1
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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; 102:291-298. [PMID: 38478957 DOI: 10.1139/bcb-2024-0004] [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] [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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2
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Qi T, Zhou Y, Sheng Y, Li Z, Yang Y, Liu Q, Ge Q. Prediction of Transcription Factor Binding Sites on Cell-Free DNA Based on Deep Learning. J Chem Inf Model 2024; 64:4002-4008. [PMID: 38798191 DOI: 10.1021/acs.jcim.4c00047] [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: 05/29/2024]
Abstract
Transcription factors (TFs) are important regulatory elements for vital cellular activities, and the identification of transcription factor binding sites (TFBS) can help to explore gene regulatory mechanisms. Research studies have proved that cfDNA (cell-free DNA) shows relatively higher coverage at TFBS due to the protection by TF from degradation by nucleases and short fragments of cfDNA are enriched in TFBS. However, there are still great difficulties in the noninvasive identification of TFBSs from experimental techniques. In this study, we propose a deep learning-based approach that can noninvasively predict TFBSs of cfDNA by learning sequence information from known TFBSs through convolutional neural networks. Under the addition of long short-term memory, our model achieved an area under the curve of 84%. Based on this model to predict cfDNA, we found consistent motifs in cfDNA fragments and lower coverage occurred upstream and downstream of these cfDNA fragments, which is consistent with a previous study. We also found that the binding sites of the same TF differ in different cell lines. TF-specific target genes were detected from cfDNA and were enriched in cancer-related pathways. In summary, our method of locating TFBSs from plasma has the potential to reflect the intrinsic regulatory mechanism from a noninvasive perspective and provide technical guidance for dynamic monitoring of disease in clinical practice.
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Affiliation(s)
- Ting Qi
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, People's Republic of China
| | - Ying Zhou
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, People's Republic of China
| | - Yuqi Sheng
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, People's Republic of China
| | - Zhihui Li
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, People's Republic of China
| | - Yuwei Yang
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, People's Republic of China
| | - Quanjun Liu
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, People's Republic of China
| | - Qinyu Ge
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, People's Republic of China
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3
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Toska E. Epigenetic mechanisms of cancer progression and therapy resistance in estrogen-receptor (ER+) breast cancer. Biochim Biophys Acta Rev Cancer 2024; 1879:189097. [PMID: 38518961 DOI: 10.1016/j.bbcan.2024.189097] [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: 01/08/2024] [Revised: 03/16/2024] [Accepted: 03/19/2024] [Indexed: 03/24/2024]
Abstract
Estrogen receptor-positive (ER+) breast cancer is the most frequent breast cancer subtype. Agents targeting the ER signaling pathway have been successful in reducing mortality from breast cancer for decades. However, mechanisms of resistance to these treatments arise, especially in the metastatic setting. Recently, it has been recognized that epigenetic dysregulation is a common feature that facilitates the acquisition of cancer hallmarks across cancer types, including ER+ breast cancer. Alterations in epigenetic regulators and transcription factors (TF) coupled with changes to the chromatin landscape have been found to orchestrate breast oncogenesis, metastasis, and the development of a resistant phenotype. Here, we review recent advances in our understanding of how the epigenome dictates breast cancer tumorigenesis and resistance to targeted therapies and discuss novel therapeutic interventions for overcoming resistance.
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Affiliation(s)
- Eneda Toska
- Sidney Kimmel Comprehensive Cancer Center and Department of Oncology, Johns Hopkins University, Baltimore, MD, USA; Department of Biochemistry and Molecular Biology, Johns Hopkins School of Public Health, Baltimore, MD, USA.
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4
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Hiatt JB, Doebley AL, Arnold HU, Adil M, Sandborg H, Persse TW, Ko M, Wu F, Quintanal Villalonga A, Santana-Davila R, Eaton K, Dive C, Rudin CM, Thomas A, Houghton AM, Ha G, MacPherson D. Molecular phenotyping of small cell lung cancer using targeted cfDNA profiling of transcriptional regulatory regions. SCIENCE ADVANCES 2024; 10:eadk2082. [PMID: 38598634 PMCID: PMC11006233 DOI: 10.1126/sciadv.adk2082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 02/27/2024] [Indexed: 04/12/2024]
Abstract
We report an approach for cancer phenotyping based on targeted sequencing of cell-free DNA (cfDNA) for small cell lung cancer (SCLC). In SCLC, differential activation of transcription factors (TFs), such as ASCL1, NEUROD1, POU2F3, and REST defines molecular subtypes. We designed a targeted capture panel that identifies chromatin organization signatures at 1535 TF binding sites and 13,240 gene transcription start sites and detects exonic mutations in 842 genes. Sequencing of cfDNA from SCLC patient-derived xenograft models captured TF activity and gene expression and revealed individual highly informative loci. Prediction models of ASCL1 and NEUROD1 activity using informative loci achieved areas under the receiver operating characteristic curve (AUCs) from 0.84 to 0.88 in patients with SCLC. As non-SCLC (NSCLC) often transforms to SCLC following targeted therapy, we applied our framework to distinguish NSCLC from SCLC and achieved an AUC of 0.99. Our approach shows promising utility for SCLC subtyping and transformation monitoring, with potential applicability to diverse tumor types.
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Affiliation(s)
- Joseph B. Hiatt
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Veterans Affairs Puget Sound Healthcare System - Seattle Branch, Seattle, WA, USA
- Division of Medical Oncology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Anna-Lisa Doebley
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, WA, USA
- Medical Scientist Training Program, University of Washington, Seattle, WA, USA
| | - Henry U. Arnold
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Mohamed Adil
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Holly Sandborg
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Thomas W. Persse
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Minjeong Ko
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Feinan Wu
- Genomics and Bioinformatics Shared Resource, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Alvaro Quintanal Villalonga
- Department of Medicine, Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Rafael Santana-Davila
- Division of Medical Oncology, Department of Medicine, University of Washington, Seattle, WA, USA
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Keith Eaton
- Division of Medical Oncology, Department of Medicine, University of Washington, Seattle, WA, USA
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Caroline Dive
- Cancer Research UK National Biomarker Centre, University of Manchester, Manchester, UK
| | - Charles M. Rudin
- Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Graduate Program in Pharmacology, Weill Cornell Medical College; New York, NY, USA
| | - Anish Thomas
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - A. McGarry Houghton
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Gavin Ha
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - David MacPherson
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
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5
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Ali M, Choudhary R, Singh K, Kumari S, Kumar R, Graham BB, Pasha MAQ, Rabyang S, Thinlas T, Mishra A. Hypobaric hypoxia modulated structural characteristics of circulating cell-free DNA in high-altitude pulmonary edema. Am J Physiol Lung Cell Mol Physiol 2024; 326:L496-L507. [PMID: 38349115 DOI: 10.1152/ajplung.00245.2023] [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: 08/01/2023] [Revised: 01/10/2024] [Accepted: 01/25/2024] [Indexed: 04/07/2024] Open
Abstract
The utility of cell-free (cf) DNA has extended as a surrogate or clinical biomarker for various diseases. However, a more profound and expanded understanding of the diverse cfDNA population and its correlation with physiological phenotypes and environmental factors is imperative for using its full potential. The high-altitude (HA; altitude > 2,500 m above sea level) environment characterized by hypobaric hypoxia offers an observational case-control design to study the differential cfDNA profile in patients with high-altitude pulmonary edema (HAPE) (number of subjects, n = 112) and healthy HA sojourners (n = 111). The present study investigated cfDNA characteristics such as concentration, fragment length size, degree of integrity, and subfractions reflecting mitochondrial-cfDNA copies in the two groups. The total cfDNA level was significantly higher in patients with HAPE, and the level increased with increasing HAPE severity (P = 0.0036). A lower degree of cfDNA integrity of 0.346 in patients with HAPE (P = 0.001) indicated the prevalence of shorter cfDNA fragments in circulation in patients compared with the healthy HA sojourners. A significant correlation of cfDNA characteristics with the peripheral oxygen saturation levels in the patient group demonstrated the translational relevance of cfDNA molecules. The correlation was further supported by multivariate logistic regression and receiver operating characteristic curve. To our knowledge, our study is the first to highlight the association of higher cfDNA concentration, a lower degree of cfDNA integrity, and increased mitochondrial-derived cfDNA population with HAPE disease severity. Further deep profiling of cfDNA fragments, which preserves cell-type specific genetic and epigenetic features, can provide dynamic physiological responses to hypoxia.NEW & NOTEWORTHY This study observed altered cell-free (cf) DNA fragment patterns in patients with high-altitude pulmonary edema and the significant correlation of these patterns with peripheral oxygen saturation levels. This suggests deep profiling of cfDNA fragments in the future may identify genetic and epigenetic mechanisms underlying physiological and pathophysiological responses to hypoxia.
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Affiliation(s)
- Manzoor Ali
- Cardio Respiratory Disease Unit, CSIR-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Raushni Choudhary
- Cardio Respiratory Disease Unit, CSIR-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Kanika Singh
- Cardio Respiratory Disease Unit, CSIR-Institute of Genomics and Integrative Biology, Delhi, India
| | - Swati Kumari
- Cardio Respiratory Disease Unit, CSIR-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Rahul Kumar
- Department of Medicine, University of California, San Francisco, California, United States
- Lung Biology Center, Zuckerberg San Francisco General Hospital, San Francisco, California, United States
| | - Brian B Graham
- Department of Medicine, University of California, San Francisco, California, United States
- Lung Biology Center, Zuckerberg San Francisco General Hospital, San Francisco, California, United States
| | | | - Stanzen Rabyang
- Department of Medicine, Sonam Norboo Memorial Hospital, Leh, India
| | - Tashi Thinlas
- Department of Medicine, Sonam Norboo Memorial Hospital, Leh, India
| | - Aastha Mishra
- Cardio Respiratory Disease Unit, CSIR-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
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6
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Moldovan N, van der Pol Y, van den Ende T, Boers D, Verkuijlen S, Creemers A, Ramaker J, Vu T, Bootsma S, Lenos KJ, Vermeulen L, Fransen MF, Pegtel M, Bahce I, van Laarhoven H, Mouliere F. Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis. Cell Rep Med 2024; 5:101349. [PMID: 38128532 PMCID: PMC10829758 DOI: 10.1016/j.xcrm.2023.101349] [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: 02/03/2023] [Revised: 09/22/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023]
Abstract
The structure of cell-free DNA (cfDNA) is altered in the blood of patients with cancer. From whole-genome sequencing, we retrieve the cfDNA fragment-end composition using a new software (FrEIA [fragment end integrated analysis]), as well as the cfDNA size and tumor fraction in three independent cohorts (n = 925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% cancer samples using at least one cfDNA measure, including 64% early-stage cancer (n = 220). cfDNA detection correlates with a shorter overall (p = 0.0086) and recurrence-free (p = 0.017) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n = 396 cancer, 90 controls) achieve a detection accuracy of 82% and area under the receiver operating characteristic curve of 0.96. In conclusion, harnessing the biological features of cfDNA can improve, at no extra cost, the diagnostic performance of liquid biopsies.
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Affiliation(s)
- Norbert Moldovan
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Ymke van der Pol
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Tom van den Ende
- Amsterdam UMC, University of Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Dries Boers
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Sandra Verkuijlen
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Aafke Creemers
- Amsterdam UMC, University of Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Jip Ramaker
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurosurgery, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Trang Vu
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Sanne Bootsma
- Amsterdam UMC, University of Amsterdam, Center for Experimental and Molecular Medicine, Laboratory for Experimental Oncology and Radiobiology, Amsterdam, the Netherlands; Cancer Center Amsterdam, Gastroenterology Endocrinology Metabolism, Amsterdam, the Netherlands; Oncode Institute, Amsterdam, the Netherlands
| | - Kristiaan J Lenos
- Amsterdam UMC, University of Amsterdam, Center for Experimental and Molecular Medicine, Laboratory for Experimental Oncology and Radiobiology, Amsterdam, the Netherlands; Cancer Center Amsterdam, Gastroenterology Endocrinology Metabolism, Amsterdam, the Netherlands; Oncode Institute, Amsterdam, the Netherlands
| | - Louis Vermeulen
- Amsterdam UMC, University of Amsterdam, Center for Experimental and Molecular Medicine, Laboratory for Experimental Oncology and Radiobiology, Amsterdam, the Netherlands; Cancer Center Amsterdam, Gastroenterology Endocrinology Metabolism, Amsterdam, the Netherlands; Oncode Institute, Amsterdam, the Netherlands
| | - Marieke F Fransen
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pulmonology, Cancer Centre Amsterdam, Amsterdam, the Netherlands
| | - Michiel Pegtel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Idris Bahce
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pulmonology, Cancer Centre Amsterdam, Amsterdam, the Netherlands
| | - Hanneke van Laarhoven
- Amsterdam UMC, University of Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Florent Mouliere
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands.
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7
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Will M, Liang J, Metcalfe C, Chandarlapaty S. Therapeutic resistance to anti-oestrogen therapy in breast cancer. Nat Rev Cancer 2023; 23:673-685. [PMID: 37500767 PMCID: PMC10529099 DOI: 10.1038/s41568-023-00604-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/29/2023] [Indexed: 07/29/2023]
Abstract
The hormone receptor oestrogen receptor-α (ER) orchestrates physiological mammary gland development, breast carcinogenesis and the progression of breast tumours into lethal, treatment-refractory systemic disease. Selective antagonism of ER signalling has been one of the most successful therapeutic approaches in oncology, benefiting patients as both a cancer preventative measure and a cancer treatment strategy. However, resistance to anti-oestrogen therapy is a major clinical challenge. Over the past decade, we have gained an understanding of how breast cancers evolve under the pressure of anti-oestrogen therapy. This is best depicted by the case of oestrogen-independent mutations in the gene encoding ER (ESR1), which are virtually absent in primary breast cancer but highly prevalent (20-40%) in anti-oestrogen-treated metastatic disease. These and other findings highlight the 'evolvability' of ER+ breast cancer and the need to understand molecular processes by which this evolution occurs. Recent development and approval of next-generation ER antagonists to target ESR1-mutant breast cancer underscores the clinical importance of this evolvability and sets a new paradigm for the treatment of ER+ breast cancers.
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Affiliation(s)
- Marie Will
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jackson Liang
- Department of Oncology Biomarker Development, Genentech, South San Francisco, CA, USA
| | - Ciara Metcalfe
- Department of Discovery Oncology, Genentech, South San Francisco, CA, USA.
| | - Sarat Chandarlapaty
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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8
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Helzer KT, Sharifi MN, Sperger JM, Shi Y, Annala M, Bootsma ML, Reese SR, Taylor A, Kaufmann KR, Krause HK, Schehr JL, Sethakorn N, Kosoff D, Kyriakopoulos C, Burkard ME, Rydzewski NR, Yu M, Harari PM, Bassetti M, Blitzer G, Floberg J, Sjöström M, Quigley DA, Dehm SM, Armstrong AJ, Beltran H, McKay RR, Feng FY, O'Regan R, Wisinski KB, Emamekhoo H, Wyatt AW, Lang JM, Zhao SG. Fragmentomic analysis of circulating tumor DNA-targeted cancer panels. Ann Oncol 2023; 34:813-825. [PMID: 37330052 PMCID: PMC10527168 DOI: 10.1016/j.annonc.2023.06.001] [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: 12/09/2022] [Revised: 05/30/2023] [Accepted: 06/06/2023] [Indexed: 06/19/2023] Open
Abstract
BACKGROUND The isolation of cell-free DNA (cfDNA) from the bloodstream can be used to detect and analyze somatic alterations in circulating tumor DNA (ctDNA), and multiple cfDNA-targeted sequencing panels are now commercially available for Food and Drug Administration (FDA)-approved biomarker indications to guide treatment. More recently, cfDNA fragmentation patterns have emerged as a tool to infer epigenomic and transcriptomic information. However, most of these analyses used whole-genome sequencing, which is insufficient to identify FDA-approved biomarker indications in a cost-effective manner. PATIENTS AND METHODS We used machine learning models of fragmentation patterns at the first coding exon in standard targeted cancer gene cfDNA sequencing panels to distinguish between cancer and non-cancer patients, as well as the specific tumor type and subtype. We assessed this approach in two independent cohorts: a published cohort from GRAIL (breast, lung, and prostate cancers, non-cancer, n = 198) and an institutional cohort from the University of Wisconsin (UW; breast, lung, prostate, bladder cancers, n = 320). Each cohort was split 70%/30% into training and validation sets. RESULTS In the UW cohort, training cross-validated accuracy was 82.1%, and accuracy in the independent validation cohort was 86.6% despite a median ctDNA fraction of only 0.06. In the GRAIL cohort, to assess how this approach performs in very low ctDNA fractions, training and independent validation were split based on ctDNA fraction. Training cross-validated accuracy was 80.6%, and accuracy in the independent validation cohort was 76.3%. In the validation cohort where the ctDNA fractions were all <0.05 and as low as 0.0003, the cancer versus non-cancer area under the curve was 0.99. CONCLUSIONS To our knowledge, this is the first study to demonstrate that sequencing from targeted cfDNA panels can be utilized to analyze fragmentation patterns to classify cancer types, dramatically expanding the potential capabilities of existing clinically used panels at minimal additional cost.
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Affiliation(s)
- K T Helzer
- Department of Human Oncology, University of Wisconsin, Madison
| | - M N Sharifi
- Carbone Cancer Center, University of Wisconsin, Madison; Department of Medicine, University of Wisconsin, Madison, USA
| | - J M Sperger
- Department of Medicine, University of Wisconsin, Madison, USA
| | - Y Shi
- Department of Human Oncology, University of Wisconsin, Madison
| | - M Annala
- Department of Urologic Sciences, Vancouver Prostate Centre, University of British Columbia, Vancouver, Canada; Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Center, Tampere, Finland
| | - M L Bootsma
- Department of Human Oncology, University of Wisconsin, Madison
| | - S R Reese
- Department of Human Oncology, University of Wisconsin, Madison; Department of Medicine, University of Wisconsin, Madison, USA
| | - A Taylor
- Department of Medicine, University of Wisconsin, Madison, USA
| | - K R Kaufmann
- Department of Medicine, University of Wisconsin, Madison, USA
| | - H K Krause
- Department of Medicine, University of Wisconsin, Madison, USA
| | - J L Schehr
- Carbone Cancer Center, University of Wisconsin, Madison
| | - N Sethakorn
- Carbone Cancer Center, University of Wisconsin, Madison; Department of Medicine, University of Wisconsin, Madison, USA
| | - D Kosoff
- Carbone Cancer Center, University of Wisconsin, Madison; Department of Medicine, University of Wisconsin, Madison, USA
| | - C Kyriakopoulos
- Carbone Cancer Center, University of Wisconsin, Madison; Department of Medicine, University of Wisconsin, Madison, USA
| | - M E Burkard
- Carbone Cancer Center, University of Wisconsin, Madison; Department of Medicine, University of Wisconsin, Madison, USA
| | - N R Rydzewski
- Department of Human Oncology, University of Wisconsin, Madison
| | - M Yu
- Carbone Cancer Center, University of Wisconsin, Madison; Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison
| | - P M Harari
- Department of Human Oncology, University of Wisconsin, Madison; Carbone Cancer Center, University of Wisconsin, Madison
| | - M Bassetti
- Department of Human Oncology, University of Wisconsin, Madison; Carbone Cancer Center, University of Wisconsin, Madison
| | - G Blitzer
- Department of Human Oncology, University of Wisconsin, Madison; Carbone Cancer Center, University of Wisconsin, Madison
| | - J Floberg
- Department of Human Oncology, University of Wisconsin, Madison; Carbone Cancer Center, University of Wisconsin, Madison
| | - M Sjöström
- Department of Radiation Oncology, University of California San Francisco, San Francisco; Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco
| | - D A Quigley
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco; Departments of Epidemiology and Biostatistics; Urology, University of California San Francisco, San Francisco
| | - S M Dehm
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
| | - A J Armstrong
- Duke Cancer Institute Center for Prostate and Urologic Cancers, Department of Medicine, Duke University, Durham
| | - H Beltran
- Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Boston
| | - R R McKay
- Moores Cancer Center, University of California San Diego, La Jolla
| | - F Y Feng
- Department of Radiation Oncology, University of California San Francisco, San Francisco; Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco; Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis; Division of Hematology and Oncology, Department of Medicine, University of California San Francisco, San Francisco
| | - R O'Regan
- Carbone Cancer Center, University of Wisconsin, Madison; Department of Medicine, University of Wisconsin, Madison, USA; Department of Medicine, University of Rochester, Rochester, USA
| | - K B Wisinski
- Carbone Cancer Center, University of Wisconsin, Madison; Department of Medicine, University of Wisconsin, Madison, USA
| | - H Emamekhoo
- Carbone Cancer Center, University of Wisconsin, Madison; Department of Medicine, University of Wisconsin, Madison, USA
| | - A W Wyatt
- Department of Urologic Sciences, Vancouver Prostate Centre, University of British Columbia, Vancouver, Canada; Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, Canada
| | - J M Lang
- Carbone Cancer Center, University of Wisconsin, Madison; Department of Medicine, University of Wisconsin, Madison, USA
| | - S G Zhao
- Department of Human Oncology, University of Wisconsin, Madison; Carbone Cancer Center, University of Wisconsin, Madison; William S. Middleton Memorial Veterans' Hospital, Madison, USA.
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9
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Shi D, Huang Y, Bai C. Studies of the Mechanism of Nucleosome Dynamics: A Review on Multifactorial Regulation from Computational and Experimental Cases. Polymers (Basel) 2023; 15:polym15071763. [PMID: 37050377 PMCID: PMC10096840 DOI: 10.3390/polym15071763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 03/28/2023] [Accepted: 03/31/2023] [Indexed: 04/05/2023] Open
Abstract
The nucleosome, which organizes the long coil of genomic DNA in a highly condensed, polymeric way, is thought to be the basic unit of chromosomal structure. As the most important protein–DNA complex, its structural and dynamic features have been successively revealed in recent years. However, its regulatory mechanism, which is modulated by multiple factors, still requires systemic discussion. This study summarizes the regulatory factors of the nucleosome’s dynamic features from the perspective of histone modification, DNA methylation, and the nucleosome-interacting factors (transcription factors and nucleosome-remodeling proteins and cations) and focuses on the research exploring the molecular mechanism through both computational and experimental approaches. The regulatory factors that affect the dynamic features of nucleosomes are also discussed in detail, such as unwrapping, wrapping, sliding, and stacking. Due to the complexity of the high-order topological structures of nucleosomes and the comprehensive effects of regulatory factors, the research on the functional modulation mechanism of nucleosomes has encountered great challenges. The integration of computational and experimental approaches, the construction of physical modes for nucleosomes, and the application of deep learning techniques will provide promising opportunities for further exploration.
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Affiliation(s)
- Danfeng Shi
- Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China
| | - Yuxin Huang
- Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China
| | - Chen Bai
- Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China
- Chenzhu (MoMeD) Biotechnology Co., Ltd., Hangzhou 310005, China
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10
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De Sarkar N, Patton RD, Doebley AL, Hanratty B, Adil M, Kreitzman AJ, Sarthy JF, Ko M, Brahma S, Meers MP, Janssens DH, Ang LS, Coleman IM, Bose A, Dumpit RF, Lucas JM, Nunez TA, Nguyen HM, McClure HM, Pritchard CC, Schweizer MT, Morrissey C, Choudhury AD, Baca SC, Berchuck JE, Freedman ML, Ahmad K, Haffner MC, Montgomery RB, Corey E, Henikoff S, Nelson PS, Ha G. Nucleosome Patterns in Circulating Tumor DNA Reveal Transcriptional Regulation of Advanced Prostate Cancer Phenotypes. Cancer Discov 2023; 13:632-653. [PMID: 36399432 PMCID: PMC9976992 DOI: 10.1158/2159-8290.cd-22-0692] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 10/01/2022] [Accepted: 11/16/2022] [Indexed: 11/19/2022]
Abstract
Advanced prostate cancers comprise distinct phenotypes, but tumor classification remains clinically challenging. Here, we harnessed circulating tumor DNA (ctDNA) to study tumor phenotypes by ascertaining nucleosome positioning patterns associated with transcription regulation. We sequenced plasma ctDNA whole genomes from patient-derived xenografts representing a spectrum of androgen receptor active (ARPC) and neuroendocrine (NEPC) prostate cancers. Nucleosome patterns associated with transcriptional activity were reflected in ctDNA at regions of genes, promoters, histone modifications, transcription factor binding, and accessible chromatin. We identified the activity of key phenotype-defining transcriptional regulators from ctDNA, including AR, ASCL1, HOXB13, HNF4G, and GATA2. To distinguish NEPC and ARPC in patient plasma samples, we developed prediction models that achieved accuracies of 97% for dominant phenotypes and 87% for mixed clinical phenotypes. Although phenotype classification is typically assessed by IHC or transcriptome profiling from tumor biopsies, we demonstrate that ctDNA provides comparable results with diagnostic advantages for precision oncology. SIGNIFICANCE This study provides insights into the dynamics of nucleosome positioning and gene regulation associated with cancer phenotypes that can be ascertained from ctDNA. New methods for classification in phenotype mixtures extend the utility of ctDNA beyond assessments of somatic DNA alterations with important implications for molecular classification and precision oncology. This article is highlighted in the In This Issue feature, p. 517.
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Affiliation(s)
- Navonil De Sarkar
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, Washington
- Department of Pathology and Prostate Cancer Center of Excellence, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Robert D. Patton
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Anna-Lisa Doebley
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
- Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, Washington
- Medical Scientist Training Program, University of Washington, Seattle, Washington
| | - Brian Hanratty
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Mohamed Adil
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Adam J. Kreitzman
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Jay F. Sarthy
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Minjeong Ko
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Sandipan Brahma
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Michael P. Meers
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Derek H. Janssens
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Lisa S. Ang
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Ilsa M. Coleman
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Arnab Bose
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Ruth F. Dumpit
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Jared M. Lucas
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Talina A. Nunez
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Holly M. Nguyen
- Department of Urology, University of Washington, Seattle, Washington
| | | | - Colin C. Pritchard
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
| | - Michael T. Schweizer
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Oncology, Department of Medicine, University of Washington, Seattle, Washington
| | - Colm Morrissey
- Department of Urology, University of Washington, Seattle, Washington
| | - Atish D. Choudhury
- Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Sylvan C. Baca
- Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | | | - Matthew L. Freedman
- Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Kami Ahmad
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Michael C. Haffner
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, Washington
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
| | - R. Bruce Montgomery
- Division of Oncology, Department of Medicine, University of Washington, Seattle, Washington
| | - Eva Corey
- Department of Urology, University of Washington, Seattle, Washington
| | - Steven Henikoff
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Howard Hughes Medical Institute, Chevy Chase, Maryland
| | - Peter S. Nelson
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, Washington
- Department of Urology, University of Washington, Seattle, Washington
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Division of Oncology, Department of Medicine, University of Washington, Seattle, Washington
- Corresponding Authors: Gavin Ha, Fred Hutchinson Cancer Center, 1100 Fairview Avenue North, Seattle, WA 98109. Phone: 206-667-2802; E-mail: ; and Peter S. Nelson, Fred Hutchinson Cancer Center, 1100 Fairview Avenue North, Seattle, WA 98109. Phone: 206-667-3377; E-mail:
| | - Gavin Ha
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Department of Genome Sciences, University of Washington, Seattle, Washington
- Corresponding Authors: Gavin Ha, Fred Hutchinson Cancer Center, 1100 Fairview Avenue North, Seattle, WA 98109. Phone: 206-667-2802; E-mail: ; and Peter S. Nelson, Fred Hutchinson Cancer Center, 1100 Fairview Avenue North, Seattle, WA 98109. Phone: 206-667-3377; E-mail:
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