Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer

It is increasingly appreciated that alternative splicing plays a key role in generating functional specificity and diversity in cancer. However, the mechanisms by which cancer mutations perturb splicing remain unknown. Here, we developed a network-based strategy, DrAS-Net, to investigate more than 2...
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Autor*in:	Yongsheng Li [verfasserIn] Nidhi Sahni [verfasserIn] Rita Pancsa [verfasserIn] Daniel J. McGrail [verfasserIn] Juan Xu [verfasserIn] Xu Hua [verfasserIn] Jasmin Coulombe-Huntington [verfasserIn] Michael Ryan [verfasserIn] Boranai Tychhon [verfasserIn] Dhanistha Sudhakar [verfasserIn] Limei Hu [verfasserIn] Michael Tyers [verfasserIn] Xiaoqian Jiang [verfasserIn] Shiaw-Yih Lin [verfasserIn] M. Madan Babu [verfasserIn] Song Yi [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	Network biology alternative splicing gene regulation genotype-phenotype relationships DrAS-Net cancer somatic mutations systems biology computational biology bioinformatics

Übergeordnetes Werk:	In: Cell Reports - Elsevier, 2015, 21(2017), 3, Seite 798-812
Übergeordnetes Werk:	volume:21 ; year:2017 ; number:3 ; pages:798-812

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.celrep.2017.09.071

Katalog-ID:	DOAJ011215577

Internformat


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520			\|a It is increasingly appreciated that alternative splicing plays a key role in generating functional specificity and diversity in cancer. However, the mechanisms by which cancer mutations perturb splicing remain unknown. Here, we developed a network-based strategy, DrAS-Net, to investigate more than 2.5 million variants across cancer types and link somatic mutations with cancer-specific splicing events. We identified more than 40,000 driver variant candidates and their 80,000 putative splicing targets deregulated in 33 cancer types and inferred their functional impact. Strikingly, tumors with splicing perturbations show reduced expression of immune system-related genes and increased expression of cell proliferation markers. Tumors harboring different mutations in the same gene often exhibit distinct splicing perturbations. Further stratification of 10,000 patients based on their mutation-splicing relationships identifies subtypes with distinct clinical features, including survival rates. Our work reveals how single-nucleotide changes can alter the repertoires of splicing isoforms, providing insights into oncogenic mechanisms for precision medicine.
650		4	\|a Network biology
650		4	\|a alternative splicing
650		4	\|a gene regulation
650		4	\|a genotype-phenotype relationships
650		4	\|a DrAS-Net
650		4	\|a cancer
650		4	\|a somatic mutations
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653		0	\|a Biology (General)
700	0		\|a Nidhi Sahni \|e verfasserin \|4 aut
700	0		\|a Rita Pancsa \|e verfasserin \|4 aut
700	0		\|a Daniel J. McGrail \|e verfasserin \|4 aut
700	0		\|a Juan Xu \|e verfasserin \|4 aut
700	0		\|a Xu Hua \|e verfasserin \|4 aut
700	0		\|a Jasmin Coulombe-Huntington \|e verfasserin \|4 aut
700	0		\|a Michael Ryan \|e verfasserin \|4 aut
700	0		\|a Boranai Tychhon \|e verfasserin \|4 aut
700	0		\|a Dhanistha Sudhakar \|e verfasserin \|4 aut
700	0		\|a Limei Hu \|e verfasserin \|4 aut
700	0		\|a Michael Tyers \|e verfasserin \|4 aut
700	0		\|a Xiaoqian Jiang \|e verfasserin \|4 aut
700	0		\|a Shiaw-Yih Lin \|e verfasserin \|4 aut
700	0		\|a M. Madan Babu \|e verfasserin \|4 aut
700	0		\|a Song Yi \|e verfasserin \|4 aut
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author_variant	y l yl n s ns r p rp d j m djm j x jx x h xh j c h jch m r mr b t bt d s ds l h lh m t mt x j xj s y l syl m m b mmb s y sy
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allfields	10.1016/j.celrep.2017.09.071 doi (DE-627)DOAJ011215577 (DE-599)DOAJd1ddbe05962542d6a9bcf1d7072cdd46 DE-627 ger DE-627 rakwb eng QH301-705.5 Yongsheng Li verfasserin aut Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is increasingly appreciated that alternative splicing plays a key role in generating functional specificity and diversity in cancer. However, the mechanisms by which cancer mutations perturb splicing remain unknown. Here, we developed a network-based strategy, DrAS-Net, to investigate more than 2.5 million variants across cancer types and link somatic mutations with cancer-specific splicing events. We identified more than 40,000 driver variant candidates and their 80,000 putative splicing targets deregulated in 33 cancer types and inferred their functional impact. Strikingly, tumors with splicing perturbations show reduced expression of immune system-related genes and increased expression of cell proliferation markers. Tumors harboring different mutations in the same gene often exhibit distinct splicing perturbations. Further stratification of 10,000 patients based on their mutation-splicing relationships identifies subtypes with distinct clinical features, including survival rates. Our work reveals how single-nucleotide changes can alter the repertoires of splicing isoforms, providing insights into oncogenic mechanisms for precision medicine. Network biology alternative splicing gene regulation genotype-phenotype relationships DrAS-Net cancer somatic mutations systems biology computational biology bioinformatics Biology (General) Nidhi Sahni verfasserin aut Rita Pancsa verfasserin aut Daniel J. McGrail verfasserin aut Juan Xu verfasserin aut Xu Hua verfasserin aut Jasmin Coulombe-Huntington verfasserin aut Michael Ryan verfasserin aut Boranai Tychhon verfasserin aut Dhanistha Sudhakar verfasserin aut Limei Hu verfasserin aut Michael Tyers verfasserin aut Xiaoqian Jiang verfasserin aut Shiaw-Yih Lin verfasserin aut M. Madan Babu verfasserin aut Song Yi verfasserin aut In Cell Reports Elsevier, 2015 21(2017), 3, Seite 798-812 (DE-627)684964562 (DE-600)2649101-1 22111247 nnns volume:21 year:2017 number:3 pages:798-812 https://doi.org/10.1016/j.celrep.2017.09.071 kostenfrei https://doaj.org/article/d1ddbe05962542d6a9bcf1d7072cdd46 kostenfrei http://www.sciencedirect.com/science/article/pii/S2211124717313761 kostenfrei https://doaj.org/toc/2211-1247 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 21 2017 3 798-812
spelling	10.1016/j.celrep.2017.09.071 doi (DE-627)DOAJ011215577 (DE-599)DOAJd1ddbe05962542d6a9bcf1d7072cdd46 DE-627 ger DE-627 rakwb eng QH301-705.5 Yongsheng Li verfasserin aut Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is increasingly appreciated that alternative splicing plays a key role in generating functional specificity and diversity in cancer. However, the mechanisms by which cancer mutations perturb splicing remain unknown. Here, we developed a network-based strategy, DrAS-Net, to investigate more than 2.5 million variants across cancer types and link somatic mutations with cancer-specific splicing events. We identified more than 40,000 driver variant candidates and their 80,000 putative splicing targets deregulated in 33 cancer types and inferred their functional impact. Strikingly, tumors with splicing perturbations show reduced expression of immune system-related genes and increased expression of cell proliferation markers. Tumors harboring different mutations in the same gene often exhibit distinct splicing perturbations. Further stratification of 10,000 patients based on their mutation-splicing relationships identifies subtypes with distinct clinical features, including survival rates. Our work reveals how single-nucleotide changes can alter the repertoires of splicing isoforms, providing insights into oncogenic mechanisms for precision medicine. Network biology alternative splicing gene regulation genotype-phenotype relationships DrAS-Net cancer somatic mutations systems biology computational biology bioinformatics Biology (General) Nidhi Sahni verfasserin aut Rita Pancsa verfasserin aut Daniel J. McGrail verfasserin aut Juan Xu verfasserin aut Xu Hua verfasserin aut Jasmin Coulombe-Huntington verfasserin aut Michael Ryan verfasserin aut Boranai Tychhon verfasserin aut Dhanistha Sudhakar verfasserin aut Limei Hu verfasserin aut Michael Tyers verfasserin aut Xiaoqian Jiang verfasserin aut Shiaw-Yih Lin verfasserin aut M. Madan Babu verfasserin aut Song Yi verfasserin aut In Cell Reports Elsevier, 2015 21(2017), 3, Seite 798-812 (DE-627)684964562 (DE-600)2649101-1 22111247 nnns volume:21 year:2017 number:3 pages:798-812 https://doi.org/10.1016/j.celrep.2017.09.071 kostenfrei https://doaj.org/article/d1ddbe05962542d6a9bcf1d7072cdd46 kostenfrei http://www.sciencedirect.com/science/article/pii/S2211124717313761 kostenfrei https://doaj.org/toc/2211-1247 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 21 2017 3 798-812
allfields_unstemmed	10.1016/j.celrep.2017.09.071 doi (DE-627)DOAJ011215577 (DE-599)DOAJd1ddbe05962542d6a9bcf1d7072cdd46 DE-627 ger DE-627 rakwb eng QH301-705.5 Yongsheng Li verfasserin aut Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is increasingly appreciated that alternative splicing plays a key role in generating functional specificity and diversity in cancer. However, the mechanisms by which cancer mutations perturb splicing remain unknown. Here, we developed a network-based strategy, DrAS-Net, to investigate more than 2.5 million variants across cancer types and link somatic mutations with cancer-specific splicing events. We identified more than 40,000 driver variant candidates and their 80,000 putative splicing targets deregulated in 33 cancer types and inferred their functional impact. Strikingly, tumors with splicing perturbations show reduced expression of immune system-related genes and increased expression of cell proliferation markers. Tumors harboring different mutations in the same gene often exhibit distinct splicing perturbations. Further stratification of 10,000 patients based on their mutation-splicing relationships identifies subtypes with distinct clinical features, including survival rates. Our work reveals how single-nucleotide changes can alter the repertoires of splicing isoforms, providing insights into oncogenic mechanisms for precision medicine. Network biology alternative splicing gene regulation genotype-phenotype relationships DrAS-Net cancer somatic mutations systems biology computational biology bioinformatics Biology (General) Nidhi Sahni verfasserin aut Rita Pancsa verfasserin aut Daniel J. McGrail verfasserin aut Juan Xu verfasserin aut Xu Hua verfasserin aut Jasmin Coulombe-Huntington verfasserin aut Michael Ryan verfasserin aut Boranai Tychhon verfasserin aut Dhanistha Sudhakar verfasserin aut Limei Hu verfasserin aut Michael Tyers verfasserin aut Xiaoqian Jiang verfasserin aut Shiaw-Yih Lin verfasserin aut M. Madan Babu verfasserin aut Song Yi verfasserin aut In Cell Reports Elsevier, 2015 21(2017), 3, Seite 798-812 (DE-627)684964562 (DE-600)2649101-1 22111247 nnns volume:21 year:2017 number:3 pages:798-812 https://doi.org/10.1016/j.celrep.2017.09.071 kostenfrei https://doaj.org/article/d1ddbe05962542d6a9bcf1d7072cdd46 kostenfrei http://www.sciencedirect.com/science/article/pii/S2211124717313761 kostenfrei https://doaj.org/toc/2211-1247 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 21 2017 3 798-812
allfieldsGer	10.1016/j.celrep.2017.09.071 doi (DE-627)DOAJ011215577 (DE-599)DOAJd1ddbe05962542d6a9bcf1d7072cdd46 DE-627 ger DE-627 rakwb eng QH301-705.5 Yongsheng Li verfasserin aut Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is increasingly appreciated that alternative splicing plays a key role in generating functional specificity and diversity in cancer. However, the mechanisms by which cancer mutations perturb splicing remain unknown. Here, we developed a network-based strategy, DrAS-Net, to investigate more than 2.5 million variants across cancer types and link somatic mutations with cancer-specific splicing events. We identified more than 40,000 driver variant candidates and their 80,000 putative splicing targets deregulated in 33 cancer types and inferred their functional impact. Strikingly, tumors with splicing perturbations show reduced expression of immune system-related genes and increased expression of cell proliferation markers. Tumors harboring different mutations in the same gene often exhibit distinct splicing perturbations. Further stratification of 10,000 patients based on their mutation-splicing relationships identifies subtypes with distinct clinical features, including survival rates. Our work reveals how single-nucleotide changes can alter the repertoires of splicing isoforms, providing insights into oncogenic mechanisms for precision medicine. Network biology alternative splicing gene regulation genotype-phenotype relationships DrAS-Net cancer somatic mutations systems biology computational biology bioinformatics Biology (General) Nidhi Sahni verfasserin aut Rita Pancsa verfasserin aut Daniel J. McGrail verfasserin aut Juan Xu verfasserin aut Xu Hua verfasserin aut Jasmin Coulombe-Huntington verfasserin aut Michael Ryan verfasserin aut Boranai Tychhon verfasserin aut Dhanistha Sudhakar verfasserin aut Limei Hu verfasserin aut Michael Tyers verfasserin aut Xiaoqian Jiang verfasserin aut Shiaw-Yih Lin verfasserin aut M. Madan Babu verfasserin aut Song Yi verfasserin aut In Cell Reports Elsevier, 2015 21(2017), 3, Seite 798-812 (DE-627)684964562 (DE-600)2649101-1 22111247 nnns volume:21 year:2017 number:3 pages:798-812 https://doi.org/10.1016/j.celrep.2017.09.071 kostenfrei https://doaj.org/article/d1ddbe05962542d6a9bcf1d7072cdd46 kostenfrei http://www.sciencedirect.com/science/article/pii/S2211124717313761 kostenfrei https://doaj.org/toc/2211-1247 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 21 2017 3 798-812
allfieldsSound	10.1016/j.celrep.2017.09.071 doi (DE-627)DOAJ011215577 (DE-599)DOAJd1ddbe05962542d6a9bcf1d7072cdd46 DE-627 ger DE-627 rakwb eng QH301-705.5 Yongsheng Li verfasserin aut Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is increasingly appreciated that alternative splicing plays a key role in generating functional specificity and diversity in cancer. However, the mechanisms by which cancer mutations perturb splicing remain unknown. Here, we developed a network-based strategy, DrAS-Net, to investigate more than 2.5 million variants across cancer types and link somatic mutations with cancer-specific splicing events. We identified more than 40,000 driver variant candidates and their 80,000 putative splicing targets deregulated in 33 cancer types and inferred their functional impact. Strikingly, tumors with splicing perturbations show reduced expression of immune system-related genes and increased expression of cell proliferation markers. Tumors harboring different mutations in the same gene often exhibit distinct splicing perturbations. Further stratification of 10,000 patients based on their mutation-splicing relationships identifies subtypes with distinct clinical features, including survival rates. Our work reveals how single-nucleotide changes can alter the repertoires of splicing isoforms, providing insights into oncogenic mechanisms for precision medicine. Network biology alternative splicing gene regulation genotype-phenotype relationships DrAS-Net cancer somatic mutations systems biology computational biology bioinformatics Biology (General) Nidhi Sahni verfasserin aut Rita Pancsa verfasserin aut Daniel J. McGrail verfasserin aut Juan Xu verfasserin aut Xu Hua verfasserin aut Jasmin Coulombe-Huntington verfasserin aut Michael Ryan verfasserin aut Boranai Tychhon verfasserin aut Dhanistha Sudhakar verfasserin aut Limei Hu verfasserin aut Michael Tyers verfasserin aut Xiaoqian Jiang verfasserin aut Shiaw-Yih Lin verfasserin aut M. Madan Babu verfasserin aut Song Yi verfasserin aut In Cell Reports Elsevier, 2015 21(2017), 3, Seite 798-812 (DE-627)684964562 (DE-600)2649101-1 22111247 nnns volume:21 year:2017 number:3 pages:798-812 https://doi.org/10.1016/j.celrep.2017.09.071 kostenfrei https://doaj.org/article/d1ddbe05962542d6a9bcf1d7072cdd46 kostenfrei http://www.sciencedirect.com/science/article/pii/S2211124717313761 kostenfrei https://doaj.org/toc/2211-1247 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 21 2017 3 798-812
language	English
source	In Cell Reports 21(2017), 3, Seite 798-812 volume:21 year:2017 number:3 pages:798-812
sourceStr	In Cell Reports 21(2017), 3, Seite 798-812 volume:21 year:2017 number:3 pages:798-812
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Network biology alternative splicing gene regulation genotype-phenotype relationships DrAS-Net cancer somatic mutations systems biology computational biology bioinformatics Biology (General)
isfreeaccess_bool	true
container_title	Cell Reports
authorswithroles_txt_mv	Yongsheng Li @@aut@@ Nidhi Sahni @@aut@@ Rita Pancsa @@aut@@ Daniel J. McGrail @@aut@@ Juan Xu @@aut@@ Xu Hua @@aut@@ Jasmin Coulombe-Huntington @@aut@@ Michael Ryan @@aut@@ Boranai Tychhon @@aut@@ Dhanistha Sudhakar @@aut@@ Limei Hu @@aut@@ Michael Tyers @@aut@@ Xiaoqian Jiang @@aut@@ Shiaw-Yih Lin @@aut@@ M. Madan Babu @@aut@@ Song Yi @@aut@@
publishDateDaySort_date	2017-01-01T00:00:00Z
hierarchy_top_id	684964562
id	DOAJ011215577
language_de	englisch
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callnumber-first	Q - Science
author	Yongsheng Li
spellingShingle	Yongsheng Li misc QH301-705.5 misc Network biology misc alternative splicing misc gene regulation misc genotype-phenotype relationships misc DrAS-Net misc cancer misc somatic mutations misc systems biology misc computational biology misc bioinformatics misc Biology (General) Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer
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topic_title	QH301-705.5 Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer Network biology alternative splicing gene regulation genotype-phenotype relationships DrAS-Net cancer somatic mutations systems biology computational biology bioinformatics
topic	misc QH301-705.5 misc Network biology misc alternative splicing misc gene regulation misc genotype-phenotype relationships misc DrAS-Net misc cancer misc somatic mutations misc systems biology misc computational biology misc bioinformatics misc Biology (General)
topic_unstemmed	misc QH301-705.5 misc Network biology misc alternative splicing misc gene regulation misc genotype-phenotype relationships misc DrAS-Net misc cancer misc somatic mutations misc systems biology misc computational biology misc bioinformatics misc Biology (General)
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title	Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer
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title_full	Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer
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title_sort	revealing the determinants of widespread alternative splicing perturbation in cancer
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title_auth	Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer
abstract	It is increasingly appreciated that alternative splicing plays a key role in generating functional specificity and diversity in cancer. However, the mechanisms by which cancer mutations perturb splicing remain unknown. Here, we developed a network-based strategy, DrAS-Net, to investigate more than 2.5 million variants across cancer types and link somatic mutations with cancer-specific splicing events. We identified more than 40,000 driver variant candidates and their 80,000 putative splicing targets deregulated in 33 cancer types and inferred their functional impact. Strikingly, tumors with splicing perturbations show reduced expression of immune system-related genes and increased expression of cell proliferation markers. Tumors harboring different mutations in the same gene often exhibit distinct splicing perturbations. Further stratification of 10,000 patients based on their mutation-splicing relationships identifies subtypes with distinct clinical features, including survival rates. Our work reveals how single-nucleotide changes can alter the repertoires of splicing isoforms, providing insights into oncogenic mechanisms for precision medicine.
abstractGer	It is increasingly appreciated that alternative splicing plays a key role in generating functional specificity and diversity in cancer. However, the mechanisms by which cancer mutations perturb splicing remain unknown. Here, we developed a network-based strategy, DrAS-Net, to investigate more than 2.5 million variants across cancer types and link somatic mutations with cancer-specific splicing events. We identified more than 40,000 driver variant candidates and their 80,000 putative splicing targets deregulated in 33 cancer types and inferred their functional impact. Strikingly, tumors with splicing perturbations show reduced expression of immune system-related genes and increased expression of cell proliferation markers. Tumors harboring different mutations in the same gene often exhibit distinct splicing perturbations. Further stratification of 10,000 patients based on their mutation-splicing relationships identifies subtypes with distinct clinical features, including survival rates. Our work reveals how single-nucleotide changes can alter the repertoires of splicing isoforms, providing insights into oncogenic mechanisms for precision medicine.
abstract_unstemmed	It is increasingly appreciated that alternative splicing plays a key role in generating functional specificity and diversity in cancer. However, the mechanisms by which cancer mutations perturb splicing remain unknown. Here, we developed a network-based strategy, DrAS-Net, to investigate more than 2.5 million variants across cancer types and link somatic mutations with cancer-specific splicing events. We identified more than 40,000 driver variant candidates and their 80,000 putative splicing targets deregulated in 33 cancer types and inferred their functional impact. Strikingly, tumors with splicing perturbations show reduced expression of immune system-related genes and increased expression of cell proliferation markers. Tumors harboring different mutations in the same gene often exhibit distinct splicing perturbations. Further stratification of 10,000 patients based on their mutation-splicing relationships identifies subtypes with distinct clinical features, including survival rates. Our work reveals how single-nucleotide changes can alter the repertoires of splicing isoforms, providing insights into oncogenic mechanisms for precision medicine.
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title_short	Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer
url	https://doi.org/10.1016/j.celrep.2017.09.071 https://doaj.org/article/d1ddbe05962542d6a9bcf1d7072cdd46 http://www.sciencedirect.com/science/article/pii/S2211124717313761 https://doaj.org/toc/2211-1247
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Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer

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