Genome Instability and Long Noncoding RNA Reveal Biomarkers for Immunotherapy and Prognosis and Novel Competing Endogenous RNA Mechanism in Colon Adenocarcinoma

Ziyuan Ren; Zhonglin Wang; Donghong Gu; Hanchen Ma; Yan Zhu; Menghua Cai; Jianmin Zhang

doi:10.3389/fcell.2021.740455

Genome Instability and Long Noncoding RNA Reveal Biomarkers for Immunotherapy and Prognosis and Novel Competing Endogenous RNA Mechanism in Colon Adenocarcinoma

Front Cell Dev Biol. 2021 Oct 20:9:740455. doi: 10.3389/fcell.2021.740455. eCollection 2021.

Authors

Ziyuan Ren^{1

2}, Zhonglin Wang^{1

3}, Donghong Gu⁴, Hanchen Ma², Yan Zhu⁵, Menghua Cai¹, Jianmin Zhang¹

Affiliations

¹ Department of Immunology, CAMS Key Laboratory for T Cell and Cancer Immunotherapy, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, State Key Laboratory of Medical Molecular Biology, Beijing, China.
² Cheeloo College of Medicine, Shandong University, Jinan, China.
³ School of Physical Science, University of California, Irvine, Irvine, CA, United States.
⁴ Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China.
⁵ Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.

Abstract

Background: Long noncoding RNAs (lncRNAs) crucially modulate DNA damage responses/repair in cancer cells. However, the underlying regulatory role of genome integrity and its clinical value in colon adenocarcinoma (COAD) remains unclear. This study links genome instability to lncRNA using computational biology techniques, in attempt to propose novel biomarkers of immunotherapy outcome, and investigated a potential competing endogenous RNA (ceRNA) as a molecular regulatory mechanism. Methods: TCGA-COAD patients were divided into genome unstable (GU)-like and genome stable (GS)-like clusters via hierarchical clustering to predict immunotherapy outcomes. Multivariate Cox model was established to predict the overall survival rate in COAD patients. Additionally, SVM and LASSO algorithms were applied to obtain hub lncRNAs. A novel genome instability-related ceRNA network was predicted with the Starbase 2.0 database. To better understand how these genes fundamentally interact during tumor progression and development, the mutation analysis and single-gene analysis for each gene was performed. Results: In contrast to those in the GS-like cluster, GU-like-cluster patients demonstrated a higher tumor mutational burden (TMB)/microsatellite instability (MSI), DNA polymerase epsilon (POLE) mutation rate, and immune checkpoint expression, all indicate a greater predictive power for response rate for immunotherapy. The novel prognostic signature demonstrated an outstanding predictive performance (AUC > 0.70). The genes in the genome insatiability-related ceRNA network (including four axes: AL161772.1-has-miR-671-5p (hsa-miR-181d-5p, has-miR-106a-5p)-NINL, AL161772.1-has-miR-106a-5p-TNFSF11, AC124067.4-hsa-miR-92b-3p (hsa-miR-589-5p)-PHYHIPL, and BOLA3-AS1-has-miR-130b-3p-SALL4) were identified as critical regulators of tumor microenvironment infiltration, cancer stemness, and drug resistance. qPCR was performed to validate the expression patterns of these genes. Furthermore, the MSI-high proportion was greater in patients with mutated type than in those with the wild type according to all four target genes, indicating that these four genes modulate genomic integrity and could serve as novel immunotherapy biomarkers. Conclusion: We demonstrated that genome instability-related lncRNA is a novel biomarker for immunotherapy outcomes and prognosis. A novel ceRNA network that modulates genomic integrity, including four lncRNA-miRNA-mRNA axes, was proposed.

Keywords: MSI; ceRNA; colon adenocarcinoma; genome instability; immune checkpoint inhibitor; lncRNA; tumor heterogeneity.