Research Paper Volume 15, Issue 14 pp 6798—6821
Molecular subtypes based on DNA sensors predict prognosis and tumor immunophenotype in hepatocellular carcinoma
- 1 Department of Microbiology, School of Basic Medical Sciences, Guangxi Medical University, Nanning 530021, China
- 2 Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530023, China
- 3 Department of Immunology, School of Basic Medical Sciences, Guangxi Medical University, Nanning 530021, China
- 4 Department of Hepatology, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530023, China
Received: December 27, 2022 Accepted: June 19, 2023 Published: July 14, 2023
https://doi.org/10.18632/aging.204870How to Cite
Copyright: © 2023 Lin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
DNA sensors play crucial roles in inflammation and have been indicated to be involved in antitumor or tumorigenesis, while it is still unclear whether DNA sensors have potential roles in the prognosis and immunotherapy of hepatocellular carcinoma (HCC). Herein, The Cancer Genome Atlas and Gene Expression Omnibus databases were used to analyze RNA sequencing data and clinical information. A total of 14 DNA sensors were collected and performed consensus clustering to determine their molecular mechanisms in HCC. Two distinct molecular subtypes (Clusters C1 and C2) were identified and were associated with different overall survival (OS). Immune subtype analysis revealed that C1 was mainly characterized by inflammation, while C2 was characterized by lymphocyte depletion. Immune scoring and immunomodulatory function analysis confirmed the different immune microenvironment of C1 and C2. Notably, significant differences in “Hot Tumor” Immunophenotype were observed between the two subtypes. Moreover, the prognostic model based on DNA sensors is capable of effectively predicting the OS of HCC patients. Besides, the chemotherapeutic drug analysis showed the different sensitivity of two subtypes. Taken together, our study shows that the proposed DNA sensors were a reliable signature to predict the prognosis and immunotherapy response with potential application in the clinical decision and treatment of HCC.
Abbreviations
HCC: hepatocellular carcinoma; ICIs: immune checkpoint inhibitors; dMMR: DNA defective mismatch repair; MSI: microsatellite instability; DDR: DNA damage response; cytoDNA: cytoplasmic DNA; CDF: cumulative distribution function; GESA: gene set enrichment analysis; TCGA: the cancer genome atlas; MHC: major histocompatibility complex; IFNG: interferon-γ; CD8: cluster of differentiation 8; PD-L1: programmed cell death 1 ligand 1; CAF: cancer associated fibroblast; MDSC: myeloid-derived suppressor cells; TAM: tumor associated macrophage; LASSO: Least absolute shrinkage and selection operator; KM: Kaplan–Meier; ROC: receiver operating characteristic; RT-qPCR: real-time quantitative polymerase chain reaction; IFI16: interferon gamma inducible protein 16; PRKDC: protein kinase, DNA-activated, catalytic subunit; DHX9: DExH-box helicase 9; DDX41: dead-box helicase 41; cGAS: cyclic GMP-AMP synthase; HNRNPA2B1: heterogeneous nuclear ribonucleoprotein A2/B1; DHX36: deah-box helicase 36; DDX60: DExD/H-Box helicase 60; AFP: alpha-fetoprotein; HRD: homologous recombination deficiency; OS: overall survival.