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Proteomic Features of Colorectal Cancer Identify Tumor Subtypes Independent of Oncogenic Mutations and Independently Predict Relapse-Free Survival. Ann Surg Oncol 2017 Dec;24(13):4051-4058

Date

09/25/2017

Pubmed ID

28936799

Pubmed Central ID

PMC6063735

DOI

10.1245/s10434-017-6054-5

Scopus ID

2-s2.0-85029712949   15 Citations

Abstract

BACKGROUND: The directed study of the functional proteome in colorectal cancer (CRC) has identified critical protein markers and signaling pathways; however, the prognostic relevance of many of these proteins remains unclear.

METHODS: We determined the prognostic implications of the functional proteome in 263 CRC tumor samples from patients treated at MD Anderson Cancer Center (MDACC) and 462 patients from The Cancer Genome Atlas (TCGA) to identify patterns of protein expression that drive tumorigenesis. A total of 163 validated proteins were analyzed by reverse phase protein array (RPPA). Unsupervised hierarchical clustering of the tumor proteins from the MDACC cohort was performed, and clustering was validated using RPPA data from TCGA CRC. Cox regression was used to identify predictors of tumor recurrence.

RESULTS: Clustering revealed dichotomization, with subtype A notable for a high epithelial-mesenchymal transition (EMT) protein signature, while subtype B was notable for high Akt/TSC/mTOR pathway components. Survival data were only available for the MDACC cohort and were used to evaluate prognostic relevance of these protein signatures. Group B demonstrated worse relapse-free survival (hazard ratio 2.11, 95% confidence interval 1.04-4.27, p = 0.039), although there was no difference in known genomic drivers between the two proteomic groups. Proteomic grouping and stage were significant predictors of recurrence on multivariate analysis. Eight proteins were found to be significant predictors of tumor recurrence on multivariate analysis: Collagen VI, FOXO3a, INPP4B, LcK, phospho-PEA15, phospho-PRAS40, Rad51, phospho-S6.

CONCLUSION: CRC can be classified into distinct subtypes by proteomic features independent of common oncogenic driver mutations. Proteomic analysis has identified key biomarkers with prognostic importance, however these findings require further validation in an independent cohort.

Author List

Clarke CN, Lee MS, Wei W, Manyam G, Jiang ZQ, Lu Y, Morris J, Broom B, Menter D, Vilar-Sanchez E, Raghav K, Eng C, Chang GJ, Simon I, Bernards R, Overman M, Mills GB, Maru D, Kopetz S

Author

Callisia N. Clarke MD Assistant Professor in the Surgery department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Biomarkers, Tumor
Cohort Studies
Colorectal Neoplasms
Female
Follow-Up Studies
Gene Expression Regulation, Neoplastic
Humans
Male
Middle Aged
Mutation
Prognosis
Proteomics
Survival Rate