bioRxivCancer Biology
MMP2 As An Independent Prognostic Stratifier In Oral Cavity Cancers
C. Hoffmann, S. Vacher, P. Sirven, C. Lecerf, L. Massenet, A. Moreira, A. Surun, A. Schnitzler, J. Klijanienko, O. Mariani, E. Jeannot, N. Badois, M. Lesnik, O. Choussy, C. Le Tourneau, M. Guillot-Delost, M. Kamal, I. Bieche, V. Soumelis
Abstract
BackgroundAround 25% of oral cavity squamous cell carcinoma (OCSCC) are not controlled by standard of care. Identifying those patients could offer them possibilities for intensified and personalized regimen. However, there is currently no validated biomarker for OCSCC patient selection in a pre-treatment setting.\n\nPatients and methodsOur objectives were to determine a robust and independent predictive biomarker for disease related death in OCSCC treated with standard of care. Tumor and juxtatumor secretome were analyzed in a prospective discovery cohort of 37 OCSCC treated by primary surgery. Independent biomarker validation was performed by RTqPCR in a retrospective cohort of 145 patients with similar clinical features. An 18-gene signature (18G) predictive of the response to PD-1 blockade was evaluated in the same cohort..\n\nResultsAmong 29 deregulated molecules in a secretome analysis, we identified soluble MMP2 as a prognostic biomarker. In our validation cohort (n=145), high levels of MMP2 and CD276, and low levels of CXCL10 and STAT1 mRNA were associated with poor prognosis in univariate analysis (Kaplan-Meier). MMP2 (p = 0.001) and extra-nodal extension (ENE) (p = 0.006) were independent biomarkers of disease-specific survival (DSS) in multivariate analysis, and defined prognostic groups with 5-year DSS ranging from 36% (MMP2highENE+) to 88% (MMP2lowENE-). The expression of 18G was similar in the different prognostic groups, suggesting comparable responsiveness to anti-PD-1.\n\nConclusionHigh levels of MMP2 was an independent and validated prognostic biomarker, which may be used to select poor prognosis patients for intensified neoadjuvant or adjuvant regimens.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: protein structure prediction
- approach: statistical model
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