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BMC Genomics. 2017 Oct 3;18(Suppl 6):678. doi: 10.1186/s12864-017-4026-6.

Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening.

Author information

1
Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St., Suite 820, Houston, TX, 77030, USA.
2
Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
3
Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 211106, China.
4
Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
5
Department of Urology, Division of Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
6
Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
7
Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St., Suite 820, Houston, TX, 77030, USA. zhongming.zhao@uth.tmc.edu.
8
Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA. zhongming.zhao@uth.tmc.edu.
9
Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. zding@mdanderson.org.
10
Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St., Suite 820, Houston, TX, 77030, USA. peilin.jia@uth.tmc.edu.

Abstract

BACKGROUND:

In 2016, it is estimated that there will be 62,700 new cases of kidney cancer in the United States, and 14,240 patients will die from the disease. Because the incidence of kidney renal clear cell carcinoma (KIRC), the most common type of kidney cancer, is expected to continue to increase in the US, there is an urgent need to find effective diagnostic biomarkers for KIRC that could help earlier detection of and customized treatment strategies for the disease. Accordingly, in this study we systematically investigated KIRC's prognostic biomarkers for survival using the reverse phase protein array (RPPA) data and the high throughput sequencing data from The Cancer Genome Atlas (TCGA).

RESULTS:

With comprehensive data available in TCGA, we systematically screened protein expression based survival biomarkers in 10 major cancer types, among which KIRC presented many protein prognostic biomarkers of survival time. This is in agreement with a previous report that expression level changes (mRNAs, microRNA and protein) may have a better performance for prognosis of KIRC. In this study, we also identified 52 prognostic genes for KIRC, many of which are involved in cell-cycle and cancer signaling, as well as 15 tumor-stage-specific prognostic biomarkers. Notably, we found fewer prognostic biomarkers for early-stage than for late-stage KIRC. Four biomarkers (the RPPA protein IDs: FASN, ACC1, Cyclin_B1 and Rad51) were found to be prognostic for survival based on both protein and mRNA expression data.

CONCLUSIONS:

Through pan-cancer screening, we found that many protein biomarkers were prognostic for patients' survival in KIRC. Stage-specific survival biomarkers in KIRC were also identified. Our study indicated that these protein biomarkers might have potential clinical value in terms of predicting survival in KIRC patients and developing individualized treatment strategies. Importantly, we found many biomarkers in KIRC at both the mRNA expression level and the protein expression level. These biomarkers shared a significant overlap, indicating that they were technically replicable.

KEYWORDS:

Kidney renal clear cell carcinoma (KIRC); Pan-cancer screening; Prognostic biomarker; Protein expression; Reverse phase protein Array (RPPA)

PMID:
28984208
PMCID:
PMC5629613
DOI:
10.1186/s12864-017-4026-6
[Indexed for MEDLINE]
Free PMC Article

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