A method for detection of cancer

Abstract

The present disclosure relates to an improved method for detection of cancer, including but not limited to urinary bladder cancer. The method of the present disclosure comprises combining somatic copy number aberration analysis on tumor fraction and analysis of targeted methylation of genes including but not limited to GALR1, HAND2 and NRN1 genes for detection of cancer, including but not limited to urinary bladder cancer.

Description

[0001] “A METHOD FOR DETECTION OF CANCER”

[0002] TECHNICAL FIELD

[0003] The present disclosure generally relates to the field of medical science, and particularly to detection of cancer, including but not limited to urinary bladder cancer and upper tract urothelial cancer. The present disclosure describes an improved non-invasive method of detecting presence or absence of such cancers in a biological sample through a combined analysis of methylation status of a set of genes and somatic copy number aberrations in a genome, through a common cell free DNA analysis. Also provided is a method of treating a subject with a corresponding anti-cancer therapy, when the method of the present disclosure detects presence of cancer.

[0004] BACKGROUND

[0005] Bladder cancer ranks amongst the ten most commonly diagnosed cancers worldwide with rising incidences on a global scale. Bladder cancer usually presents with painless hematuria and is diagnosed by cystoscopy. However, the occurrence of bladder cancer among individuals with asymptomatic microscopic hematuria is also estimated to be between 1.2-3.1%, while for those with macroscopic hematuria, is estimated to be around 13.8%. Moreover, as around 80% of bladder cancer patients are diagnosed with non-muscle invasive bladder cancer (NMIBC), stringent and long-term surveillance with cystoscopy is vital due to high recurrence rates and risk of progression to muscle-invasive bladder cancer. While cystoscopy offers a reliable diagnostic tool, major drawbacks include its invasiveness, high costs, need for frequent hospital visits, and risk of complications. Hence, there is an urgent need for the development of non- invasive and cost-effective alternatives for cystoscopy to enhance the detection of primary and recurrent bladder cancer.

[0006] Urinary biomarkers represent a promising solution for improving bladder cancer management. The classical form of urinary analysis is urine cytology, which is combined with cystoscopy in daily clinical practice during surveillance. However, it is widely recognized that the sensitivity of urine cytology is insufficient, especially in low-grade (LG) patients. Urinary analyses based on cell or protein biomarkers are known to be susceptible to interference from benign conditions, such as infection or bladder treatments. Therefore, urine-based DNA tests may offer a more valuable alternative for reliable bladder cancer detection. Urine as an upcoming liquid biopsy, also provides a direct and concentrated source of bladder cancer-derived DNA for further analysis. As compared to plasma-based liquid biopsies, urinebased tests show an increased sensitivity, particularly for LG NMIBC. However, the data is limited on its practical use in detecting bladder cancers.

[0007] Another approach that seemed promising was methylation analysis of cancer biomarkers. However, diagnostic accuracy of cancer biomarkers was noted to be compromised as not all tumors exhibit specific changes that aim to detect the cancer, including bladder cancer. Additionally, choosing specific cancer biomarkers for accurate diagnosis with improved sensitivity is a challenge as there is limited data for the same.

[0008] While different techniques provide some advantages, they also come with their own challenges, as mentioned above. Accordingly, there continues to be a need for a non-invasive method, that detects urinary bladder cancer with high specificity and sensitivity from a simple biological sample such as urine. Further, such a method should not be merely theoretical but must be well supported through experimentation and confirmations, along with comparisons with individually known techniques to ensure that such a method makes improvements over specificity and sensitivity provided by existing methods. The present disclosure aims to provide a method that addresses these issues pertaining to detecting of urinary bladder cancer.

[0009] SUMMARY OF THE DISCLOSURE

[0010] Accordingly, in order to address the drawback or limitation noted in the art, the present disclosure describes an improved non-invasive method for detecting cancer, including but not limited to urinary bladder cancer, non-muscle invasive bladder cancer or upper tract urothelial cancer. The method of the present disclosure is simple, minimizes sample input, reduces analysis time, cost effective and maximizes test accuracy in low yield samples.

[0011] In some embodiments, the present disclosure provides a method for detecting presence or absence of cancer in a biological sample, through a combined analysis of methylation status of a set of genes and somatic copy number aberrations in a genome.

[0012] In some embodiments, the said method for detecting presence or absence of cancer in a biological sample comprises acts of:

[0013] • purifying DNA from a biological sample and preparing corresponding sequencing libraries; • performing at least one quantitative methylation assay on one fraction of the sequencing libraries and calculating the methylation levels of three genes - GALR1, HAND2, and NRN1;

[0014] • performing shallow whole-genome sequencing on a second fraction of the sequencing libraries and quantifying total cell free DNA in the fraction; and

[0015] • preparing a profile of the biological sample comprising results from the methylation assay and the total cell free DNA quantification, and comparing the profile with a standard control profile for detecting presence or absence of cancer in the biological sample.

[0016] In some embodiments, the said method for detecting presence or absence of cancer in a biological sample comprises acts of: extracting DNA from a biological sample, such as urine; subjecting the extracted DNA to EM-sequence library preparation; subjecting one fraction of the library to at least one quantitative methylation assay; calculating methylation levels of three genes - GALR1, HAND2, and NRN1 in the said fraction; subjecting a second fraction of the library to shallow whole-genome sequencing; quantifying total cell free DNA in the second fraction; employing univariable and multivariable logistic regression analysis to combine the results from the methylation assay and the quantification of cell free DNA to prepare a profile of the biological sample; and comparing the prepared profile with a standard control profile for detecting presence or absence of cancer in the biological sample.

[0017] In some embodiments, the somatic copy number aberrations in the genome is determined by the quantification of the total cell free DNA in the biological sample.

[0018] In some embodiments, the method of the present disclosure provides sensitivity ranging from about 95% to 100% and specificity ranging from about 98% to 100%, upon performing targeted methylation of the said markers and somatic copy number aberration analysis of cell free DNA from a sample, including but not limited to urine. In some embodiments, when the method of the present disclosure detects presence of cancer, the method further comprises treating a subject with a corresponding anti-cancer therapy.

[0019] In some embodiments, the methylation levels of the combination of three markers - NRN1, GALR1 and HAND2, synergistically improve the accuracy, specificity, and / or sensitivity of detection of cancer, including but not limited to bladder cancer, compared to the accuracy, specificity, and / or sensitivity of detection provided by methylation levels of just one or two of the biomarkers from NRN1, GALR1 and HAND2. That is, the accuracy, specificity, and / or sensitivity of detection of cancer decreases if any one or two of the three markers are missing or replaced by other methylation markers.

[0020] BRIEF DESCRIPTION OF THE FIGURES

[0021] In order that the disclosure may be readily understood and put into practical effect, reference is made to exemplary embodiments as illustrated with reference to the accompanying figures. The figures together with detailed description below, are incorporated in and form part of the specification, and serve to further illustrate the embodiments and explain various principles and advantages, where:

[0022] FIGURE 1 depicts illustrative steps present in the method of the present disclosure for diagnosis of cancer.

[0023] FIGURE 2 illustrates plots describing methylation levels of markers (HAND2, GALR1 and NRN1) from standard quantitative methylation-specific PCR (qMSP) and the method of the present disclosure (iSECURE).

[0024] FIGURE 3 illustrates a plot describing tumor fraction analysis in a sample (of bladder cancer) and control.

[0025] FIGURE 4 illustrates plots describing somatic copy number aberrations in bladder cancer samples (A, B and C) and in control sample (D).

[0026] FIGURE 5 illustrates plots describing methylation levels of 19 candidate genes in a pilot series of urine collected from bladder cancer patients (n=14) and controls (n=14). FIGURE 6 illustrates a plot describing a diagnostic performance of GALR1 / HAND2 / NRN1 compared to existing marker panel GHSR / MAL for both low- and high-grade bladder tumors.

[0027] FIGURE 7 illustrates a plot describing a diagnostic performance of GALR1 / HAND2 / NRN1 compared to existing marker panel GHSR / MAL for low-grade bladder tumors.

[0028] DETAILED DESCRIPTION

[0029] Unless otherwise defined, all terms used in the disclosure, including technical and scientific terms, have meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. By means of further guidance, term definitions are included for better understanding of the present disclosure.

[0030] As used herein, the term “comprising” when placed before the recitation of steps in a method means that the method encompasses one or more steps that are additional to those expressly recited, and that the additional one or more steps may be performed before, between, and / or after the recited steps. For example, a method comprising steps a, b, and c encompasses a method of steps a, b, x, and c, a method of steps a, b, c, and x, as well as a method of steps x, a, b, and c. Furthermore, the term “comprising” when placed before the recitation of steps in a method does not (although it may) require sequential performance of the listed steps, unless the content clearly dictates otherwise. For example, a method comprising steps a, b, and c encompasses, for example, a method of performing steps in the order of steps a, c, and b, the order of steps c, b, and a, and the order of steps c, a, and b, etc.

[0031] With respect to the use of substantially any plural and / or singular terms herein, those having skill in the art can translate from the plural to the singular and / or from the singular to the plural as is appropriate to the context and / or application. The various singular / plural permutations may be expressly set forth herein for sake of clarity. The suffix “(s)” at the end of any term in the present disclosure envisages in scope both the singular and plural forms of said term.

[0032] As used in this specification and the appended claims, the singular forms “a,” “an” and “the” includes both singular and plural references unless the content clearly dictates otherwise. For example, the term “inserted at a position” as used herein in reference to a polypeptide sequence refers to insertion at one or more (such as one, two, three, etc.) amino acid positions in the polypeptide sequence. The use of the expression ‘at least’ or ‘at least one’ suggests the use of one or more elements or ingredients or quantities, as the use may be in the embodiment of the disclosure to achieve one or more of the desired objects or results. As such, the terms “a” (or “an”), “one or more”, and “at least one” can be used interchangeably herein.

[0033] Numerical ranges stated in the form ‘from x to y’ include the values mentioned and those values that lie within the range of the respective measurement accuracy as known to the skilled person. If several preferred numerical ranges are stated in this form, of course, all the ranges formed by a combination of the different end points are also included.

[0034] The terms “about” or “approximately” as used herein when referring to a measurable value such as a parameter, an amount, a temporal duration, and the like, are meant to encompass variations of and from the specified value, such as variations of + / -10% or less, + / -5% or less, + / -1% or less, and + / -0.1% or less of and from the specified value, insofar such variations are appropriate to perform in the disclosed invention. It is to be understood that the value to which the modifier “about” or “approximately” refers is itself also specifically, and preferably, disclosed.

[0035] As used herein, the terms “include” (any form of “include”, such as “include”), “have” (and “have”), “comprise” etc. any form of “having”, “including” (and any form of “including” such as “including”), “containing”, “comprising” or “comprises” are inclusive and will be understood to imply the inclusion of a stated element, integer or step, or group of elements, integers or steps, but not the exclusion of any other element, integer or step, or group of elements, integers or steps

[0036] As regards the embodiments characterized in this specification, it is intended that each embodiment be read independently as well as in combination with another embodiment. For example, in case of an embodiment 1 reciting 3 alternatives A, B and C, an embodiment 2 reciting 3 alternatives D, E and F and an embodiment 3 reciting 3 alternatives G, H and I, it is to be understood that the specification unambiguously discloses embodiments corresponding to combinations A, D, G; A, D, H; A, D, I; A, E, G; A, E, H; A, E, I; A, F, G; A, F, H; A, F, I;

[0037] B, D, G; B, D, H; B, D, I; B, E, G; B, E, H; B, E, I; B, F, G; B, F, H; B, F, I; C, D, G; C, D, H;

[0038] C, D, I; C, E, G; C, E, H; C, E, I; C, F, G; C, F, H; C, F, I, unless specifically mentioned otherwise. The term ‘exemplary’ or ‘exemplary embodiment’ as used herein refers to ‘serving as an example, instance, or illustration.’ Any embodiment of implementation of the present subject matter described herein as ‘exemplary’ is not necessarily to be construed as preferred or advantageous over other embodiments.

[0039] Reference throughout this specification to ‘some embodiments’, ‘one embodiment’ or ‘an embodiment’ means that a particular feature, structure or characteristic described in connection with the embodiment may be included in at least one embodiment of the present disclosure. Thus, the appearances of the phrases ‘in some embodiments’, ‘in one embodiment’ or ‘in an embodiment’ in various places throughout this specification may not necessarily all refer to the same embodiment. It is appreciated that certain features of the disclosure, which are for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the disclosure, which are, for brevity described in the context of a single embodiment, may also be provided separately or in any suitable sub-combination.

[0040] As used herein, the term ‘bladder cancer’ or ‘urinary bladder cancer’ refers to cancer or tumor arising from the tissues of the urinary bladder and includes non-muscle invasive bladder cancer (NMIBC) and muscle invasive bladder cancer (MIBC), urothelial carcinoma, squamous cell carcinoma and adenocarcinoma.

[0041] The present disclosure relates to a simple, time efficient, cost effective and an improved method for diagnosis of cancer, including but not limited to urinary bladder cancer.

[0042] In some embodiments, the method of the present disclosure describes a non-invasive detection / diagnosis of cancer, including but not limited to urinary bladder cancer. The method of the present disclosure enables diagnosis of cancer without relying on pre-existing knowledge of specific (epi)genetic changes. Accordingly, the present disclosure provides a method for detecting presence or absence of cancer including but not limited to urinary bladder cancer, in a biological sample, through a combined analysis of methylation status of a set of genes and somatic copy number aberrations in a genome. The inventors of the present disclosure have thus integrated methylation / hypermethylation analysis of cancer biomarkers / genes, and somatic copy number aberration based on tumor fraction, for detecting presence or absence of cancer in a biological sample.

[0043] In some embodiments of the present disclosure, the non-invasive method for detecting presence or absence of cancer in a biological sample, through a combined analysis of methylation status of a set of genes and somatic copy number aberrations in a genome, comprises acts of:

[0044] • purifying DNA from a biological sample and preparing corresponding sequencing libraries;

[0045] • performing at least one quantitative methylation assay on one fraction of the sequencing libraries and calculating the methylation levels of at least two predetermined genes;

[0046] • performing shallow whole-genome sequencing on a second fraction of the sequencing libraries and quantifying total cell free DNA in the fraction; and

[0047] • preparing a profile of the biological sample comprising results from the methylation assay and the total cell free DNA quantification, and comparing the profile with a standard control profile for detecting presence or absence of cancer in the biological sample.

[0048] In some embodiments of the present disclosure, the non-invasive method for detecting presence or absence of cancer in a biological sample, through a combined analysis of methylation status of a set of genes and somatic copy number aberrations in a genome, comprises acts of:

[0049] • purifying DNA from a biological sample and preparing corresponding sequencing libraries;

[0050] • performing at least one quantitative methylation assay on one fraction of the sequencing libraries and calculating the methylation levels of three genes - GALR1, HAND2, NRN1;

[0051] • performing shallow whole-genome sequencing on a second fraction of the sequencing libraries and quantifying total cell free DNA in the fraction; and

[0052] • preparing a profile of the biological sample comprising results from the methylation assay and the total cell free DNA quantification, and comparing the profile with a standard control profile for detecting presence or absence of cancer in the biological sample. In some embodiments, the method of the present disclosure begins by purifying the cell free DNA from a biological sample, and subjecting it to library preparation. While one fraction of the library or certain DNA sequences from the library are then subjected to at least one quantitative methylation assay, a second fraction of the library or leftover DNA sequences are simultaneosuly or sequentially subjected to whole-genome sequencing. The results of the methylation analysis, and whole genome sequencing that results in determination of somatic copy number aberration analysis are combined to detect cancer.

[0053] In some embodiments, the quantitative methylation assay and the shallow whole-genome sequencing on fractions of the sequencing libraries are performed in any order and sequence, and are performed simultaneously or one after the other. Thus, the present disclosure also envisages a method where the quantitative methylation assay on a second fraction follows the shallow whole-genome sequencing on a first fraction of the sequencing library.

[0054] In some embodiments, the library preparation is carried out by subjecting the purified DNA to enzyme based conversion, thereby producing high quality libraries that enable superior detection of methylation and hypermethylation from fewer sequencing reads.

[0055] In some embodiments, the method of the present disclosure results in cancer detection with improved sensitivity and specificity, as compared to detection through individual methylation or somatic copy number analysis.

[0056] In some embodiments, the cancer being detected through the method of the present disclosure is urinary bladder cancer or upper tract urothelial cancer.

[0057] In some embodiments, the cancer being detected through the method of the present disclosure is a primary urinary bladder cancer or a recurring urinary bladder cancer.

[0058] In some embodiments, the cancer being detected through the method of the present disclosure is non-muscle invasive urinary bladder cancer or muscle invasive urinary bladder cancer. Such a cancer may be either primary urinary bladder cancer or a recurring urinary bladder cancer. In some embodiments, the cancer being detected through the method of the present disclosure is a low-grade bladder cancer.

[0059] In some embodiments, the biological sample on which the method of the present disclosure is performed is selected from a group comprising urine, blood and soft tissue, or any combination thereof.

[0060] Thus, in some embodiments of the present disclosure, the non-invasive method for detecting presence or absence of urinary bladder cancer in a urine sample, through a combined analysis of methylation status of a set of genes and somatic copy number aberrations in a genome, comprises acts of:

[0061] • purifying DNA from urine and preparing corresponding sequencing libraries;

[0062] • performing at least one quantitative methylation assay on one fraction or certain DNA sequences of the sequencing libraries and calculating the methylation levels of at least two predetermined genes;

[0063] • performing shallow whole-genome sequencing on a second fraction or leftover sequences of the sequencing libraries and quantifying total cell free DNA in the fraction; and

[0064] • preparing a profile of the urine comprising results from the methylation assay and the total cell free DNA quantification, and comparing the profile with a standard control profile for detecting presence or absence of cancer in the urine.

[0065] In some embodiments, the predetermined genes that are checked for methylation are selected from a group comprising NRN 1 , GALR1 and HAND2. As the method of the present disclosure mandates calculating the methylation levels of at least two genes, the said genes could be any combination of NRN1, GALR1 and HAND2, including NRN1 and GALR1; GALR1 and HAND2; NRN1 and HAND2; or NRN1, GALR1 and HAND2. In some embodiments of the present disclosure, one or more of the genes within the gene combinations disclosed herein for calculation of methylation status, are either wild-type genes or mutated genes.

[0066] In some embodiments of the present disclosure, the non-invasive method for detecting presence or absence of urinary bladder cancer in a urine sample, through a combined analysis of methylation status of a set of genes and somatic copy number aberrations in a genome, comprises acts of: • purifying DNA from urine and preparing corresponding sequencing libraries;

[0067] • performing at least one quantitative methylation assay on one fraction or certain DNA sequences of the sequencing libraries and calculating the methylation levels of three genes - GALR1, HAND2, and NRN1;

[0068] • performing shallow whole-genome sequencing on a second fraction or leftover sequences of the sequencing libraries and quantifying total cell free DNA in the fraction; and

[0069] • preparing a profile of the urine comprising results from the methylation assay and the total cell free DNA quantification, and comparing the profile with a standard control profile for detecting presence or absence of cancer in the urine.

[0070] In some embodiments, the methylation assay employed on one fraction of the sequencing libraries or certain DNA sequences from the library is selected from a group comprising quantitative specific methylation polymerase (qSMP) chain reaction, CRISPR assay, high resolution melting assay, high performance liquid chromatography-ultraviolet (HPLC-UV), Liquid chromatography coupled with tandem mass spectrometry (LC-MS / MS), ELISA based assay, PCR based amplification fragment length polymorphism (AFLP) or restriction fragment length polymorphism (RFLP) and luminometric methylation assay (LUMA), or any combination thereof.

[0071] In some embodiments, the quantitative methylation assay employed in the present disclosure is a bi sulfite-free assay.

[0072] In some embodiments, the methylation assay employed on one fraction of the sequencing libraries or certain DNA sequences from the library is quantitative specific methylation polymerase (qSMP) chain reaction.

[0073] In some embodiments, the qSMP is performed by primers selected from a group of sequences set forth as sequence id. nos. 1 to 8, along with corresponding probes selected from a group of sequences set forth as sequence id nos. 9 to 12.

[0074] Thus, in some embodiments of the present disclosure, the non-invasive method for detecting presence or absence of cancer in a biological sample, such as a urine sample, through a combined analysis of methylation status of a set of genes and somatic copy number aberrations in a genome, comprises acts of:

[0075] • purifying DNA from a urine sample and preparing corresponding sequencing libraries;

[0076] • performing at least one quantitative methylation assay selected from a group comprising quantitative specific methylation polymerase (qSMP) chain reaction, CRISPR assay, high resolution melting assay, high performance liquid chromatography -ultraviolet (HPLC-UV), Liquid chromatography coupled with tandem mass spectrometry (LC-MS / MS), ELISA based assay, PCR based amplification fragment length polymorphism (AFLP) or restriction fragment length polymorphism (RFLP) and luminometric methylation assay (LUMA), or any combination thereof, on one fraction or certain DNA sequences of the sequencing libraries and calculating the methylation levels of three genes - NRN1, GALR1 and HAND2;

[0077] • performing shallow whole-genome sequencing on a second fraction or leftover sequences of the sequencing libraries and quantifying total cell free DNA in the fraction; and

[0078] • preparing a profile of the biological sample comprising results from the methylation assay and the total cell free DNA quantification, and comparing the profile with a standard control profile for detecting presence or absence of cancer in the biological sample.

[0079] In some embodiments of the present disclosure, the non-invasive method for detecting presence or absence of cancer in a urine sample, through a combined analysis of methylation status of a set of genes and somatic copy number aberrations in a genome, comprises acts of:

[0080] • purifying DNA from a urine sample and preparing corresponding sequencing libraries;

[0081] • performing quantitative specific methylation polymerase (qSMP) chain reaction, on one fraction or certain DNA sequences of the sequencing libraries and calculating the methylation levels of three genes - NRN1, GALR1 and HAND2;

[0082] • performing shallow whole-genome sequencing on a second fraction or leftover sequences of the sequencing libraries and quantifying total cell free DNA in the fraction; and • preparing a profile of the urine sample comprising results from the methylation assay and the total cell free DNA quantification, and comparing the profile with a standard control profile for detecting presence or absence of cancer in the urine sample.

[0083] The inventors of the present disclosure selected three specific biomarkers - NRN1, GALR1 and HAND2 - from 19 gene markers that were found to be hyper methylated in bladder cancer based on the sensitivity and specificity of 100% and AUC of 1 exhibited by these three markers (Table 7). Thus, the methylation levels of the combination of three markers, NRN1, GALR1 and HAND2, exhibit enhanced diagnostic accuracy of detecting cancer, including bladder cancer.

[0084] In some embodiments, the methylation levels of the combination of three markers - NRN1, GALR1 and HAND2, synergistically improve the accuracy, specificity, and / or sensitivity of detection of cancer, including but not limited to bladder cancer, compared to the accuracy, specificity, and / or sensitivity of detection provided by methylation levels of just one or two of the biomarkers from NRN1, GALR1 and HAND2. That is, the accuracy, specificity, and / or sensitivity of detection of cancer decreases if any one or two of the three markers are missing or replaced by other methylation markers.

[0085] In some embodiments, within the ambit of the present disclosure, the methylation levels are calculated relative to the reference gene ACTB using the comparative quantification cycle method.

[0086] In some embodiments, within the ambit of the present disclosure, the preparation of the profile of the biological sample such as a urine sample, comprising results from methylation analysis and total cell free DNA analysis is carried out through univariable and multivariable logistic regression analysis. For evaluating complementarity of SCNA and methylation, multivariable logistic regression with backward selection is preferably used. The predicted probabilities from the log2 -transformed Ct values may be utilized to construct receiver operating curves (ROC), incorporating the area under the curve (AUC). Optimal sensitivity and specificity can suitably be determined using the Youden's Index (J).

[0087] Through the method of the present disclosure and the combined analysis of methylation status of a set of genes and somatic copy number aberrations in a genome, the inventors of the present disclosure have enhanced diagnostic accuracy of detecting cancer, including but not limited to urinary bladder cancer, when compared to analysis of tumor fraction alone, without consideration of the methylation statuses of the biomarkers employed herein. As a result, the method of the present disclosure achieves sensitivity ranging from about 95% to 100%, including all values within the range, for instance, 95.1%, 95.2%, 95.3%, 95.4% and so on and so forth, up until 100%, and including subranges of the range 95% to 100%; and specificity ranging from about 98% to 100%, including all the values in the range, for instance 98.1%, 98.2%, 98.3%, 98.4% and so on and so forth, up until 100%, and including subranges of the range 98% to 100%.

[0088] In an exemplary embodiment, the method of the present disclosure has enhanced diagnostic accuracy in detecting urinary bladder cancer from a sample, including but not limited to urine with sensitivity of about 96% and specificity of about 100%, when compared to analysis of tumor fraction alone, without consideration of the methylation statuses of the biomarkers employed herein.

[0089] In some embodiments, methylation levels of three genes, GALR1, HAND2 and NRN1, in combination with somatic copy number aberrations provide accurate detection of all grades of bladder cancer.

[0090] In some embodiments, methylation levels of three genes, GALR1, HAND2 and NRN1, in combination with somatic copy number aberrations provide accurate detection of low-grade bladder cancers.

[0091] In some embodiments, methylation levels of GALR1, HAND2 and NRN1 provide a specificity of detection of bladder cancer ranging from about 88% to about 95%, upon analyzing cell free DNA from a sample, including but not limited to urine.

[0092] In some embodiments, methylation levels of GALR1, HAND2 andNRNl provide a sensitivity of detection of bladder cancer ranging from about 63% to about 75%, upon analyzing cell free DNA from a sample, including but not limited to urine. In some embodiments, methylation levels of GALR1, HAND2 andNRNl provide a sensitivity of detection of about 73%, compared to the sensitivity of about 64% provided by the methylation levels of existing markers GHSR / MAL for all grades of bladder cancer.

[0093] In some embodiments, methylation levels of GALR1, HAND2 and NRN1 provide an overall AUC of 0.86, compared to the AUC of 0.85 provided by the methylation levels of existing markers GHSR / MAL for detecting all grades of bladder cancer.

[0094] In some embodiments, methylation levels of GALR1, HAND2 andNRNl provide a sensitivity of about 64%, compared to the sensitivity of about 48% provided by the methylation levels of existing markers GHSR / MAL for detecting low-grade bladder cancer.

[0095] In some embodiments, methylation levels of GALR1, HAND2 and NRN1 provide an overall AUC of 0.80, compared to the AUC of 0.76 provided by the methylation levels of existing markers GHSR / MAL for detecting low-grade bladder cancer.

[0096] In some embodiments, in the method of the present disclosure, methylation levels of the genes, including but not limited to GALR1, HAND2 and NRN1 genes is analysed by quantitative methylation specific polymerase chain reactions (qMSP). Following are the illustrative primers and probes employed in the qMSP:

[0097]

[0098] Table 1 : Primer and probe sequences for methylation analysis of GALR1, HAND2, and NRN1 by qMSP.

[0099] In some embodiments, the method of the present disclosure can detect presence or absence of cancer, including but not limited to urinary bladder cancer from minute amounts of DNA in a biological sample. In an embodiment, the method of the present disclosure can provide improved detection of urinary bladder cancer from a sample having DNA amount as low as about 50 ng. In another embodiment, the method of the present disclosure can provide improved detection of urinary bladder cancer from a sample having DNA amount as low as about 10 ng.

[0100] In some embodiments, the method of the present disclosure can provide improved detection of cancer, including but not limited to urinary bladder cancer with a sensitivity ranging from about 95% to 100% and specificity ranging from about 98% to 100%, when compared to analysis of tumor fraction alone, without consideration of the methylation statuses of the genes employed herein, in a duration that is approximately 2 days lesser than carrying out methylation analysis and somatic copy number aberration analysis, separately.

[0101] In some embodiments, within the ambit of the present disclosure, the detection of urinary bladder cancer in urine cfDNA by combining somatic cell number aberration (SCNA) analysis with multi-gene methylation marker is termed as integrated SEquencing-based Copy number and methylation analysis in URinE, and abbreviated as iSECURE.

[0102] In some embodiments, Figure 1 of the present disclosure provides illustration of the steps involved in the method of the present disclosure for detection of cancer, including but not limited to urinary bladder cancer. According to the Figure 1, the method of the present disclosure comprises acts of- extracting cell free DNA from biological sample, such as urine; subjecting the extracted DNA to sequencing library preparation (for example - by EM- Seq library preparation); performing sequencing and copy number analysis of the DNA sequences from the prepared sequence library; and performing targeted methylation analysis of the markers including but not limited to GALR1, HAND2 and NRN1 genes on leftover EM-Seq libraries for assessing the methylation levels of said genes; and combining results of somatic copy number aberration analysis and results of targeted methylation analysis for diagnosis of cancer, such as bladder cancer. In an exemplary embodiment, the method of the present disclosure for detecting cancer, including but not limited to urinary bladder cancer in a biological sample suspected of having cancer comprises acts of - extraction of DNA from a biological sample, such as urine; subjecting the extracted DNA to EM-sequence library preparation; subjecting the DNA sequence(s) from the library to somatic copy number aberration analysis to assess the aberration from normal state of the DNA; performing targeted methylation analysis on left over sequences from the library by quantitative methylation-specific PCR (qMSP) of markers including but not limited to GALR1, HAND2 and NRN1 genes to determine methylation levels of said genes; and combining results of somatic copy number aberration analysis and targeted methylation analysis through univariable and multivariable logistic regression analysis for detecting the cancer, including but not limited to urinary bladder cancer.

[0103] The method of the present disclosure surprisingly reduces background methylation signals in control samples before amplifying the target regions of interest and thereby enhances test accuracy. Further, the concurrent methylation analysis of set of GALR1, HAND2 and NRN1 genes and somatic copy number aberration (SCNA) based on tumor fraction is able to provide enhanced diagnostic accuracy in detecting cancer, including but not limited to urinary bladder cancer with minute amounts of sample input, including but not limited to urine sample.

[0104] The subject matter of embodiments of the present disclosure is described here with specificity to meet statutory requirements, but this description is not necessarily intended to limit the scope of the disclosure. The disclosed subject matter may be embodied in other ways, may include different elements or steps, and may be used in conjunction with other existing or future technologies. This description should not be interpreted as implying any particular order or arrangement among or between various steps or elements except when the order of individual steps or arrangement of elements is explicitly described.

[0105] EXAMPLES

[0106] Materials and Methods: i. Study Population: A total of 24 primary bladder cancer patients were sex- and age-matched with 24 controls with microscopic or macroscopic hematuria. Urine samples were collected between 2018 and 2022 at Amsterdam University Medical Centers (location Vrije Universiteit) and at Onze Li eve Vrouwen Gasthuis (location East and West). Patients with microscopic or macroscopic hematuria suspected of primary bladder cancer on cystoscopy with presence of urothelial carcinoma confirmed by histology after transurethral resection of the bladder tumor (TURBT) were eligible for inclusion. Patients presenting with microscopic or macroscopic hematuria, no signs of urothelial carcinoma of the bladder on cystoscopy and no signs of urothelial carcinoma on ultrasound or CT scan, were employed for the control group. Patients were excluded if they had a history of another malignancy. Patient and tumor characteristics were obtained from the electronic patient file.

[0107] The study protocol was approved by the Medical Ethical Committee board of the Amsterdam UMC (2018.355 [16-10-2018], WO 18.155 [21-12-2018]). All participants were 18 years or older and signed informed consent for study participation prior to inclusion. Table 2 below describes patient and tumor characteristics as described above.

[0108] Table 2: Patient and tumor characteristics

[0109] 11. Sample collection and processing:

[0110] Urine samples were collected preoperatively and processed within about 24 hours to 72 hours as per the processing and storage protocol described in “Bosschi eter J, Bach S, Bijnsdorp IV, Segerink LI, Rurup WF, van Splunter AP, et al. A protocol for urine collection and storage prior to DNA methylation analysis. PLoS One. 2018;13(8):e0200906”. DNA isolated from the urine samples was preserved by addition of Ethylenediaminetetraacetic acid (EDTA) at a final concentration of about 40mM. Urine pellet and supernatant were obtained by centrifugation of about 15 mL urine at about 800xg for about 10 minutes and was stored at about -20 °C or about -80 °C.

[0111] Example 1: DNA methylation analysis by quantiative methylation-specific PCR

[0112] A QIAamp DNA Mini Kit (Qiagen GmbH, Hilden, Germany) was used for DNA isolation of urine pellet. DNA concentration was quantified using a NanoDrop 1000 (Thermo Fisher Scientific, Waltham, MA, US). Up to about 250 ng of purified DNA was treated with sodium bisulfite using the EZ DNA Methylation Kit (Zymo Research, Orange, CA, USA) to convert unmethylated cytosines. All procedures were carried out following manufacturers’ instructions.

[0113] Methylation levels of the GALR1, HAND2 and NRN1 genes were analyzed by quantitative methylation-specific polymerase chain reactions (qMSP) in bisulfite treated purified DNA from urine pellet. Primer and probe sequences employed for qMSP are as described above in Table 1.

[0114] Reaction conditions of multiplex qMSP assays included up to about 50 ng modified DNA, mixed with Epitect Multiplex PCR Mastermix (Qiagen, Venlo, Netherlands), about 2.5 pM to 5.0 pM of each primer, and about 5.0 pM to 10.0 pM of each Taqman probe in a total volume of about 12.5 pl. The qMSP assays were run using a ViiA7 real-time PCR-system (Applied Biosystems, Foster City, CA, USA) using QuantStudioTM Real-Time PCR Software (v 1.6.1). Synthetic gBlocks™ Gene Fragments (Integrated DNA Technologies) covering the target amplicons were included in each run as a positive control. H2O was included in each run as a negative control. Samples with an ACTB quantification cycle (Cq) exceeding 32 were excluded to guarantee sample quality and sufficient input. Promotor hypermethylation levels of target genes were calculated relative to the reference gene ACTB using the comparative Cq method: 2A-(Cq marker - Cq ACTB) x 100.

[0115] Table 3 below illustrates sensitivity and specificity derived from analysis of targeted methylation analysis of markers HAND2, GALR1 and NRN1.

[0116] Table 3

[0117] Example 2: Shallow whole-genome sequencing of urine cell-free DNA

[0118] DNA isolation from urine supernatant samples was performed using the Zymo Quick-DNA Urine Kit (Zymo Research). Purified DNA from urine supernatant samples of tumor cases and controls were analyzed by shallow whole-genome sequencing (~lx coverage) to assess somatic copy number aberrations (SCNA) and cell-free DNA fragmentation patterns. Total cfDNA was quantified using a Cell-free DNA ScreenTape assay (Agilent) using the Agilent 4200 TapeStation System (Agilent). Sequencing libraries were prepared using the NEBNext® Enzymatic Methyl-seq (EM-Seq) kit (NEB, Ipswich, MA, USA). EM-seq was executed following to manufacturers’ instructions for standard insert libraries with 14 PCR cycles. Before pooling, libraries were quantified, and quality checked using the DI 000 ScreenTape Analysis Assay (Agilent). Paired-end 150bp libraries were pooled in equimolar amounts and sequenced using NovaSeq6000 (Illumina) (GenomeScan, Leiden).

[0119] Sequencing resulted in a sufficient read count for all samples (median mapped paired read count of 28.8M). Tumor fraction (i.e., fraction of cfDNA derived from the tumor) was significantly higher in the urine of bladder cancer patients compared to controls (see Figure 3). Illustrative examples of aberrant and normal copy number profiles of sequenced urine samples of bladder cancer patients and controls are shown in figures 4A to 4D. The bladder cancer patients (A,B,C) exhibited an aberrant genome-wide copy number profile with gains (red) and losses (green), whereas no significant aberrations were found in the hematuria control (D). Univariable logistic regression was performed to calculate the AUC for the tumor fraction with a cutoff level of 5%, which yielded an AUC of 0.94 (95%CI 0.87-1.00) and corresponding sensitivity of 88% at specificity 100%. Table 4 below illustrates sensitivity and specificity derived SCNA analysis based on tumor fraction.

[0120] Table 4

[0121] Example 3: Combined analysis of DNA methylation and somatic copy number aberrations (iSECURE)

[0122] A method was performed by combining targeted methylation analysis and somatic copy number aberration analysis. To begin with, the combined analysis of DNA methylation and SCNA was streamlined by evaluating whether the methylation levels of GALR1, HAND2 and NRN1 can be determined from EM-Seq libraries. A total of about 1.5 pl EM-Seq library of each sample was used as input for multiplex qMSP. Methylation analyses were carried out according to the same procedure described in Example 1 above.

[0123] Univariable logistic regression was performed to calculate the AUCs and corresponding sensitivities / specifi cities for the individual methylation markers which resulted in a virtually equal performance of the markers using the standard qMSP and iSECURE method (Table 5). For individual markers HAND2 and GALR1, an AUC of 0.97 (95%CI 0.91-1.00) at 88% sensitivity and 100% specificity was achieved using iSECURE. NRN1 resulted in an AUC of 0.90 (95%CI 0.83-1.00) at 83% sensitivity and 100% specificity.

[0124] Standard qMSP iSECURE method

[0125] HAND2

[0126] AUC (95% CI) 0.91 (0.82-1.00) 0.97 (0.91-1.00)

[0127] Sensitivity (95% CI) 0.79 (0.63-0.92) 0.88 (0.75-1.00)

[0128] Specificity (95% CI) 0.95 (0.84-1.00) 1.00

[0129] GALR1

[0130] AUC (95% CI) 0.97 (0.93-1.00) 0.97 (0.94-1.00)

[0131] Sensitivity (95% CI) 0.96 (0.88-1.00) 0.88 (0.71-1.00)

[0132] Specificity (95% CI) 0.89 (0.74-1.00) 1.00

[0133] NRN1

[0134] AUC (95% CI) 0.96 (0.91-1.00) 0.90 (0.83-1.00)

[0135] Sensitivity (95% CI) 0.88 (0.75-1.00) 0.83 (0.67-0.96)

[0136] Specificity (95% CI) 0.95 (0.84-1.00) 1.00

[0137] Table 5

[0138] Sequencing data was processed using a pipeline controlled by Snakemake (v. 7.14.0). Briefly, trimming of sequencing adapters and indexes was carried out using bbduk.sh (v. 38.79) [https: / / sourceforge.net / projects / bbmap / ] in paired mode with parameters ‘ktrim=r k=23 mink=l 1 hdist=l ’ and the adapter reference dataset provided with the software. Enzymatically converted reads were mapped to the GRCh38 human genome assembly (GeneBank accession: GCA_000001405.28) using biscuit (v. 1.0.2.20220113) [https: / / huishenlab.github.io / biscuit / ]. Reads with a mapping quality lower than 5, unmapped reads, secondary mappings, chimeric and PCR duplicates were filtered using samtools (v. 1.12)

[0139] [https: / / github.com / samtools / samtools] and sambamba markdup (v. 0.8.1)

[0140] [http s : / / I omereiter . github . i o / samb amb a / ] .

[0141] Reads passing the filtering step were submitted for SCNA analysis and tumor fraction estimation using ichorCNA (v. 0.3.2.0) (17) Default settings were used, except the use of an in-house panel-of-normals from shallow whole-genome sequencing, setting the non-tumor fraction parameter restart values to c(0.95, 0.99, 0.995, 0.999). The tumor fraction exhibiting the highest log likelihood was reported.

[0142] Statistical analysis

[0143] Categorical data were described as frequencies and percentages, and continuous data with medians and interquartile range (IQR). Methylation levels were reported as log2 -transformed Cq ratios and presented in box plots. The Mann-Whitney U test was performed to compare methylation levels of bladder cancer patients and controls. The Wilcoxon test was used to compare methylation levels of standard qMSP and iSECURE between paired controls and bladder cancer samples.

[0144] Univariable logistic regression analysis was performed to assess the performance of each individual methylation marker for standard qMSP and iSECURE. For evaluating complementarity of SCNA and methylation, multivariable logistic regression with backward selection was used. The predicted probabilities from the log2 -transformed Cq values were utilized to construct receiver operating curves (ROC), incorporating the area under the curve (AUC). Optimal sensitivity and specificity was determined using the Youden's Index (J).

[0145] Data was analyzed using R (version 4.0.3 with packages: haven, tidyverse, tableone, ggplot2, ggpubr, pROC, MASS). P-values are two-sided and considered statistically significant when P<0.05.

[0146] Table 6 below demonstrates results of combined targeted methylation analysis and SCNA analysis according to the method of the present disclosure.

[0147] Methylation levels in controls were significantly lower using the iSECURE method for HAND2 (P=0.004) and GALR1 (P=0.049) and showed a trend towards significance for NRN 1 (P=0.050), thereby increasing specificity compared to the standard method for qMSP as described in Example 1 above (Figures 2A-C).

[0148] Table 6:

[0149] According to results of Table 6 and drawing comparisons with Tables 3 and 4, diagnostic accuracy was clearly enhanced by the present method where targeted methylation analysis of the genes was combined with SCNA based on tumor fraction. Particularly, this process resulted in determining methylation levels of an optimal gene panel of NRN1 / GALR1 / HAND2 and additionally determining aberration of tumor fraction at an AUC of 0.99 (95%CI 0.97-1.00), leading to a sensitivity of 96% and a specificity of 100%. However, a sensitivity of 92% was achieved when the sample was subjected to a process of targeted methylation analysis alone and a sensitivity of 88% was achieved when the sample was subjected to a process of somatic copy number aberration alone. Thus, present process significantly improves the diagnostic accuracy of detecting urinary bladder cancer.

[0150] Example 4: Rationale for Selection of individual methylation markers: GALR1 / HAND2 / NRN1

[0151] The performance of 19 methylation markers with high methylation levels in bladder cancer and other cancer types was evaluated to find a methylation marker combination with improved specificity, sensitivity, and / or accuracy for bladder cancer detection in urine. The following genes were included to select the most promising markers: CDO1, TAC1, SOX17, ASCL1, LHX8, ZNF582, C2CD4D, GALR1, NRN1, CDH13, HAND2, GHSR, SST, ZIC1, FAM19A4, PHACTR3, MAL, miR-129, and miR-935. Methylation status was verified for hypermethylation in bladder cancer using The Cancer Genome Atlas (TCGA) data. In this pilot series of 19 inhouse methylation markers, promoter hypermethylation of the genes GAI.R1. HAND2, and NRN1 was significantly increased in bladder cancer cases (n=14) compared to controls (n=14; <0.001) and showed a perfect diagnostic performance with an area under receiving operating characteristic curve (AUC) value of 1.00 (Figure 5 and Table 7). These findings led to the development of a multiplex qMSP assay, targeting GALR1, HAND2, and NRN1 together with the reference gene ACTB for normalization and quality control purposes.

[0152] Marker AUC 95%-CI (lower) 95%-CI (upper) Sensitivity Specificity

[0153] CDO1 0.96 0.90 0.96 0.86 1.00

[0154] TAC1 0.82 0.65 0.82 0.71 0.92

[0155] SOX17 0.94 0.82 1.00 0.93 1.00

[0156] ASCL1 0.81 0.62 0.81 0.71 1.00

[0157] LHX8 0.93 0.80 0.93 0.86 1.00

[0158] ZNF582 0.85 0.70 0.85 0.64 1.00

[0159] C2CD4D 0.66 0.44 0.66 0.36 1.00

[0160] GALR1 1.00 1.00 1.00 1.00 1.00

[0161] NRN1 1.00 1.00 1.00 1.00 1.00

[0162] CDH13 0.95 0.87 0.95 0.86 1.00

[0163] HAND2 1.00 1.00 1.00 1.00 1.00

[0164] GHSR 0.9952 0.982 1.00 1.00 0.93

[0165] SST 0.93 0.84 0.93 0.93 0.92

[0166] ZIC1 0.9929 0.9756 1.00 1.00 0.93

[0167] FAM19A4 0.82 0.66 0.82 0.57 1.00

[0168] PHACTR3 0.76 0.59 0.76 0.57 1.00

[0169] MAL 0.91 0.78 0.91 0.86 1.00 miR129 0.86 0.71 0.86 0.79 1.00 miR935 0.86 0.72 0.86 0.71 1.00

[0170] Table 7: Diagnostic performance of the 19 candidate genes (univariable logistic regression) for bladder cancer detection in urine. A total of 11 of the above-mentioned 19 in-house methylation markers have recently been extensively assessed in a larger training and validation series (Beijert 2024, Scientific Reports doi: 10.1038 / s41598-024-77781-0). The following genes were included in the Beijert study: CDO1, TAC1, 80X17, LHX8, ASCL1, ZNF582, NRN1, GALR1, C2CD4D, CDH13 and HAND2. By using a training (BC n=77, control n=69) and validation cohort (BC n=63, control n=71), GALR1, HAND2, and NRN1 were comprehensively selected from the 11 candidate markers. Methylation levels were significantly elevated in bladder cancer as compared to controls in both cohorts (P < 0.001). In this study, the combined marker set demonstrated an area under the curve (AUC) of 0.94 at 84% (95% CI: 76-92%) sensitivity and 96% (95% CI: 91-100%) specificity in the training cohort. The validation cohort yielded nearly equivalent accuracy (AUC 0.89, sensitivity 76% (95% CI: 65-86%), specificity 93% (95% CI: 86-99%).

[0171] Example 5: GALR1 / HAND2 / NRN1 outperforms existing marker panel GHSR / MAL in diagnostic accuracy

[0172] A head-to-head comparison of the new marker panel GALR1 / HAND2 / NRN1 was performed with existing marker panel and GHSR / MAL (Bosschieter et al. Epigenomics 2019 doi: 10.2217 / epi-2018-0094; Hentschel et al. Clin epigenetics 2022 doi: 10.1186 / sl3148-022- 01240-8.; Beijert et al. World J urology 2024; doi: 10.1007 / s00345-024-05287-5). For this, first, these marker panels including an independent set of both low- and high-grade bladder cancer were compared (Figure 6; Table 8). The new marker panel showed a higher overall AUC value when compared with GHSR / MAL (AUC 0.86 vs. 0.85) (Figure 6).

[0173] Cohort size Sensitivity Specificity

[0174] Marker panel

[0175] (LG+HG) (LG+HG)

[0176] BC (n=64) vs. control

[0177] GALR1 / HAND2 / NRN1 0.73 0.94

[0178] (n=62)

[0179] BC (n=64) vs. control

[0180] GHSR / MAL 0.64 0.98

[0181] (n=62)

[0182] BC = bladder cancer, HG = high-grade, LG = low-grade.

[0183] Table 8: Diagnostic performance of the marker panels (multivariable logistic regression) for the detection of bladder cancer (all grades).

[0184] Subsequently, the performance of the marker panel for the detection of low-grade bladder only was evaluated (Figure 7; Table 9). Here, the differences in diagnostic performance were more pronounced with the new marker panel GALR1 / HAND2 / NRN1 being most accurate for detecting low-grade bladder cancer when compared with GHSR / MAL (AUC 0.80 vs. 0.76; Figure 7). Cohort size Sensitivity

[0185] Marker panel Specificity (LG)

[0186] BC (n=25) vs. control

[0187] GALR1 / HAND2 / NRN1 0.64 0.89

[0188] (n=62)

[0189] BC (n=25 vs. control

[0190] GHSR / MAL 0.48 0.95

[0191] (n=62)

[0192] BC = bladder cancer, LG = low-grade.

[0193] Table 9: Diagnostic performance of the marker panels (multivariable logistic regression) for the detection of low-grade bladder cancer.

[0194] Statistical analysis performed in Examples 4 and 5

[0195] Methylation levels are expressed as square root-transformed Ct ratios and presented in boxplots. Methylation levels between controls and cases were compared using the nonparametric Mann-Whitney U test.

[0196] Individual marker performances were estimated by univariable logistic regression analysis as described previously (Beijert 2024, Scientific Reports doi: 10.1038 / s41598-024-77781-0). Briefly, AUC values were calculated using the predicted probabilities from the univariable logistic regression.

[0197] Marker panel performances were calculated by multivariable logistic regression analysis as described before (Beijert 2024, Scientific Reports). In short, AUC values were assessed using the predicted probabilities from the multivariable logistic regression. Sensitivities and specificities were based on the Youden's Index (J)-threshold. Diagnostic performances of marker panels for the detection of low-grade cancer were evaluated in a sub-analysis in which only low-grade were taken along in the multivariable regression analyses which were performed as described above. Reported p values were considered statistically significant at < 0.05. Statistical analyses were performed in RStudio (v4.4.2) using the compare Groups (v4.5.1), dplyr (1.0.2), ggplot2 (v3.3.5), and pROC (vl.18.0) packages.

[0198] Additional embodiments and features of the present disclosure will be apparent to one of ordinary skill in art based on the description provided herein. The embodiments herein provide various features and advantageous details thereof in the description. Descriptions of well- known / conventional methods and techniques are omitted so as to not unnecessarily obscure the embodiments herein.

[0199] The foregoing description fully reveals the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and / or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments in this disclosure have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein, without departing from the principles of the disclosure.

[0200] Any discussion of documents, acts, materials, devices, articles and the like that has been included in this specification is solely for the purpose of providing a context for the disclosure. It is not to be taken as an admission that any or all of these matters form a part of the prior art base or were common general knowledge in the field relevant to the disclosure as it existed anywhere before the priority date of this application.

Claims

CLAIMS1. A method for detecting presence or absence of cancer in a biological sample, through a combined analysis of methylation status of a set of genes and somatic copy number aberrations in a genome, said method comprising acts of:• purifying DNA from a biological sample and preparing corresponding sequencing libraries;• performing at least one quantitative methylation assay on one fraction of the sequencing libraries and calculating the methylation levels of three genes - GALR1, HAND2, and NRN1;• performing shallow whole-genome sequencing on a second fraction of the sequencing libraries and quantifying total cell free DNA in the fraction; and• preparing a profile of the biological sample comprising results from the methylation assay and the total cell free DNA quantification, and comparing the profile with a standard control profile for detecting presence or absence of cancer in the biological sample.

2. The method of claim 1, wherein the cancer is urinary bladder cancer or upper tract urothelial cancer.

3. The method of claim 2, wherein the urinary bladder cancer is a primary urinary bladder cancer or a recurring urinary bladder cancer; and wherein the cancer is nonmuscle invasive or muscle invasive bladder cancer.

4. The method of any one of claims 1 to 3, wherein the biological sample is selected from a group comprising urine, blood, liquid biopsies and soft tissue, or any combination thereof.

5. The method of any one of claims 1 to 4, wherein the somatic copy number aberrations in the genome is determined by the quantification of the total cell free DNA.

6. The method of any one of claims 1 to 5, wherein the methylation assay is selected from a group comprising quantitative specific methylation polymerase (qSMP) chain reaction, CRISPR assay, high resolution melting assay, high performance liquid chromatography -ultraviolet (HPLC-UV), Liquid chromatography coupled with tandem mass spectrometry (LC-MS / MS), ELISA based assay, PCR based amplification fragment length polymorphism (AFLP) or restriction fragment length polymorphism (RFLP) and luminometric methylation assay (LUMA), or any combination thereof.

7. The method of claim 6, wherein the qSMP is performed by primers selected from a group of sequences set forth as sequence id. nos. 1 to 8, along with corresponding probes set forth as sequence id nos. 9 to 12.

8. The method of any one of claims 1 to 7, wherein the quantitative methylation assay is a bi sulfite-free assay.

9. The method of any one of claims 1 to 8, wherein the preparation of the profile of the biological sample comprising results from methylation analysis and total cell free DNA analysis is carried out through univariable and multivariable logistic regression analysis.

10. The method of any one of claims 1 to 9, wherein the methylation levels are calculated relative to the reference gene ACTB using the comparative quantification cycle method.

11. The method of any one of claims 1 to 10, wherein quantity of the DNA purified from the biological sample is at least 10 ng.

12. The method of any one of claims 1 to 11, where when the method detects presence of cancer, the method further comprises treating a subject with a corresponding anticancer therapy.

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