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Lukacova E, Hanzlikova Z, Podlesnyi P, Sedlackova T, Szemes T, Grendar M, Samec M, Hurtova T, Malicherova B, Leskova K, Budis J, Burjanivova T. Novel liquid biopsy CNV biomarkers in malignant melanoma. Sci Rep 2024; 14:15786. [PMID: 38982214 PMCID: PMC11233564 DOI: 10.1038/s41598-024-65928-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 06/25/2024] [Indexed: 07/11/2024] Open
Abstract
Malignant melanoma (MM) is known for its abundance of genetic alterations and a tendency for rapid metastasizing. Identification of novel plasma biomarkers may enhance non-invasive diagnostics and disease monitoring. Initially, we examined copy number variations (CNV) in CDK genes (CDKN2A, CDKN2B, CDK4) using MLPA (gDNA) and ddPCR (ctDNA) analysis. Subsequently, low-coverage whole genome sequencing (lcWGS) was used to identify the most common CNV in plasma samples, followed by ddPCR verification of chosen biomarkers. CNV alterations in CDK genes were identified in 33.3% of FFPE samples (Clark IV, V only). Detection of the same genes in MM plasma showed no significance, neither compared to healthy plasmas nor between pre- versus post-surgery plasma. Sequencing data showed the most common CNV occurring in 6q27, 4p16.1, 10p15.3, 10q22.3, 13q34, 18q23, 20q11.21-q13.12 and 22q13.33. CNV in four chosen genes (KIF25, E2F1, DIP2C and TFG) were verified by ddPCR using 2 models of interpretation. Model 1 was concordant with lcWGS results in 54% of samples, for model 2 it was 46%. Although CDK genes have not been proven to be suitable CNV liquid biopsy biomarkers, lcWGS defined the most frequently affected chromosomal regions by CNV. Among chosen genes, DIP2C demonstrated a potential for further analysis.
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Affiliation(s)
- E Lukacova
- Department of Molecular Biology and Genomics, Comenius University in Bratislava, Jessenius Faculty of Medicine in Martin (JFM CU), Martin, Slovakia
| | | | - P Podlesnyi
- Instituto de Investigaciones Biomedicas de Barcelona (IIBB), CSIC /Centro Investigacion Biomedica en Red Enfermedades Neurodegenerativas (CiberNed), Barcelona, Spain
| | - T Sedlackova
- Geneton Ltd., Bratislava, Slovakia
- Science Park, Comenius University in Bratislava, Bratislava, Slovakia
| | - T Szemes
- Geneton Ltd., Bratislava, Slovakia
- Science Park, Comenius University in Bratislava, Bratislava, Slovakia
| | - M Grendar
- Laboratory of Bioinformatics and Biostatistics, Biomedical Center Martin, Comenius University in Bratislava, Jessenius Faculty of Medicine in Martin (JFM CU), Martin, Slovakia
| | - M Samec
- Department of Medical Biology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - T Hurtova
- Department of Dermatovenereology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - B Malicherova
- Department of Clinical Biochemistry, University Hospital in Martin and Jessenius Faculty of Medicine, Comenius University, Martin, Slovakia
| | - K Leskova
- Department of Pathological Anatomy, Jessenius Faculty of Medicine and University Hospital in Martin, Comenius University, Martin, Slovakia
| | - J Budis
- Geneton Ltd., Bratislava, Slovakia
- Science Park, Comenius University in Bratislava, Bratislava, Slovakia
| | - T Burjanivova
- Department of Molecular Biology and Genomics, Comenius University in Bratislava, Jessenius Faculty of Medicine in Martin (JFM CU), Martin, Slovakia.
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2
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Zhou J, Pan Y, Wang S, Wang G, Gu C, Zhu J, Tan Z, Wu Q, He W, Lin X, Xu S, Yuan K, Zheng Z, Gong X, JiangHe C, Han Z, Huang B, Ruan R, Feng M, Cui P, Yang H. Early detection and stratification of colorectal cancer using plasma cell-free DNA fragmentomic profiling. Genomics 2024; 116:110876. [PMID: 38849019 DOI: 10.1016/j.ygeno.2024.110876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 04/17/2024] [Accepted: 04/27/2024] [Indexed: 06/09/2024]
Abstract
Timely accurate and cost-efficient detection of colorectal cancer (CRC) is of great clinical importance. This study aims to establish prediction models for detecting CRC using plasma cell-free DNA (cfDNA) fragmentomic features. Whole-genome sequencing (WGS) was performed on cfDNA from 620 participants, including healthy individuals, patients with benign colorectal diseases and CRC patients. Using WGS data, three machine learning methods were compared to build prediction models for the stratification of CRC patients. The optimal model to discriminate CRC patients of all stages from healthy individuals achieved a sensitivity of 92.31% and a specificity of 91.14%, while the model to separate early-stage CRC patients (stage 0-II) from healthy individuals achieved a sensitivity of 88.8% and a specificity of 96.2%. Additionally, the cfDNA fragmentation profiles reflected disease-specific genomic alterations in CRC. Overall, this study suggests that cfDNA fragmentation profiles may potentially become a noninvasive approach for the detection and stratification of CRC.
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Affiliation(s)
- Jiyuan Zhou
- Department of Gastroenterology, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuanke Pan
- College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China
| | - Shubing Wang
- Department of Oncology, Shenzhen Key Laboratory of Gastrointestinal Cancer Translational Research, Cancer Institute, Peking University Shenzhen Hospital, Shenzhen-Peking University-Hong Kong University of Science and Technology Medical Center, Shenzhen, China
| | - Guoqiang Wang
- Department of Gastrointestinal Surgery, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chengxin Gu
- Department of Gastroenterology, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jinxin Zhu
- College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China
| | - Zhenlin Tan
- Department of Gastroenterology, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qixian Wu
- Department of Gastroenterology, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Weihuang He
- Shenzhen Rapha Biotechnology Incorporate, Shenzhen, China
| | - Xiaohui Lin
- Department of Oncology, People's Hospital of Shenzhen Baoan District, The Second Affiliated Hospital of Shenzhen University, Shenzhen, China
| | - Shu Xu
- Department of Oncology, Shenzhen Hospital, University of Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Kehua Yuan
- Department of Oncology, Yantian Hospital, South University of Science and Technology, Shenzhen, Guangdong, China
| | - Ziwen Zheng
- Department of Gastroenterology, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiaoqing Gong
- Department of Gastroenterology, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chenhao JiangHe
- Department of Gastroenterology, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Zhoujian Han
- Department of Gastroenterology, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Bingding Huang
- College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China
| | - Ruyun Ruan
- College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China
| | - Mingji Feng
- Shenzhen Rapha Biotechnology Incorporate, Shenzhen, China
| | - Pin Cui
- Shenzhen Rapha Biotechnology Incorporate, Shenzhen, China.
| | - Hui Yang
- Department of Gastroenterology, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
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3
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Senturk Kirmizitas T, van den Berg C, Boers R, Helmijr J, Makrodimitris S, Dag HH, Kerkhofs M, Beaufort C, Kraan J, van IJcken WFJ, Gribnau J, Garkhail P, Boer GND, Roes EM, van Beekhuizen H, Gunel T, Wilting S, Martens J, Jansen M, Boere I. Epigenetic and Genomic Hallmarks of PARP-Inhibitor Resistance in Ovarian Cancer Patients. Genes (Basel) 2024; 15:750. [PMID: 38927686 PMCID: PMC11203368 DOI: 10.3390/genes15060750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 05/30/2024] [Accepted: 06/04/2024] [Indexed: 06/28/2024] Open
Abstract
BACKGROUND Patients with advanced-stage epithelial ovarian cancer (EOC) receive treatment with a poly-ADP ribose-polymerase (PARP) inhibitor (PARPi) as maintenance therapy after surgery and chemotherapy. Unfortunately, many patients experience disease progression because of acquired therapy resistance. This study aims to characterize epigenetic and genomic changes in cell-free DNA (cfDNA) associated with PARPi resistance. MATERIALS AND METHODS Blood was taken from 31 EOC patients receiving PARPi therapy before treatment and at disease progression during/after treatment. Resistance was defined as disease progression within 6 months after starting PARPi and was seen in fifteen patients, while sixteen patients responded for 6 to 42 months. Blood cfDNA was evaluated via Modified Fast Aneuploidy Screening Test-Sequencing System (mFast-SeqS to detect aneuploidy, via Methylated DNA Sequencing (MeD-seq) to find differentially methylated regions (DMRs), and via shallow whole-genome and -exome sequencing (shWGS, exome-seq) to define tumor fractions and mutational signatures. RESULTS Aneuploid cfDNA was undetectable pre-treatment but observed in six patients post-treatment, in five resistant and one responding patient. Post-treatment ichorCNA analyses demonstrated in shWGS and exome-seq higher median tumor fractions in resistant (7% and 9%) than in sensitive patients (7% and 5%). SigMiner analyses detected predominantly mutational signatures linked to mismatch repair and chemotherapy. DeSeq2 analyses of MeD-seq data revealed three methylation signatures and more tumor-specific DMRs in resistant than in responding patients in both pre- and post-treatment samples (274 vs. 30 DMRs, 190 vs. 57 DMRs, Χ2-test p < 0.001). CONCLUSION Our genome-wide Next-Generation Sequencing (NGS) analyses in PARPi-resistant patients identified epigenetic differences in blood before treatment, whereas genomic alterations were more frequently observed after progression. The epigenetic differences at baseline are especially interesting for further exploration as putative predictive biomarkers for PARPi resistance.
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Affiliation(s)
- Tugce Senturk Kirmizitas
- University Medical Center Rotterdam, Department of Medical Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (T.S.K.); (J.H.); (S.M.); (H.H.D.); (M.K.); (C.B.); (J.K.); (S.W.); (J.M.); (I.B.)
- Institute of Graduate Studies in Sciences, Istanbul University, Istanbul 34116, Turkey
| | - Caroline van den Berg
- University Medical Center Rotterdam, Department of Gynecological Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (C.v.d.B.); (P.G.); (G.N.-d.B.); (E.-M.R.); (H.v.B.)
| | - Ruben Boers
- University Medical Center Rotterdam, Department of Developmental Biology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (R.B.); (J.G.)
| | - Jean Helmijr
- University Medical Center Rotterdam, Department of Medical Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (T.S.K.); (J.H.); (S.M.); (H.H.D.); (M.K.); (C.B.); (J.K.); (S.W.); (J.M.); (I.B.)
| | - Stavros Makrodimitris
- University Medical Center Rotterdam, Department of Medical Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (T.S.K.); (J.H.); (S.M.); (H.H.D.); (M.K.); (C.B.); (J.K.); (S.W.); (J.M.); (I.B.)
| | - Hamit Harun Dag
- University Medical Center Rotterdam, Department of Medical Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (T.S.K.); (J.H.); (S.M.); (H.H.D.); (M.K.); (C.B.); (J.K.); (S.W.); (J.M.); (I.B.)
| | - Marijn Kerkhofs
- University Medical Center Rotterdam, Department of Medical Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (T.S.K.); (J.H.); (S.M.); (H.H.D.); (M.K.); (C.B.); (J.K.); (S.W.); (J.M.); (I.B.)
| | - Corine Beaufort
- University Medical Center Rotterdam, Department of Medical Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (T.S.K.); (J.H.); (S.M.); (H.H.D.); (M.K.); (C.B.); (J.K.); (S.W.); (J.M.); (I.B.)
| | - Jaco Kraan
- University Medical Center Rotterdam, Department of Medical Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (T.S.K.); (J.H.); (S.M.); (H.H.D.); (M.K.); (C.B.); (J.K.); (S.W.); (J.M.); (I.B.)
| | - Wilfred F. J. van IJcken
- University Medical Center Rotterdam, Center of Biomics, Erasmus MC, 3015 GD Rotterdam, The Netherlands;
| | - Joost Gribnau
- University Medical Center Rotterdam, Department of Developmental Biology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (R.B.); (J.G.)
| | - Pakriti Garkhail
- University Medical Center Rotterdam, Department of Gynecological Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (C.v.d.B.); (P.G.); (G.N.-d.B.); (E.-M.R.); (H.v.B.)
| | - Gatske Nieuwenhuyzen-de Boer
- University Medical Center Rotterdam, Department of Gynecological Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (C.v.d.B.); (P.G.); (G.N.-d.B.); (E.-M.R.); (H.v.B.)
| | - Eva-Maria Roes
- University Medical Center Rotterdam, Department of Gynecological Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (C.v.d.B.); (P.G.); (G.N.-d.B.); (E.-M.R.); (H.v.B.)
| | - Heleen van Beekhuizen
- University Medical Center Rotterdam, Department of Gynecological Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (C.v.d.B.); (P.G.); (G.N.-d.B.); (E.-M.R.); (H.v.B.)
| | - Tuba Gunel
- Department of Molecular Biology & Genetics, Istanbul University, Istanbul 34134, Turkey;
| | - Saskia Wilting
- University Medical Center Rotterdam, Department of Medical Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (T.S.K.); (J.H.); (S.M.); (H.H.D.); (M.K.); (C.B.); (J.K.); (S.W.); (J.M.); (I.B.)
| | - John Martens
- University Medical Center Rotterdam, Department of Medical Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (T.S.K.); (J.H.); (S.M.); (H.H.D.); (M.K.); (C.B.); (J.K.); (S.W.); (J.M.); (I.B.)
| | - Maurice Jansen
- University Medical Center Rotterdam, Department of Medical Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (T.S.K.); (J.H.); (S.M.); (H.H.D.); (M.K.); (C.B.); (J.K.); (S.W.); (J.M.); (I.B.)
| | - Ingrid Boere
- University Medical Center Rotterdam, Department of Medical Oncology, Erasmus MC, 3015 GD Rotterdam, The Netherlands; (T.S.K.); (J.H.); (S.M.); (H.H.D.); (M.K.); (C.B.); (J.K.); (S.W.); (J.M.); (I.B.)
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4
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Rickles-Young M, Tinoco G, Tsuji J, Pollock S, Haynam M, Lefebvre H, Glover K, Owen DH, Collier KA, Ha G, Adalsteinsson VA, Cibulskis C, Lennon NJ, Stover DG. Assay Validation of Cell-Free DNA Shallow Whole-Genome Sequencing to Determine Tumor Fraction in Advanced Cancers. J Mol Diagn 2024; 26:413-422. [PMID: 38490303 PMCID: PMC11090203 DOI: 10.1016/j.jmoldx.2024.01.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 09/21/2023] [Accepted: 01/18/2024] [Indexed: 03/17/2024] Open
Abstract
Blood-based liquid biopsy is increasingly used in clinical care of patients with cancer, and fraction of tumor-derived DNA in circulation (tumor fraction; TFx) has demonstrated clinical validity across multiple cancer types. To determine TFx, shallow whole-genome sequencing of cell-free DNA (cfDNA) can be performed from a single blood sample, using an established computational pipeline (ichorCNA), without prior knowledge of tumor mutations, in a highly cost-effective manner. We describe assay validation of this approach to facilitate broad clinical application, including evaluation of assay sensitivity, precision, repeatability, reproducibility, pre-analytic factors, and DNA quality/quantity. Sensitivity to detect TFx of 3% (lower limit of detection) was 97.2% to 100% at 1× and 0.1× mean sequencing depth, respectively. Precision was demonstrated on distinct sequencing instruments (HiSeqX and NovaSeq) with no observable differences. The assay achieved prespecified 95% agreement of TFx across replicates of the same specimen (repeatability) and duplicate samples in different batches (reproducibility). Comparison of samples collected in EDTA and Streck tubes from single venipuncture in 23 patients demonstrated that EDTA or Streck tubes were comparable if processed within 8 hours. On the basis of a range of DNA inputs (1 to 50 ng), 20 ng cfDNA is the preferred input, with 5 ng minimum acceptable. Overall, this shallow whole-genome sequencing of cfDNA and ichorCNA approach offers sensitive, precise, and reproducible quantitation of TFx, facilitating assay application in clinical cancer care.
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Affiliation(s)
- Micah Rickles-Young
- Genomics Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Gabriel Tinoco
- Division of Medical Oncology, The Ohio State University College of Medicine, Columbus, Ohio; Ohio State University Comprehensive Cancer Center, Columbus, Ohio
| | - Junko Tsuji
- Genomics Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Sam Pollock
- Genomics Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Marcy Haynam
- Ohio State University Comprehensive Cancer Center, Columbus, Ohio; Stefanie Spielman Comprehensive Breast Center, Columbus, Ohio
| | - Heather Lefebvre
- Ohio State University Comprehensive Cancer Center, Columbus, Ohio; Stefanie Spielman Comprehensive Breast Center, Columbus, Ohio
| | - Kristyn Glover
- Ohio State University Comprehensive Cancer Center, Columbus, Ohio; Stefanie Spielman Comprehensive Breast Center, Columbus, Ohio
| | - Dwight H Owen
- Division of Medical Oncology, The Ohio State University College of Medicine, Columbus, Ohio; Ohio State University Comprehensive Cancer Center, Columbus, Ohio
| | - Katharine A Collier
- Division of Medical Oncology, The Ohio State University College of Medicine, Columbus, Ohio; Ohio State University Comprehensive Cancer Center, Columbus, Ohio
| | - Gavin Ha
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Viktor A Adalsteinsson
- Genomics Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Carrie Cibulskis
- Genomics Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Niall J Lennon
- Genomics Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts.
| | - Daniel G Stover
- Division of Medical Oncology, The Ohio State University College of Medicine, Columbus, Ohio; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; Stefanie Spielman Comprehensive Breast Center, Columbus, Ohio.
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Abstract
With the rapid development of science and technology, cell-free DNA (cfDNA) is rapidly becoming an important biomarker for tumor diagnosis, monitoring and prognosis, and this cfDNA-based liquid biopsy technology has great potential to become an important part of precision medicine. cfDNA is the total amount of free DNA in the systemic circulation, including DNA fragments derived from tumor cells and all other somatic cells. Tumor cells release fragments of DNA into the bloodstream, and this source of cfDNA is called circulating tumor DNA (ctDNA). cfDNA detection has become a major focus in the field of tumor research in recent years, which provides a new opportunity for non-invasive diagnosis and prognosis of cancer. In this paper, we discuss the limitations of the study on the origin and dynamics analysis of ctDNA, and how to solve these problems in the future. Although the future faces major challenges, it also contains great potential.
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Liu SC. Circulating tumor DNA in liquid biopsy: Current diagnostic limitation. World J Gastroenterol 2024; 30:2175-2178. [PMID: 38681986 PMCID: PMC11045476 DOI: 10.3748/wjg.v30.i15.2175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 03/07/2024] [Accepted: 04/02/2024] [Indexed: 04/19/2024] Open
Abstract
With the rapid development of science and technology, cell-free DNA (cfDNA) is rapidly becoming an important biomarker for tumor diagnosis, monitoring and prognosis, and this cfDNA-based liquid biopsy technology has great potential to become an important part of precision medicine. cfDNA is the total amount of free DNA in the systemic circulation, including DNA fragments derived from tumor cells and all other somatic cells. Tumor cells release fragments of DNA into the bloodstream, and this source of cfDNA is called circulating tumor DNA (ctDNA). cfDNA detection has become a major focus in the field of tumor research in recent years, which provides a new opportunity for non-invasive diagnosis and prognosis of cancer. In this paper, we discuss the limitations of the study on the origin and dynamics analysis of ctDNA, and how to solve these problems in the future. Although the future faces major challenges, it also contains great potential.
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Affiliation(s)
- Shi-Cai Liu
- School of Medical Information, Wannan Medical College, Wuhu 241002, Anhui Province, China
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7
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Penny L, Main SC, De Michino SD, Bratman SV. Chromatin- and nucleosome-associated features in liquid biopsy: implications for cancer biomarker discovery. Biochem Cell Biol 2024. [PMID: 38478957 DOI: 10.1139/bcb-2024-0004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2024] Open
Abstract
Cell-free DNA (cfDNA) from the bloodstream has been studied for cancer biomarker discovery, and chromatin-derived epigenetic features have come into the spotlight for their potential to expand clinical applications. Methylation, fragmentation, and nucleosome positioning patterns of cfDNA have previously been shown to reveal epigenomic and inferred transcriptomic information. More recently, histone modifications have emerged as a tool to further identify tumor-specific chromatin variants in plasma. A number of sequencing methods have been developed to analyze these epigenetic markers, offering new insights into tumor biology. Features within cfDNA allow for cancer detection, subtype and tissue of origin classification, and inference of gene expression. These methods provide a window into the complexity of cancer and the dynamic nature of its progression. In this review, we highlight the array of epigenetic features in cfDNA that can be extracted from chromatin- and nucleosome-associated organization and outline potential use cases in cancer management.
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Affiliation(s)
- Lucas Penny
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
| | - Sasha C Main
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
| | - Steven D De Michino
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
| | - Scott V Bratman
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON M5T 1P5, Canada
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8
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Wang B, Wang M, Lin Y, Zhao J, Gu H, Li X. Circulating tumor DNA methylation: a promising clinical tool for cancer diagnosis and management. Clin Chem Lab Med 2024; 0:cclm-2023-1327. [PMID: 38443752 DOI: 10.1515/cclm-2023-1327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 02/19/2024] [Indexed: 03/07/2024]
Abstract
Cancer continues to pose significant challenges to the medical community. Early detection, accurate molecular profiling, and adequate assessment of treatment response are critical factors in improving the quality of life and survival of cancer patients. Accumulating evidence shows that circulating tumor DNA (ctDNA) shed by tumors into the peripheral blood preserves the genetic and epigenetic information of primary tumors. Notably, DNA methylation, an essential and stable epigenetic modification, exhibits both cancer- and tissue-specific patterns. As a result, ctDNA methylation has emerged as a promising molecular marker for noninvasive testing in cancer clinics. In this review, we summarize the existing techniques for ctDNA methylation detection, describe the current research status of ctDNA methylation, and present the potential applications of ctDNA-based assays in the clinic. The insights presented in this article could serve as a roadmap for future research and clinical applications of ctDNA methylation.
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Affiliation(s)
- Binliang Wang
- Department of Respiratory Medicine, Huangyan Hospital Affiliated to Wenzhou Medical University, Taizhou, P.R. China
| | - Meng Wang
- Institute of Health Education, Hangzhou Center for Disease Control and Prevention, Hangzhou, P.R. China
| | - Ya Lin
- Zhejiang University of Chinese Medicine, Hangzhou, P.R. China
| | - Jinlan Zhao
- Scientific Research Department, Zhejiang Shengting Medical Company, Hangzhou, P.R. China
| | - Hongcang Gu
- Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, P.R. China
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Science, Hefei, P.R. China
| | - Xiangjuan Li
- Department of Gynaecology, Hangzhou Obstetrics and Gynecology Hospital, Hangzhou, P.R. China
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Jiang Z, Luo K, Yang G, Li Y, Li L, Wang G, Qin T, Li J. An Electrochemiluminescent Sensor Based on Glycosyl Imprinting and Aptamer for the Detection of Cancer-Related Extracellular Vesicles. Anal Chem 2024; 96:2550-2558. [PMID: 38314707 DOI: 10.1021/acs.analchem.3c04991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
Cancer-related extracellular vesicles (EVs) are considered important biomarkers for cancer diagnosis because they can convey a large amount of information about tumor cells. In order to detect cancer-related EVs efficiently, an electrochemiluminescence (ECL) sensor for the specific identification and highly sensitive detection of EVs in the plasma of cancer patients was constructed based on dual recognitions by glycosyl-imprinted polymer (GIP) and aptamer. The characteristic glycosyl Neu5Ac-α-(2,6)-Gal-β-(1-4)-GlcNAc trisaccharide on the surface of EVs was used as a template molecule and 3-aminophenylboronic acid as a functional monomer to form a glycosyl-imprinted polymer by electropolymerization. After glycosyl elution, the imprinted film specifically recognized and adsorbed the EVs in the sample, and then the CD63 aptamer-bipyridine ruthenium (Aptamer-Ru(bpy)) was added to combine with the CD63 glycoprotein on the extracellular vesicle's surface, thus providing secondary recognition of the EVs. Finally, the EVs were quantitatively detected according to the ECL signal produced by the labeled bipyridine ruthenium. When more EVs were captured by the imprinted film, more probes were obtained after incubation, and the ECL signal was stronger. Under the optimized conditions, the ECL signal showed a good linear relationship with the concentration of EVs in the range of 9.5 × 102 to 9.5 × 107 particles/mL, and the limit of detection was 641 particles/mL. The GIP sensor can discriminate between the EV contents of cancer patients and healthy controls with high accuracy. Because of its affordability, high sensitivity, and ease of use, it is anticipated to be employed for cancer early detection and diagnosis.
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Affiliation(s)
- Zejun Jiang
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China
| | - Kui Luo
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China
| | - Guangwei Yang
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China
| | - Yang Li
- College of Chemistry and Bioengineering, Guilin University of Technology, Guilin 541004, China
| | - Ling Li
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China
| | - Guocong Wang
- College of Chemistry and Bioengineering, Guilin University of Technology, Guilin 541004, China
| | - Tao Qin
- Affiliated Hospital of Guilin Medical University, Guilin 541001, China
| | - Jianping Li
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China
- College of Chemistry and Bioengineering, Guilin University of Technology, Guilin 541004, China
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10
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Wang R, Yang Y, Lu T, Cui Y, Li B, Liu X. Circulating cell-free DNA-based methylation pattern in plasma for early diagnosis of esophagus cancer. PeerJ 2024; 12:e16802. [PMID: 38313016 PMCID: PMC10838104 DOI: 10.7717/peerj.16802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 12/26/2023] [Indexed: 02/06/2024] Open
Abstract
With the increased awareness of early tumor detection, the importance of detecting and diagnosing esophageal cancer in its early stages has been underscored. Studies have consistently demonstrated the crucial role of methylation levels in circulating cell-free DNA (cfDNA) in identifying and diagnosing early-stage cancer. cfDNA methylation pertains to the methylation state within the genomic scope of cfDNA and is strongly associated with cancer development and progression. Several research teams have delved into the potential application of cfDNA methylation in identifying early-stage esophageal cancer and have achieved promising outcomes. Recent research supports the high sensitivity and specificity of cfDNA methylation in early esophageal cancer diagnosis, providing a more accurate and efficient approach for early detection and improved clinical management. Accordingly, this review aims to present an overview of methylation-based cfDNA research with a focus on the latest developments in the early detection of esophageal cancer. Additionally, this review summarizes advanced analytical technologies for cfDNA methylation that have significantly benefited from recent advancements in separation and detection techniques, such as methylated DNA immunoprecipitation sequencing (MeDIP-seq). Recent findings suggest that biomarkers based on cfDNA methylation may soon find successful applications in the early detection of esophageal cancer. However, large-scale prospective clinical trials are required to identify the potential of these biomarkers.
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Affiliation(s)
- Rui Wang
- School of Public Health, Jilin University, Changchun, Jilin, China
| | - Yue Yang
- Department of Thoracic Surgery, First Hospital of Jilin University, Changchun, Jilin, China
| | - Tianyu Lu
- Department of Thoracic Surgery, First Hospital of Jilin University, Changchun, Jilin, China
| | - Youbin Cui
- Department of Thoracic Surgery, First Hospital of Jilin University, Changchun, Jilin, China
| | - Bo Li
- School of Public Health, Jilin University, Changchun, Jilin, China
| | - Xin Liu
- Department of Thoracic Surgery, First Hospital of Jilin University, Changchun, Jilin, China
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11
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LeeVan E, Pinsky P. Predictive Performance of Cell-Free Nucleic Acid-Based Multi-Cancer Early Detection Tests: A Systematic Review. Clin Chem 2024; 70:90-101. [PMID: 37791504 DOI: 10.1093/clinchem/hvad134] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 07/24/2023] [Indexed: 10/05/2023]
Abstract
BACKGROUND Cancer-screening tests that can detect multiple cancer types, or multi-cancer early detection (MCED) tests, have emerged recently as a potential new tool in decreasing cancer morbidity and mortality. Most MCED assays are based on detecting cell-free tumor DNA (CF-DNA) in the blood. MCEDs offer the potential for screening for cancer organ sites with high mortality, both with and without recommended screening. However, their clinical utility has not been established. Before clinical utility can be established, the clinical validity of MCEDs, i.e., their ability to predict cancer status, must be demonstrated. In this study we performed a systematic review of the predictive ability for cancer of cell-free-nucleic acid-based MCED tests. CONTENT We searched PubMed for relevant publications from January 2017 to February 2023, using MeSH terms related to multi-cancer detection, circulating DNA, and related concepts. Of 1811 publications assessed, 61 were reviewed in depth and 20 are included in this review. For almost all studies, the cancer cases were assessed at time of diagnosis. Most studies reported specificity (generally 95% or higher) and overall sensitivity (73% median). The median number of cancer types assessed per assay was 5. Many studies also reported sensitivity by stage and/or cancer type. Sensitivity generally increased with stage. SUMMARY To date, relatively few published studies have assessed the clinical validity of MCED tests. Most used cancer cases assessed at diagnosis, with generally high specificity and variable sensitivity depending on cancer type and stage. The next steps should be testing in the intended-use population, i.e., asymptomatic persons.
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Affiliation(s)
- Elyse LeeVan
- Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, United States
| | - Paul Pinsky
- Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, United States
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12
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Zhan J, Chen C, Zhang N, Zhong S, Wang J, Hu J, Liu J. An artificial intelligence model for embryo selection in preimplantation DNA methylation screening in assisted reproductive technology. BIOPHYSICS REPORTS 2023; 9:352-361. [PMID: 38524697 PMCID: PMC10960573 DOI: 10.52601/bpr.2023.230035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 11/28/2023] [Indexed: 03/26/2024] Open
Abstract
Embryo quality is a critical determinant of clinical outcomes in assisted reproductive technology (ART). A recent clinical trial investigating preimplantation DNA methylation screening (PIMS) revealed that whole genome DNA methylation level is a novel biomarker for assessing ART embryo quality. Here, we reinforced and estimated the clinical efficacy of PIMS. We introduce PIMS-AI, an innovative artificial intelligence (AI) based model, to predict the probability of an embryo producing live birth and subsequently assist ART embryo selection. Our model demonstrated robust performance, achieving an area under the curve (AUC) of 0.90 in cross-validation and 0.80 in independent testing. In simulated embryo selection, PIMS-AI attained an accuracy of 81% in identifying viable embryos for patients. Notably, PIMS-AI offers significant advantages over conventional preimplantation genetic testing for aneuploidy (PGT-A), including enhanced embryo discriminability and the potential to benefit a broader patient population. In conclusion, our approach holds substantial promise for clinical application and has the potential to significantly improve the ART success rate.
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Affiliation(s)
- Jianhong Zhan
- Institute of Biophysics, Chinese Academy of Science, Beijing 100101, China
| | - Chuangqi Chen
- Guangdong Women's and Children's Hospital, Guangzhou 511400, China
| | - Na Zhang
- Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | | | - Jiaming Wang
- Institute of Biophysics, Chinese Academy of Science, Beijing 100101, China
- University of the Chinese Academy of Science, Beijing 101408, China
- School of Future Technology, University of the Chinese Academy of Science, Beijing 100049, China
| | - Jinzhou Hu
- Institute of Biophysics, Chinese Academy of Science, Beijing 100101, China
- University of the Chinese Academy of Science, Beijing 101408, China
| | - Jiang Liu
- Institute of Biophysics, Chinese Academy of Science, Beijing 100101, China
- University of the Chinese Academy of Science, Beijing 101408, China
- School of Future Technology, University of the Chinese Academy of Science, Beijing 100049, China
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13
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Melton CA, Freese P, Zhou Y, Shenoy A, Bagaria S, Chang C, Kuo CC, Scott E, Srinivasan S, Cann G, Roychowdhury-Saha M, Chang PY, Singh AH. A Novel Tissue-Free Method to Estimate Tumor-Derived Cell-Free DNA Quantity Using Tumor Methylation Patterns. Cancers (Basel) 2023; 16:82. [PMID: 38201510 PMCID: PMC10777919 DOI: 10.3390/cancers16010082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/07/2023] [Accepted: 12/20/2023] [Indexed: 01/12/2024] Open
Abstract
Estimating the abundance of cell-free DNA (cfDNA) fragments shed from a tumor (i.e., circulating tumor DNA (ctDNA)) can approximate tumor burden, which has numerous clinical applications. We derived a novel, broadly applicable statistical method to quantify cancer-indicative methylation patterns within cfDNA to estimate ctDNA abundance, even at low levels. Our algorithm identified differentially methylated regions (DMRs) between a reference database of cancer tissue biopsy samples and cfDNA from individuals without cancer. Then, without utilizing matched tissue biopsy, counts of fragments matching the cancer-indicative hyper/hypo-methylated patterns within DMRs were used to determine a tumor methylated fraction (TMeF; a methylation-based quantification of the circulating tumor allele fraction and estimate of ctDNA abundance) for plasma samples. TMeF and small variant allele fraction (SVAF) estimates of the same cancer plasma samples were correlated (Spearman's correlation coefficient: 0.73), and synthetic dilutions to expected TMeF of 10-3 and 10-4 had estimated TMeF within two-fold for 95% and 77% of samples, respectively. TMeF increased with cancer stage and tumor size and inversely correlated with survival probability. Therefore, tumor-derived fragments in the cfDNA of patients with cancer can be leveraged to estimate ctDNA abundance without the need for a tumor biopsy, which may provide non-invasive clinical approximations of tumor burden.
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14
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Li C, Shao J, Li P, Feng J, Li J, Wang C. Circulating tumor DNA as liquid biopsy in lung cancer: Biological characteristics and clinical integration. Cancer Lett 2023; 577:216365. [PMID: 37634743 DOI: 10.1016/j.canlet.2023.216365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 08/22/2023] [Accepted: 08/23/2023] [Indexed: 08/29/2023]
Abstract
Lung cancer maintains high morbidity and mortality rate globally despite significant advancements in diagnosis and treatment in the era of precision medicine. Pathological analysis of tumor tissue, the current gold standard for lung cancer diagnosis, is intrusive and intrinsically confined to evaluating the limited amount of tissues that could be physically extracted. However, tissue biopsy has several limitations, including the invasiveness of the procedure and difficulty in obtaining samples for patients at advanced stages., there Additionally,has been no major breakthrough in tumor biomarkers with high specificity and sensitivity, particularly for early-stage lung cancer. Liquid biopsy has been considered a feasible auxiliary tool for tearly dianosis, evaluating treatment responses and monitoring prognosis of lung cancer. Circulating tumor DNA (ctDNA), an ideal biomarker of liquid biopsy, has emerged as one of the most reliable tools for monitoring tumor processes at molecular levels. Herein, this review focuses on tumor heterogeneity to elucidate the superiority of liquid biopsy and retrospectively discussdeciphersolution. We systematically elaborate ctDNA biological characteristics, introduce methods for ctDNA detection, and discuss the current role of plasma ctDNA in lung cancer management. Finally, we summarize the drawbacks of ctDNA analysis and highlight its potential clinical application in lung cancer.
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Affiliation(s)
- Changshu Li
- Department of Pulmonary and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Respiratory Health and Multimorbidity, West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Jun Shao
- Department of Pulmonary and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Respiratory Health and Multimorbidity, West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Peiyi Li
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, China
| | - Jiaming Feng
- West China School of Medicine, Sichuan University, Chengdu, China
| | - Jingwei Li
- Department of Pulmonary and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Respiratory Health and Multimorbidity, West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Chengdi Wang
- Department of Pulmonary and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Respiratory Health and Multimorbidity, West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China.
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15
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Kim SY, Jeong S, Lee W, Jeon Y, Kim YJ, Park S, Lee D, Go D, Song SH, Lee S, Woo HG, Yoon JK, Park YS, Kim YT, Lee SH, Kim KH, Lim Y, Kim JS, Kim HP, Bang D, Kim TY. Cancer signature ensemble integrating cfDNA methylation, copy number, and fragmentation facilitates multi-cancer early detection. Exp Mol Med 2023; 55:2445-2460. [PMID: 37907748 PMCID: PMC10689759 DOI: 10.1038/s12276-023-01119-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 08/10/2023] [Accepted: 08/16/2023] [Indexed: 11/02/2023] Open
Abstract
Cell-free DNA (cfDNA) sequencing has demonstrated great potential for early cancer detection. However, most large-scale studies have focused only on either targeted methylation sites or whole-genome sequencing, limiting comprehensive analysis that integrates both epigenetic and genetic signatures. In this study, we present a platform that enables simultaneous analysis of whole-genome methylation, copy number, and fragmentomic patterns of cfDNA in a single assay. Using a total of 950 plasma (361 healthy and 589 cancer) and 240 tissue samples, we demonstrate that a multifeature cancer signature ensemble (CSE) classifier integrating all features outperforms single-feature classifiers. At 95.2% specificity, the cancer detection sensitivity with methylation, copy number, and fragmentomic models was 77.2%, 61.4%, and 60.5%, respectively, but sensitivity was significantly increased to 88.9% with the CSE classifier (p value < 0.0001). For tissue of origin, the CSE classifier enhanced the accuracy beyond the methylation classifier, from 74.3% to 76.4%. Overall, this work proves the utility of a signature ensemble integrating epigenetic and genetic information for accurate cancer detection.
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Affiliation(s)
| | | | | | - Yujin Jeon
- IMBdx Inc., Seoul, 08506, Republic of Korea
| | | | | | - Dongin Lee
- Department of Chemistry, Yonsei University, Seoul, 03722, Republic of Korea
| | - Dayoung Go
- IMBdx Inc., Seoul, 08506, Republic of Korea
| | - Sang-Hyun Song
- Cancer Research Institute, Seoul National University, Seoul, 03080, Republic of Korea
| | - Sanghoo Lee
- Seoul Clinical Laboratories Healthcare Inc., Yongin-si, Gyenggi-do, 16954, Republic of Korea
| | - Hyun Goo Woo
- Department of Physiology, Ajou University School of Medicine, Suwon, 16499, Republic of Korea
| | - Jung-Ki Yoon
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Stanford University, Stanford, CA, USA
| | - Young Sik Park
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Hospital, Seoul, 03080, Republic of Korea
| | - Young Tae Kim
- Cancer Research Institute, Seoul National University, Seoul, 03080, Republic of Korea
- Department of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, Seoul, 03080, Republic of Korea
| | - Se-Hoon Lee
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute of Health Sciences and Technology, Sungkyunkwan University, Seoul, 03063, Republic of Korea
| | - Kwang Hyun Kim
- Department of Urology, Ewha Womans University Seoul Hospital, Seoul, 07804, Republic of Korea
| | - Yoojoo Lim
- IMBdx Inc., Seoul, 08506, Republic of Korea
| | - Jin-Soo Kim
- IMBdx Inc., Seoul, 08506, Republic of Korea
- Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, 07061, Republic of Korea
| | | | - Duhee Bang
- Department of Chemistry, Yonsei University, Seoul, 03722, Republic of Korea.
| | - Tae-You Kim
- IMBdx Inc., Seoul, 08506, Republic of Korea.
- Cancer Research Institute, Seoul National University, Seoul, 03080, Republic of Korea.
- Department of Internal Medicine, Seoul National University Hospital, Seoul, 03080, Republic of Korea.
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 08826, Republic of Korea.
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16
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Nguyen VTC, Nguyen TH, Doan NNT, Pham TMQ, Nguyen GTH, Nguyen TD, Tran TTT, Vo DL, Phan TH, Jasmine TX, Nguyen VC, Nguyen HT, Nguyen TV, Nguyen THH, Huynh LAK, Tran TH, Dang QT, Doan TN, Tran AM, Nguyen VH, Nguyen VTA, Ho LMQ, Tran QD, Pham TTT, Ho TD, Nguyen BT, Nguyen TNV, Nguyen TD, Phu DTB, Phan BHH, Vo TL, Nai THT, Tran TT, Truong MH, Tran NC, Le TK, Tran THT, Duong ML, Bach HPT, Kim VV, Pham TA, Tran DH, Le TNA, Pham TVN, Le MT, Vo DH, Tran TMT, Nguyen MN, Van TTV, Nguyen AN, Tran TT, Tran VU, Le MP, Do TT, Phan TV, Nguyen HDL, Nguyen DS, Cao VT, Do TTT, Truong DK, Tang HS, Giang H, Nguyen HN, Phan MD, Tran LS. Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization. eLife 2023; 12:RP89083. [PMID: 37819044 PMCID: PMC10567114 DOI: 10.7554/elife.89083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/13/2023] Open
Abstract
Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.
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