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Erschienen in:
21.09.2017 | Translational Research and Biomarkers
Proteomic Features of Colorectal Cancer Identify Tumor Subtypes Independent of Oncogenic Mutations and Independently Predict Relapse-Free Survival
Erschienen in: Annals of Surgical Oncology | Ausgabe 13/2017
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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.