AUTHOR=Li Luyi , Gao Hui , Wang Danhan , Jiang Hao , Wang Hongzhu , Yu Jiajian , Jiang Xin , Huang Changjiang 

TITLE=Metabolism-Relevant Molecular Classification Identifies Tumor Immune Microenvironment Characterization and Immunotherapeutic Effect in Cervical Cancer

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=Volume 8 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2021.624951

DOI=10.3389/fmolb.2021.624951

ISSN=2296-889X

ABSTRACT=Cervical cancer (CESC) is a gynecologic malignant tumor associated with high incidence and mortality rates because of its distinctive management complexity. Herein, we characterized the molecular features of CESC based on the metabolic gene expression profile by establishing a novel classification system. Integrative analysis was made on TCGA human CESC samples. Unsupervised clustering of RNA sequencing data on 2752 formerly described metabolic genes identified three METAclusters in CESC patients. These METAclusters for prognostic value, immune characteristics, metabolic features, transcriptome features and immunotherapeutic effectiveness existed distinct differences. Then we analyzed 207 DEGs among the three METAclusters and as well identified three geneclusters. Correspondingly, these geneclusters showed highly consistent differential expression among the aforementioned features, supporting the authenticity of the metabolism-relevant molecular classification. Finally, a scoring system termed as METAscore was constructed which emerged as an independent prognostic biomarker, related to CESC transcriptome features, metabolic features, immune characteristics, and had immunotherapeutic implication for individual patient. These findings depicted a new classification and a metabolic scoring system in CESC based on the metabolic pattern, thereby furthering the understanding of CESC genetic signatures and aiding in the evaluation of patient responses to cancer immunotherapies