Identification of Novel Tumor Microenvironment-Related Long Noncoding RNAs to Determine the Prognosis and Response to Immunotherapy of Hepatocellular Carcinoma Patients

• DOI: 10.3389/fmolb.2021.781307
• Publication Date: 2021-12-24T07:28:27Z
• Authors: Shenglan Huang; Jian Zhang; Xiaolan Lai; Lingling Zhuang; Jianbing Wu
• Keywords: immune checkpoint inhibitors; 0303 health sciences; 03 medical and health sciences; lncRNA; QH301-705.5; tumor microenvironment; Molecular Biosciences; hepatocellular carcinoma; prognostic signature; Biology (General); 3. Good health

Introduction: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with poor prognosis. The tumor microenvironment (TME) plays a vital role in HCC progression. Thus, this research was designed to analyze correlation between TME and prognosis patients construct TME-related long noncoding RNA (lncRNA) signature determine patients’ response immunotherapy. Methods: We assessed stromal–immune–estimate scores within using ESTIMATE (Estimation Stromal Immune Cells Malignant Tumor Tissues Using Expression Data) algorithm based on Cancer Genome Atlas database, their associations survival clinicopathological parameters were also analyzed. Thereafter, differentially expressed lncRNAs filtered out according immune stromal scores. Cox regression analysis performed build lncRNA risk signature. Kaplan–Meier used explore prognostic value Furthermore, we explored biological functions features high- low-risk groups. Lastly, probed association model treatment responses checkpoint inhibitors (ICIs) HCC. Results: stromal, immune, estimate obtained utilizing for showed that high significantly correlated better patients. Six screened model. curves suggested low had than those risk. Receiver operating characteristic (ROC) curve analyses indicated could predict exactly independently. Functional enrichment revealed some tumor- immune-related pathways activated high-risk group. cells, which important enhancing toward cancer, increased In addition, there close ICIs signature, can be Conclusion: analyzed influence A novel established, effectively applied as an independent biomarker predictor