Prognostic Gene Signature for Squamous Cell Carcinoma with a Higher Risk for Treatment Failure and Accelerated MEK-ERK Pathway Activity

Bohai Feng; Kai Wang; Esther Herpel; Michaela Plath; Wilko Weichert; Kolja Freier; Karim Zaoui; Jochen Hess

doi:10.3390/cancers13205182

Prognostic Gene Signature for Squamous Cell Carcinoma with a Higher Risk for Treatment Failure and Accelerated MEK-ERK Pathway Activity

Cancers (Basel). 2021 Oct 15;13(20):5182. doi: 10.3390/cancers13205182.

Authors

Bohai Feng^{1

2}, Kai Wang³, Esther Herpel⁴, Michaela Plath², Wilko Weichert⁵, Kolja Freier⁶, Karim Zaoui², Jochen Hess^{2

7}

Affiliations

¹ Department of Otorhinolaryngology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310000, China.
² Department of Otorhinolaryngology, Head and Neck Surgery, Heidelberg University Hospital, 69120 Heidelberg, Germany.
³ Department of Respiratory Medicine, Fourth Affiliated Hospital of Zhejiang University School of Medicine, Yiwu 322000, China.
⁴ Institute of Pathology, University Hospital Heidelberg, and NCT Tissue Bank, National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany.
⁵ Institute of Pathology, Technical University Munich (TUM), and German Cancer Consortium (DKTK) Partner Site, 80333 Munich, Germany.
⁶ Department of Oral and Maxillofacial Surgery, Saarland University Hospital, 66421 Homburg, Germany.
⁷ Molecular Mechanisms of Head and Neck Tumors, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.

Abstract

Squamous cell carcinoma (SCC) is the most prevalent histological type of human cancer, including head and neck squamous cell carcinoma (HNSCC). However, reliable prognostic gene signatures for SCC and underlying genetic and/or epigenetic principles are still unclear. We identified 37 prognostic candidate genes by best cutoff computation based on survival in a pan-SCC cohort (n = 1334) of The Cancer Genome Atlas (TCGA), whose expression stratified not only the pan-SCC cohort but also independent HNSCC validation cohorts into three distinct prognostic subgroups. The most relevant prognostic genes were prioritized by a Least Absolute Shrinkage and Selection Operator Cox regression model and were used to identify subgroups with high or low risks for unfavorable survival. An integrative analysis of multi-omics data identified FN1, SEMA3A, CDH2, FBN1, COL5A1, and ADAM12 as key nodes in a regulatory network related to the prognostic phenotype. An in-silico drug screen predicted two MEK inhibitors (Trametinib and Selumetinib) as effective compounds for high-risk SCC based on the Cancer Cell Line Encyclopedia, which is supported by a higher p-MEK1/2 immunohistochemical staining of high-risk HNSCC. In conclusion, our data identified a molecular classifier for high-risk HNSCC as well as other SCC patients, who might benefit from treatment with MEK inhibitors.

Keywords: HNSCC; MEK inhibitors; MEK-ERK signaling; genetic and epigenetic alterations; multi-omics analysis; prognostic classifier; squamous cell carcinoma.