Proteomic Features of Colorectal Cancer Identify Tumor Subtypes Independent of Oncogenic Mutations and Independently Predict Relapse-Free Survival

Callisia N. Clarke, Michael S. Lee, Wei Wei, Ganiraju Manyam, Zhi Qin Jiang, Yiling Lu, Jeffrey Morris, Bradley Broom, David Menter, Eduardo Vilar-Sanchez, Kanwal Raghav, Cathy Eng, George J. Chang, Iris Simon, Rene Bernards, Michael Overman, Gordon Mills, Dipen Maru, Scott Kopetz

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)4051-4058
Number of pages8
JournalAnnals of Surgical Oncology
Volume24
Issue number13
DOIs
StatePublished - Dec 1 2017
Externally publishedYes

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Proteomics
Colorectal Neoplasms
Recurrence
Mutation
Survival
Neoplasms
Proteins
Cluster Analysis
Protein Array Analysis
Atlases
Proteome
Multivariate Analysis
Genome
S 6
Epithelial-Mesenchymal Transition
Carcinogenesis
Collagen
Biomarkers
Confidence Intervals

ASJC Scopus subject areas

  • Surgery
  • Oncology

Cite this

Proteomic Features of Colorectal Cancer Identify Tumor Subtypes Independent of Oncogenic Mutations and Independently Predict Relapse-Free Survival. / Clarke, Callisia N.; Lee, Michael S.; Wei, Wei; Manyam, Ganiraju; Jiang, Zhi Qin; Lu, Yiling; Morris, Jeffrey; Broom, Bradley; Menter, David; Vilar-Sanchez, Eduardo; Raghav, Kanwal; Eng, Cathy; Chang, George J.; Simon, Iris; Bernards, Rene; Overman, Michael; Mills, Gordon; Maru, Dipen; Kopetz, Scott.

In: Annals of Surgical Oncology, Vol. 24, No. 13, 01.12.2017, p. 4051-4058.

Research output: Contribution to journalArticle

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, G, Maru, D & Kopetz, S 2017, 'Proteomic Features of Colorectal Cancer Identify Tumor Subtypes Independent of Oncogenic Mutations and Independently Predict Relapse-Free Survival', Annals of Surgical Oncology, vol. 24, no. 13, pp. 4051-4058. https://doi.org/10.1245/s10434-017-6054-5
Clarke, Callisia N. ; Lee, Michael S. ; Wei, Wei ; Manyam, Ganiraju ; Jiang, Zhi Qin ; Lu, Yiling ; Morris, Jeffrey ; Broom, Bradley ; Menter, David ; Vilar-Sanchez, Eduardo ; Raghav, Kanwal ; Eng, Cathy ; Chang, George J. ; Simon, Iris ; Bernards, Rene ; Overman, Michael ; Mills, Gordon ; Maru, Dipen ; Kopetz, Scott. / Proteomic Features of Colorectal Cancer Identify Tumor Subtypes Independent of Oncogenic Mutations and Independently Predict Relapse-Free Survival. In: Annals of Surgical Oncology. 2017 ; Vol. 24, No. 13. pp. 4051-4058.
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title = "Proteomic Features of Colorectal Cancer Identify Tumor Subtypes Independent of Oncogenic Mutations and Independently Predict Relapse-Free Survival",
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.",
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T1 - Proteomic Features of Colorectal Cancer Identify Tumor Subtypes Independent of Oncogenic Mutations and Independently Predict Relapse-Free Survival

AU - Clarke, Callisia N.

AU - Lee, Michael S.

AU - Wei, Wei

AU - Manyam, Ganiraju

AU - Jiang, Zhi Qin

AU - Lu, Yiling

AU - Morris, Jeffrey

AU - Broom, Bradley

AU - Menter, David

AU - Vilar-Sanchez, Eduardo

AU - Raghav, Kanwal

AU - Eng, Cathy

AU - Chang, George J.

AU - Simon, Iris

AU - Bernards, Rene

AU - Overman, Michael

AU - Mills, Gordon

AU - Maru, Dipen

AU - Kopetz, Scott

PY - 2017/12/1

Y1 - 2017/12/1

N2 - 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.

AB - 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.

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