Pathway and network analysis of more than 2500 whole cancer genomes

Research output: Contribution to journal › Journal article › Research › peer-review

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Pathway and network analysis of more than 2500 whole cancer genomes. / Reyna, Matthew A.; Haan, David; Paczkowska, Marta; Verbeke, Lieven P.C.; Vazquez, Miguel; Kahraman, Abdullah; Pulido-Tamayo, Sergio; Barenboim, Jonathan; Wadi, Lina; Dhingra, Priyanka; Shrestha, Raunak; Getz, Gad; Lawrence, Michael S.; Pedersen, Jakob Skou; Rubin, Mark A.; Wheeler, David A.; Brunak, Søren; Izarzugaza, Jose M.G.; Khurana, Ekta; Marchal, Kathleen; von Mering, Christian; Sahinalp, S. Cenk; Valencia, Alfonso; Abascal, Federico; Amin, Samirkumar B.; Bader, Gary D.; Bandopadhayay, Pratiti; Beroukhim, Rameen; Bertl, Johanna; Boroevich, Keith A.; Busanovich, John; Campbell, Peter J.; Carlevaro-Fita, Joana; Chakravarty, Dimple; Chan, Calvin Wing Yiu; Chen, Ken; Choi, Jung Kyoon; Deu-Pons, Jordi; Diamanti, Klev; Feuerbach, Lars; Fink, J. Lynn; Fonseca, Nuno A.; Frigola, Joan; Gambacorti-Passerini, Carlo; Garsed, Dale W.; Gerstein, Mark; Larsson, Erik; Nielsen, Morten Muhlig; Sidiropoulos, Nikos; Weischenfeldt, Joachim; PCAWG Drivers and Functional Interpretation Working Group; PCAWG Consortium.

In: Nature Communications, Vol. 11, No. 1, 729, 2020, p. 1-17.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Reyna, MA, Haan, D, Paczkowska, M, Verbeke, LPC, Vazquez, M, Kahraman, A, Pulido-Tamayo, S, Barenboim, J, Wadi, L, Dhingra, P, Shrestha, R, Getz, G, Lawrence, MS, Pedersen, JS, Rubin, MA, Wheeler, DA, Brunak, S, Izarzugaza, JMG, Khurana, E, Marchal, K, von Mering, C, Sahinalp, SC, Valencia, A, Abascal, F, Amin, SB, Bader, GD, Bandopadhayay, P, Beroukhim, R, Bertl, J, Boroevich, KA, Busanovich, J, Campbell, PJ, Carlevaro-Fita, J, Chakravarty, D, Chan, CWY, Chen, K, Choi, JK, Deu-Pons, J, Diamanti, K, Feuerbach, L, Fink, JL, Fonseca, NA, Frigola, J, Gambacorti-Passerini, C, Garsed, DW, Gerstein, M, Larsson, E, Nielsen, MM, Sidiropoulos, N, Weischenfeldt, J, PCAWG Drivers and Functional Interpretation Working Group & PCAWG Consortium 2020, 'Pathway and network analysis of more than 2500 whole cancer genomes', Nature Communications, vol. 11, no. 1, 729, pp. 1-17. https://doi.org/10.1038/s41467-020-14367-0

APA

Reyna, M. A., Haan, D., Paczkowska, M., Verbeke, L. P. C., Vazquez, M., Kahraman, A., Pulido-Tamayo, S., Barenboim, J., Wadi, L., Dhingra, P., Shrestha, R., Getz, G., Lawrence, M. S., Pedersen, J. S., Rubin, M. A., Wheeler, D. A., Brunak, S., Izarzugaza, J. M. G., Khurana, E., ... PCAWG Consortium (2020). Pathway and network analysis of more than 2500 whole cancer genomes. Nature Communications, 11(1), 1-17. [729]. https://doi.org/10.1038/s41467-020-14367-0

Vancouver

Reyna MA, Haan D, Paczkowska M, Verbeke LPC, Vazquez M, Kahraman A et al. Pathway and network analysis of more than 2500 whole cancer genomes. Nature Communications. 2020;11(1):1-17. 729. https://doi.org/10.1038/s41467-020-14367-0

Author

Reyna, Matthew A. ; Haan, David ; Paczkowska, Marta ; Verbeke, Lieven P.C. ; Vazquez, Miguel ; Kahraman, Abdullah ; Pulido-Tamayo, Sergio ; Barenboim, Jonathan ; Wadi, Lina ; Dhingra, Priyanka ; Shrestha, Raunak ; Getz, Gad ; Lawrence, Michael S. ; Pedersen, Jakob Skou ; Rubin, Mark A. ; Wheeler, David A. ; Brunak, Søren ; Izarzugaza, Jose M.G. ; Khurana, Ekta ; Marchal, Kathleen ; von Mering, Christian ; Sahinalp, S. Cenk ; Valencia, Alfonso ; Abascal, Federico ; Amin, Samirkumar B. ; Bader, Gary D. ; Bandopadhayay, Pratiti ; Beroukhim, Rameen ; Bertl, Johanna ; Boroevich, Keith A. ; Busanovich, John ; Campbell, Peter J. ; Carlevaro-Fita, Joana ; Chakravarty, Dimple ; Chan, Calvin Wing Yiu ; Chen, Ken ; Choi, Jung Kyoon ; Deu-Pons, Jordi ; Diamanti, Klev ; Feuerbach, Lars ; Fink, J. Lynn ; Fonseca, Nuno A. ; Frigola, Joan ; Gambacorti-Passerini, Carlo ; Garsed, Dale W. ; Gerstein, Mark ; Larsson, Erik ; Nielsen, Morten Muhlig ; Sidiropoulos, Nikos ; Weischenfeldt, Joachim ; PCAWG Drivers and Functional Interpretation Working Group ; PCAWG Consortium. / Pathway and network analysis of more than 2500 whole cancer genomes. In: Nature Communications. 2020 ; Vol. 11, No. 1. pp. 1-17.

Bibtex

@article{eb784e8567b64d679188983e101eee0b,
title = "Pathway and network analysis of more than 2500 whole cancer genomes",
abstract = "The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.",
author = "Reyna, {Matthew A.} and David Haan and Marta Paczkowska and Verbeke, {Lieven P.C.} and Miguel Vazquez and Abdullah Kahraman and Sergio Pulido-Tamayo and Jonathan Barenboim and Lina Wadi and Priyanka Dhingra and Raunak Shrestha and Gad Getz and Lawrence, {Michael S.} and Pedersen, {Jakob Skou} and Rubin, {Mark A.} and Wheeler, {David A.} and S{\o}ren Brunak and Izarzugaza, {Jose M.G.} and Ekta Khurana and Kathleen Marchal and {von Mering}, Christian and Sahinalp, {S. Cenk} and Alfonso Valencia and Federico Abascal and Amin, {Samirkumar B.} and Bader, {Gary D.} and Pratiti Bandopadhayay and Rameen Beroukhim and Johanna Bertl and Boroevich, {Keith A.} and John Busanovich and Campbell, {Peter J.} and Joana Carlevaro-Fita and Dimple Chakravarty and Chan, {Calvin Wing Yiu} and Ken Chen and Choi, {Jung Kyoon} and Jordi Deu-Pons and Klev Diamanti and Lars Feuerbach and Fink, {J. Lynn} and Fonseca, {Nuno A.} and Joan Frigola and Carlo Gambacorti-Passerini and Garsed, {Dale W.} and Mark Gerstein and Erik Larsson and Nielsen, {Morten Muhlig} and Nikos Sidiropoulos and Joachim Weischenfeldt and {PCAWG Drivers and Functional Interpretation Working Group} and {PCAWG Consortium}",
year = "2020",
doi = "10.1038/s41467-020-14367-0",
language = "English",
volume = "11",
pages = "1--17",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "nature publishing group",
number = "1",

}

RIS

TY - JOUR

T1 - Pathway and network analysis of more than 2500 whole cancer genomes

AU - Reyna, Matthew A.

AU - Haan, David

AU - Paczkowska, Marta

AU - Verbeke, Lieven P.C.

AU - Vazquez, Miguel

AU - Kahraman, Abdullah

AU - Pulido-Tamayo, Sergio

AU - Barenboim, Jonathan

AU - Wadi, Lina

AU - Dhingra, Priyanka

AU - Shrestha, Raunak

AU - Getz, Gad

AU - Lawrence, Michael S.

AU - Pedersen, Jakob Skou

AU - Rubin, Mark A.

AU - Wheeler, David A.

AU - Brunak, Søren

AU - Izarzugaza, Jose M.G.

AU - Khurana, Ekta

AU - Marchal, Kathleen

AU - von Mering, Christian

AU - Sahinalp, S. Cenk

AU - Valencia, Alfonso

AU - Abascal, Federico

AU - Amin, Samirkumar B.

AU - Bader, Gary D.

AU - Bandopadhayay, Pratiti

AU - Beroukhim, Rameen

AU - Bertl, Johanna

AU - Boroevich, Keith A.

AU - Busanovich, John

AU - Campbell, Peter J.

AU - Carlevaro-Fita, Joana

AU - Chakravarty, Dimple

AU - Chan, Calvin Wing Yiu

AU - Chen, Ken

AU - Choi, Jung Kyoon

AU - Deu-Pons, Jordi

AU - Diamanti, Klev

AU - Feuerbach, Lars

AU - Fink, J. Lynn

AU - Fonseca, Nuno A.

AU - Frigola, Joan

AU - Gambacorti-Passerini, Carlo

AU - Garsed, Dale W.

AU - Gerstein, Mark

AU - Larsson, Erik

AU - Nielsen, Morten Muhlig

AU - Sidiropoulos, Nikos

AU - Weischenfeldt, Joachim

AU - PCAWG Drivers and Functional Interpretation Working Group

AU - PCAWG Consortium

PY - 2020

Y1 - 2020

N2 - The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.

AB - The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.

U2 - 10.1038/s41467-020-14367-0

DO - 10.1038/s41467-020-14367-0

M3 - Journal article

C2 - 32024854

AN - SCOPUS:85079060258

VL - 11

SP - 1

EP - 17

JO - Nature Communications

JF - Nature Communications

SN - 2041-1723

IS - 1

M1 - 729

ER -

ID: 236371819