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The prognostic potential of alternative transcript isoforms across human tumors

Juan L. Trincado, E. Sebestyén, A. Pagés, View ORCID ProfileE. Eyras
doi: https://doi.org/10.1101/036947
Juan L. Trincado
1Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, E08003 Barcelona, Spain
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E. Sebestyén
2The Firc Institute of Molecular Oncology (IFOM), Via Adamello 16, 20139 Milan, Italy
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A. Pagés
1Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, E08003 Barcelona, Spain
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E. Eyras
1Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, E08003 Barcelona, Spain
3Catalan Institution for Research and Advanced Studies (ICREA), Passeig Lluís Companys 23, E08010 Barcelona, Spain
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Abstract

Background Phenotypic changes during cancer progression are associated to alterations in gene expression, which can be exploited to build molecular signatures for tumor stage identification and prognosis. However, it is not yet known whether the relative abundance of transcript isoforms may be informative for clinical stage and survival.

Methods Using information theory and machine learning methods, we integrated RNA sequencing and clinical data from The Cancer Genome Atlas project to perform the first systematic analysis of the prognostic potential of transcript isoforms in 12 solid tumors to build new predictive signatures for stage and prognosis. This study was also performed in breast tumors according to estrogen receptor status and melanoma tumors with proliferative and invasive phenotypes.

Results Transcript isoform signatures accurately separate early from late stage and metastatic from non-metastatic tumors, and are predictive of the survival of patients with undetermined lymph node invasion or metastatic status. These signatures show similar, and sometimes better, accuracies compared with known gene expression signatures, and are largely independent of gene expression changes. Furthermore, we show frequent transcript isoform changes in breast tumors according to estrogen receptor status, and in melanoma tumors according to the invasive or proliferative phenotype, and derive accurate predictive models of stage and survival within each patient subgroup.

Conclusions Our analyses reveal new signatures based on transcript isoform abundances that characterize tumor phenotypes and their progression independently of gene expression. Transcript isoform signatures appear especially relevant to determine lymph node invasion and metastasis, and may potentially contribute towards current strategies of precision cancer medicine.

Footnotes

  • The authors declare no conflict of interests.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted May 19, 2016.
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The prognostic potential of alternative transcript isoforms across human tumors
Juan L. Trincado, E. Sebestyén, A. Pagés, E. Eyras
bioRxiv 036947; doi: https://doi.org/10.1101/036947
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The prognostic potential of alternative transcript isoforms across human tumors
Juan L. Trincado, E. Sebestyén, A. Pagés, E. Eyras
bioRxiv 036947; doi: https://doi.org/10.1101/036947

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