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Gaiti F, Chaligne R, Gu H, Brand RM, Kothen-Hill S, Schulman R, Grigorev K, Risso D, Kim KT, Pastore A, Huang KY, Alonso A, Sheridan C, Omans ND, Biederstedt E, Clement K, Wang L, Felsenfeld JA, Bhavsar EB, Aryee MJ, Allan JN, Furman R, Gnirke A, Wu CJ, Meissner A, Landau DA. Epigenetic evolution and lineage histories of chronic lymphocytic leukaemia. Nature 2019; 569:576-580. [PMID: 31092926 PMCID: PMC6533116 DOI: 10.1038/s41586-019-1198-z] [Citation(s) in RCA: 162] [Impact Index Per Article: 32.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 04/12/2019] [Indexed: 11/22/2022]
Abstract
Genetic and epigenetic intra-tumoral heterogeneity cooperate to shape the evolutionary course of cancer1. Chronic lymphocytic leukaemia (CLL) is a highly informative model for cancer evolution as it undergoes substantial genetic diversification and evolution after therapy2,3. The CLL epigenome is also an important disease-defining feature4,5, and growing populations of cells in CLL diversify by stochastic changes in DNA methylation known as epimutations6. However, previous studies using bulk sequencing methods to analyse the patterns of DNA methylation were unable to determine whether epimutations affect CLL populations homogeneously. Here, to measure the epimutation rate at single-cell resolution, we applied multiplexed single-cell reduced-representation bisulfite sequencing to B cells from healthy donors and patients with CLL. We observed that the common clonal origin of CLL results in a consistently increased epimutation rate, with low variability in the cell-to-cell epimutation rate. By contrast, variable epimutation rates across healthy B cells reflect diverse evolutionary ages across the trajectory of B cell differentiation, consistent with epimutations serving as a molecular clock. Heritable epimutation information allowed us to reconstruct lineages at high-resolution with single-cell data, and to apply this directly to patient samples. The CLL lineage tree shape revealed earlier branching and longer branch lengths than in normal B cells, reflecting rapid drift after the initial malignant transformation and a greater proliferative history. Integration of single-cell bisulfite sequencing analysis with single-cell transcriptomes and genotyping confirmed that genetic subclones mapped to distinct clades, as inferred solely on the basis of epimutation information. Finally, to examine potential lineage biases during therapy, we profiled serial samples during ibrutinib-associated lymphocytosis, and identified clades of cells that were preferentially expelled from the lymph node after treatment, marked by distinct transcriptional profiles. The single-cell integration of genetic, epigenetic and transcriptional information thus charts the lineage history of CLL and its evolution with therapy.
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Affiliation(s)
- Federico Gaiti
- New York Genome Center, New York, NY, 10013, USA,Weill Cornell Medicine, New York, NY, 10021, USA
| | - Ronan Chaligne
- New York Genome Center, New York, NY, 10013, USA,Weill Cornell Medicine, New York, NY, 10021, USA
| | - Hongcang Gu
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Ryan Matthew Brand
- New York Genome Center, New York, NY, 10013, USA,Weill Cornell Medicine, New York, NY, 10021, USA
| | - Steven Kothen-Hill
- New York Genome Center, New York, NY, 10013, USA,Weill Cornell Medicine, New York, NY, 10021, USA
| | - Rafael Schulman
- New York Genome Center, New York, NY, 10013, USA,Weill Cornell Medicine, New York, NY, 10021, USA
| | | | - Davide Risso
- Weill Cornell Medicine, New York, NY, 10021, USA,Department of Statistical Sciences, University of Padova, Padova, 35121, Italy
| | - Kyu-Tae Kim
- New York Genome Center, New York, NY, 10013, USA,Weill Cornell Medicine, New York, NY, 10021, USA
| | - Alessandro Pastore
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Kevin Y. Huang
- New York Genome Center, New York, NY, 10013, USA,Weill Cornell Medicine, New York, NY, 10021, USA
| | | | | | - Nathaniel D. Omans
- New York Genome Center, New York, NY, 10013, USA,Weill Cornell Medicine, New York, NY, 10021, USA
| | - Evan Biederstedt
- New York Genome Center, New York, NY, 10013, USA,Weill Cornell Medicine, New York, NY, 10021, USA
| | - Kendell Clement
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Lili Wang
- Department of Pathology, Massachusetts General Hospital, Boston, MA, 02114, USA,Beckman Research Institute, City of Hope, Monrovia, CA, 91016, USA
| | | | | | - Martin J. Aryee
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA,Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | | | | | - Andreas Gnirke
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Catherine J. Wu
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA,Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Alexander Meissner
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA,Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
| | - Dan A. Landau
- New York Genome Center, New York, NY, 10013, USA,Weill Cornell Medicine, New York, NY, 10021, USA,Corresponding author: Dan A. Landau, MD, PhD, Weill Cornell Medicine, Belfer Research Building, 413 East 69th Street, New York, NY 10021,
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Zviran A, Hill ST, Schulman R, Shah M, Deochand S, Ha G, Reed S, Rotem D, Gydush G, Rhoades J, Huang K, Liao W, Maloney D, Omans N, Malbari M, Spinelli CF, Kazancioglu S, Robine N, Adalsteinsson V, Houck-Loomis B, Altorki N, Landau DA. Abstract 3247: Genome-wide cell-free DNA mutation integration for sensitive cancer detection. Cancer Res 2018. [DOI: 10.1158/1538-7445.am2018-3247] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Solid malignancies are often diagnosed at a late stage with dismal prognosis. Even after cancer is diagnosed, we lack sensitive tools to guide difficult therapeutic decisions such as adjuvant therapy. Sensitive cancer detection by blood biopsy can therefore transform care by enabling early detection and residual disease monitoring.
Cell free DNA mutation detection has shown significant promise in its ability to survey the somatic genome and enable detection of cancer mutations in the peripheral blood. However, the combination of low tumor fraction and limiting number of DNA fragments in a typical plasma sample, restrict the probability of detecting early stage cancer in cfDNA through current deep targeted sequencing methods.
Focusing on non-small cell lung cancer (NSCLC), we reasoned that we would need to supplant depth of sequencing with breadth of sequencing to overcome the fundamental limitation of low input of cfDNA. To do so, we apply whole genome sequencing (WGS) that allows us to base sensitive detection on the cumulative signal provided by 10,000-30,000 somatic mutations observed in a substantial proportion of NSCLC. We developed an analytic method that integrates genome-wide mutation signal to obtain a tumor fraction (TF) estimate, and thus allow sensitive detection of residual disease and quantitative dynamic monitoring of disease burden. Benchmarking on artificial plasma showed TF detection sensitivity as low as 1:100,000, two orders of magnitude more sensitive than currently available methods.
To test this method, we performed WGS on resected NSCLC and matched germline samples of 8 NSCLC patients, as well as on matched pre- and post-surgery cfDNA. Patient-specific somatic mutations were identified in the tumor/normal pairs and used for the estimation of TF in the matched plasma samples. We detect pre-surgery circulating tumor DNA (ctDNA) in all of the early-stage pre-operative samples and in ~40% post-operative patients, correlated with post-operative disease progression.
In early cancer detection, tumor DNA is not available, requiring de-novo mutation detection in cfDNA. To do so, we first trained a convolutional neuronal network to distinguish between cancer altered sequencing reads and reads affected by sequencing errors. This was followed by genome-wide pattern matching to a specific genomic signature that mark lung cancer mutations (Tobacco signature) indicating the presence of ctDNA in the patient plasma. Applying this method to the pre-operative early stage lung cancer samples and plasma samples from 5 patients with benign nodules (CT-detected) showed an accurate discrimination between malignant and benign nodules, suggesting a potential role in improving the positive predictive value of lung cancer screening in at-risk populations.
These results show that genome-wide mutation integration is a promising novel approach for ultra-sensitive early detection and residual disease monitoring.
Citation Format: Asaf Zviran, Steven T. Hill, Rafael Schulman, Minita Shah, Sunil Deochand, Gavin Ha, Sarah Reed, Denisse Rotem, Greg Gydush, Justin Rhoades, Kevin Huang, Will Liao, Dillon Maloney, Nathan Omans, Murtaza Malbari, Cathy F. Spinelli, Selena Kazancioglu, Nicolas Robine, Viktor Adalsteinsson, Brian Houck-Loomis, Nasser Altorki, Dan A. Landau. Genome-wide cell-free DNA mutation integration for sensitive cancer detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3247.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | - Will Liao
- 1New York Genome Center, New York, NY
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Moorhead JC, Gallery ME, Mannle T, Chaney WC, Conrad LC, Dalsey WC, Herman S, Hockberger RS, McDonald SC, Packard DC, Rapp MT, Rorrie CC, Schafermeyer RW, Schulman R, Whitehead DC, Hirschkorn C, Hogan P. A study of the workforce in emergency medicine. Ann Emerg Med 1998; 31:595-607. [PMID: 9581144 DOI: 10.1016/s0196-0644(98)70207-0] [Citation(s) in RCA: 53] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
STUDY OBJECTIVE Emergency medicine has progressed significantly since its initial recognition as a medical specialty. Relatively little factual information is known, however, regarding who or how many physicians practice emergency medicine. The purpose of this study is to determine the total number of physicians practicing clinical emergency medicine during a specified period, to describe certain characteristics of those individuals, and to estimate the total number of full-time equivalents (FTEs), as well as the total number of individuals needed to staff those FTEs. METHODS Data were gathered from a survey of a random sample of 2,062 hospitals drawn from a population of 5,220 hospitals reported by the American Hospital Association as having, or potentially having, an emergency department. The survey instrument addressed items such as descriptive data on the institution, enumeration of physicians in the ED, as well as the total number working during the period June 1, 1997, through June 14, 1997. Demographic data on the individuals were also collected. RESULTS A total of 942 hospitals responded (a 45.7% return rate). These hospitals reported a total of 5,872 physicians were working during the specified period, or an average of 7.48 persons scheduled per institution. The physicians were scheduled for a total of 297,062 hours. The average standard for FTE was 40 clinical hours per week. This equates to 3,713 FTEs or 4.96 FTEs per institution. The ratio of persons to FTEs was 1.51:1. With regard to demographics, 83% of the physicians were men and 81% were white. Their average age was 42 years. As to professional credentials, 58% were emergency medicine-residency trained and 53% were board certified in emergency medicine; 46% were certified by the American Board of Emergency Medicine. CONCLUSION Given that there are 4,945 hospitals with EDs and given that the data indicate there are 4.96 FTEs per ED, the total number of FTEs is projected to be 24,548 (standard error = 437). Given further that the data indicate a physician/FTE ratio of 1.51:1, we conclude that there are 36,990 persons (standard error = 683) needed to staff those FTEs. When adjusted for persons working at more than one ED, that number is reduced to 32,026.
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Affiliation(s)
- J C Moorhead
- American College of Emergency Physicians, Dallas, TX, USA
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