The present invention relates to a sensitive quantitative real-time PCR method using specific DNA hypermethylation as biomarker for cancer detection, more specifically, for early detection, diagnosis, and monitoring the circulating tumor cells and tumor cell DNA in a patient blood sample.
A Sequence Listing, comprising 139 SEQ ID NOS, is submitted herewith in both .txt and .pdf formats, is part of the present application, and is incorporated herein by reference in its entirety.
Approximately 90% of cancer deaths are caused by the hematogenous spread and subsequent growth of tumors at distant organs; this process is termed “metastasis.” Emerging evidence indicates that the disseminating tumor cells present in the peripheral blood and bone marrow represent an early, rather than a late event in cancer development. These circulating tumor cells (CTCs) like “malignant seeds” are relevant to overt metastases and death [1, 2]. Clinically, the major obstacle to the cure of cancer is metastasis. If the tumors are detected before metastasis, the cure rate is near to 100%. Once metastasized, the tumor is usually incurable. Therefore, early detection and diagnosis of cancer before an overt metastasis has become a central issue for cure of cancer. On the other hand, most hematopoietic tumors are derived from bone marrow or lymphoid tissues and the leukemia and lymphoma cells naturally circulate in blood [3]. Early detection of CTC and leukemic and lymphoma cells and characterization of molecular signature of these tumor cells provide vital insight information for early diagnosis, early medical intervention, and thus save lives. An important molecular signature in cancer cells is aberrant DNA hypermethylation in functional genes. This epigenetic alteration is not only an early event in tumorigenesis, but a useful biomarker for cancer detection [4, 5].
Furthermore, during tumor progression, a small fraction of tumor cells constantly die by necrosis and/or apoptosis. Tumor cell DNA is released into blood or biofluids after lysis. These DNAs not only carry tumor genetic information (mutations), but also epigenetic alterations (DNA methylation). Aberrant DNA hypermethylation is the most common, often tumor-specific and detectable markers [6]. However, the levels of cell-free tumor DNA in blood are usually very low and the detection requires extremely sensitive and specific methods.
While morphology assessment was the golden-standard for the diagnosis of cancer, an integrated system of clinical features, imaging, endoscopy, biopsy, morphology, immunophenotype, genetic analysis has become the new standard of care in modern diagnostics of cancer. In recent years, additional cancer biomarkers such as proteins, DNA, mRNA, microRNA, either in a specific or a profiling assay, play important role in clinical diagnosis and patient management. This is especially important in early diagnosis, monitoring disease course and detecting minimal residual disease.
In the case of diagnosis of a hematopoietic malignancy, delineating cell lineage using various modalities is a starting point to categorize, classify and define a hematologic tumor [3]. Immunophenotyping by either flow cytometry or immunohistochemistry is used in routine diagnosis in the vast majority of hematopoietic malignancies [7].
Genetic abnormalities such as point mutations, copy number, amplification, expression levels, and chromosomal translocations detected by either molecular analysis or molecular cytogenetics [such as fluorescent in situ hybridization (FISH)] are increasingly utilized to define hematopoietic and other cancer cells [3, 7-9]. However, genetic analysis may not be a perfect method to detect malignancy. For instance, the chromosomal translocation t(14;18)(q32;q21), a hallmark for follicular lymphoma (FL), was detected in 75% of FL cases [10]. However, this translocation could be detected in up to 66% of healthy adults' peripheral blood with no evidence of FL when using a sensitive real-time PCR method [11]. Most importantly, not all cancers carry the uniform mutations. In fact, specific genetic mutations are detectable only in a small fraction of cancer patients that makes genetic detection difficulty and impractical [12].
Therefore, there is a need to provide a new and improved method/system for cancer detection.
In one aspect of the invention, a new and improved method for detecting cancer cells and monitoring circulating tumor cells (CTCs) and tumor cell DNA in a patient's blood (or other biofluids) sample is described. The method utilizes specific cancer DNA methylation as biomarker combined with a sensitive and quantitative real-time PCR detection. The inventive method comprises three steps: DNA extraction from patient specimens, DNA digestion with multiple selected methylation sensitive enzymes, and a TaqMan probe or SYBR Green florescence-based real-time PCR amplification with specific probe and/or primers. The patient samples may be whole blood, buffy coat, isolated mononuclear cells, plasma or serum, and other biofluids.
In another aspect of the invention, a total of 40 DNA methylation biomarkers identified by the present method are described. These markers are typically located in the CG rich promoter or the first exon region (CpG island or CGI) of a gene. These genes include HOXD10, COX2, KLF4, SLC26A4, DLC-1, PCDHGA12A, RPIB9, SOX2, CXCR4, HIN1, SFRP2, DAPK1, CD44, CDH1, PGRB, OLIG2, NOR1, SOCS1, RECK, MAFB, p15, HOXD11, HOXA11, HOXA6, HOXA7, HOXD9, HOXA9, HOXC4, PCDHA13, HIC1, CDH13, HOXA4, PCDHA6, PCDHB15, PTPN6, APC, GSTP1, ADAM12, p16, and GABRBA. The newly described DNA methylation loci may be employed as biomarkers to detect major types of human malignancies including hematopoietic tumors, solid tumors, and cutaneous tumor.
Particular aspects provide methods for the diagnosis, prognosis or detection of circulating cancer cells in a subject, comprising: contacting genomic DNA, obtained from a biological sample of a human subject and having at least one genomic DNA target sequence selected from the CpG island group consisting of HOXD10, COX2, KLF4, SLC26A4, DLC-1, PCDHGA12A, RPIB9, SOX2, CXCR4, HIN1, SFRP2, DAPK1, CD44, CDH1, PGRB, OLIG2, NOR1, SOCS1, RECK, MAFB, p15, HOXD11, HOXA11, HOXA6, HOXA7, HOXD9, HOXA9, HOXC4, PCDHA13, HIC1, CDH13, HOXA4, PCDHA6, PCDHB15, PTPN6, APC, GSTP1, ADAM12, p16, GABRBA, and portions thereof, with a plurality of different methylation-sensitive restriction enzymes each having at least one CpG methylation-sensitive cleavage site within the at least one genomic DNA target sequence, wherein the at least one target sequence is either cleaved or not cleaved by each of said plurality of different methylation-sensitive restriction enzymes; amplifying the contacted genomic DNA with at least one primer set defining at least one amplicon comprising the at least one target sequence, or the portion thereof, having the at least one CpG methylation-sensitive cleavage site for each of the plurality of different methylation-sensitive restriction enzymes to provide an amplificate; and determining, based on a presence or absence of, or on a pattern or property of the amplificate relative to that of a normal control, a methylation state of at least one CpG dinucleotide sequence of the at least one target nucleic acid sequence, wherein a method for the diagnosis, prognosis or detection of circulating cancer cells in the human subject is afforded.
In certain embodiment, amplification comprises at least one of standard, multiplex, nested and real-time formats.
In particular embodiments, the at least one target sequence comprises the RPIB9 gene CpG island, or a portion thereof. In certain aspects, the at least one target sequence additionally comprises at least one of the PCDHGA 12 gene CpG island, and portions thereof. In certain aspects, the at least one target sequence additionally comprises at least one of the DLC-1 gene CpG island, and portions thereof. Particular aspects comprise amplification of a plurality of target sequences within the DLC-1 gene CpG island. In certain embodiments, the at least one target sequence additionally comprises (e.g., in addition to RPIB9) the PCDHGA 12 and DLC-1 CpG islands, or portions thereof.
In certain aspects, said methylation sensitive enzyme comprises at least two selected from the group consisting of Acil, HpaII, HinP1I, BstUI, Hha I, and Tai I. Particular embodiments comprise digestion with Acil, HpaII, HinP1I, and BstUI.
In certain aspects, the at least one genomic DNA target sequence comprises at least 3, at least 4, at least 5, or at least 6 methylation-sensitive restriction sites.
In particular embodiments, the at least one genomic DNA target sequence comprises at least four different methylation-sensitive restriction sites, and contacting comprises contacting the at least one genomic DNA target sequence with a respective four different methylation-sensitive restriction enzymes.
In certain embodiments, the biological sample comprises at least one of whole blood, buffy coat, isolated mononuclear cells, isolated blood cells, plasma, serum, bone marrow, and other body fluids (e.g., stool, colonic effluent, urine, saliva, etc.).
In certain aspects, the cancer comprises at least one of hematopoietic tumors, solid tumors, and cutaneous tumors, acute lymphoblastic leukemia (ALL), minimal residual disease (MRD) in acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), lung cancer, breast cancer, ovarian cancer, prostate cancer, colon cancer, and melanoma.
Particular aspects comprise diagnosis or detection of at least one of acute lymphoblastic leukemia (ALL), minimal residual disease (MRD) in acute lymphoblastic leukemia (ALL), and acute myeloid leukemia (AML) in biofluids or tissue samples of either hematopoietic or solid tumors.
Particular aspects comprise diagnosis or detection of at least one of lung cancer, breast cancer, ovarian cancer, prostate cancer, colon cancer, and melanoma in biofluids or tissue samples comprising cancer cells.
In certain embodiments, the relative sensitivity in detecting cancer is one malignant cell or allele in one million normal cells or alleles (10−6).
In certain aspects, the relative sensitivity in detecting at least one of acute lymphoblastic leukemia (ALL), minimal residual disease (MRD), and acute myeloid leukemia (AML) is one malignant cell or allele in one million normal cells or alleles (10−6).
In certain aspects, the relative sensitivity in detecting at least one of lung cancer, breast cancer, ovarian cancer, prostate cancer, colon cancer, and melanoma is one malignant cell or allele in one million normal cells or alleles (10−6).
In particular embodiments, the biological sample is from a post-chemotherapy subject.
In particular embodiments, the cancer comprises acute lymphoblastic leukemia, and the at least on marker is selected from the group consisting of DLC-1, PCDHGA12A, CDH1, HOXD10, RPIB9, CD44, COX2, SOX2, KLF4, SLC26A, RECK, HOXA9, HOXD11, HOXA6, ADAM12, and HOXC4.
In particular embodiments, the cancer comprises chronic lymphocytic leukemia, and the at least on marker is selected from the group consisting of DLC-1, PCDHGA12A, HOXD10, CD44, COX2, HOXA9, HOXA4, HOXD11, and HOXA6.
In particular embodiments, the cancer comprises follicular lymphoma, and the at least on marker is selected from the group consisting of DLC-1, PCDHGA12A, CDH1, HOXD10, RPIB9, COX2, KLF4, HOXA9, HOXA6, HOXC4, and SLC26A4.
In particular embodiments, the cancer comprises mantle cell lymphoma, and the at least on marker is selected from the group consisting of DLC-1, PCDHGA12A, HOXD10, HOXA9, HOXD11, and HOXA6.
In particular embodiments, the cancer comprises Burkett lymphoma, and the at least on marker is selected from the group consisting of DLC-1, PCDHGA12A, CDH1, HOXD10, RPIB9, CD44, COX2, KLF4, HOXA9, HOXD11, HOXA6, HOXC4, and SLC26A4.
In particular embodiments, the cancer comprises diffuse large B-cell lymphoma, and the at least on marker is selected from the group consisting of DLC-1, PCDHGA12A, CDH1, HOXD10, RPIB9, COX2, KLF4, HOXA6, and SLC26A4.
In particular embodiments, the cancer comprises multiple myeloma, and the at least on marker is selected from the group consisting of DLC-1, PCDHGA12A, CDH1, COX2, KLF4, HOXA9, HOXD11, HOXA6, HOXC4, HOXD10, and SLC26A.
In particular embodiments, the cancer comprises acute myeloid leukemia, and the at least on marker is selected from the group consisting of PCDHGA12A, CDH1, HOXD10, CD44, CXCR1, KLF4, SLC26A, CDH13, HOXA9, HOXD11, HOXA6, HOXC4, ADAM12, and SLC26A4.
In particular embodiments, the cancer comprises myelodysplastic syndrome, and the at least on marker is selected from the group consisting of PCDHGA12A, SOCS-1, and HIN1.
In particular embodiments, the cancer comprises breast cancer, and the at least on marker is selected from the group consisting of DLC-1, PCDHGA12A, HOXD10, RPIB9, COX2, RECK, HOXA11, HOXA7, HOXA9, HOXD9, HOXD11, PCDHB15, PCDHA6, PCDHA13, PTPN6, HIC1, CDH13, GSTP1, ADAM12, p16, GABRBA, and APC.
In particular embodiments, the cancer comprises lung cancer, and the at least on marker is selected from the group consisting of PCDHGA12A, HOXD10, HOXA7, HOXA6, HOXA9, PCDHB15, PCDHA6, PCDHA13, PTPN6, GSTP1, and HIC1.
In particular embodiments, the cancer comprises colon cancer, and the at least on marker is selected from the group consisting of DLC-1, PCDHGA12A, HOXD10, RPIB9, CD44, COX2, SOX2, CXCR1, SLC26A, RECK, HOXA7, HOXA6, HOXA9, PCDHB15, PCDHA6, PCDHA13, PTPN6, ADAM12, p16, and HIC1.
In particular embodiments, the cancer comprises ovarian cancer, and the at least on marker is selected from the group consisting of PCDHGA12A, HOXD10, SLC26A, CDH13, and RECK.
In particular embodiments, the cancer comprises prostate cancer, and the at least on marker is selected from the group consisting of PCDHGA12A, HOXD10, COX2, HOXA7, HOXA6, HOXA9, HOXD11, HOXD9, PCDHB15, PCDHA6, PTPN6, HIC1, APC, CDH13, CDH5, HOXA11, GSTP1, p16, GABRBA, and HOXA7.
In particular embodiments, the cancer comprises melanoma, and the at least on marker is selected from the group consisting of PCDHGA12A, HOXD10, KLF4, and COX2.
According to certain embodiments, disclosed herein are methods useful for detection of the circulating tumor cells (CTCs) and tumor cell DNA utilizing the tumor-specific hypermethylation loci as biomarkers with either a TaqMan probe or SYBR Green flourescence-based real-time PCR technology. The present disclosure is developed upon the Applicants' detection methodology described in United States Patent Application Publication Number 2010/0248228, which is incorporated by reference in its entirety. According to the Applicants' prior application, the cancer cell detection method based on abnormal CpG hypermethylation may contain three sequential steps: 1) DNA isolation and extraction, 2) DNA digestion with pre-selected methylation sensitive enzymes, and 3) PCR process with specific primers. The present disclosure describes a method utilizing the real-time PCR process and identifies additional tumor-specific methylatation biomarkers. The prior detection method detects DNA methylation without the conventional bisulfite treatment using multiple pre-selected methylation sensitive restriction enzymes in clinical setting, Multiple Methylation Sensitive Enzyme Restriction PCR (MSR-PCR), whereas the present invention employing real-time PCR technology with expanded biomarkers is Taqman probe-based real-time PCR (qtMSR-PCR) and SYBR Green flourescence-based real-time PCR (qsMSR-PCR). Since the platform is a real-time PCR, the method is quantitative in nature.
A total of 118 human genomic loci have been examined. Forty cancer specific DNA hypermethylation loci have been identified by the present disclosed method, either in MSR-PCR or qMSR-PCR or both formats. These markers include the genes of HOXD10, COX2, KLF4, SLC26A4, DLC-1, PCDHGA12A, RPIB9, SOX2, CXCR4, HIN1, SFRP2, DAPK1, CD44, CDH1, PGRB, OLIG2, NOR1, SOCS1, RECK, MAFB, p15, HOXD11, HOXA11, HOXA6, HOXA7, HOXD9, HOXA9, HOXC4, PCDHA13, HIC1, CDH13, HOXA4, PCDHA6, PCDHB15, PTPN6, APC, GSTP1, ADAM12, p16, and GABRBA. Each DNA methylation locus is found to be positive in at least one or more cancer types of cell lines and/or patient samples. The cancer cell lines used in this study include B-cell acute lymphoblastic leukemia (NALM-6, MN-60, SD1, CALL3), T-cell acute lymphoblastic leukemia (Jurkat); chronic lymphocytic leukemia (Mec 1, Mec 2, Wac-3), follicular lymphoma (RL and SC-1); mantle cell lymphoma (Granta); Burkitt lymphoma (Daudi and Raji), diffuse large B-cell lymphoma (DB); acute myeloid leukemia (KG-1, KG-1a, and Kasumi-1), breast cancer (MCF7, T-47D, HTB-26D), lung cancer (NC1-H69, NCI-H1395), colon cancer (HT-29), ovarian cancer (OVCA433 and DOV13), prostate cancer (PC-3, LNCaP), and melanoma (SK-MEL-1). Some of these cell lines are listed in Table 1.
Biomarker HOXD10 can be used in detection of several hematopoietic tumors, such as B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia, chronic lymphocytic leukemia, follicular lymphoma; mantle cell lymphoma; Burkitt lymphoma, diffuse large B-cell lymphoma, acute myeloid leukemia. It can also be used in detection of several carcinoma, such as breast cancer, lung cancer, colon cancer, ovarian cancer, prostate cancer. In addition, it can be used in detection of melanoma.
Biomarker COX 2 can be used in detection of several hematopoietic tumors, such as B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia, chronic lymphocytic leukemia, follicular lymphoma, Burkitt lymphoma, diffuse large B-cell lymphoma, and multiple myeloma. It can also be used in detection of several carcinoma, such as breast cancer and prostate cancer. In addition, it can be used in detection of melanoma.
Biomarker KLF4 can be used in detection of several hematopoietic tumors, such as B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia, multiple myeloma, acute myeloid leukemia, Diffuse large B-cell lymphoma, and Burkitt lymphoma. It can also be used in detection of carcinoma, such as ovarian cancer.
Biomarker SLC26A4 can be used in detection of several hematopoietic tumors, such as B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia, chronic lymphocytic leukemia, follicular lymphoma, mantle cell lymphoma, Burkitt lymphoma, diffuse large B-cell lymphoma, multiple myeloma, and acute myeloid leukemia. It can also be used in detection of several carcinoma, such as colon cancer and ovarian cancer.
Biomarker DLC-1 can be used in detection of several hematopoietic tumors, such as B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia, chronic lymphocytic leukemia, follicular lymphoma, mantle cell lymphoma, Burkett lymphoma, diffuse large B-cell lymphoma, and multiple myeloma. It can also be used in detection of carcinoma, such as colon cancer.
Biomarker PCDHGA12A can be used in detection of several hematopoietic tumors, such as B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia, chronic lymphocytic leukemia, follicular lymphoma; mantle cell lymphoma, Burkitt lymphoma, diffuse large B-cell lymphoma, multiple myeloma, acute myeloid leukemia, and myelodysplastic syndrome. It can also be used in detection of carcinoma, such as breast cancer, lung cancer, colon cancer, ovarian cancer, and prostate cancer. In addition, it can be used in detection of melanoma.
Biomarker RPIB9 can be used in detection of several hematopoietic tumors, such as B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia, follicular lymphoma, Burkitt lymphoma, diffuse large B-cell lymphoma, and multiple myeloma. It can also be used in detection of carcinoma, such as colon cancer.
Biomarker SOX2 can be used in detection of several hematopoietic tumors, such as B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia, diffuse large B-cell lymphoma, and Burkitt lymphoma. It can also be used in detection of carcinoma, such as colon cancer.
Biomarker CXCR4 can be used in detection of acute myeloid leukemia and colon cancer.
Biomaker HIN1 can be used in detection of B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia, multiple myeloma, acute myeloid leukemia, diffuse large B-cell lymphoma, Burkitt lymphoma, and multiple myeloma.
Biomarker SFRP2 can be used in detection of B-cell acute lymphoblastic leukemia, acute myeloid leukemia, and multiple myeloma.
Biomarker DAPK1 can be used in detection of B-cell acute lymphoblastic leukemia, acute myeloid leukemia, and multiple myeloma.
Biomarker CD44 can be used in detection of B-cell acute lymphoblastic leukemia, chronic lymphocytic leukemia, Burkitt lymphoma, and diffuse large B-cell lymphoma.
Biomarker CDH1 can be used in detection of B-cell acute lymphoblastic leukemia, acute myeloid leukemia, and Burkitt lymphoma.
Biomarker PGRB can be used in detection of B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia, acute myeloid leukemia, and multiple myeloma.
Biomarker OLIG2 can be used in detection of B-cell acute lymphoblastic leukemia and acute myeloid leukemia.
Biomarker NOR1 can be used in detection of B-cell acute lymphoblastic leukemia and acute myeloid leukemia.
Biomarker SOCS1 can be used in detection of B-cell acute lymphoblastic leukemia, acute myeloid leukemia and myelodysplastic syndrome.
Biomarker RECK can be used in detection of colon cancer.
Biomarker MAFB can be used in detection of B-cell acute lymphoblastic leukemia.
Biomaker p15 can be used in detection of acute myeloid leukemia.
Biomarker HOXD11 can be used in detection of acute lymphoblastic leukemia, chronic lymphocytic leukemia, mantle cell lymphoma, Burkett lymphoma, multiple myeloma, acute myeloid leukemia. It can also be used in detection of carcinoma, such as breast cancer, and prostate cancer.
Biomarker HOXA11 can be used in detection of carsinoma such as breast cancer and prostate cancer.
Biomarker HOXA6 can be used in detection of acute lymphoblastic leukemia, chronic lymphocytic leukemia, follicular lymphoma, mantle cell lymphoma, Burkett lymphoma, diffuse large B-cell lymphoma, multiple myeloma, and acute myeloid leukemia. It can also be used in detection of carcinoma, such as lung cancer, colon cancer, and prostate cancer.
Biomarker HOXA7 can be used in detection of carcinoma, such as breast cancer, lung cancer, colon cancer, and prostate cancer.
Biomarker HOXD9 can also be used in detection of carcinoma, such as breast cancer and prostate cancer.
Biomarker HOXA9 can be used in detection of acute lymphoblastic leukemia, chronic lymphocytic leukemia, follicular lymphoma, Burkett lymphoma, and multiple myeloma. It can also be used in detection of carcinoma, such as breast cancer, and lung cancer.
Biomarker HOXC4 can be used in detection of acute lymphoblastic leukemia, follicular lymphoma, Burkett lymphoma, multiple myeloma, and acute myeloid leukemia.
Biomarker PCDHA13 can be used in detection of carcinoma, such as breast cancer, lung cancer, and colon cancer.
Biomarker HIC1 can be used in detection of carcinoma, such as breast cancer, lung cancer, colon cancer, and prostate cancer.
Biomarker CDH13 can be used in detection of acute myeloid leukemia as well as carcinoma, such as breast cancer, ovarian cancer, and prostate cancer.
Biomarker HOXA4 can be used in detection of chronic lymphocytic leukemia.
Biomarker PCDHA6 can be used in detection of carcinoma, such as breast cancer, lung cancer, colon cancer, and prostate cancer.
Biomarker PCDHB15 can be used in detection of carcinoma, such as breast cancer, lung cancer, colon cancer, and prostate cancer.
Biomarker PTPN6 can be used in detection of carcinoma, such as breast cancer, lung cancer, colon cancer, and prostate cancer.
Biomarker APC can be used in detection of carcinoma, such as breast cancer and prostate cancer.
Biomarker GSTP1 can be used in detection of carcinoma, such as breast cancer, lung cancer, and prostate cancer.
Biomarker ADAM12 can be used in detection of breast cancer, colon cancer, acute lymphoblastic leukemia, and acute myeloid leukemia.
Biomarker p16 can be used in detection of prostate cancer, breast cancer, and colon cancer.
Biomarker GABRBA can be used in detection of prostate cancer and breast cancer.
The above mentioned and additional DNA methylation biomarkers can also be categorized by the types of tumors. For example, biomarkers to detect hematopoietic tumors can include: For acute lymphoblastic leukemia, DLC-1, PCDHGA12A, CDH1, HOXD10, RPIB9, CD44, COX2, SOX2, KLF4, SLC26A, RECK, HOXA9, HOXD11, HOXA6, ADAM12, and HOXC4; for chronic lymphocytic leukemia, DLC-1, PCDHGA12A, HOXD10, CD44, COX2, HOXA9, HOXA4, HOXD11, and HOXA6; for follicular lymphoma, DLC-1, PCDHGA12A, CDH1, HOXD10, RPIB9, COX2, KLF4, HOXA9, HOXA6, HOXC4, and SLC26A4; for mantle cell lymphoma, DLC-1, PCDHGA12A, HOXD10, HOXA9, HOXD11, and HOXA6; for Burkett lymphoma, DLC-1, PCDHGA12A, CDH1, HOXD10, RPIB9, CD44, COX2, KLF4, HOXA9, HOXD11, HOXA6, HOXC4, and SLC26A4; for diffuse large B-cell lymphoma, DLC-1, PCDHGA12A, CDH1, HOXD10, RPIB9, COX2, KLF4, HOXA6, and SLC26A4; for multiple myeloma, DLC-1, PCDHGA12A, CDH1, COX2, KLF4, HOXA9, HOXD11, HOXA6, HOXC4, HOXD10, and SLC26A; for acute myeloid leukemia, PCDHGA12A, CDH1, HOXD10, CD44, CXCR1, KLF4, SLC26A, CDH13, HOXA9, HOXD11, HOXA6, HOXC4, ADAM12, and SLC26A4; and for myelodysplastic syndrome, PCDHGA12A, SOCS-1, and HIN1.
The biomarkers for detection of carcinoma can include: For breast cancer, DLC-1, PCDHGA12A, HOXD10, RPIB9, COX2, RECK, HOXA11, HOXA7, HOXA9, HOXD9, HOXD11, PCDHB15, PCDHA6, PCDHA13, PTPN6, HIC1, CDH13, GSTP1, ADAM12, p16, GABRBA, and APC; for lung cancer, PCDHGA12A, HOXD10, HOXA7, HOXA6, HOXA9, PCDHB15, PCDHA6, PCDHA13, PTPN6, GSTP1, and HIC1; for colon cancer, DLC-1, PCDHGA12A, HOXD10, RPIB9, CD44, COX2, SOX2, CXCR1, SLC26A, RECK, HOXA7, HOXA6, HOXA9, PCDHB15, PCDHA6, PCDHA13, PTPN6, ADAM12, p16, and HIC1; for ovarian cancer, PCDHGA12A, HOXD10, SLC26A, CDH13, and RECK; and for prostate cancer, PCDHGA12A, HOXD10, COX2, HOXA7, HOXA6, HOXA9, HOXD11, HOXD9, PCDHB15, PCDHA6, PTPN6, HIC1, APC, CDH13, CDH5, HOXA11, GSTP1, p16, GABRBA, and HOXA7.
The biomarkers for detection of melanoma can include PCDHGA12A, HOXD10, KLF4, and COX2.
The invention further provides several exemplary procedures employing the inventive method in either conventional PCR, TaqMan probe-based real-time PCR, or SYBR Green flourescence-based real-time PCR with 3 biomarkers, DLC-1, PCDHGA12, and RPIB9 selected from the tumor-specific CGI methylation loci to detect B-cell neoplasms in a variety of B-cell lines and B lymphoblastic leukemia (B-ALL) patient blood or bone marrow specimens (
Materials and Methods
Tumor Cell Lines and Cell Line DNAs. Table 1 lists the hematopoietic tumor cell lines used in the present study. These cell lines represent a spectrum of major types of B-cell neoplasms including acute lymphoblastic leukemia, mature B-cell neoplasms, and plasma cell myeloma. All cell lines were maintained in RPMI 1640 medium supplemented with 10% FCS and 100 μg/ml of penicillin/streptomycin at standard cell culture conditions. Cells in the exponential growth phase were harvested for DNA extraction or kept at −80° C. until DNA extraction. Solid tumor cell line DNAs, including breast cancer (MCF-7, T-47D, HTB-26D), lung cancer (NC1-H69, NC1-H1395), prostate cancer (PC-3, LNCaP), colon cancer (HT-29), and melanoma (SK-MEL-1), were purchased from ATCC (Manassas, Va., USA). Ovarian cancer (OVCA433, DOV13) cell line pellets were the gift from Dr. Sharon Stack, Department of Pathology and Anatomical Sciences, the University of Missouri School of Medicine, Columbia, Mo.
Patient Samples and DNA Extraction. Bone marrow aspirates and peripheral blood samples were obtained from leukemia or other cancer patients at initial diagnosis as well as at follow-up visits at the Children's Hospital and Ellis Fischel Cancer Center of University of Missouri Health Care (Columbia, Mo.), the University of California at Irvine Medical Center (Irvine, Calif.) and the University of Texas Southwestern Medical Center (Dallas, Tex.) in compliance with the local Institutional Review Board (IRB) requirements. The mononuclear cell fraction from bone marrow aspirates was isolated with Ficoll-Paque Plus medium (GE Healthcare Bio-Sciences Co., Piscataway, N.J.) by gradient centrifugation and stored in liquid nitrogen until use. Peripheral blood samples in EDTA additive tubes were stored at −20° C. until use. Additionally, some bone marrow and blood smears from archived unstained slides were scraped to retrieve cells. Genomic DNA was extracted from 20 cell lines and a total of 209 clinical specimens (60 bone marrows and 149 peripheral blood samples) from 60 B-ALL patients, 105 other cancer patients and 25 healthy volunteers or non-cancer patients. Table 2 summarizes a series of 31 B-ALL clinical cases of bone marrow aspirates at initial diagnosis. Genomic DNA was isolated using the QIAamp DNA Blood mini kit (Qiagen, Valencia, Calif.). DNA concentration and purity were determined by a NanoDrop 1000 spectrophotometer (Thermo Scientific, Wilmington, Del.). Normal male and female genomic DNAs from pooled human peripheral blood were purchased from Promega (Madison, Wis.).
Multiple Methylation Sensitive Enzyme Restriction PCR (MSR-PCR), Quantitative Real-time Methylation Specific PCR (qMSP), Quantitative TaqMan Probe-based Real-time MSR-PCR (qtMSR-PCR), and Quantitative SYBR Green fluorescence-based Real-time MSR-PCR (qsMSR-PCR). MSR-PCR comprises three sequential steps: DNA extraction, DNA digestion and PCR (
In the nested PCR, the digested DNA was first amplified with DLC-1 primers FF/BR yielding a 383 base pair (bp) product. Then, an internal DLC-1 primer set AF/AR (160 bp) was used to amplify an aliquot of the first PCR product in the second round of PCR (
For qMSP, genomic DNA was treated with sodium bisulfite (EZ DNA methylation kit; Zymo Research, Orange, Calif.) and the real-time PCR was carried out in ABsolute QPCR mix (ABgene, Rochester, N.Y.) in a SmartCycler System (Cepheid, Sunnyvale, Calif.) as previously described [13, 14]. The sequences of primers (DLC-1Q) and probe (DLC-1Q Probe) are listed in Table 3. A positive result was defined when the ratio of DLC-1 to fl-actin signal is greater than 400. The results from MSR-PCR and qMSP were later compared on the same DNA samples in
For TaqMan probe-based qtMSR-PCR, the digested and undigested normal (digestion control) and B-ALL patient DNA samples were amplified at an iQ5 Real-time PCR detection system (BIO-RAD, Hercules, Calif.). In a typical qMSR-PCR, 20 ng of digested DNA, DLC-1Q1 primers (0.25 μM), DLC-1 TaqMan probe (0.5 μM) (IDT, Coralville, Iowa) were mixed with 2×iQ Supermix (BIO-RAD, Hercules, Calif.) in a final volume of 20 μl. The PCR program includes 3 min of denaturation at 95° C. followed by 50 cycles at 95° C. for 15 s and 60° C. for 60 s. To generate the standard curve, nearly whole CpG island of DLC-1 gene was amplified using DLC-1w primers in GoTaq Polymerase 2× green master mix (Promega, Madison, Wis.). The PCR fragment was then purified with DNA Clean and Concentrator −5 (Zymo Research, Orange, Calif.), quantified with NanoDrop 1000 spectrophotometer and used as template. The template was diluted from 108 copies to 1 copy per reaction at a dilution factor of 10. The standard curve was constructed with linear regression by build-in software of iQ5 (
Similarly, for SYBR-green-based qsMSR-PCR, the digested DNA samples were amplified at an iQ5 Real-time PCR detection system (BIO-RAD, Hercules, Calif.). In a typical qMSR-PCR, 10 ng of digested DNA, DLC-1Q1 primers (0.25 μM each), were mixed with 10 ul of 2×SYBR Green/Fluorescein qPCR Master Mix (SABioscience, Frederick, Md.) in a final volume of 20 μl. A 2 step PCR program includes 10 min of denaturation at 95° C. (HotStart) followed by 50 cycles at 95° C. for 15 s and 64° C. for 60 s. After completion of PCR amplification, a melting curve program including 95° C. for 1 min, 64° C. for 2 min, and 64° C. to 95° C. at 2° C./min to generate melting curve (
The relative methylation level of each sample can be calculated by the delta (delta Ct) method. The same amount of M. Sss I-treated normal male human DNA was amplified as positive control and the promoter of β-actin (ACTB), without the cut site of these four enzymes in the amplified region, serve as endogenous control. After PCR reaction, the mean Ct value for the ACTB gene was subtracted from the mean Ct value of DLC-1 for each sample, using the following formula:
DLC-1ΔCt=(mean DLC-1 Ct−mean ACTB Ct)
DLC-1ΔΔCt=DLC-1ΔCt_sample—DLC-1ΔCt_Positive control
The DLC-1 relative methylation level (2−DLC-1ΔΔCt×100%) was calculated for each detected sample besides the negative controls.
Results
1. Distinct DNA Methylation Patterns between Leukemic Cells and Normal Blood Cells. First, the patterns of genomic DNA methylation of acute lymphoblastic leukemia cell lines with those of normal blood samples after digestion with methylation sensitive enzymes were compared. As shown in
2. DCL-1, a Candidate Gene for Methylation Analysis. The genomic structure of the DLC-1 CGI, an 824 bp DNA segment encompassing the promoter region, exon 1, and part of the first intron of the gene is shown in
3. Sensitivity of MSR-PCR. Analytic sensitivity can be divided into absolute and relative sensitivity [15]. Absolute sensitivity refers to the capability of detecting a minimal quantity of methylated target DNA in tumor cells. Relative sensitivity refers to the capability of detecting the smallest fraction of methylated tumor cell DNA in the presence of an excess amount of unmethylated normal cell DNA. The analytic sensitivity of MSR-PCR is shown in
4. Validation of MSR-PCR on B-cell Neoplastic Cell Lines and B-ALL Patients. After having established a sensitive detection method using a B-ALL cell line, a total of 18 leukemia cell lines (Table 1) and B-ALL patient samples is tested with two additional markers, PCDHGA12 and RPIB9 (
Subsequently, clinical bone marrow aspirates from 31 B-ALL patients at initial diagnosis were examined with MSR-PCR for DLC-1 methylation. The methylation was detected in 61% (19/31) of B-ALL patients (Table 2, data not shown). CGI methylation of DLC-1, PCDHGA12 and RPIB9 was then examined in an additional 29 B-ALL bone marrow aspirates with a multiplex MSR-PCR showing a positive rate of 55% (16/29), 62% (18/29), and 31% (9/29), respectively. Taking three genes together, methylation was detected at least in one gene in 83% (24/29) of this series (
Next, it was further examined as to whether the method may detect leukemia cells in peripheral blood samples of B-ALL patients. DLC-1 methylation was detected in 54% (15/28) of the cases (lanes B1-B28), but neither in 4 normal blood samples (lanes NB1-NB4) nor in pooled normal blood DNA (lane C2) (
In order to develop a more sensitive and quantitative real-time PCR method (qMSR-PCR), a 763 bp fragment encompassing nearly whole region of CpG island of DLC-1 gene was amplified by PCR using DLC-1w primers. The standard curve showed an adequate linearity from 10 to 108 copies per reaction (
5. Potential Use of MSR-PCR as a Tool in Monitoring B-ALL Patients. Next, it is to decide whether this method may be used to monitor the clinical course of B-ALL patients in both bone marrow and blood samples from the same patients. Bone marrow aspirates and peripheral blood samples including scraped cells from archived unstained slides (Ms) collected at different time points from 4 B-ALL patients were used. The MSR-PCR gel image along with the corresponding qMSP results is shown (
6. Use of MSR-PCR as a Tool to Determine Hypermethylation State of Certain Marker Loci in Specific Cell Lines. Shown in Tables 4 and 5 are the results from Applicants' examination of the use of MSR-PCR to determine the hypermethylation state of marker loci in cancer cell lines. For Table 4, DNA was obtained from lung cancer cell lines (H69 and H1395), breast cancer cell lines (MCF7, MB231, and T47D), prostate cancer cell lines (LnCaP and PC3), a colon cancer cell line (HT29), and a Sss I positive cell line (positive control) and subjected to the restriction digestion and PCR analysis as described herein. The marker loci used to determine hypermethylation state for lung cancer are 213-PCDHA13, 278-PCDHGA12, 206-HOXA9, 220-PTPN6, and 277-HOXD10; for breast cancer 277-HOXD10, 278-PCDHGA12, 213-PCDHA13, 273-HOXA11, 274-HOXA7, 280-HOXA9, 202-HOXD9, and 209-PCDHB15; for prostate cancer 232-APC, 93-COX2, 220-PTPN6, 277-HOXD10, and 278-PCDHGA12; and for colon cancer 99-RECK, 213-PCDHA13, 229-CDH13, and 278-PCDHGA12. In Table 4, plus (“+”) symbols are used to designate the presence of a characteristic marker amplicon (amplified after digestions with methylation-sensitive restriction enzymes according to the real-time PCR and gel-based methods described herein). Single (“+”), double (“++”), and triple (“+++”) designations indicate the relative quantitative amount of the respective characteristic marker amplicons, respectively based on the real-time PCR and/or gel-based methods described herein.
For Table 5, DNA was obtained from ALL, AML, and MM cell lines and subjected to the restriction digestion and PCR analysis as described herein. The marker loci used to determine hypermethylation state for ALL, AML, and MM are HOXD10, COX2, KLF4, SLC26A4, DLC-1, PCDHGA12A, RPIB9, SOX2, HIN1, SFRP2, DAPK1, CDH1, PGRB, OLIG2, NOR1, SOCS1, MAFB, p15, HOXD11, HOXD10, HOXA9, HIC1, CDH13, GSTP1, and GABRBA. In Table 5, the presence or absence of a characteristic marker amplicon (amplified after digestions with methylation-sensitive restriction enzymes according to gel-based methods described herein) is designated as “−” or “+”, respectively.
Sequences of Primers and CpGs for Marker Genes. The sequences can also be found at the website http://genome.ucsc.edu/.
The present invention is developed upon the prior method disclosed by the United States Patent Application Publication Number 2010/0248228 detecting DNA methylation without bisulfite treatment in clinical setting. Methylation sensitive enzymes are a group of DNA restriction endonucleases that cleave DNA at their recognition sites only when the cytosine of CG is not methylated. The enzymes do not cut the sites containing methylated CG dinucleotides. Although this feature has been utilized to study DNA methylation in developmental biology and in high throughput DNA methylation profiling [16-21], a specific method for tumor cell detection in the clinical setting has not been established. Using multiple methylation sensitive enzymes in this method, unmethylated DNA of normal cells in patient specimens is digested into small fragments; whereas methylated DNA in tumor cells is resistant to digestion and remains intact. These tumor-specific densely hypermethylated regions, often present in CGIs, are differentially amplified by various PCR methods (
Compared with other DNA methylation detection methods [21-29], this method possessed several advantages. First, the method is simple and the whole procedure comprises of three sequential steps: DNA isolation, digestion and a conventional multiplex PCR (
In addition, the methods herein disclosed were shown to detect hypermethylated loci in both solid tumor cell lines (representing lung, breast, prostate and colon cancers) and hematopoetic cell lines (representing Lymphocytic acute leukemia, acute myeloid leukemia, multiple myeloma).
Like genetic abnormalities in cancer, not all leukemia/lymphoma or carcinoma patients carry the same epigenetic markers. It is critical to select markers that contribute to tumorigenesis, but not just biological “noise” at the genetic and epigenetic levels. In this regard, we selected three DNA methylation markers, DLC-1, PCDHGA12 and RPIB9 as the testing cases, that all play important roles in leukemogenesis and lymphomagenesis. Interestingly, DNA methylation of these three genes demonstrates different specificity in B-cell neoplasms (
In conclusion, the invention has developed a new type with multiple platforms of PCR-based cancer cell DNA methylation detective method. These platforms include a conventional gel-based PCR, a nested ultra sensitive PCR, a TaqMan probe-based real-time PCR, and SYBR Green fluorescence-based real-time PCR. This unique method was validated by an independent bisulfite-based real-time qMSP assay in clinical patient specimens. Compared with other published DNA methylation detective methods [21-29], this new method demonstrated high sensitivity and specificity, simplicity and quantitative feature. The DNA sample does not require a bisulfite treatment and the background of the assay is very low. In addition, a total of 40 DNA methylation loci in functional genes have been identified with these methods that allows the broad clinical applications for residual circulating tumor cell or tumor DNA detection in both hematopoietic and solid tumors. The invention represents a new type of cancer biomarker detection that can potentially be used in cancer screening, early detection, assessment of therapeutic response, detection of early metastasis and minimal residual disease [37-40].
While the invention has been described in connection with specific embodiments thereof, it will be understood that the inventive device is capable of further modifications. This patent application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains and as may be applied to the essential features herein before set forth.
Cited references incorporated by reference herein for their respective teachings.
This application claims the benefit of priority to U.S. Provisional Patent Application No. 61/462,127, filed 28 Jan. 2011 and entitled “DNA METHYLATION BIOMARKERS FOR RARE CIRCULATING CANCER CELL DETECTION,” which is incorporated herein by reference in its entirety.
Number | Date | Country | |
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61462127 | Jan 2011 | US |