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Gene and isoform expression signatures associated with tumor stage in kidney renal clear cell carcinoma

BACKGROUND: Identification of expression alternations between early and late stage cancers is helpful for understanding cancer development and progression. Much research has been done focusing on stage-dependent gene expression profiles. In contrast, relatively fewer studies on isoform expression pr...

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Autores principales: Liu, Qi, Zhao, Shilin, Su, Pei-Fang, Yu, Shyr
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4028983/
https://www.ncbi.nlm.nih.gov/pubmed/24564989
http://dx.doi.org/10.1186/1752-0509-7-S5-S7
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author Liu, Qi
Zhao, Shilin
Su, Pei-Fang
Yu, Shyr
author_facet Liu, Qi
Zhao, Shilin
Su, Pei-Fang
Yu, Shyr
author_sort Liu, Qi
collection PubMed
description BACKGROUND: Identification of expression alternations between early and late stage cancers is helpful for understanding cancer development and progression. Much research has been done focusing on stage-dependent gene expression profiles. In contrast, relatively fewer studies on isoform expression profiles have been performed due to the difficulty of quantification and noisy splicing. Here we conducted both gene- and isoform-level analysis on RNA-seq data of 234 stage I and 81 stage IV kidney renal clear cell carcinoma patients, aiming to uncover the stage-dependent expression signatures and investigate the advantage of isoform expression profiling for identifying advanced stage cancers and predicting clinical outcome. RESULTS: Both gene and isoform expression signatures are useful for distinguishing cancer stages. They provide common and unique information associated with cancer progression and metastasis. Combining gene and isoform signatures even improves the classification performance and reveals additional important biological processes, such as angiogenesis and TGF−beta signaling pathway. Moreover, expression abundance of a number of genes and isoforms is predictive of the risk of cancer death in an independent dataset, such as gene and isoform expression of ITPKA, the expression of a functional important isoform of UPS19. CONCLUSION: Isoform expression profiling provides unique and important information which cannot be detected by gene expression profiles. Combining gene and isoform expression signatures helps to identify advanced stage cancers, predict clinical outcome, and present a comprehensive view of cancer development and progression.
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spelling pubmed-40289832014-06-17 Gene and isoform expression signatures associated with tumor stage in kidney renal clear cell carcinoma Liu, Qi Zhao, Shilin Su, Pei-Fang Yu, Shyr BMC Syst Biol Research BACKGROUND: Identification of expression alternations between early and late stage cancers is helpful for understanding cancer development and progression. Much research has been done focusing on stage-dependent gene expression profiles. In contrast, relatively fewer studies on isoform expression profiles have been performed due to the difficulty of quantification and noisy splicing. Here we conducted both gene- and isoform-level analysis on RNA-seq data of 234 stage I and 81 stage IV kidney renal clear cell carcinoma patients, aiming to uncover the stage-dependent expression signatures and investigate the advantage of isoform expression profiling for identifying advanced stage cancers and predicting clinical outcome. RESULTS: Both gene and isoform expression signatures are useful for distinguishing cancer stages. They provide common and unique information associated with cancer progression and metastasis. Combining gene and isoform signatures even improves the classification performance and reveals additional important biological processes, such as angiogenesis and TGF−beta signaling pathway. Moreover, expression abundance of a number of genes and isoforms is predictive of the risk of cancer death in an independent dataset, such as gene and isoform expression of ITPKA, the expression of a functional important isoform of UPS19. CONCLUSION: Isoform expression profiling provides unique and important information which cannot be detected by gene expression profiles. Combining gene and isoform expression signatures helps to identify advanced stage cancers, predict clinical outcome, and present a comprehensive view of cancer development and progression. BioMed Central 2013-12-09 /pmc/articles/PMC4028983/ /pubmed/24564989 http://dx.doi.org/10.1186/1752-0509-7-S5-S7 Text en Copyright © 2013 Liu et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Liu, Qi
Zhao, Shilin
Su, Pei-Fang
Yu, Shyr
Gene and isoform expression signatures associated with tumor stage in kidney renal clear cell carcinoma
title Gene and isoform expression signatures associated with tumor stage in kidney renal clear cell carcinoma
title_full Gene and isoform expression signatures associated with tumor stage in kidney renal clear cell carcinoma
title_fullStr Gene and isoform expression signatures associated with tumor stage in kidney renal clear cell carcinoma
title_full_unstemmed Gene and isoform expression signatures associated with tumor stage in kidney renal clear cell carcinoma
title_short Gene and isoform expression signatures associated with tumor stage in kidney renal clear cell carcinoma
title_sort gene and isoform expression signatures associated with tumor stage in kidney renal clear cell carcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4028983/
https://www.ncbi.nlm.nih.gov/pubmed/24564989
http://dx.doi.org/10.1186/1752-0509-7-S5-S7
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