodiments, the subject has or is suspected of having leiomyosarcoma (LMS). In some embodiments, the subject has or is suspected of having uterine leiomyosarcoma.

[0009] In some embodiments, the methylation profile indicates that the subject has leiomyosarcoma. In some embodiments, the one or more genes or chromosome locations are selected from: chr5.159602480; KIFC2; TWIST1; NPAS4; chr7.26416987; SPEG; GLI2; THEM7; and any combination thereof, and the methylation profile indicates that the subject has leiomyosarcoma (LMS). In some embodiments, the one or more genes or chromosome locations are: chr5.159602480; KIFC2; TWIST1; NPAS4; chr7.26416987; SPEG; GLI2; and THEM7, and the methylation profile indicates that the subject has leiomyosarcoma (LMS).

[0010] In some embodiments, the one or more CpG sites are selected from: cg24579851; cgl5006175; cg25228422; cgl4699728; cg24755163; cg24496841; cg00803453; cg23032184; cg06619621; and any combination thereof, and the methylation profile (e.g., the presence or absence or frequency of methylation at one of more of the CpG sites) indicates that the subject has leiomyosarcoma (LMS). In some embodiments, the one or more CpG sites are selected from: cg24579851; cgl5006175; cg25228422; cgl4699728; cg24755163; cg24496841; cg00803453; cg23032184; and cg06619621 , and the methylation profile indicates that the subject has leiomyosarcoma (LMS).

[0011] In some embodiments, the one or more genes or chromosome locations are selected from: APOLD1; SLC12A4; CCNE2; chr8.40057011; EFNA5; ABL1; chrl4.31698967;CDKN2A; SPRR2C; PVT1; ADM; chrl6.10956460; and any combination thereof, and the methylation profile distinguishes between uterine leiomyoma (LM) and uterine leiomyosarcoma (uLMS). In some embodiments, the one or more genes or chromosome locations are: APOLD1; SLC12A4; CCNE2; chr8.40057011; EFNA5; ABL1; chrl4.31698967; CDKN2A; SPRR2C;PVT1; ADM; and chr 16.10956460, and the methylation profile distinguishes between uterine leiomyoma (LM) and uterine leiomyosarcoma (uLMS).

[0012] In some embodiments, the one or more CpG sites are selected from: cg27423445; cg00420526; cgl4001824; cg08900470; cg22009908; cgl4471330; cgl0348234; cg23322868; cg07804289; cgl 1201447; cg26955482; cg01085454; cg04102657; and any combination thereof, and the methylation profile (e.g., the presence or absence or frequency of methylation at one of more of the CpG sites) distinguishes between uterine leiomyoma (LM) and uterine leiomyosarcoma (uLMS). In some embodiments, the one or more CpG sites are selected from: cg27423445; cg00420526; cgl4001824; cg08900470; cg22009908; cgl4471330; cgl0348234; cg23322868; cg07804289; cgl 1201447; cg26955482; cg01085454; and cg04102657, and the methylation profile distinguishes between uterine leiomyoma (LM) and uterine leiomyosarcoma (uLMS).

[0013] In some embodiments, determining the methylation profile further comprises comparing the methylation level at least one CpG site in one or more genes or chromosome locations to a methylation level of the corresponding at least one CpG site in a control sample. In some embodiments, the at least one CpG site is individually associated with an area under a ROC curve (AUC) greater than or equal to 0.8, and wherein the ROC curve discriminatesbetween a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample. In some embodiments, the at least one CpG site are collectively associated with an area under a ROC curve (AUC) greater than or equal to 0.8, and wherein the ROC curve discriminates between a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample. In some embodiments, the control sample is from a healthy subject or a subject that does not have cancer. In some embodiments, the control sample is from a subject that does not have leiomyosarcoma.

[0014] In some embodiments, determining the methylation profile for at least one CpG site in one or more genes or chromosome locations comprises calculating a methylation score and / or a methylation frequency for the at least one CpG site.

[0015] In some embodiments, the method further comprises assaying one or more leiomyosarcoma, uterine leiomyosarcoma, or leiomyoma biomarkers. In some embodiments, the method further comprises determining the mutational profile and / or copy number alterations of one or more leiomyosarcoma, uterine leiomyosarcoma, or leiomyoma biomarkers.

[0016] In some embodiments, the biological sample is a blood product sample or a tissue sample. In some embodiments, the biological sample is a gynecological tissue sample. In some embodiments, the biological sample is a tumor sample.

[0017] In some embodiments, the DNA is cell-free DNA (cfDNA). In some embodiments, the DNA is genomic DNA.

[0018] In some embodiments, the methods further comprise obtaining a biological sample from the subject and isolating the DNA sample.

[0019] In some embodiments, the method further comprises administering one or more interventions to the subject based on the methylation profile.

[0020] Other aspects and embodiments of the disclosure will be apparent in light of the following detailed description and accompanying figures.BRIEF DESCRIPTION OF THE DRAWINGS

[0021] FIG. 1 is supervised clustering of 254 LMS and 94 other soft tissue tumors based on methylation level of 9 CpGs (Stanford dataset).

[0022] FIG. 2 is supervised clustering of 79 LMS and 126 other soft tissue tumors based on methylation level of 9 CpGs (TCGA dataset).

[0023] FIG. 3 shows feature selection for accurate distinction between uterine LM and uterine LMS (uLMS).

[0024] FIG. 4 is a ROC curve, area under the curve = 0.98, in the LM and uLMS validation cohort.

[0025] FIG. 5 is supervised clustering based on 13CpGs in the training cohort (Stanford dataset).

[0026] FIG. 6 is supervised clustering based on 13CpGs in the validation cohort (Stanford dataset).

[0027] FIG. 7 is a ROC curve, area under the curve equals 1, in the independent cohort of 7 LM and 15 uLMS with publicly available data.

[0028] FIG. 8 is supervised clustering based on 13 CpGs in the independent cohort of 7 LM and 15 uLMS with publicly available data.

[0029] FIG. 9 is a Venn diagram of 13 CpGs identified (“LM vs LMS”) and previously published CpGs associated with age, as reported by Hannum et al. (Molecular’ Cell, 49(2), 359- 367, (2013)), Horvath et al. (Genome Biology, 14(10), R115, (2013)), and in the epiTOC signature (Yang, Z., et al. Genome Biology, 77(1), 205, (2016)).DETAILED DESCRIPTION

[0030] The present disclosure relates to characterizing a sample from a subject having or suspected of having leiomyosarcoma (LMS). In particular, the present disclosure provides compositions and methods for assessing a sample from a subject by using methylation profiling, optionally in combination with mutational profiling and copy number alterations.

[0031] Section headings as used in this section and the entire disclosure herein are merely for organizational purposes and are not intended to be limiting.1. Definitions

[0032] Throughout the specification and claims, the following terms take the meanings explicitly associated herein, unless the context clearly dictates otherwise. The phrase “in one embodiment” as used herein does not necessarily refer to the same embodiment, though it may. Furthermore, the phrase “in another embodiment” as used herein does not necessarily refer to a different embodiment, although it may. Thus, as described below, various embodiments of the invention may be readily combined, without departing from the scope or spirit of the invention.

[0033] In addition, as used herein, the term “or” is an inclusive “or” operator and is equivalent to the term “and / or” unless the context clearly dictates otherwise. The term “based on” is not exclusive and allows for being based on additional factors not described, unless the context clearly dictates otherwise. In addition, throughout the specification, the meaning of “a,” “an,” and “the” include plural references. The meaning of “in” includes “in” and “on.”

[0034] The terms “comprise(s),” “include(s),” “having,” “has,” “can,” “contain(s),” and variants thereof, as used herein, are intended to be open-ended transitional phrases, terms, or words that do not preclude the possibility of additional acts or structures. The transitional phrase “consisting essentially of’ as used in claims in the present application limits the scope of a claim to the specified materials or steps “and those that do not materially affect the basic and novel characteristic(s)” of the claimed invention, as discussed in In re Herz, 537 F.2d 549, 551-52, 190 USPQ 461, 463 (CCPA 1976). For example, a composition “consisting essentially of’ recited elements may contain an unrecited contaminant at a level such that, though present, the contaminant does not alter the function of the recited composition as compared to a pure composition, i.e., a composition “consisting of” the recited components. The present disclosure also contemplates other embodiments “comprising,” “consisting of,” and “consisting essentially of,” the embodiments or elements presented herein, whether explicitly set forth or not.

[0035] The terms “one or more” and “at least one” as used herein, refers to one and numbers higher than one. For example, the term “one or more” encompasses any of the following: two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, ten or more, eleven or more, twelve or more, thirteen or more, fourteen or more, fifteen or more, twenty or more, fifty or more, 100 or more, or an even greater number. Similarly, the term “at least one” encompasses two, three, four, five, ten, fifteen, twenty, or more.

[0036] For the recitation of numeric ranges herein, each intervening number there between with the same degree of precision is explicitly contemplated. For example, for the range of 6-9, the numbers 7 and 8 are contemplated in addition to 6 and 9, and for the range 6.0-7.0, the number 6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6.9, and 7.0 are explicitly contemplated.

[0037] Unless otherwise defined herein, scientific, and technical terms used in connection with the present disclosure shall have the meanings that are commonly understood by those of ordinary skill in the art. The meaning and scope of the terms should be clear; in the event, however of any latent ambiguity, definitions provided herein take precedent over anydictionary or extrinsic definition. Further, unless otherwise required by context, singular terms shall include pluralities and plural terms shall include the singular.

[0038] A “biomarker” includes a biological compound, such as a protein and a fragment thereof, a peptide, a polypeptide, a proteoglycan, a glycoprotein, a lipoprotein, a carbohydrate, a lipid, a nucleic acid, an organic on inorganic chemical, a natural polymer, a cell fragment, an exosome, and a small molecule, that is present in a biological sample and that may be isolated from, or measured in, the biological sample. Furthermore, a biomarker may be the entire intact molecule, or a portion thereof that may be partially functional or recognized, for example, by an antibody or other specific binding protein. A biomarker may be associated with a given state of a subject, such as a particular stage of disease. A measurable aspect of a biomarker may include, for example, the presence, absence, or concentration of the biomarker in the biological sample from the subject and / or relative changes of any of the measurable aspects compared to a standard (e.g., internal or from a healthy subject). The measurable aspect may also be a ratio of two or more measurable aspects of two or more biomarkers. Biomarker, as used herein, also encompasses a biomarker profile comprising measurable aspects of two or more individual biomarkers. The two or more individual biomarkers may be from the same or different classes of biomarkers such as, for example, a nucleic acid and a carbohydrate, or may measure the same or different measurable aspect such as, for example, absence of one biomarker and concentration of another. A biomarkcr profile may comprise any number of individual biomarkers or features thereof. In another embodiment, the biomarker profile comprises at least one measurable aspect of at least one internal standard. Methods of identifying and quantifying biomarkers are well known in the art and include histological and molecular methods such as enzyme-linked immunosorbent assays (ELISA) and other immunoassays, gel electrophoresis protein and DNA arrays, mass spectrometry, colorimetric assays, electrochemical assays, and fluorescence methods.

[0039] As used herein, the term “circulating cell-free DNA” or “cfDNA” refers to DNA that is circulating in the peripheral blood of a patient. The DNA molecules in cell-free DNA may have a median size that is below 1 kb (e.g., in the range of 50 bp to 500 bp, 80 bp to 400 bp, or 100-1,000 bp), although fragments having a median size outside of this range may be present. cfDNA can be highly fragmented and in some cases can have a mean fragment size of about 165-250 bp. cfDNA can be obtained by centrifuging whole blood to remove all cells, and thenisolating the DNA from the remaining plasma or scrum, Circulating cell-free DNA is generally double-stranded, but can be made single stranded by denaturation. Cell-free DNA may contain circulating tumor DNA (ctDNA), e.g., tumor DNA circulating freely in the blood of a subject or circulating fetal DNA (if the subject is a pregnant female).

[0040] As used herein, the term “circulating tumor DNA” (or “ctDNA”) is tumor-derived DNA that is circulating in the peripheral blood of a patient. ctDNA is of tumor origin and originates directly from the tumor or from circulating tumor cells (CTCs), which are viable, intact tumor cells that shed from primary tumors and enter the bloodstream or lymphatic system.

[0041] As used herein, the term “control” when used in reference to nucleic acid detection or analysis refers to a nucleic acid having known features (e.g., known sequence, known copynumber per cell, known modification state, such as methylation state), for use in comparison to an experimental target (e.g., a nucleic acid of unknown features). A control may be a wild-type gene against which a test or target nucleic acid in an assay can be normalized.

[0042] The terms “determining,” “measuring,” “evaluating,” “assessing,” “assaying,” and “analyzing” are used interchangeably herein to refer to any form of measurement, and include determining if an element is present or not. These terms include both quantitative and / or qualitative determinations. Assaying may be relative or absolute. For example, “assaying” can be determining whether the methylation profile is less than or “greater than or equal to” a particular threshold, (the threshold can be prc-dctcrmincd or can be determined by assaying a control sample). On the other hand, “assaying to determine the methylation profile” can mean determining a quantitative value (using any convenient metric) that represents the level of methylation at a CpG site. The methylation profile can be expressed in arbitrary units associated with a particular assay (e.g., fluorescence units, e.g., mean fluorescence intensity (MFI)), or can be expressed as an absolute value with defined units (e.g., number of methylated CpG sites in a cfDNA gene, frequency of methylation at a CpG site in cfDNA, etc.). Additionally, the level of methylation at a CpG site can be compared to the methylation profile of one or more additional CpG sites to derive a normalized value that represents a normalized methylation profile. The specific metric (or units) chosen is not crucial as long as the same units are used (or conversion to the same units is performed) when evaluating multiple samples from the same individual (e.g., samples taken at different points in time from the same individual). This is because the unitscancel when calculating a fold-change (i.e., determining a ratio) in the methylation profile from one sample to the next (e.g., samples taken at different points in time from the same individual).

[0043] The term “gene” refers to a nucleic acid (e.g., DNA or RNA) sequence that comprises coding sequences necessary for the production of an RNA, or of a polypeptide or its precursor. A functional polypeptide can be encoded by a full-length coding sequence or by any portion of the coding sequence as long as the desired activity or functional properties (e.g., enzymatic activity, ligand binding, signal transduction, etc.) of the polypeptide are retained. The term “portion” when used in reference to a gene refers to fragments of that gene. The fragments may range in size from a few nucleotides to the entire gene sequence minus one nucleotide. Thus, a nucleotide comprising at least a portion of a “gene” may comprise fragments of the gene or the entire gene.

[0044] The term “gene” also encompasses the coding regions of a structural gene and includes sequences located adjacent to the coding region on both the 5' and 3' ends, e.g., for a distance of about 1 kb on either end, such that the gene corresponds to the length of the full-length mRNA (e.g., comprising coding, regulatory, structural, and other sequences). The sequences that are located 5' of the coding region and that are present on the mRNA are referred to as 5' nontranslated or untranslated sequences. The sequences that are located 3' or downstream of the coding region and that are present on the mRNA are referred to as 3' non-translated or 3' untranslated sequences. The term “gene” encompasses both cDNA and genomic forms of a gene. The term “gene” encompasses non-coding regulatory regions located 3' or 5' from the coding region. In some organisms (e.g., eukaryotes), a genomic form or clone of a gene contains the coding region interrupted with non-coding sequences termed “introns” or “intervening regions” or “intervening sequences.” Introns are segments of a gene that are transcribed into nuclear RNA (hnRNA); introns may contain regulatory elements such as enhancers. Introns are removed or “spliced out” from the nuclear or primary transcript; introns therefore are absent in the messenger RNA (mRNA) transcript. The mRNA functions during translation to specify the sequence or order of amino acids in a nascent polypeptide.

[0045] In addition to containing introns, genomic forms of a gene may also include sequences located on both the 5' and 3' ends of the sequences that are present on the RNA transcript. These sequences are referred to as “flanking” sequences or regions (these flanking sequences are located 5' or 3' to the non-translated sequences present on the mRNA transcript). The 5' flanking region may contain regulatory sequences such as promoters and enhancers that control orinfluence the transcription of the gene. The 3' flanking region may contain sequences that direct the termination of transcription, posttranscriptional cleavage, and polyadenylation.

[0046] The term “wild-type” when made in reference to a gene refers to a gene that has the characteristics of a gene isolated from a naturally occurring source. The term “wild-type” when made in reference to a gene product refers to a gene product that has the characteristics of a gene product isolated from a naturally occurring source. The term “wild-type” when made in reference to a protein refers to a protein that has the characteristics of a naturally occurring protein. The term “naturally occurring” as applied to an object refers to the fact that an object can be found in nature. For example, a polypeptide or polynucleotide sequence that is present in an organism (including viruses) that can be isolated from a source in nature, and which has not been intentionally modified by the hand of a person in the laboratory is naturally occurring. A wildtype gene is often that gene or allele that is most frequently observed in a population and is thus arbitrarily designated the “normal” or “wild-type” form of the gene. In contrast, the term “modified” or “mutant” when made in reference to a gene or to a gene product refers, respectively, to a gene or to a gene product that displays modifications in sequence and / or functional properties (e.g., altered characteristics) when compared to the wild-type gene or gene product. It is noted that naturally occurring mutants can be isolated; these are identified by the fact that they have altered characteristics when compared to the wild-type gene or gene product.

[0047] The term “isolated” when used in relation to a nucleic acid, as in “an isolated oligonucleotide” refers to a nucleic acid sequence that is identified and separated from at least one contaminant nucleic acid with which it is ordinarily associated in its natural source. Isolated nucleic acid is present in a form or setting that is different from that in which it is found in nature. In contrast, non-isolated nucleic acids, such as DNA and RNA, are found in the state they exist in nature.

[0048] As used herein a “methylated nucleotide” or a “methylated nucleotide base” refers to the presence of a methyl moiety on a nucleotide base, where the methyl moiety is not present in a recognized typical nucleotide base. For example, cytosine does not contain a methyl moiety on its pyrimidine ring, but 5-methylcytosine contains a methyl moiety at position 5 of its pyrimidine ring. Therefore, cytosine is not a methylated nucleotide and 5-methylcytosine is a methylated nucleotide. In another example, thymine contains a methyl moiety at position 5 of its pyrimidinering; however, for purposes herein, thymine is not considered a methylated nucleotide when present in DNA since thymine is a typical nucleotide base of DNA.

[0049] As used herein, a “methylated nucleic acid molecule” refers to a nucleic acid molecule that contains one or more methylated nucleotides. In accordance with this, a methylated nucleic acid molecule can be a gene or marker (or can be associated with a gene or marker, including the regulatory region and / or coding region of a gene or marker), which can be referred to as a “differentially methylated region” (or DMR) or a “methylated DNA marker” (MDM). Other terms known in the art for describing a methylated nucleic acid molecule can also be used.

[0050] As used herein, a “methylation profile,” “methylation state,” and “methylation status” of a nucleic acid molecule refers to the presence or absence of one or more methylated nucleotide bases in the nucleic acid molecule. For example, a nucleic acid molecule containing a methylated cytosine is considered methylated (e.g., the methylation state of the nucleic acid molecule is methylated). A nucleic acid molecule that does not contain any methylated nucleotides is considered unmethylated. Methylation profile may also refer to the amount of methylation within a particular methylation marker in comparison with an established norm or control. Methylation profile may also refer to whether one or more cytosine residues present in a CpG context have or do not have a methylation group. Methylation profile may also alternatively describe whether a one or more target CpG di-nucleotides are methylated. The methylation profile can be represented or indicated by a methylation level, frequency, fraction, ratio, percent, etc. A methylation profile can be generated, for example, by quantifying the amount of intact nucleic acid present following restriction digestion with a methylation dependent restriction enzyme or by comparing amplification profiles after bisulfite reaction or by comparing sequences of methylation reagent-treated and untreated nucleic acids. For example, cytosine methylation at CpG islands may be determined by treating the sample with bisulfite and determining the difference using methylation-specific probes, sequencing, and / or microarrays.

[0051] The methylation profile of a particular nucleic acid sequence (e.g., a gene marker or chromosomal DNA region as described herein) can indicate the methylation state of every base in the sequence or can indicate the methylation state of a subset of the bases (e.g., of one or more cytosines) within the sequence, or can indicate information regarding regional methylation density within the sequence with or without providing precise information of the locations within the sequence the methylation occurs.

[0052] Typically, methylation of human DNA occurs on a dinucleotide sequence including an adjacent guanine and cytosine where the cytosine is located 5' of the guanine (also termed CpG dinucleotide sequences). Most cytosines within the CpG dinucleotides are methylated in the human genome, however some remain unmethylated in specific CpG dinucleotide rich genomic regions, known as CpG islands. As used herein, a “CpG island” or “cytosine-phosphate-guanine island”) refers to a G:C-rich region of genomic DNA containing an increased number of CpG dinucleotides relative to total genomic DNA. Methylation profile may be determined in CpG islands, e.g., at promoter regions. In some embodiments, the CpG site is present in a coding region or a regulatory region. It will be appreciated though that other sequences in the human genome are prone to DNA methylation such as CpA and CpT.

[0053] As used herein, the term “methylation level” as applied to a methylation marker refers to the amount of methylation within a particular methylation marker. Methylation level may also refer to the amount of methylation within a particular methylation marker in comparison with an established norm or control. Methylation level may also refer to whether one or more cytosine residues present in a CpG context have or do not have a methylation group. Methylation level may also refer to the fraction of cells in a sample that do or do not have a methylation group on such cytosines. Methylation level may also alternatively describe whether a single CpG dinucleotide is methylated.

[0054] As used herein, “methylation frequency” or “methylation percent (%)” refer to the number of instances in which a molecule or locus is methylated relative to the number of instances the molecule or locus is unmethylated.

[0055] The term “methylation score” as used herein is a score indicative of detected methylation events in a marker or panel of markers in comparison with median methylation events for the marker or panel of markers from a random population of mammals (e.g., a random population of 10, 20, 30, 40, 50, 100, or 500 mammals) that do not have a specific indication (e.g., leiomyosarcoma). An elevated methylation score in a marker or panel of markers can be any score provided that the score is greater than a corresponding reference score. For example, an elevated score of methylation in a marker or panel of markers can be 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more fold greater than the reference methylation score.

[0056] As used herein, a “methylation- specific reagent” refers to a reagent that modifies a nucleotide of the nucleic acid molecule as a function of the methylation state of the nucleic acidmolecule, or a methylation-specific reagent, refers to a compound or composition or other agent that can change the nucleotide sequence of a nucleic acid molecule in a manner that reflects the methylation state of the nucleic acid molecule. Such methods can be applied in a manner in which unmethylated nucleotides (e.g., each unmethylated cytosine) is modified to a different nucleotide. For example, in some embodiments, such a reagent can deaminate unmethylated cytosine nucleotides to produce deoxy uracil residues. Examples of such reagents include, but are not limited to, a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, a bisulfite reagent, a TET enzyme, and a borane reducing agent.

[0057] Any suitable method may be used for determining a methylation profile. Exemplary techniques include, without limitation, methylation- sensitive arbitrarily -primed polymerase chain reaction (MS AP-PCR), methylation- sensitive single nucleotide primer extension (Ms-SNuPE), methylation-specific PCR (MSP), methylation-sensitive DNA restriction enzyme analysis, restriction enzyme-based sequencing, restriction enzyme-based microarray analysis, combined bisulfite restriction analysis (COBRA), methylated CpG island amplification (MCA), methylated CpG island amplification and microarray (MCAM), Hpall tiny fragment enrichment by ligation- mediated PCR (HELP), bisulfite sequencing, bisulfite microarray analysis, methylation- specific pyrosequencing, HELP- sequencing (HELP-seq), TET-assisted pyridine borane sequencing (TAPS), Glal hydrolysis and ligation adapter dependent PCR (GLAD-PCR), methylated DNA immunoprecipitation- sequencing (McDIP-Scq), or methylated DNA immunoprccipitation- microarray analysis (MeDIP-chip), Southern blotting with methyl-sensitive restriction enzymes, and methylation-specific giant magnetoresistive sensor-based microarray analysis.

[0058] The terms “obtained” or “obtaining” as used herein can also include the physical extraction or isolation of a sample from a subject. Accordingly, a sample can be isolated from a subject (and thus “obtained”) by the same person or same entity that subsequently assays the sample. When a sample is “extracted” or “isolated” from a first parly or entity and then transferred (e.g., delivered, mailed, etc.) to a second party, the sample was “obtained” by the first party (and also “isolated” by the first party), and then subsequently “obtained” (but not “isolated”) by the second party. Accordingly, in some embodiments, the step of obtaining does not comprise the step of isolating a sample.

[0059] “Polynucleotide” or “oligonucleotide” or “nucleic acid,” as used herein, means at least two nucleotides covalently linked together. The polynucleotide may be DNA, RNA, or a hybrid,where the polynucleotide may contain combinations of deoxyribo- and ribo-nucleotides, and combinations of bases including uracil, adenine, thymine, cytosine, guanine, inosine, xanthine hypoxanthine, isocytosine and isoguanine. The nucleic acid, whether DNA or RNA may comprise non-natural nucleotides, modified nucleotides, and / or non- nucleotide building blocks that can exhibit the same function as natural nucleotides (e.g., “nucleotide analogs”). Nucleic acids may be obtained by chemical synthesis methods or by recombinant methods. Polynucleotides may be single- or double-stranded or may contain portions of both double stranded and single stranded sequence. The depiction of a single strand also defines the sequence of the complementary strand. Thus, a nucleic acid also encompasses the complementary strand of a depicted single strand. Many variants of a nucleic acid may be used for the same purpose as a given nucleic acid. Thus, a nucleic acid also encompasses substantially identical nucleic acids and complements thereof.

[0060] A “receiver operating characteristic” curve or “ROC” curve refers to a graphical plot that illustrates the performance of a binary classifier system as its discrimination threshold is varied. For example, an ROC curve can be a plot of the true positive rate against the false positive rate for the different possible cutoff points of a diagnostic test. It is created by plotting the fraction of true positives out of the positives (TPR = true positive rate) vs. the fraction of false positives out of the negatives (FPR = false positive rate), at various threshold settings. TPR is also known as sensitivity, and FPR is one minus the specificity or true negative rate. The ROC curve demonstrates the tradeoff between sensitivity and specificity (any increase in sensitivity will be accompanied by a decrease in specificity); the closer the curve follows the left-hand border and then the top border of the ROC space, the more accurate the test; the closer the curve comes to the 45-degree diagonal of the ROC space, the less accurate the test; the slope of the tangent line at a cutoff point gives the likelihood ratio (LR) for that value of the test; and the area under the curve is a measure of test accuracy.

[0061] The term “AUC” as used herein is an abbreviation for the “area under a curve.” It refers to the area under a Receiver Operating Characteristic (ROC) curve. The ROC curve is a plot of the true positive rate against the false positive rate for the different possible cut points of a diagnostic test. It shows the trade-off between sensitivity and specificity depending on the selected cut point (any increase in sensitivity will be accompanied by a decrease in specificity). The area under an ROC curve (AUC) is a measure for the accuracy of a diagnostic test (thelarger the area the better; the optimum is 1 ; a random test would have a ROC curve lying on the diagonal with an area of 0.5; for reference: J. P. Egan. (1975) Signal Detection Theory and ROCAnalysis, Academic Press, New York) A preferred AUC may be at least about 0.700, at least about 0.750, at least about 0.800, at least about 0.850, at least about 0.900, at least about 0.950, at least about 0.980, at least about 0.990, or at least about 0.995, or more.

[0062] As used herein, the terms “sample,” “test sample,” and “biological sample” refer to a sample containing or suspected of containing a marker useful in the methods of the present disclosure. The sample can be any suitable sample obtained from any suitable subject, typically a mammal (e.g., squirrels, mice, rats, non-human primates, or humans). In some embodiments, the subject is a human. The sample may be obtained from any suitable biological source, such as, a physiological fluid including, but not limited to, whole blood, serum, plasma, interstitial fluid, saliva, ocular lens fluid, cerebral spinal fluid, sweat, urine, milk, ascites fluid, mucous, synovial fluid, peritoneal fluid, vaginal fluid, menses, amniotic fluid, semen, feces, and the like. In some embodiments, the sample is obtained from a blood product (e.g., whole blood, serum, plasma, or other blood source), an oropharyngeal swab, a rectal swab, a genital swab, saliva, urine, or semen. The sample can be obtained from a subject using routine techniques known to those skilled in the ail, and the sample may be used directly as obtained from the biological source or following a pretreatment to modify the character of the sample. Such pretreatment may include, for example, preparing plasma from blood, diluting viscous fluids, filtration, precipitation, dilution, distillation, mixing, concentration, inactivation of interfering components, the addition of reagents, lysing, and the like. The sample may be refrigerated (2- 8 °C) or frozen (-20 °C or lower) following collection and prior to analysis.

[0063] A “subject” or “patient” may be human or non-human and may include, for example, animal strains or species used as “model systems” for research purposes, such a mouse model as described herein. Likewise, the subject may include either adults or juveniles (e.g., children). Moreover, subject may mean any living organism, preferably a mammal (e.g., humans and nonhumans) that may benefit from the administration of compositions contemplated herein. Examples of mammals include, but are not limited to, any member of the Mammalian class: humans, non-human primates such as chimpanzees, and other apes and monkey species; farm animals such as cattle, horses, sheep, goats, swine; domestic animals such as rabbits, dogs, and cats; laboratory animals including rodents, such as rats, mice and guinea pigs, and the like.Examples of non-mammals include, but are not limited to, birds, fish, and the like. In one embodiment, the mammal is a human.

[0064] Preferred methods and materials are described below, although methods and materials similar or equivalent to those described herein can be used in practice or testing of the present disclosure. All publications, patent applications, patents and other references mentioned herein are incorporated by reference in their entirety. The materials, methods, and examples disclosed herein are illustrative only and not intended to be limiting.2. Methods

[0065] The present disclosure provides methods for characterizing a biological sample, for example, a biological sample obtained from a subject. Embodiments of the present disclosure include methylation biomarkers capable of distinguishing leiomyosarcoma from other soft tissue tumors (e.g., dedifferentiated liposarcoma, myxofibrosarcoma, undifferentiated pleomorphic sarcoma, malignant peripheral nerve sheath tumors and synovial sarcoma), from related benign conditions such as leiomyoma, or healthy controls. In some embodiments, the methods include determining if the subject has leiomyosarcoma, uterine leiomyosarcoma, or leiomyoma. Also disclosed herein are methods for differentiating uterine leiomyosarcoma and leiomyoma in a subject. In some embodiments, the subject has or is suspected of having leiomyosarcoma (LMS). In some embodiments, the subject has or is suspected of having uterine leiomyosarcoma (uLMS).

[0066] In accordance with these embodiments, the methods comprise determining a methylation profde of a DNA sample (e.g., a cfDNA sample) obtained from a subject based on the presence or absence of methylation of one or more CpG sites present in one or more genes or chromosome locations (as described in Table 1) using a methylation-specific assay.

[0067] In some embodiments, the methods of the present disclosure include treating the biological sample from the subject with a reagent that modifies DNA in a methylation- specific manner; and measuring or determining a methylation level a methylation profile for at least one CpG site in one or more genes or chromosome locations using a methylation-specific assay. In some embodiments, the one or more genes or chromosome locations are selected from: APOLD1; SLC12A4; CCNE2; chr8.40057011; EFNA5; ABL1; chr!4.31698967; CDKN2A;SPRR2C; PVT1; ADM; chrl6.10956460; chr5.159602480; KIFC2; TWIST1; NPAS4; chr7.26416987; SPEG; GLI2; and THEM7P.

[0068] As would be understood by one of ordinary skill in the art based on the present disclosure, the methylation markers described herein can be used individually to aid in distinguishing leiomyosarcoma from other soft tissue tumors, from related benign conditions such as leiomyoma, or healthy controls. In some embodiments, the one or more of the methylation markers of the present disclosure can be combined to form a signature, an overall methylation score, or an overall methylation frequency capable of distinguishing leiomyosarcoma from other soft tissue tumors, from related benign conditions such as leiomyoma, or healthy controls.

[0069] In some embodiments, the method comprises determining a methylation profile for at least one CpG site in two genes or chromosome locations, three genes or chromosome locations, four genes or chromosome locations, five genes or chromosome locations, six genes or chromosome locations, seven genes or chromosome locations, eight genes or chromosome locations, nine genes or chromosome locations, ten genes or chromosome locations, eleven genes or chromosome locations, or twelve genes or chromosome locations selected from: APOLD1; SLC12A4; CCNE2; chr8.40057011; EFNA5; ABL1; chrl4.31698967; CDKN2A; SPRR2C; PVT1; ADM; chr!6.10956460; chr5.159602480; KIFC2; TWIST1; NPAS4; chr7.26416987;SPEG; GLI2; and THEM7P.

[0070] In some embodiments, the methods comprise determining a methylation profile for at least one CpG site in one or more or all genes or chromosome locations selected from: chr5.159602480; KIFC2; TWIST1; NPAS4; chr7.26416987; SPEG; GLI2; and THEM7. In some embodiments, the methods comprise determining a methylation profile for at least one CpG site in one or more or all genes or chromosome locations selected from: APOLD1; SLC12A4;CCNE2; chr8.40057011; EFNA5; ABL1; chrl4.31698967; CDKN2A; SPRR2C; PVT1; ADM; and chr 16.10956460.

[0071] In some embodiments, the one or more genes or chromosome locations are selected from: chr5.159602480; KIFC2; TWIST1; NPAS4; chr7.26416987; SPEG; GLI2; THEM7; and any combination thereof, and the methylation profile indicates that the subject has leiomyosarcoma (LMS). In some embodiments, the one or more genes or chromosome locationsare: chr5.159602480; KIFC2; TWIST1; NPAS4; chr7.26416987; SPEG; GLI2; and THEM7, and the methylation profile indicates that the subject has leiomyosarcoma (LMS).

[0072] In some embodiments, the one or more genes or chromosome locations are selected from: APOLD1; SLC12A4; CCNE2; chr8.40057011; EFNA5; ABL1; chrl4.31698967;CDKN2A; SPRR2C; PVT1; ADM; chrl6.10956460; and any combination thereof, and the methylation profile distinguishes between uterine leiomyoma (LM) and uterine leiomyosarcoma (uLMS). In some embodiments, the one or more genes or chromosome locations are: APOLD1 ; SLC12A4; CCNE2; chr8.40057011; EFNA5; ABL1; chrl4.31698967; CDKN2A; SPRR2C; PVT1; ADM; and chr 16.10956460, and the methylation profile distinguishes between uterine leiomyoma (LM) and uterine leiomyosarcoma (uLMS).

[0073] The one or more CpG sites may be selected from: cg24579851; cgl5006175; cg25228422; cgl4699728; cg24755163; cg24496841; cg00803453; cg23032184; and cg06619621 and / or cg27423445; cg00420526; cgl4001824; cg08900470; cg22009908; cgl4471330; cgl0348234; cg23322868; cg07804289; cgl 1201447; cg26955482; cg01085454; and cg04102657, as referenced in the Illumina CpG loci database with CpG loci IDs (see Table 1). In some embodiments, the one or more CpG sites are selected from: cg24579851; cgl5006175; cg25228422; cgl4699728; cg24755163; cg24496841; cg00803453; cg23032184; and cg06619621. In some embodiments, the one or more CpG sites are selected from: cg27423445; cg00420526; cgl4001824; cg08900470; cg22009908; cgl4471330; cgl0348234; cg23322868; cg07804289; cgl 1201447; cg26955482; cg01085454; and cg04102657.

[0074] In some embodiments, the one or more CpG sites are selected from: cg24579851; cgl5006175; cg25228422; cgl4699728; cg24755163; cg24496841; cg00803453; cg23032184; cg06619621; and any combination thereof, and the methylation profile (e.g., the presence or absence or frequency of methylation at one of more of the CpG sites) indicates that the subject has leiomyosarcoma (LMS). In some embodiments, the one or more CpG sites are selected from: cg24579851; cgl5006175; cg25228422; cgl4699728; cg24755163; cg24496841; cg00803453; cg23032184; and cg06619621, and the methylation profile indicates that the subject has leiomyosarcoma (LMS).

[0075] In some embodiments, the one or more CpG sites are selected from: cg27423445; cg00420526; cgl4001824; cg08900470; cg22009908; cgl4471330; cgl0348234; cg23322868; cg07804289; cgl 1201447; cg26955482; cg01085454; cg04102657; and any combinationthereof, and the methylation profile (e.g., the presence or absence or frequency of methylation at one of more of the CpG sites) distinguishes between uterine leiomyoma (LM) and uterine leiomyosarcoma (uLMS). In some embodiments, the one or more CpG sites are selected from: cg27423445; cg00420526; cgl4001824; cg08900470; cg22009908; cgl4471330; cgl0348234; cg23322868; cg07804289; cgl 1201447; cg26955482; cg01085454; and cg04102657, and the methylation profile distinguishes between uterine leiomyoma (LM) and uterine leiomyosarcoma (uLMS).

[0076] In some embodiments, determining the methylation profile comprises comparing the methylation level at least one CpG site in one or more genes or chromosome locations to a corresponding methylation level in a control sample. The control sample may be from a healthy subject (e.g., a subject who does not have cancer). The control sample may be from a subject that does not have leiomyosarcoma. For example, the control sample may from a cancer subject (e.g., a subject having a soft tissue cancer, such as dedifferentiated liposarcoma, myxofibrosarcoma, undifferentiated pleomorphic sarcoma, malignant peripheral nerve sheath tumors and synovial sarcoma) but not leiomyosarcoma. Alternatively, the control sample may be a sample from a subject that has a non-cancerous condition, e.g., leiomyoma.

[0077] In some embodiments, the methylation profile capable of distinguishing a leiomyosarcoma sample from a control sample is associated with an area under a ROC curve (AUC) greater than or equal to 0.5 (e.g., 0.6, 0.7, 0.8, 0.9, or more), wherein the ROC curve discriminates between a subject having or suspected of having LMS and a control DNA sample. The control sample may be a sample from a subject that does not have cancer (e.g., a healthy control), a sample having a related benign condition such as leiomyoma, or a sample from a subject that has a type of cancer that is not LMS (e.g., a sample from other soft tissue tumors).

[0078] In some embodiments, the at least one CpG site is individually associated with an area under a ROC curve (AUC) greater than or equal to 0.7, and the ROC curve discriminates between a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample. In some embodiments, the at least one CpG site is individually associated with an area under a ROC curve (AUC) greater than or equal to 0.8, and the ROC curve discriminates between a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample. In some embodiments, the at least one CpG site is individually associated with an area under a ROC curve (AUC) greater than or equal to 0.9, and the ROC curve discriminatesbetween a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample. In some embodiments, the at least one CpG site is individually associated with an area under a ROC curve (AUC) greater than or equal to 0.95, and the ROC curve discriminates between a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample.

[0079] In some embodiments, the at least one CpG sites are collectively associated with an area under a ROC curve (AUC) greater than or equal to 0.7, and the ROC curve discriminates between a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample. In some embodiments, the at least one CpG sites are collectively associated with an area under a ROC curve (AUC) greater than or equal to 0.8, and the ROC curve discriminates between a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample. In some embodiments, the at least one CpG sites are collectively associated with an area under a ROC curve (AUC) greater than or equal to 0.9, and the ROC curve discriminates between a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample. In some embodiments, the at least one CpG sites are collectively associated with an area under a ROC curve (AUC) greater than or equal to 0.95, and the ROC curve discriminates between a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample.

[0080] Determining a methylation profile can involve any means known in the art. Exemplary methylation assays include, without limitation, methylation-sensitive arbitrarily-primed polymerase chain reaction (MS AP-PCR), methylation- sensitive single nucleotide primer extension (Ms-SNuPE), methylation- specific PCR (MSP), methylation- sensitive DNA restriction enzyme analysis, restriction enzyme-based sequencing, restriction enzyme-based microarray analysis, combined bisulfite restriction analysis (COBRA), methylated CpG island amplification (MCA), methylated CpG island amplification and microarray (MCAM), Hpall tiny fragment enrichment by ligation-mediated PCR (HELP), bisulfite sequencing, bisulfite microarray analysis (e.g., EPIC DNA methylation microarray and Infinium Methylation EPIC assay (Illumina)), methylation- specific pyrosequencing, HELP- sequencing (HELP-seq), TET-assisted pyridine borane sequencing (TAPS), Glal hydrolysis and ligation adapter dependent PCR (GLAD-PCR), methylated DNA immunoprecipitation- sequencing (MeDIP-Seq), or methylated DNA immunoprecipitation-microarray analysis (MeDIP-chip), Southern blotting with methyl-sensitive restriction enzymes, and methylation-specific giant magnetoresistive sensor-based microarray analysis.

[0081] Bisulfite sequencing uses bisulfite treatment of DNA before sequencing to detect methylation sites. Treatment of DNA with bisulfite converts cytosine residues to uracil, but does not affect methylated cytosine residues. After bisulfite treatment, the only cytosines remaining in the DNA are methylated cytosines. Thus, sequencing the DNA after bisulfite treatment reveals the methylation status of individual cytosine residues at single-nucleotide resolution.

[0082] The MS AP-PCR assay uses methylation- sensitive restriction enzymes to digest DNA and PCR with CG-rich primers to selectively amplify regions that contain CpG dinucleotides.

[0083] The MethyLight assay uses bisulfite-dependent, quantitative fluorescence-based realtime PCR with methylation- specific priming and methylation- specific fluorescent probing for detection of DNA methylation. Digital MethyLight combines the MethyLight assay with digital PCR to allow detection of individual methylated molecules. The HeavyMethyl assay uses methylation specific blocking probes (also referred to herein as blockers) covering CpG positions between, or covered by, amplification primers to enable methylation- specific selective amplification of a nucleic acid sample. The HeavyMethyl MethyLight assay is a variation of the MethyLight™ assay, wherein the MethyLight™ assay is combined with methylation specific blocking probes covering CpG positions between the amplification primers.

[0084] The Ms-SNuPE assay uses bisulfite treatment of DNA combined with PCR using primers designed to hybridize immediately upstream of the CpG site(s) and electrophoresis of amplicons on polyacrylamide gels for visualization and quantitation. Treatment of DNA (genomic or cfDNA) with sodium bisulfite causes unmethylated cytosines to be converted to uracils, During the PCR step, uracil is replicated as thymine, and methylcytosine is replicated as cytosine during amplification. The ratio of methylated versus unmethylated cytosine (C versus T) at the original CpG sites can be determined by incubating the gel-isolated PCR product, primer(s), and Taq polymerase with either [32P]dCTP or [32P]TTP followed by denaturing polyacrylamide gel electrophoresis and phosphorimage analysis. Ms-SNuPE primers can also be designed to incorporate either [32P]dATP or [32P]dGTP into the opposite strand to assess methylation status depending on which CpG site is analyzed.

[0085] The MSP assay uses bisulfite treatment of DNA for conversion of non-methylated cytosines to uracils and subsequent amplification with primers specific for methylated versus unmethylated DNA.

[0086] The COBRA assay uses bisulfite treatment of DNA for conversion of non-methylated cytosines to uracils, locus-specific PCR amplification of the bisulfite-converted DNA, restriction digestion, electrophoresis an analysis of restriction patterns on a gel.

[0087] The MCA assay uses methylation-sensitive restriction enzymes to digest DNA, followed by adaptor ligation and PCR to selectively amplify methylated CpG-rich sequences.

[0088] The MCAM assay uses MCA in combination with a CpG island microarray to detect DNA methylation in a high-throughput fashion.

[0089] The HELP assay uses the methylation- sensitive restriction enzyme, Hpall, to cut DNA, and a methylation-insensitive isoschizomer, Mspl, as a control. Microarray analysis is performed with microarrays containing probes designed to detect the Hpall / Mspl fragments. HELP-seq combines the HELP assay with massively parallel sequencing of DNA methylation sites.

[0090] The GLAD-PCR assay uses a site-specific methyl-directed DNA-endonucleases that cleave only methylated DNA, followed by ligation of DNA fragments to universal adapters for high-throughput PCR.

[0091] The MeDIP assay uses an antibody against 5 -methylcytosine to immunoprecipitate methylated DNA fragments. This technique can be combined with high-throughput DNA detection methods using microarray hybridization (MeDIP-chip) or next-generation sequencing (MeDIP-seq).

[0092] TET-assisted pyridine borane sequencing (TAPS) uses the ten-eleven translocation (TET) enzyme to catalyze oxidation of 5-methylcytosine and 5-hydroxymethylcytosine to 5- carboxylcytosine, followed by pyridine borane reduction to produce dihydrouracil. Unmodified cytosine is not affected.

[0093] Methylation-specific giant magnetoresistive sensor-based microarray analysis combines methylation specific PCR and melt curve analysis on a giant magnetoresistive (GMR) biosensor. The GMR biosensor comprises synthetic DNA probes that target methylated or unmethylated CpG sites in the PCR amplicons. After hybridization of the PCR amplicons to the GMR biosensor, the difference in melting temperature (Tm) between the two types of probes is measured.

[0094] Southern Blotting can also be used to detect DNA methylation. The DNA is first digested with methylation- sensitive restriction enzymes, and the restriction fragments are analyzed by Southern Blot.

[0095] Following a methylation- specific assay or nucleic acid separation, the resulting nucleic acids may be subjected to sequence-based analysis in order to determine the presence or absence of methylation at the at least one CpG sites. Next generation sequencing technologies suitable for use with the disclosed methods and various methylation assays are widely available. Examples include the 454 Life Sciences platform (Roche, Branford, CT) (Margulies et al. 2005 Nature, 437, 376-380); Illumina's Genome Analyzer, GoldenGate Methylation Assay, or Infinium Methylation Assays, i.e., Infinium HumanMethylation 27K BeadArray or VeraCode GoldenGate methylation array (Illumina, San Diego, CA); QX200™ Droplet Digital™ PCR System from Bio-Rad; or DNA Sequencing by Ligation, SOLID System (Applied Biosystems / Life Technologies); Helicos True Single Molecule DNA sequencing technology; single molecule, real-time (SMRT™) technology of Pacific Biosciences, and sequencing (Soni and Meller, 2007, Clin. Chem. 53, 1996-2001); semiconductor sequencing (Ion Torrent; Personal Genome Machine); DNA nanoball sequencing and technologies that do not require amplification or otherwise transform native DNA prior to sequencing (e.g., Pacific Biosciences and Helicos), such as nanopore-based strategies (e.g., Oxford Nanopore, Genia Technologies, and Nabsys). These systems allow the sequencing of many nucleic acid molecules isolated from a specimen at high orders of multiplexing in a parallel fashion.

[0096] In some embodiments, the methods further comprise analysis of other genetic and protein markers for leiomyosarcoma, uterine leiomyosarcoma, or leiomyoma. For example, the methods may further comprise determining a mutational profile the DNA sample comprising detecting one or more DNA substitutions, insertions, or deletions in one or more genes and / or determining copy number alterations of one or more genes. The one or more genes may include, but are not limited to: ABCA5, ADGRF3, AKAP9, APOBR, ARHGAP27, ARHGEF17, ARID1A, ATM, ATP2A2, ATR, ATRX, B3GNT9, C6orfl, CCDC88C, CD96, CDH1, CDH20, CDKN2A, CELSR3, CENPF, CHD6, CHIT1, COMP, COPS4, CYP4V2, DCHS2, DLGAP1, DMKN, DSPP, EPHA7, F8, FAM208B, GPRIN1, GRB14, GTF3C4, HINFP, HIVEP3, HMHA1, HOMER3, HRAS, HSF2BP, IRGC, JMJD1C, JPH2, KDM6A, KIAA1549, KIAA1958, KIF17, KIT, KMT2D, KRAS, KRT10, KRT77, MED12, MRPL15, NBEAL2,NCKAP5, OBSCN, PABPN1L, PCDH15, PCDH17, PCDH9, PCNXL2, PHACTR1, PIEZO1, PPP1R3A, PPRC1, PRR21, PTCHD1, PTCHD4, PTEN, PTPN21, RBI, SEC 16 A, SETX, SIRT3, SLC38A10, SLC9B2, SMARCAL1, SPEN, SPHKAP, SPTBN1, TLR5, TLR9, TNK1, TP53, UACA, ZEB1, and ZFPM2 (See Przybyl J. et al., Clinical Cancer Res. 2018 Jun 1 ;24(1 l):2688-2699 and Przybyl J. et al., JCO Precis Oncol. 2019;3:10.1200 / po.18.00409, incorporated herein by reference in their entirety).

[0097] Determining a mutational profile can involve any means or assay known in the art, including but not limited to, generating a library of nucleic acid molecules isolated from the tumor sample, and performing target enrichment. In some embodiments, the method comprises sequencing target nucleic acids that are generated using target enrichment and identifying the at least one nucleotide substitution, deletion, insertion, and / or translocation.

[0098] As described above for the methylation profile. In some embodiments, determining the mutational profile comprises comparing the mutational profile, to a control sample mutational profile. For example, a mutational profile of a sample from a subject that does not have cancer (e.g., a healthy control), a sample having a related benign condition such as leiomyoma, or a sample from a subject that has a type of cancer that is not LMS (e.g., a sample from other soft tissue tumors).

[0099] Determining copy number alterations can involve any means or assay known in the art, including by not limited to multiplex ligation-dependent probe amplification (MLPA), microarray based comparative genomic hybridization (aCGH) and SNP microarrays, RNA sequencing, fluorescence in situ hybridization (FISH), PCR based methods, next generation sequencing technologies (e.g., paired-end mapping based detection (PE), split read based detection (SR), de novo assembly based detection (DA) read depth based detection (RD), use of targeted panels) paralog-ratio testing (PRT), and molecular copy number counting (MCC).

[0100] As described above for the methylation profile. In some embodiments, determining the copy number alterations comprises comparing the copy number alterations, to a control sample copy number alterations. For example, copy number alterations of a sample from a subject that does not have a subject that does not have cancer (e.g., a healthy control), a sample having a related benign condition such as leiomyoma, or a sample from a subject that has a type of cancer that is not LMS (e.g., a sample from other soft tissue tumors).

[0101] The analysis of one or markers (e.g., one or more CpG sites, one or more genes or chromosome locations, and / or one or more leiomyosarcoma, uterine leiomyosarcoma, or leiomyoma biomarkers) can be carried out separately or simultaneously with additional markers within one test sample. For example, several markers can be combined into one test for efficient processing of multiple samples and for potentially providing greater diagnostic and / or prognostic accuracy. In addition, one skilled in the art would recognize the value of testing multiple samples (for example, at successive time points) from the same subject. Such testing of serial samples can allow the identification of changes in marker methylation states over time. Changes in marker status (e.g., methylation state), as well as the absence of change in marker status, can provide useful information, e.g., about disease status.

[0102] In some embodiments, one or more pattern recognition methods can be used in analyzing the methylation profile, the mutational profile, and / or the copy number alterations. The quantitative values may be combined in linear or non-linear fashion to calculate one or more scores for an individual (e.g., for likelihood of LMS). For example, a likelihood score indicates the probability that the sample is from a patient who has no evidence of disease or a patient who has LMS or uterine LMS . The models for pattern recognition methods can be provided in machine readable format and may be used to correlate the frequency or levels of methylation at CpG sites, mutations, or copy number alterations with a disease state, and / or to designate a treatment modality for a patient or class of patients. In some embodiments, a machine learning method (e.g., supervised, unsupervised, etc.) is used to classify a patient.

[0103] The sample may be any source or derived from any source containing or suspected of containing a marker as described above. In some embodiments, the sample is a liquid biological sample. In some embodiments, the sample is a blood or blood product (e.g., plasma, serum, whole blood, buffy coat, etc.) sample. In some embodiments, the sample is tissue sample. In some embodiments, the sample is a tumor sample. In some embodiments, the sample is a gynecological tissue sample (e.g., from the uterus, vagina, ovary, or other gynecological area). In some embodiments, the sample is from a uterine mass (e.g., suspected tumor or fibroid).

[0104] The sample can be obtained from the subject using routine techniques known to those skilled in the art, and the sample may be used directly as obtained from the biological source or following a pretreatment to modify the character of the sample. Such pretreatment may include, for example, preparing plasma from blood, diluting viscous fluids, filtration, precipitation,dilution, distillation, mixing, concentration, inactivation of interfering components, the addition of reagents, lysing, and the like.

[0105] In some embodiments, the methods comprise obtaining a biological sample from the subject and isolating the DNA sample. Any method known in the art for isolating DNA may be suitable for use with the disclosed methods. For example, the isolation methods may facilitate producing DNA samples which are highly -purified and lacking contaminants useful in the methylation and mutational analysis methods described above. The technology is not limited in the methods used to prepare the samples and provide a nucleic acid for testing. In some embodiments, the DNA is cfDNA. In some embodiments, the DNA is genomic DNA.

[0106] The methods disclosed herein may be used to determine an appropriate intervention based on the determination of leiomyosarcoma, uterine leiomyosarcoma, or leiomyoma as found through the methylation profiling, alone or in combination with the mutational profiling and copy number alterations. Thus, in some embodiments, the methods further comprise administration of one or more interventions to the subject based on the methylation profile. As such, the methods described herein may be integrated into a treatment regimen for a subject. For example, in some embodiments, the biological sample(s) is analyzed by the methods described herein and the subject is treated based on the results (e.g., commence a new treatment, continue existing treatment, change in treatment (e.g., change in intervention type, dose, timing, etc.), or stop treatment).

[0107] In some embodiments of the technology, a method for diagnosing leiomyosarcoma or uterine leiomyosarcoma or leiomyoma in a subject is provided. The terms “diagnosing” and “diagnosis” as used herein refer to methods by which the skilled artisan can estimate and even determine whether or not a subject is suffering from a given disease or condition or may develop a given disease or condition in the future (e.g., determining a risk of developing a given disease or condition or determining a prognosis). The skilled artisan often makes a diagnosis on the basis of one or more diagnostic indicators, such as for example one or more biomarkers (e.g., one or more methylated markers, methylated marker genes, genes, DMRs, and / or DNA methylated markers as disclosed herein), the methylation state of which is indicative of the presence, severity, or absence of the condition.

[0108] The treatment may be administration of an active agent or a therapy not connected to administration of another agent, e.g., surgery, immunotherapy, radiotherapy. In someembodiments, the treatment comprises administration of an anti-cancer agent or chemotherapeutic. “Anti-cancer agent” or “chemotherapeutic,” as used herein, refers to any small molecule or other drug used in cancer treatment or prevention, whether cytostatic, cytotoxic, kinase inhibitor, or other MOA. Chemotherapeutics include, but are not limited to, cyclophosphamide, methotrexate, 5-fluorouracil, doxorubicin, docetaxel, daunorubicin, bleomycin, vinblastine, dacarbazine, cisplatin, paclitaxel, raloxifene hydrochloride, tamoxifen citrate, abemacicilib, afinitor, alpelisib, anastrozole, pamidronate, anastrozole, exemestane, capecitabine, epirubicin hydrochloride, eribulin mesylate, toremifene, fulvestrant, letrozole, gemcitabine, goserelin, ixabepilone, emtansine, lapatinib, olaparib, megestrol, neratinib, palbociclib, ribociclib, talazoparib, thiotepa, toremifene, methotrexate, and tucatinib.

[0109] In some embodiments, the treating comprises active surveillance. As such, the methods described herein find use in classifying a patient as suitable for active surveillance. During active surveillance, the subject is monitored with additional screenings or tests for changes in overall health or changes directly related to progression of the disease. Methylation profiles and / or one or more leiomyosarcoma, uterine leiomyosarcoma, or leiomyoma biomarkers can be measured in each of the samples taken from different time points and qualitative and / or quantitative differences noted.3. Kits or systems

[0110] Also provided are kits or systems that can be used to conduct the methods described herein. Such kits can be used to diagnose a subject with LMS, aid in selection or appropriate interventions, or monitoring responses to interventions. The kit may include one or more agents for detection of methylated biomarkers, a container for holding a biological sample (e.g., blood, plasma, tissue) isolated from a human subject; and printed instructions for carrying out the disclosed methods with the biological sample or a portion of the biological sample to detect the methylation profile, one or more leiomyosarcoma, uterine leiomyosarcoma, or leiomyoma biomarkers, or any combination thereof. The reagents may be packaged in separate containers.

[0111] The kit may further comprise one or more control reference samples and reagents for performing a methylation assay as described above. For example, the subject kits may include reagents for determining the frequency or level of methylation such as a bisulfite reagent, methylation-sensitive restriction enzymes, PCR primers that selectively amplify DNA regionsthat contain CpG dinucleotides, methylation-specific primers, methylation- specific probes, or a combination thereof.

[0112] Individual member components of the kits may be physically packaged together or separately. The components of the kits may be provided in bulk packages (e.g., multi-use packages) or single-use packages. The kits provided herein are in suitable packaging. Suitable packaging includes, but is not limited to, vials, bottles, jars, flexible packaging, and the like.

[0113] The kits can also comprise instructions for using the components of the kit. The instructions are relevant materials or methodologies pertaining to the kits. The materials may include any combination of the following: background information, list of components and their availability information (purchase information, etc.), brief or detailed protocols for using the compositions, troubleshooting, references, technical support, and any other related documents. Instructions can be supplied with the kits or as a separate member component, either as a paper form or an electronic form which may be supplied on a computer readable memory device or downloaded from an internet website, or as a recorded presentation.

[0114] It is understood that the disclosed kits can be employed in connection with the disclosed methods.4. ExamplesMethodsMethods for DNA methylation profiling

[0115] Five hundred nanograms of genomic DNA from tumor specimens was used for genomewide DNA methylation profiling with the Infinium Methylation EPIC microarrays (Illumina).

[0116] The data has been analyzed using a custom pipeline in R (version 3.6.3). For specimen quality control, > 90% of probes were measured with p < 0.05 on at least 3 separate beads (using “detectionP” function in the minfi package version 1.32.0, and the “beadcount” function in the wateRmelon package version 1.30.0). The samples have a log2 median intensity of the methylated and unmethylated channels > 9 (using “shinySummarize” function in the minfi package). The data was normalized using Illumina preprocessing (“preprocesslllumina” function in the minfi package), and it was verified that the specimens had a bimodal distribution of beta values. Next, individual poor quality probes (measured with p > 0.01), probes associated with single nucleotide polymorphisms (“dropLociWithSnps” function in the minfi package), cross-reactive probes(“xreactive_probes” function in the maxprobes package version 0.0.2) and probes associated with sex chromosomes were removed.Example 1Identification of LMS-specific DNA methylation signature

[0117] To identify DNA methylation markers (CpGs) specific for leiomyosarcoma (LMS), differential methylation analysis was performed using 348 tumor specimens: 254 LMS (primary, recurrent, and metastatic) and 94 soft tissue tumors of other types (fibrotic tumors, desmoid type fibromatosis and gastrointestinal stromal tumors). Differential methylation analysis was performed using ChAMP package. This analysis identified 9 differentially methylated CpGs between LMS and other tumors with fold change > 3 or < -3, and adjusted p value < 0.0001. These 9 CpGs allowed for accurate separation of LMS from other types of tumors (FIG. 1). 9 CpGs: cg24579851; cgl5006175; cg25228422; cgl4699728; cg24755163; cg24496841; cg00803453; cg23032184; cg06619621.

[0118] The publicly available data from 206 sarcoma specimens, including 79 LMS, generated by The Cancer Genome Atlas, were used to validate the ability of the 9 CpGs to separate LMS from other types of soft tissue tumors (dedifferentiated liposarcoma, myxofibrosarcoma, undifferentiated pleomorphic sarcoma, malignant peripheral nerve sheath tumors and synovial sarcoma) (FIG. 2).

[0119] Heatmaps that visualize supervised clustering were plotted using ClustVis package in R (version 0.0.0.9000). Beta values were used for unsupervised clustering with Euclidean distance and average linkage method.Example 2Identification of DNA methylation markers specific for uterine leiomyoma (LM) compared to uterine leiomyosarcoma (uLMS)

[0120] To identify DNA methylation markers that can be useful for accurate distinction between uterine leiomyoma (LM) and uterine leiomyosarcoma (uLMS), differential methylation analysis was performed using 274 tumor specimens: 164 LM and 110 primary uLMS. Differential methylation analysis was performed using ChAMP package. This analysis identified 206 differentially methylated CpGs between LM and uLMS with fold change > 2 or < -2, and adjusted p value < 0.0001. The 274 tumor specimens were then randomly split into training and validationcohorts (137 specimens each). Random forest algorithm was applied to these training and validation cohorts to identify 31 DNA methylation markers (among the 206 differentially methylated markers) with the mean decrease accuracy > 15. These 31 CpGs were further narrowed down to selection of 13 CpGs, based on 3 criteria: i) error rate, ii) number of misclassified cases in validation, and iii) area under the curve (AUC) (FIG. 3). These 13 CpGs allowed for LM and uLMS classification with 0.73% error rate in the training cohort (i.e., 1 / 137 misclassified specimens), and area under the curve of 0.98 in the validation cohort (FIG. 4). Supervised clustering illustrates accurate separation of LM and uLMS in the Stanford dataset (FIGS. 5 and 6). 13 CpGs: cg27423445; cg00420526; cgl4001824; cg08900470; cg22009908; cgl4471330; cgl0348234; cg23322868; cg07804289; cgl 1201447; cg26955482; cg01085454; cg04102657.

[0121] The publicly available data from 7 LM and 15 uLMS (PMID: 33479225) were used as an independent cohort to validate the utility of 13 CpGs for accurate distinction between these diagnoses (AUC =1) (FIGS. 7 and 8).

[0122] Heatmaps that visualize supervised clustering were plotted using ClustVis package in R (version 0.0.0.9000).

[0123] Previous publications reported that selected DNA methylation markers are associated with age (PMIDs: 24138928, 23177740, 27716309). Since uterine LM is usually diagnosed in patients younger than patients with uLMS, it was verified that the signature is not related to age, and that there was no overlap between the 13 CpGs identified, and the previously published CpGs associated with age (FIG. 9).Table 1. CpG loci IDs (from Illumina CpG database) with Gene Name or Position as determined by UCSC Genome Browser for human genome version GRCh37 / hgl9

[0124] All references, including publications, patent applications, and patents, cited herein arc hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein.

[0125] All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate the invention, and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.

[0126] Preferred embodiments of this invention are described herein, including the best mode known to the inventors for carrying out the invention. Variations of those preferred embodiments may become apparent to those of ordinary skill in the art upon reading the foregoing description. The inventors expect skilled artisans to employ such variations as appropriate, and the inventors intend for the invention to be practiced otherwise than as specifically described herein.Accordingly, this invention includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by the invention unless otherwise indicated herein or otherwise clearly contradicted by context.

Claims

CLAIMSWhat is claimed is:

1. A method for characterizing a biological sample from a subject, comprising: treating the biological sample from the subject with a reagent that modifies DNA in a methylation-specific manner; and determining a methylation profile for at least one CpG site in one or more genes or chromosome locations using a methylation- specific assay, wherein the one or more genes or chromosome locations are selected from: APOLD1; SLC12A4; CCNE2; chr8.40057011; EFNA5; ABL1; chrl4.31698967; CDKN2A; SPRR2C; PVT1; ADM; chrl6.10956460; chr5.159602480; KIFC2; TWIST1; NPAS4; chr7.26416987; SPEG; GLI2; and THEM7P.

2. The method of claim 1, wherein the method comprises determining a methylation profile for at least one CpG site in two genes or chromosome locations, three genes or chromosome locations, four genes or chromosome locations, five genes or chromosome locations, six genes or chromosome locations, seven genes or chromosome locations, eight genes or chromosome locations, nine genes or chromosome locations, ten genes or chromosome locations, eleven genes or chromosome locations, or twelve genes or chromosome locations.

3. The method of claim 1 or 2, wherein the one or more CpG sites are selected from: cg24579851; cgl5006175; cg25228422; cgl4699728; cg24755163; cg24496841; cg00803453; cg23032184; cg06619621 cg27423445; cg00420526; cgl4001824; cg08900470; cg22009908; cgl4471330; cgl0348234; cg23322868; cg07804289; egl 1201447; cg26955482; cg01085454; and cg041026574. The method of any of claims 1-3, wherein the subject has or is suspected of having leiomyosarcoma (LMS).

5. The method of claim 4, wherein the leiomyosarcoma is uterine leiomyosarcoma.

6. The method of any of claims 1-5, wherein the methylation profile indicates that the subject has leiomyosarcoma (LMS).

7. The method of any of claims 1-6, wherein the one or more genes or chromosome locations are selected from: chr5.159602480; KIFC2; TWIST1; NPAS4; chr7.26416987; SPEG; GLI2; THEM7; and any combination thereof, wherein the methylation profile indicates that the subject has leiomyosarcoma (LMS).

8. The method of claim 7, wherein the one or more CpG sites are selected from: cg24579851; cgl5006175; cg25228422; cgl4699728; cg24755163; cg24496841; cg00803453; cg23032184; cg06619621; and any combination thereof, wherein the methylation profile indicates that the subject has leiomyosarcoma (LMS).

9. The method of any of claims 1-6, wherein the one or more genes or chromosome locations are selected from: APOLD1; SLC12A4; CCNE2; chr8.40057011; EFNA5; ABL1; chrl4.31698967; CDKN2A; SPRR2C; PVT1; ADM; chrl6.10956460; and any combination thereof, wherein the methylation profile distinguishes between uterine leiomyoma (LM) and uterine leiomyosarcoma (uLMS).

10. The method of claim 9, wherein the one or more CpG sites are selected from: cg27423445; cg00420526; cgl4001824; cg08900470; cg22009908; cgl4471330; cgl0348234; cg23322868; cg07804289; cgl 1201447; cg26955482; cg01085454; cg04102657; and any combination thereof, wherein the methylation profile distinguishes between uterine leiomyoma (LM) and uterine leiomyosarcoma (uLMS).

11. The method of any of claims 1-10, wherein determining the methylation profile comprises comparing the methylation level at least one CpG site in one or more genes or chromosome locations to a methylation level of the corresponding at least one CpG site in a control sample.

12. The method of any of claims 1-11, wherein the at least one CpG site is individually associated with an area under a ROC curve (AUC) greater than or equal to 0.8, and wherein theROC curve discriminates between a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample.

13. The method of any of claims 1-12, wherein the at least one CpG site are collectively associated with an area under a ROC curve (AUC) greater than or equal to 0.8, and wherein the ROC curve discriminates between a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample.

14. The method of any of claims 11-13, wherein the control sample is from a healthy subject or a subject that does not have cancer.

15. The method of any of claims 11-13, wherein the control sample is from a subject that does not have leiomyosarcoma.

16. The method of any of claims 1-15, wherein determining the methylation profile for at least one CpG site in one or more genes or chromosome locations comprises calculating a methylation score and / or a methylation frequency for the at least one CpG site.

17. The method of any of claims 1-16, wherein the biological sample is a blood product sample or a tissue sample.

18. The method of any of claims 1-17, wherein the biological sample is a gynecological tissue sample.

19. The method of any of claims 1-18, wherein the biological sample is a tumor sample.

20. The method of any of claims 1-19, wherein the DNA is genomic DNA and wherein method further comprises isolating genomic DNA from the sample.

21. The method of any of claims 1-19, wherein the DNA is cell-free DNA (cfDNA), and wherein method further comprises isolating cfDNA from the sample.

22. The method of any of claims 1-21, wherein the method further comprises assaying one or more leiomyosarcoma, uterine leiomyosarcoma, or leiomyoma biomarkers.

23. The method of claim 22, wherein the method further comprises determining the mutational profile and / or copy number alterations of one or more leiomyosarcoma, uterine leiomyosarcoma, or leiomyoma biomarkers.

24. A method for characterizing a gynecological tissue sample from a subject, comprising: treating the gynecological tissue sample from the subject with a reagent that modifiesDNA in a methylation- specific manner; and determining a methylation profile for at least one CpG site in one or more genes or chromosome locations using a methylation- specific assay, wherein the one or more genes or chromosome locations are selected from: APOLD1; SLC12A4; CCNE2; chr8.40057011; EFNA5; ABL1; chrl4.31698967; CDKN2A; SPRR2C; PVT1; ADM; and chr 16.10956460.

25. The method of claim 24, wherein the one or more CpG sites arc selected from: cg27423445; cg00420526; cgl4001824; cg08900470; cg22009908; cgl4471330; cgl0348234; cg23322868; cg07804289; cgl 1201447; cg26955482; cg01085454; cg04102657; and any combination thereof, wherein the methylation profile distinguishes between uterine leiomyoma (LM) and uterine leiomyosarcoma (uLMS).

26. The method of claim 24 or 25, wherein the methylation profile indicates that the subject has uterine leiomyosarcoma.

27. The method of any of claims 24-26, wherein the methylation profile indicates that the subject has leiomyoma.

28. The method of any of claims 24-27, wherein the method further comprises obtaining a biological sample from the subject and isolating the DNA sample.

29. The method of any of claims 24-28, wherein determining the methylation profile comprises comparing the methylation level at least one CpG site in one or more corresponding genes or chromosome locations to a corresponding methylation level in a control sample.

30. The method of any of claims 24-29, wherein the at least one CpG site is individually associated with an area under a ROC curve (AUC) greater than or equal to 0.8, and wherein the ROC curve discriminates between a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample.

31. The method of any of claims 24-30, wherein the at least one CpG site are collectively associated with an area under a ROC curve (AUC) greater than or equal to 0.8, and wherein the ROC curve discriminates between a sample from a subject having or suspected of having leiomyosarcoma (LMS) and a control sample.

32. The method of any of claims 29-31, wherein the control sample is from a healthy subject or a subject that docs not have cancer or leiomyosarcoma.

33. The method of any of claims 24-32, wherein determining the methylation profile for at least one CpG site in one or more genes or chromosome locations comprises calculating a methylation score and / or a methylation frequency for the at least one CpG site.

34. The method of any of claims 24-33, wherein the biological sample is a tumor or fibroid sample.

35. The method of any of claims 24-34, wherein the DNA is genomic DNA and wherein method further comprises isolating genomic DNA from the sample.

36. The method of any of claims 24-35, wherein the method further comprises assaying one or more leiomyosarcoma, uterine leiomyosarcoma, or leiomyoma biomarkers.

37. The method of any of claims 36, wherein the method further comprises determining the mutational profile and / or copy number alterations of one or more leiomyosarcoma, uterine leiomyosarcoma, or leiomyoma biomarkers.

38. The method of any one of claims 1-37, wherein the method further comprises administering one or more interventions to the subject based on the methylation profile.

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