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Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer
We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethy...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5957518/ https://www.ncbi.nlm.nih.gov/pubmed/29625048 http://dx.doi.org/10.1016/j.cell.2018.03.022 |
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author | Hoadley, Katherine A. Yau, Christina Hinoue, Toshinori Wolf, Denise M. Lazar, Alexander J. Drill, Esther Shen, Ronglai Taylor, Alison M. Cherniack, Andrew D. Thorsson, Vésteinn Akbani, Rehan Bowlby, Reanne Wong, Christopher K. Wiznerowicz, Maciej Sanchez-Vega, Francisco Robertson, A. Gordon Schneider, Barbara G. Lawrence, Michael S. Noushmehr, Houtan Malta, Tathiane M. Stuart, Joshua M. Benz, Christopher C. Laird, Peter W. |
author_facet | Hoadley, Katherine A. Yau, Christina Hinoue, Toshinori Wolf, Denise M. Lazar, Alexander J. Drill, Esther Shen, Ronglai Taylor, Alison M. Cherniack, Andrew D. Thorsson, Vésteinn Akbani, Rehan Bowlby, Reanne Wong, Christopher K. Wiznerowicz, Maciej Sanchez-Vega, Francisco Robertson, A. Gordon Schneider, Barbara G. Lawrence, Michael S. Noushmehr, Houtan Malta, Tathiane M. Stuart, Joshua M. Benz, Christopher C. Laird, Peter W. |
author_sort | Hoadley, Katherine A. |
collection | PubMed |
description | We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development. |
format | Online Article Text |
id | pubmed-5957518 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
record_format | MEDLINE/PubMed |
spelling | pubmed-59575182019-04-05 Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer Hoadley, Katherine A. Yau, Christina Hinoue, Toshinori Wolf, Denise M. Lazar, Alexander J. Drill, Esther Shen, Ronglai Taylor, Alison M. Cherniack, Andrew D. Thorsson, Vésteinn Akbani, Rehan Bowlby, Reanne Wong, Christopher K. Wiznerowicz, Maciej Sanchez-Vega, Francisco Robertson, A. Gordon Schneider, Barbara G. Lawrence, Michael S. Noushmehr, Houtan Malta, Tathiane M. Stuart, Joshua M. Benz, Christopher C. Laird, Peter W. Cell Article We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development. 2018-04-05 /pmc/articles/PMC5957518/ /pubmed/29625048 http://dx.doi.org/10.1016/j.cell.2018.03.022 Text en This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Hoadley, Katherine A. Yau, Christina Hinoue, Toshinori Wolf, Denise M. Lazar, Alexander J. Drill, Esther Shen, Ronglai Taylor, Alison M. Cherniack, Andrew D. Thorsson, Vésteinn Akbani, Rehan Bowlby, Reanne Wong, Christopher K. Wiznerowicz, Maciej Sanchez-Vega, Francisco Robertson, A. Gordon Schneider, Barbara G. Lawrence, Michael S. Noushmehr, Houtan Malta, Tathiane M. Stuart, Joshua M. Benz, Christopher C. Laird, Peter W. Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer |
title | Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer |
title_full | Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer |
title_fullStr | Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer |
title_full_unstemmed | Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer |
title_short | Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer |
title_sort | cell-of-origin patterns dominate the molecular classification of 10,000 tumors from 33 types of cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5957518/ https://www.ncbi.nlm.nih.gov/pubmed/29625048 http://dx.doi.org/10.1016/j.cell.2018.03.022 |
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