1
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Unterman I, Avrahami D, Katsman E, Triche TJ, Glaser B, Berman BP. CelFiE-ISH: a probabilistic model for multi-cell type deconvolution from single-molecule DNA methylation haplotypes. Genome Biol 2024; 25:151. [PMID: 38858759 PMCID: PMC11163775 DOI: 10.1186/s13059-024-03275-x] [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: 08/20/2023] [Accepted: 05/13/2024] [Indexed: 06/12/2024] Open
Abstract
Deconvolution methods infer quantitative cell type estimates from bulk measurement of mixed samples including blood and tissue. DNA methylation sequencing measures multiple CpGs per read, but few existing deconvolution methods leverage this within-read information. We develop CelFiE-ISH, which extends an existing method (CelFiE) to use within-read haplotype information. CelFiE-ISH outperforms CelFiE and other existing methods, achieving 30% better accuracy and more sensitive detection of rare cell types. We also demonstrate the importance of marker selection and of tailoring markers for haplotype-aware methods. While here we use gold-standard short-read sequencing data, haplotype-aware methods will be well-suited for long-read sequencing.
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Affiliation(s)
- Irene Unterman
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Dana Avrahami
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Endocrinology and Metabolism, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Efrat Katsman
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Timothy J Triche
- Center for Epigenetics, Van Andel Research Institute, Grand Rapids, MI, USA
| | - Benjamin Glaser
- Department of Endocrinology and Metabolism, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Benjamin P Berman
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
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2
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McNamara ME, Jain SS, Oza K, Muralidaran V, Kiliti AJ, McDeed AP, Patil D, Cui Y, Schmidt MO, Riegel AT, Kroemer AH, Wellstein A. Circulating, cell-free methylated DNA indicates cellular sources of allograft injury after liver transplant. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.04.588176. [PMID: 38617373 PMCID: PMC11014558 DOI: 10.1101/2024.04.04.588176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Post-transplant complications reduce allograft and recipient survival. Current approaches for detecting allograft injury non-invasively are limited and do not differentiate between cellular mechanisms. Here, we monitor cellular damages after liver transplants from cell-free DNA (cfDNA) fragments released from dying cells into the circulation. We analyzed 130 blood samples collected from 44 patients at different time points after transplant. Sequence-based methylation of cfDNA fragments were mapped to patterns established to identify cell types in different organs. For liver cell types DNA methylation patterns and multi-omic data integration show distinct enrichment in open chromatin and regulatory regions functionally important for the respective cell types. We find that multi-tissue cellular damages post-transplant recover in patients without allograft injury during the first post-operative week. However, sustained elevation of hepatocyte and biliary epithelial cfDNA beyond the first week indicates early-onset allograft injury. Further, cfDNA composition differentiates amongst causes of allograft injury indicating the potential for non-invasive monitoring and timely intervention.
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Affiliation(s)
- Megan E. McNamara
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
| | - Sidharth S. Jain
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
| | - Kesha Oza
- MedStar Georgetown Transplant Institute, MedStar Georgetown University Hospital and Center for Translational Transplant Medicine, Georgetown University Medical Center, Washington, DC, USA
- Department of General Surgery, MedStar Georgetown University Hospital, Washington, DC, USA
| | - Vinona Muralidaran
- MedStar Georgetown Transplant Institute, MedStar Georgetown University Hospital and Center for Translational Transplant Medicine, Georgetown University Medical Center, Washington, DC, USA
| | - Amber J. Kiliti
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
| | - A. Patrick McDeed
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
| | - Digvijay Patil
- MedStar Georgetown Transplant Institute, MedStar Georgetown University Hospital and Center for Translational Transplant Medicine, Georgetown University Medical Center, Washington, DC, USA
| | - Yuki Cui
- MedStar Georgetown Transplant Institute, MedStar Georgetown University Hospital and Center for Translational Transplant Medicine, Georgetown University Medical Center, Washington, DC, USA
| | - Marcel O. Schmidt
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
| | - Anna T. Riegel
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
| | - Alexander H.K. Kroemer
- MedStar Georgetown Transplant Institute, MedStar Georgetown University Hospital and Center for Translational Transplant Medicine, Georgetown University Medical Center, Washington, DC, USA
| | - Anton Wellstein
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
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3
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Franceschini GM, Quaini O, Mizuno K, Orlando F, Ciani Y, Ku SY, Sigouros M, Rothmann E, Alonso A, Benelli M, Nardella C, Auh J, Freeman D, Hanratty B, Adil M, Elemento O, Tagawa ST, Feng FY, Caffo O, Buttigliero C, Basso U, Nelson PS, Corey E, Haffner MC, Attard G, Aparicio A, Demichelis F, Beltran H. Noninvasive Detection of Neuroendocrine Prostate Cancer through Targeted Cell-free DNA Methylation. Cancer Discov 2024; 14:424-445. [PMID: 38197680 PMCID: PMC10905672 DOI: 10.1158/2159-8290.cd-23-0754] [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: 07/11/2023] [Revised: 10/31/2023] [Accepted: 12/15/2023] [Indexed: 01/11/2024]
Abstract
Castration-resistant prostate cancer (CRPC) is a heterogeneous disease associated with phenotypic subtypes that drive therapy response and outcome differences. Histologic transformation to castration-resistant neuroendocrine prostate cancer (CRPC-NE) is associated with distinct epigenetic alterations, including changes in DNA methylation. The current diagnosis of CRPC-NE is challenging and relies on metastatic biopsy. We developed a targeted DNA methylation assay to detect CRPC-NE using plasma cell-free DNA (cfDNA). The assay quantifies tumor content and provides a phenotype evidence score that captures diverse CRPC phenotypes, leveraging regions to inform transcriptional state. We tested the design in independent clinical cohorts (n = 222 plasma samples) and qualified it achieving an AUC > 0.93 for detecting pathology-confirmed CRPC-NE (n = 136). Methylation-defined cfDNA tumor content was associated with clinical outcomes in two prospective phase II clinical trials geared towards aggressive variant CRPC and CRPC-NE. These data support the application of targeted DNA methylation for CRPC-NE detection and patient stratification. SIGNIFICANCE Neuroendocrine prostate cancer is an aggressive subtype of treatment-resistant prostate cancer. Early detection is important, but the diagnosis currently relies on metastatic biopsy. We describe the development and validation of a plasma cell-free DNA targeted methylation panel that can quantify tumor fraction and identify patients with neuroendocrine prostate cancer noninvasively. This article is featured in Selected Articles from This Issue, p. 384.
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Affiliation(s)
- Gian Marco Franceschini
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Orsetta Quaini
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Kei Mizuno
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Francesco Orlando
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Yari Ciani
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Sheng-Yu Ku
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Michael Sigouros
- Institute for Computational Biomedicine and Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York
| | - Emily Rothmann
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Alicia Alonso
- Institute for Computational Biomedicine and Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York
| | | | - Caterina Nardella
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Joonghoon Auh
- Institute for Computational Biomedicine and Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York
| | - Dory Freeman
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Brian Hanratty
- Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Mohamed Adil
- Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Olivier Elemento
- Institute for Computational Biomedicine and Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York
| | - Scott T. Tagawa
- Department of Medicine, Division of Medical Oncology, Weill Cornell Medicine, New York, New York
| | - Felix Y. Feng
- Department of Radiation Oncology, University of California San Francisco, San Francisco, California
| | - Orazio Caffo
- Department of Medical Oncology, Santa Chiara Hospital, Trento, Italy
| | - Consuelo Buttigliero
- Department of Oncology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Turin, Italy
| | - Umberto Basso
- Department of Oncology, Istituto Oncologico Veneto IOV - IRCCS, Padua, Italy
| | | | - Eva Corey
- University of Washington, Seattle, Washington
| | - Michael C. Haffner
- Fred Hutchinson Cancer Research Center, Seattle, Washington
- University of Washington, Seattle, Washington
| | - Gerhardt Attard
- Cancer Institute and University College London Hospitals, University College London, London, United Kingdom
| | - Ana Aparicio
- Department of GU Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Francesca Demichelis
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Himisha Beltran
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
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4
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Albinati L, Bianchi A, Beekman R. The emerging field of opportunities for single-cell DNA methylation studies in hematology and beyond. Front Mol Biosci 2023; 10:1286716. [PMID: 37954981 PMCID: PMC10637949 DOI: 10.3389/fmolb.2023.1286716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 10/12/2023] [Indexed: 11/14/2023] Open
Affiliation(s)
- Leone Albinati
- Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Agostina Bianchi
- Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Renée Beekman
- Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Centre Nacional d’Anàlisi Genòmica (CNAG), Barcelona, Spain
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
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5
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Rink BD, Stevens BK. Incidental Detection of Malignancies With Cell-Free DNA Screening. Clin Obstet Gynecol 2023; 66:607-615. [PMID: 37443422 DOI: 10.1097/grf.0000000000000800] [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: 07/15/2023]
Abstract
Cell-free circulating DNA is an evolving technology with important clinical applications in both obstetric care and oncology. In the challenging patient with pregnancy and co-existing malignancy, the utility of cell-free DNA both for aneuploidy screening and cancer identification is an area of active research. Understanding the physiology associated with circulating cell-free DNA and subsequent laboratory evaluation is critical for clinicians caring for the obstetric patient with cell-free fetal DNA screening results suggestive of malignancy. Ongoing research is necessary to determine best practices for the evaluation and management of these patients with promising applications in the advancement of precision medicine.
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Affiliation(s)
- Britton D Rink
- Mount Carmel Health Systems, Division of Genetic and Genomic Medicine, Nationwide Children's Hospital, Columbus, Ohio
| | - Blair K Stevens
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of Texas McGovern Medical School, Houston, Texas
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6
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Kwon HJ, Shin SH, Kim HH, Min NY, Lim Y, Joo TW, Lee KJ, Jeong MS, Kim H, Yun SY, Kim Y, Park D, Joo J, Bae JS, Lee S, Jeong BH, Lee K, Lee H, Kim HK, Kim K, Um SW, An C, Lee MS. Advances in methylation analysis of liquid biopsy in early cancer detection of colorectal and lung cancer. Sci Rep 2023; 13:13502. [PMID: 37598236 PMCID: PMC10439900 DOI: 10.1038/s41598-023-40611-w] [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: 04/30/2023] [Accepted: 08/14/2023] [Indexed: 08/21/2023] Open
Abstract
Methylation patterns in cell-free DNA (cfDNA) have emerged as a promising genomic feature for detecting the presence of cancer and determining its origin. The purpose of this study was to evaluate the diagnostic performance of methylation-sensitive restriction enzyme digestion followed by sequencing (MRE-Seq) using cfDNA, and to investigate the cancer signal origin (CSO) of the cancer using a deep neural network (DNN) analyses for liquid biopsy of colorectal and lung cancer. We developed a selective MRE-Seq method with DNN learning-based prediction model using demethylated-sequence-depth patterns from 63,266 CpG sites using SacII enzyme digestion. A total of 191 patients with stage I-IV cancers (95 lung cancers and 96 colorectal cancers) and 126 noncancer participants were enrolled in this study. Our study showed an area under the receiver operating characteristic curve (AUC) of 0.978 with a sensitivity of 78.1% for colorectal cancer, and an AUC of 0.956 with a sensitivity of 66.3% for lung cancer, both at a specificity of 99.2%. For colorectal cancer, sensitivities for stages I-IV ranged from 76.2 to 83.3% while for lung cancer, sensitivities for stages I-IV ranged from 44.4 to 78.9%, both again at a specificity of 99.2%. The CSO model's true-positive rates were 94.4% and 89.9% for colorectal and lung cancers, respectively. The MRE-Seq was found to be a useful method for detecting global hypomethylation patterns in liquid biopsy samples and accurately diagnosing colorectal and lung cancers, as well as determining CSO of the cancer using DNN analysis.Trial registration: This trial was registered at ClinicalTrials.gov (registration number: NCT04253509) for lung cancer on 5 February 2020, https://clinicaltrials.gov/ct2/show/NCT04253509 . Colorectal cancer samples were retrospectively registered at CRIS (Clinical Research Information Service, registration number: KCT0008037) on 23 December 2022, https://cris.nih.go.kr , https://who.init/ictrp . Healthy control samples were retrospectively registered.
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Affiliation(s)
- Hyuk-Jung Kwon
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - Sun Hye Shin
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea
| | - Hyun Ho Kim
- Department of Surgery, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 327 Sosa-Ro, Bucheon, 14647, Republic of Korea
| | - Na Young Min
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - YuGyeong Lim
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - Tae-Woon Joo
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - Kyoung Joo Lee
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - Min-Seon Jeong
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - Hyojung Kim
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - Seon-Young Yun
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - YoonHee Kim
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - Dabin Park
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - Joungsu Joo
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - Jin-Sik Bae
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - Sunghoon Lee
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea
| | - Byeong-Ho Jeong
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea
| | - Kyungjong Lee
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea
| | - Hayemin Lee
- Department of Surgery, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 327 Sosa-Ro, Bucheon, 14647, Republic of Korea
| | - Hong Kwan Kim
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea
| | - Kyongchol Kim
- Gangnam Major Hospital, 452 Dogok-Ro, Gangnam-Gu, Seoul, 06279, Republic of Korea
| | - Sang-Won Um
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea.
| | - Changhyeok An
- Department of Surgery, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 327 Sosa-Ro, Bucheon, 14647, Republic of Korea.
| | - Min Seob Lee
- R&D Department, Eone-Diagnomics Genome Center, Inc., 143 Gaetbeol-Ro, Yeonsu-Gu, Incheon, 21999, Republic of Korea.
- Diagnomics, Inc., 5795 Kearny Villa Rd., San Diego, CA, 92123, USA.
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7
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McNamara ME, Loyfer N, Kiliti AJ, Schmidt MO, Shabi-Porat S, Jain SS, Martinez Roth S, McDeed AP, Shahrour N, Ballew E, Lin YT, Li HH, Deslattes Mays A, Rudra S, Riegel AT, Unger K, Kaplan T, Wellstein A. Circulating cell-free methylated DNA reveals tissue-specific, cellular damage from radiation treatment. JCI Insight 2023; 8:e156529. [PMID: 37318863 PMCID: PMC10443812 DOI: 10.1172/jci.insight.156529] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 05/31/2023] [Indexed: 06/17/2023] Open
Abstract
Radiation therapy is an effective cancer treatment, although damage to healthy tissues is common. Here we analyzed cell-free, methylated DNA released from dying cells into the circulation to evaluate radiation-induced cellular damage in different tissues. To map the circulating DNA fragments to human and mouse tissues, we established sequencing-based, cell-type-specific reference DNA methylation atlases. We found that cell-type-specific DNA blocks were mostly hypomethylated and located within signature genes of cellular identity. Cell-free DNA fragments were captured from serum samples by hybridization to CpG-rich DNA panels and mapped to the DNA methylation atlases. In a mouse model, thoracic radiation-induced tissue damage was reflected by dose-dependent increases in lung endothelial and cardiomyocyte methylated DNA in serum. The analysis of serum samples from patients with breast cancer undergoing radiation treatment revealed distinct dose-dependent and tissue-specific epithelial and endothelial responses to radiation across multiple organs. Strikingly, patients treated for right-sided breast cancers also showed increased hepatocyte and liver endothelial DNA in the circulation, indicating the impact on liver tissues. Thus, changes in cell-free methylated DNA can uncover cell-type-specific effects of radiation and provide a readout of the biologically effective radiation dose received by healthy tissues.
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Affiliation(s)
- Megan E. McNamara
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, USA
| | - Netanel Loyfer
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Amber J. Kiliti
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, USA
| | - Marcel O. Schmidt
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, USA
| | - Sapir Shabi-Porat
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Sidharth S. Jain
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, USA
| | - Sarah Martinez Roth
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, USA
| | - A. Patrick McDeed
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, USA
| | - Nesreen Shahrour
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, USA
| | | | - Yun-Tien Lin
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, USA
| | - Heng-Hong Li
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, USA
| | | | - Sonali Rudra
- Medstar Georgetown University Hospital, Washington DC, USA
| | - Anna T. Riegel
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, USA
| | - Keith Unger
- Medstar Georgetown University Hospital, Washington DC, USA
| | - Tommy Kaplan
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
- Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Anton Wellstein
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, USA
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8
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Li S, Zeng W, Ni X, Liu Q, Li W, Stackpole ML, Zhou Y, Gower A, Krysan K, Ahuja P, Lu DS, Raman SS, Hsu W, Aberle DR, Magyar CE, French SW, Han SHB, Garon EB, Agopian VG, Wong WH, Dubinett SM, Zhou XJ. Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring. Proc Natl Acad Sci U S A 2023; 120:e2305236120. [PMID: 37399400 PMCID: PMC10334733 DOI: 10.1073/pnas.2305236120] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 05/16/2023] [Indexed: 07/05/2023] Open
Abstract
Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.
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Affiliation(s)
- Shuo Li
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
| | - Weihua Zeng
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
| | - Xiaohui Ni
- EarlyDiagnostics Inc., Los Angeles, CA90095
| | - Qiao Liu
- Department of Statistics, Stanford University, Stanford, CA94305
| | - Wenyuan Li
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Institute for Quantitative & Computational Biosciences, University of California at Los Angeles, Los Angeles, CA90095
| | - Mary L. Stackpole
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- EarlyDiagnostics Inc., Los Angeles, CA90095
| | - Yonggang Zhou
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
| | - Arjan Gower
- Department of Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
| | - Kostyantyn Krysan
- Department of Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
- Veterans Administration (VA) Greater Los Angeles Health Care System, Los Angeles, CA90073
| | - Preeti Ahuja
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
| | - David S. Lu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
| | - Steven S. Raman
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
- Department of Surgery, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
| | - William Hsu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
| | - Denise R. Aberle
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Department of Bioengineering, University of California, Los Angeles, CA90095
| | - Clara E. Magyar
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
| | - Samuel W. French
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
| | - Steven-Huy B. Han
- Department of Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
| | - Edward B. Garon
- Department of Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
| | - Vatche G. Agopian
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
- Department of Surgery, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
| | - Wing Hung Wong
- Department of Statistics, Stanford University, Stanford, CA94305
- Department of Biomedical Data Science, Stanford University, Stanford, CA94305
| | - Steven M. Dubinett
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Department of Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
- Veterans Administration (VA) Greater Los Angeles Health Care System, Los Angeles, CA90073
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
| | - Xianghong Jasmine Zhou
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Institute for Quantitative & Computational Biosciences, University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
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9
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Keukeleire P, Makrodimitris S, Reinders M. Cell type deconvolution of methylated cell-free DNA at the resolution of individual reads. NAR Genom Bioinform 2023; 5:lqad048. [PMID: 37274121 PMCID: PMC10236360 DOI: 10.1093/nargab/lqad048] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 02/28/2023] [Accepted: 05/19/2023] [Indexed: 06/06/2023] Open
Abstract
Cell-free DNA (cfDNA) are DNA fragments originating from dying cells that are detectable in bodily fluids, such as the plasma. Accelerated cell death, for example caused by disease, induces an elevated concentration of cfDNA. As a result, determining the cell type origins of cfDNA molecules can provide information about an individual's health. In this work, we aim to increase the sensitivity of methylation-based cell type deconvolution by adapting an existing method, CelFiE, which uses the methylation beta values of individual CpG sites to estimate cell type proportions. Our new method, CelFEER, instead differentiates cell types by the average methylation values within individual reads. We additionally improved the originally reported performance of CelFiE by using a new approach for finding marker regions that are differentially methylated between cell types. We show that CelFEER estimates cell type proportions with a higher correlation (r = 0.94 ± 0.04) than CelFiE (r = 0.86 ± 0.09) on simulated mixtures of cell types. Moreover, we show that the cell type proportion estimated by CelFEER can differentiate between ALS patients and healthy controls, between pregnant women in their first and third trimester, and between pregnant women with and without gestational diabetes.
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Affiliation(s)
| | | | - Marcel Reinders
- To whom correspondence should be addressed. Tel: +31 15 27 86424;
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10
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LaSalle JM. Epigenomic signatures reveal mechanistic clues and predictive markers for autism spectrum disorder. Mol Psychiatry 2023; 28:1890-1901. [PMID: 36650278 PMCID: PMC10560404 DOI: 10.1038/s41380-022-01917-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 12/05/2022] [Accepted: 12/09/2022] [Indexed: 01/18/2023]
Abstract
Autism spectrum disorder (ASD) comprises a heterogeneous group of neurodevelopmental outcomes in children with a commonality in deficits in social communication and language combined with repetitive behaviors and interests. The etiology of ASD is heterogeneous, as several hundred genes have been implicated as well as multiple in utero environmental exposures. Over the past two decades, epigenetic investigations, including DNA methylation, have emerged as a novel way to capture the complex interface of multivariate ASD etiologies. More recently, epigenome-wide association studies using human brain and surrogate accessible tissues have revealed some convergent genes that are epigenetically altered in ASD, many of which overlap with known genetic risk factors. Unlike transcriptomes, epigenomic signatures defined by DNA methylation from surrogate tissues such as placenta and cord blood can reflect past differences in fetal brain gene transcription, transcription factor binding, and chromatin. For example, the discovery of NHIP (neuronal hypoxia inducible, placenta associated) through an epigenome-wide association in placenta, identified a common genetic risk for ASD that was modified by prenatal vitamin use. While epigenomic signatures are distinct between different genetic syndromic causes of ASD, bivalent chromatin and some convergent gene pathways are consistently epigenetically altered in both syndromic and idiopathic ASD, as well as some environmental exposures. Together, these epigenomic signatures hold promising clues towards improved early prediction and prevention of ASD as well genes and gene pathways to target for pharmacological interventions. Future advancements in single cell and multi-omic technologies, machine learning, as well as non-invasive screening of epigenomic signatures during pregnancy or newborn periods are expected to continue to impact the translatability of the recent discoveries in epigenomics to precision public health.
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Affiliation(s)
- Janine M LaSalle
- Department of Medical Microbiology and Immunology, Perinatal Origins of Disparities Center, MIND Institute, Genome Center, Environmental Health Sciences Center, University of California Davis, Davis, CA, USA.
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11
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Moser T, Kühberger S, Lazzeri I, Vlachos G, Heitzer E. Bridging biological cfDNA features and machine learning approaches. Trends Genet 2023; 39:285-307. [PMID: 36792446 DOI: 10.1016/j.tig.2023.01.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 01/10/2023] [Accepted: 01/19/2023] [Indexed: 02/15/2023]
Abstract
Liquid biopsies (LBs), particularly using circulating tumor DNA (ctDNA), are expected to revolutionize precision oncology and blood-based cancer screening. Recent technological improvements, in combination with the ever-growing understanding of cell-free DNA (cfDNA) biology, are enabling the detection of tumor-specific changes with extremely high resolution and new analysis concepts beyond genetic alterations, including methylomics, fragmentomics, and nucleosomics. The interrogation of a large number of markers and the high complexity of data render traditional correlation methods insufficient. In this regard, machine learning (ML) algorithms are increasingly being used to decipher disease- and tissue-specific signals from cfDNA. Here, we review recent insights into biological ctDNA features and how these are incorporated into sophisticated ML applications.
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Affiliation(s)
- Tina Moser
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria
| | - Stefan Kühberger
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria
| | - Isaac Lazzeri
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria
| | - Georgios Vlachos
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria
| | - Ellen Heitzer
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria.
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12
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Johnston AD, Ross JP, Ma C, Fung KYC, Locke WJ. Epigenetic liquid biopsies for minimal residual disease, what's around the corner? Front Oncol 2023; 13:1103797. [PMID: 37081990 PMCID: PMC10110851 DOI: 10.3389/fonc.2023.1103797] [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: 11/21/2022] [Accepted: 03/23/2023] [Indexed: 04/22/2023] Open
Abstract
Liquid biopsy assays for minimal residual disease (MRD) are used to monitor and inform oncological treatment and predict the risk of relapse in cancer patients. To-date, most MRD assay development has focused on targeting somatic mutations. However, epigenetic changes are more frequent and universal than genetic alterations in cancer and circulating tumor DNA (ctDNA) retains much of these changes. Here, we review the epigenetic signals that can be used to detect MRD, including DNA methylation alterations and fragmentation patterns that differentiate ctDNA from noncancerous circulating cell-free DNA (ccfDNA). We then summarize the current state of MRD monitoring; highlight the advantages of epigenetics over genetics-based approaches; and discuss the emerging paradigm of assaying both genetic and epigenetic targets to monitor treatment response, detect disease recurrence, and inform adjuvant therapy.
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13
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Mino-Kenudson M, Schalper K, Cooper W, Dacic S, Hirsch FR, Jain D, Lopez-Rios F, Tsao MS, Yatabe Y, Beasley MB, Yu H, Sholl LM, Brambilla E, Chou TY, Connolly C, Wistuba I, Kerr KM, Lantuejoul S. Predictive Biomarkers for Immunotherapy in Lung Cancer: Perspective From the International Association for the Study of Lung Cancer Pathology Committee. J Thorac Oncol 2022; 17:1335-1354. [PMID: 36184066 DOI: 10.1016/j.jtho.2022.09.109] [Citation(s) in RCA: 61] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 09/08/2022] [Accepted: 09/12/2022] [Indexed: 10/14/2022]
Abstract
Immunotherapy including immune checkpoint inhibitors (ICIs) has become the backbone of treatment for most lung cancers with advanced or metastatic disease. In addition, they have increasingly been used for early stage tumors in neoadjuvant and adjuvant settings. Unfortunately, however, only a subset of patients experiences meaningful response to ICIs. Although programmed death-ligand 1 (PD-L1) protein expression by immunohistochemistry (IHC) has played a role as the principal predictive biomarker for immunotherapy, its performance may not be optimal, and it suffers multiple practical issues with different companion diagnostic assays approved. Similarly, tumor mutational burden (TMB) has multiple technical issues as a predictive biomarker for ICIs. Now, ongoing research on tumor- and host immune-specific factors has identified immunotherapy biomarkers that may provide better response and prognosis prediction, in particular in a multimodal approach. This review by the International Association for the Study of Lung Cancer Pathology Committee provides an overview of various immunotherapy biomarkers, including updated data on PD-L1 IHC and TMB, and assessments of neoantigens, genetic and epigenetic signatures, immune microenvironment by IHC and transcriptomics, and microbiome and pathologic response to neoadjuvant immunotherapies. The aim of this review is to underline the efficacy of new individual or combined predictive biomarkers beyond PD-L1 IHC and TMB.
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Affiliation(s)
- Mari Mino-Kenudson
- Department of Pathology, Massachusetts General Hospital & Harvard Medical School, Boston, Massachusetts
| | - Kurt Schalper
- Department of Pathology, Yale University School of Medicine, New Haven, Connecticut
| | - Wendy Cooper
- Royal Prince Alfred Hospital, NSW Health Pathology and University of Sydney, Camperdown, Australia
| | - Sanja Dacic
- Department of Pathology, Yale University School of Medicine, New Haven, Connecticut
| | - Fred R Hirsch
- Center for Thoracic Oncology, The Tisch Cancer Institute, New York, New York; Icahn School of Medicine, Mount Sinai Health System, New York, New York
| | - Deepali Jain
- All India Institute of Medical Sciences, New Delhi, India
| | - Fernando Lopez-Rios
- Department of Pathology, "Doce de Octubre" University Hospital, Madrid, Spain
| | - Ming Sound Tsao
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | | | - Mary Beth Beasley
- Icahn School of Medicine, Mount Sinai Health System, New York, New York
| | - Hui Yu
- Center for Thoracic Oncology, The Tisch Cancer Institute, New York, New York; Icahn School of Medicine, Mount Sinai Health System, New York, New York
| | - Lynette M Sholl
- Department of Pathology, Brigham and Women's Hospital & Harvard Medical School, Boston, Massachusetts
| | | | | | - Casey Connolly
- International Association for the Study of Lung Cancer, Denver, Colorado
| | - Ignacio Wistuba
- The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Keith M Kerr
- Department of Pathology, Aberdeen Royal Infirmary, Aberdeen, United Kingdom
| | - Sylvie Lantuejoul
- Université Grenoble Alpes, Grenoble, France; Centre Léon Bérard Unicancer, Lyon, France.
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14
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The cell-free DNA methylome captures distinctions between localized and metastatic prostate tumors. Nat Commun 2022; 13:6467. [PMID: 36309516 PMCID: PMC9617856 DOI: 10.1038/s41467-022-34012-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 10/07/2022] [Indexed: 12/25/2022] Open
Abstract
Metastatic prostate cancer remains a major clinical challenge and metastatic lesions are highly heterogeneous and difficult to biopsy. Liquid biopsy provides opportunities to gain insights into the underlying biology. Here, using the highly sensitive enrichment-based sequencing technology, we provide analysis of 60 and 175 plasma DNA methylomes from patients with localized and metastatic prostate cancer, respectively. We show that the cell-free DNA methylome can capture variations beyond the tumor. A global hypermethylation in metastatic samples is observed, coupled with hypomethylation in the pericentromeric regions. Hypermethylation at the promoter of a glucocorticoid receptor gene NR3C1 is associated with a decreased immune signature. The cell-free DNA methylome is reflective of clinical outcomes and can distinguish different disease types with 0.989 prediction accuracy. Finally, we show the ability of predicting copy number alterations from the data, providing opportunities for joint genetic and epigenetic analysis on limited biological samples.
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15
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Oberhofer A, Bronkhorst AJ, Uhlig C, Ungerer V, Holdenrieder S. Tracing the Origin of Cell-Free DNA Molecules through Tissue-Specific Epigenetic Signatures. Diagnostics (Basel) 2022; 12:diagnostics12081834. [PMID: 36010184 PMCID: PMC9406971 DOI: 10.3390/diagnostics12081834] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 07/15/2022] [Accepted: 07/25/2022] [Indexed: 12/11/2022] Open
Abstract
All cell and tissue types constantly release DNA fragments into human body fluids by various mechanisms including programmed cell death, accidental cell degradation and active extrusion. Particularly, cell-free DNA (cfDNA) in plasma or serum has been utilized for minimally invasive molecular diagnostics. Disease onset or pathological conditions that lead to increased cell death alter the contribution of different tissues to the total pool of cfDNA. Because cfDNA molecules retain cell-type specific epigenetic features, it is possible to infer tissue-of-origin from epigenetic characteristics. Recent research efforts demonstrated that analysis of, e.g., methylation patterns, nucleosome occupancy, and fragmentomics determined the cell- or tissue-of-origin of individual cfDNA molecules. This novel tissue-of origin-analysis enables to estimate the contributions of different tissues to the total cfDNA pool in body fluids and find tissues with increased cell death (pathologic condition), expanding the portfolio of liquid biopsies towards a wide range of pathologies and early diagnosis. In this review, we summarize the currently available tissue-of-origin approaches and point out the next steps towards clinical implementation.
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16
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Sánchez-Herrero E, Serna-Blasco R, Robado de Lope L, González-Rumayor V, Romero A, Provencio M. Circulating Tumor DNA as a Cancer Biomarker: An Overview of Biological Features and Factors That may Impact on ctDNA Analysis. Front Oncol 2022; 12:943253. [PMID: 35936733 PMCID: PMC9350013 DOI: 10.3389/fonc.2022.943253] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 06/16/2022] [Indexed: 11/13/2022] Open
Abstract
Cancer cells release nucleic acids, freely or associated with other structures such as vesicles into body fluids, including blood. Among these nucleic acids, circulating tumor DNA (ctDNA) has emerged as a minimally invasive biomarker for tumor molecular profiling. However, certain biological characteristics of ctDNA are still unknown. Here, we provide an overview of the current knowledge about ctDNA biological features, including size and structure as well as the mechanisms of ctDNA shedding and clearance, and the physio-pathological factors that determine ctDNA levels. A better understanding of ctDNA biology is essential for the development of new methods that enable the analysis of ctDNA.
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Affiliation(s)
- Estela Sánchez-Herrero
- Liquid Biopsy Laboratory. Biomedical Sciences Research Institute Puerta de Hierro-Majadahonda, Majadahonda, Spain
- +D Department, Atrys Health, Barcelona, Spain
| | - Roberto Serna-Blasco
- Liquid Biopsy Laboratory. Biomedical Sciences Research Institute Puerta de Hierro-Majadahonda, Majadahonda, Spain
| | - Lucia Robado de Lope
- Liquid Biopsy Laboratory. Biomedical Sciences Research Institute Puerta de Hierro-Majadahonda, Majadahonda, Spain
| | | | - Atocha Romero
- Liquid Biopsy Laboratory. Biomedical Sciences Research Institute Puerta de Hierro-Majadahonda, Majadahonda, Spain
- Medical Oncology Department, Hospital Universitario Puerta de Hierro-Majadahonda, Majadahonda, Spain
- *Correspondence: Atocha Romero, ; orcid.org/0000-0002-1634-7397
| | - Mariano Provencio
- Liquid Biopsy Laboratory. Biomedical Sciences Research Institute Puerta de Hierro-Majadahonda, Majadahonda, Spain
- Medical Oncology Department, Hospital Universitario Puerta de Hierro-Majadahonda, Majadahonda, Spain
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17
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Chan HT, Chin YM, Low SK. Circulating Tumor DNA-Based Genomic Profiling Assays in Adult Solid Tumors for Precision Oncology: Recent Advancements and Future Challenges. Cancers (Basel) 2022; 14:3275. [PMID: 35805046 PMCID: PMC9265547 DOI: 10.3390/cancers14133275] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 06/30/2022] [Accepted: 07/02/2022] [Indexed: 12/04/2022] Open
Abstract
Genomic profiling using tumor biopsies remains the standard approach for the selection of approved molecular targeted therapies. However, this is often limited by its invasiveness, feasibility, and poor sample quality. Liquid biopsies provide a less invasive approach while capturing a contemporaneous and comprehensive tumor genomic profile. Recent advancements in the detection of circulating tumor DNA (ctDNA) from plasma samples at satisfactory sensitivity, specificity, and detection concordance to tumor tissues have facilitated the approval of ctDNA-based genomic profiling to be integrated into regular clinical practice. The recent approval of both single-gene and multigene assays to detect genetic biomarkers from plasma cell-free DNA (cfDNA) as companion diagnostic tools for molecular targeted therapies has transformed the therapeutic decision-making procedure for advanced solid tumors. Despite the increasing use of cfDNA-based molecular profiling, there is an ongoing debate about a 'plasma first' or 'tissue first' approach toward genomic testing for advanced solid malignancies. Both approaches present possible advantages and disadvantages, and these factors should be carefully considered to personalize and select the most appropriate genomic assay. This review focuses on the recent advancements of cfDNA-based genomic profiling assays in advanced solid tumors while highlighting the major challenges that should be tackled to formulate evidence-based guidelines in recommending the 'right assay for the right patient at the right time'.
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Affiliation(s)
- Hiu Ting Chan
- Project for Development of Liquid Biopsy Diagnosis, Cancer Precision Medicine Center, Japanese Foundation for Cancer Research, Tokyo 135-8550, Japan; (Y.M.C.); (S.-K.L.)
| | - Yoon Ming Chin
- Project for Development of Liquid Biopsy Diagnosis, Cancer Precision Medicine Center, Japanese Foundation for Cancer Research, Tokyo 135-8550, Japan; (Y.M.C.); (S.-K.L.)
- Cancer Precision Medicine, Inc., Kawasaki 213-0012, Japan
| | - Siew-Kee Low
- Project for Development of Liquid Biopsy Diagnosis, Cancer Precision Medicine Center, Japanese Foundation for Cancer Research, Tokyo 135-8550, Japan; (Y.M.C.); (S.-K.L.)
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18
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Guemri J, Pierre-Jean M, Brohard S, Oussada N, Horgues C, Bonnet E, Mauger F, Deleuze JF. Methylated ccfDNA from plasma biomarkers of Alzheimer's disease using targeted bisulfite sequencing. Epigenomics 2022; 14:451-468. [PMID: 35416052 DOI: 10.2217/epi-2021-0491] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: Noninvasive biomarkers such as methylated ccfDNA from plasma could help to support the diagnosis of Alzheimer's disease (AD). Methods: A targeted sequencing protocol was developed to identify candidate biomarkers of AD in methylated ccfDNA extracted from plasma. Results: The authors identified differentially methylated CpGs, regions of which were the same as those identified in previous AD studies. Specifically, a differentially methylated CpG of the LHX2 gene previously identified in a plasma study of AD was replicated in the study. The MBP and DUSP22 regions have been identified in other brain studies of AD and in the authors' study. Conclusion: Although these biomarkers must be validated in other cohorts, methylated ccfDNA could be a relevant noninvasive biomarker in AD.
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Affiliation(s)
- Julien Guemri
- Université Paris-Saclay, Commissariat à l'Energie Atomique et aux Energies Alternatives, Centre National de Recherche en Génomique Humaine, Evry, 91057, France
| | - Morgane Pierre-Jean
- Université Paris-Saclay, Commissariat à l'Energie Atomique et aux Energies Alternatives, Centre National de Recherche en Génomique Humaine, Evry, 91057, France
| | - Solène Brohard
- Université Paris-Saclay, Commissariat à l'Energie Atomique et aux Energies Alternatives, Centre National de Recherche en Génomique Humaine, Evry, 91057, France
| | - Nouara Oussada
- Université Paris-Saclay, Commissariat à l'Energie Atomique et aux Energies Alternatives, Centre National de Recherche en Génomique Humaine, Evry, 91057, France
| | - Caroline Horgues
- Université Paris-Saclay, Commissariat à l'Energie Atomique et aux Energies Alternatives, Centre National de Recherche en Génomique Humaine, Evry, 91057, France
| | - Eric Bonnet
- Université Paris-Saclay, Commissariat à l'Energie Atomique et aux Energies Alternatives, Centre National de Recherche en Génomique Humaine, Evry, 91057, France
| | - Florence Mauger
- Université Paris-Saclay, Commissariat à l'Energie Atomique et aux Energies Alternatives, Centre National de Recherche en Génomique Humaine, Evry, 91057, France
| | - Jean-François Deleuze
- Université Paris-Saclay, Commissariat à l'Energie Atomique et aux Energies Alternatives, Centre National de Recherche en Génomique Humaine, Evry, 91057, France
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19
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The Role of DNA Methylation and DNA Methyltransferases in Cancer. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1389:317-348. [DOI: 10.1007/978-3-031-11454-0_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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