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Aberrant DNA methylation defines isoform usage in cancer, with functional implications
Alternative transcript isoforms are common in tumors and act as potential drivers of cancer. Mechanisms determining altered isoform expression include somatic mutations in splice regulatory sites or altered splicing factors. However, since DNA methylation is known to regulate transcriptional isoform...
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| Published in: | PLoS computational biology 2019-07, Vol.15 (7), p.e1007095-e1007095 |
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| description | Alternative transcript isoforms are common in tumors and act as potential drivers of cancer. Mechanisms determining altered isoform expression include somatic mutations in splice regulatory sites or altered splicing factors. However, since DNA methylation is known to regulate transcriptional isoform activity in normal cells, we predicted the highly dysregulated patterns of DNA methylation present in cancer also affect isoform activity. We analyzed DNA methylation and RNA-seq isoform data from 18 human cancer types and found frequent correlations specifically within 11 cancer types. Examining the top 25% of variable methylation sites revealed that the location of the methylated CpG site in a gene determined which isoform was used. In addition, the correlated methylation-isoform patterns classified tumors into known subtypes and predicted distinct protein functions between tumor subtypes. Finally, methylation-correlated isoforms were enriched for oncogenes, tumor suppressors, and cancer-related pathways. These findings provide new insights into the functional impact of dysregulated DNA methylation in cancer and highlight the relationship between the epigenome and transcriptome. |
| doi_str_mv | 10.1371/journal.pcbi.1007095 |
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Mechanisms determining altered isoform expression include somatic mutations in splice regulatory sites or altered splicing factors. However, since DNA methylation is known to regulate transcriptional isoform activity in normal cells, we predicted the highly dysregulated patterns of DNA methylation present in cancer also affect isoform activity. We analyzed DNA methylation and RNA-seq isoform data from 18 human cancer types and found frequent correlations specifically within 11 cancer types. Examining the top 25% of variable methylation sites revealed that the location of the methylated CpG site in a gene determined which isoform was used. In addition, the correlated methylation-isoform patterns classified tumors into known subtypes and predicted distinct protein functions between tumor subtypes. Finally, methylation-correlated isoforms were enriched for oncogenes, tumor suppressors, and cancer-related pathways. These findings provide new insights into the functional impact of dysregulated DNA methylation in cancer and highlight the relationship between the epigenome and transcriptome.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1007095</identifier><identifier>PMID: 31329578</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Alternative Splicing ; Binding sites ; Bioinformatics ; Biology and life sciences ; Cancer ; Cancer genetics ; Cell growth ; Computational Biology ; Correlation ; CpG Islands ; Deoxyribonucleic acid ; DNA ; DNA Methylation ; Endometrial cancer ; Female ; Gene expression ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Genes ; Genetic aspects ; Genomes ; Genomics ; Head & neck cancer ; Health aspects ; Humans ; Isoforms ; Male ; Medicine and Health Sciences ; Methylation ; Motor vehicle drivers ; Mutation ; Neoplasm Proteins - genetics ; Neoplasm Proteins - metabolism ; Neoplasms - classification ; Neoplasms - genetics ; Neoplasms - metabolism ; Protein Isoforms - genetics ; Protein Isoforms - metabolism ; Proteins ; Ribonucleic acid ; RNA ; RNA polymerase ; RNA, Neoplasm - genetics ; RNA, Neoplasm - metabolism ; Sequence Analysis, RNA ; Splicing ; Splicing factors ; Squamous cell carcinoma ; Suppressors ; Transcription ; Transcription (Genetics) ; Transcription Initiation Site ; Transcription Termination, Genetic ; Tumorigenesis ; Tumors</subject><ispartof>PLoS computational biology, 2019-07, Vol.15 (7), p.e1007095-e1007095</ispartof><rights>COPYRIGHT 2019 Public Library of Science</rights><rights>This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. 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Mechanisms determining altered isoform expression include somatic mutations in splice regulatory sites or altered splicing factors. However, since DNA methylation is known to regulate transcriptional isoform activity in normal cells, we predicted the highly dysregulated patterns of DNA methylation present in cancer also affect isoform activity. We analyzed DNA methylation and RNA-seq isoform data from 18 human cancer types and found frequent correlations specifically within 11 cancer types. Examining the top 25% of variable methylation sites revealed that the location of the methylated CpG site in a gene determined which isoform was used. In addition, the correlated methylation-isoform patterns classified tumors into known subtypes and predicted distinct protein functions between tumor subtypes. Finally, methylation-correlated isoforms were enriched for oncogenes, tumor suppressors, and cancer-related pathways. These findings provide new insights into the functional impact of dysregulated DNA methylation in cancer and highlight the relationship between the epigenome and transcriptome.</description><subject>Alternative Splicing</subject><subject>Binding sites</subject><subject>Bioinformatics</subject><subject>Biology and life sciences</subject><subject>Cancer</subject><subject>Cancer genetics</subject><subject>Cell growth</subject><subject>Computational Biology</subject><subject>Correlation</subject><subject>CpG Islands</subject><subject>Deoxyribonucleic acid</subject><subject>DNA</subject><subject>DNA Methylation</subject><subject>Endometrial cancer</subject><subject>Female</subject><subject>Gene expression</subject><subject>Gene Expression Profiling</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Genes</subject><subject>Genetic aspects</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Head & neck cancer</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Isoforms</subject><subject>Male</subject><subject>Medicine and Health Sciences</subject><subject>Methylation</subject><subject>Motor vehicle drivers</subject><subject>Mutation</subject><subject>Neoplasm Proteins - genetics</subject><subject>Neoplasm Proteins - metabolism</subject><subject>Neoplasms - classification</subject><subject>Neoplasms - genetics</subject><subject>Neoplasms - metabolism</subject><subject>Protein Isoforms - genetics</subject><subject>Protein Isoforms - metabolism</subject><subject>Proteins</subject><subject>Ribonucleic acid</subject><subject>RNA</subject><subject>RNA polymerase</subject><subject>RNA, Neoplasm - genetics</subject><subject>RNA, Neoplasm - metabolism</subject><subject>Sequence Analysis, RNA</subject><subject>Splicing</subject><subject>Splicing factors</subject><subject>Squamous cell carcinoma</subject><subject>Suppressors</subject><subject>Transcription</subject><subject>Transcription (Genetics)</subject><subject>Transcription Initiation Site</subject><subject>Transcription Termination, Genetic</subject><subject>Tumorigenesis</subject><subject>Tumors</subject><issn>1553-7358</issn><issn>1553-734X</issn><issn>1553-7358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqVkk1v1DAQhiMEoqXwDxBE4gJSd_HEcZxckFYFykpVkfi6Wo4zznqV2Fs7Afrvcbpp1UVckA8ejZ9558OTJM-BLIFyeLt1o7eyW-5UbZZACCcVe5AcA2N0wSkrH96zj5InIWwJiWZVPE6OKNCsYrw8Tn6savRe2iF9f7lKexw2150cjLNpg9pYDKkJTjvfp2OQLabGpkpahf40_WWGTapHqyZcdqnpd51RN8HhafJIyy7gs_k-Sb5__PDt7NPi4vP5-mx1sVAFpcNCN8DqQhOQGiskTLKSFo1WvIFaA2BD8qaqqcaCszLLUEFZc4CaY0lYnjN6krzc6-46F8Q8kiCyjOd5bDbjkVjvicbJrdh500t_LZw04sbhfCukH4zqUNCcQVVkSGPWXJKy1hxlJcuKNwwyUketd3O2se6xUWgHL7sD0cMXazaidT9FEesHmIp5PQt4dzViGERvgsKukxbdONVdlBQKABrRV3-h_-5uuadaGRswVruYV8XTYG-Us_EPo3_FKgYlpWQa2JuDgMgM-Hto5RiCWH_98h_s5SGb71nlXQge9d1UgIhpX2_LF9O-inlfY9iL-xO9C7pdUPoHNfDm7g</recordid><startdate>20190701</startdate><enddate>20190701</enddate><creator>Chen, Yun-Ching</creator><creator>Elnitski, Laura</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISN</scope><scope>ISR</scope><scope>3V.</scope><scope>7QO</scope><scope>7QP</scope><scope>7TK</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>LK8</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-1065-019X</orcidid><orcidid>https://orcid.org/0000-0002-5342-083X</orcidid></search><sort><creationdate>20190701</creationdate><title>Aberrant DNA methylation defines isoform usage in cancer, with functional implications</title><author>Chen, Yun-Ching ; Elnitski, Laura</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c633t-fd15b6f01afe9e05a5836dfc7d1bf11ed04d9b3fe675822ec18b711b7e8054453</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Alternative Splicing</topic><topic>Binding sites</topic><topic>Bioinformatics</topic><topic>Biology and life sciences</topic><topic>Cancer</topic><topic>Cancer genetics</topic><topic>Cell growth</topic><topic>Computational Biology</topic><topic>Correlation</topic><topic>CpG Islands</topic><topic>Deoxyribonucleic acid</topic><topic>DNA</topic><topic>DNA Methylation</topic><topic>Endometrial cancer</topic><topic>Female</topic><topic>Gene expression</topic><topic>Gene Expression Profiling</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Genes</topic><topic>Genetic aspects</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Head & neck cancer</topic><topic>Health aspects</topic><topic>Humans</topic><topic>Isoforms</topic><topic>Male</topic><topic>Medicine and Health Sciences</topic><topic>Methylation</topic><topic>Motor vehicle drivers</topic><topic>Mutation</topic><topic>Neoplasm Proteins - genetics</topic><topic>Neoplasm Proteins - metabolism</topic><topic>Neoplasms - classification</topic><topic>Neoplasms - genetics</topic><topic>Neoplasms - metabolism</topic><topic>Protein Isoforms - genetics</topic><topic>Protein Isoforms - metabolism</topic><topic>Proteins</topic><topic>Ribonucleic acid</topic><topic>RNA</topic><topic>RNA polymerase</topic><topic>RNA, Neoplasm - genetics</topic><topic>RNA, Neoplasm - metabolism</topic><topic>Sequence Analysis, RNA</topic><topic>Splicing</topic><topic>Splicing factors</topic><topic>Squamous cell carcinoma</topic><topic>Suppressors</topic><topic>Transcription</topic><topic>Transcription (Genetics)</topic><topic>Transcription Initiation Site</topic><topic>Transcription Termination, Genetic</topic><topic>Tumorigenesis</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Yun-Ching</creatorcontrib><creatorcontrib>Elnitski, Laura</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Canada</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Open Access: DOAJ - Directory of Open Access Journals</collection><jtitle>PLoS computational biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Yun-Ching</au><au>Elnitski, Laura</au><au>Ioshikhes, Ilya</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Aberrant DNA methylation defines isoform usage in cancer, with functional implications</atitle><jtitle>PLoS computational biology</jtitle><addtitle>PLoS Comput Biol</addtitle><date>2019-07-01</date><risdate>2019</risdate><volume>15</volume><issue>7</issue><spage>e1007095</spage><epage>e1007095</epage><pages>e1007095-e1007095</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><abstract>Alternative transcript isoforms are common in tumors and act as potential drivers of cancer. Mechanisms determining altered isoform expression include somatic mutations in splice regulatory sites or altered splicing factors. However, since DNA methylation is known to regulate transcriptional isoform activity in normal cells, we predicted the highly dysregulated patterns of DNA methylation present in cancer also affect isoform activity. We analyzed DNA methylation and RNA-seq isoform data from 18 human cancer types and found frequent correlations specifically within 11 cancer types. Examining the top 25% of variable methylation sites revealed that the location of the methylated CpG site in a gene determined which isoform was used. In addition, the correlated methylation-isoform patterns classified tumors into known subtypes and predicted distinct protein functions between tumor subtypes. Finally, methylation-correlated isoforms were enriched for oncogenes, tumor suppressors, and cancer-related pathways. These findings provide new insights into the functional impact of dysregulated DNA methylation in cancer and highlight the relationship between the epigenome and transcriptome.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>31329578</pmid><doi>10.1371/journal.pcbi.1007095</doi><orcidid>https://orcid.org/0000-0003-1065-019X</orcidid><orcidid>https://orcid.org/0000-0002-5342-083X</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Alternative Splicing Binding sites Bioinformatics Biology and life sciences Cancer Cancer genetics Cell growth Computational Biology Correlation CpG Islands Deoxyribonucleic acid DNA DNA Methylation Endometrial cancer Female Gene expression Gene Expression Profiling Gene Expression Regulation, Neoplastic Genes Genetic aspects Genomes Genomics Head & neck cancer Health aspects Humans Isoforms Male Medicine and Health Sciences Methylation Motor vehicle drivers Mutation Neoplasm Proteins - genetics Neoplasm Proteins - metabolism Neoplasms - classification Neoplasms - genetics Neoplasms - metabolism Protein Isoforms - genetics Protein Isoforms - metabolism Proteins Ribonucleic acid RNA RNA polymerase RNA, Neoplasm - genetics RNA, Neoplasm - metabolism Sequence Analysis, RNA Splicing Splicing factors Squamous cell carcinoma Suppressors Transcription Transcription (Genetics) Transcription Initiation Site Transcription Termination, Genetic Tumorigenesis Tumors |
| title | Aberrant DNA methylation defines isoform usage in cancer, with functional implications |
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