Research Paper Volume 16, Issue 6 pp 5163—5183

Novel histone acetylation-related lncRNA signature for predicting prognosis and tumor microenvironment in esophageal carcinoma

Batter Han1, *, , Ying Ma2, *, , Pengjie Yang1, *, , Fangchao Zhao3, *, , Haiyong Zhu3, *, , Shujun Li3, , Rong Yu1, , Subudao Bao4, ,

  • 1 Department of Thoracic Surgery, Peking University Cancer Hospital Inner Mongolia Hospital, Hohhot 010010, China
  • 2 Department of Thoracic Surgery, Mongolia Medical University Affiliated Hospital, Hohhot 010050, China
  • 3 Department of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang 050000, China
  • 4 Mongolian Medicine College, Inner Mongolia Medical University, Hohhot 010110, China
* Equal contribution

Received: June 30, 2023       Accepted: January 2, 2024       Published: March 13, 2024      

https://doi.org/10.18632/aging.205636
How to Cite

Copyright: © 2024 Han et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Histone acetylation is one of the most common epigenetic modifications and plays a crucial role in tumorigenesis. However, the prognostic significance of histone acetylation-related lncRNAs (HARlncRNAs) in esophageal carcinoma (ESCA) is not well understood. A total of 653 differentially expressed lncRNAs (DElncRNAs) were identified between 162 ESCA tissues and 11 normal tissues in the TCGA database, and 7 of them were correlated with acetylation regulators. We employed univariate Cox regression analysis, combining it with clinical prognosis information, to select 3 prognostic-related HARlncRNAs for further analysis. Subsequently, we used LASSO regression analysis to construct a risk signature for ESCA and identified C21orf62-AS1 and SSTR5.AS1 as potential biomarkers for the prognosis of ESCA patients. Based on the risk score calculated using the risk signature, we categorized patients into high- and low-risk groups. We identified the risk score as an independent risk factor and validated it in the training, test, and GSE53624 datasets. Additionally, patients categorized by their risk scores exhibited distinct immune statuses, tumor mutation burdens, responses to immunotherapy, and drug sensitivities.

Abbreviations

ESCC: esophageal squamous cell carcinoma; ESCA: esophageal cancer; lncRNAs: long non-coding RNAs; HARlncRNAs: histone acetylation-related lncRNAs; HARGs: histone acetylation-related genes; CNV: copy number variation; GEO: Gene Expression Omnibus; TCGA: The Cancer Genome Atlas; GTEx: Genotype-Tissue Expression; FPKM: fragment per kilobase method; LASSO: least absolute shrinkage and selection operator; ROC: receiver operating characteristic; GO: gene ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; ssGSEA: single-sample gene set enrichment analysis; TMB: tumor mutation burden; ICGs: immune checkpoint genes; TIDE: tumour immune dysfunction and exclusion; qRT-PCR: quantitative real-time polymerase chain reaction; DEG: differentially expressed gene; IC50: the half-maximal inhibitory concentration.