Combined bulk RNA and single-cell RNA analyses reveal TXNL4A as a new biomarker for hepatocellular carcinoma

Yifan Li; Qiaozhen Zhu; Shuchang Zhou; Jiangtao Chen; Aoyu Du; Changjiang Qin

doi:10.3389/fonc.2023.1202732

Combined bulk RNA and single-cell RNA analyses reveal TXNL4A as a new biomarker for hepatocellular carcinoma

Front Oncol. 2023 May 25:13:1202732. doi: 10.3389/fonc.2023.1202732. eCollection 2023.

Authors

Yifan Li¹, Qiaozhen Zhu², Shuchang Zhou¹, Jiangtao Chen¹, Aoyu Du³, Changjiang Qin¹

Affiliations

¹ Department of Gastrointestinal Surgery, Huaihe Hospital of Henan University, Kaifeng, Henan, China.
² Infection and Immunity Institute and Translational Medical Center, Huaihe Hospital, Kaifeng, Henan, China.
³ Department of Plastic Surgery, Huaihe Hospital of Henan University, Kaifeng, Henan, China.

Abstract

Introduction: Hepatocellular carcinoma (HCC) has a high mortality rate worldwide. The dysregulation of RNA splicing is a major event leading to the occurrence, progression, and drug resistance of cancer. Therefore, it is important to identify new biomarkers of HCC from the RNA splicing pathway.

Methods: We performed the differential expression and prognostic analyses of RNA splicing-related genes (RRGs) using The Cancer Genome Atlas-liver hepatocellular carcinoma (LIHC). The International Cancer Genome Consortium (ICGC)-LIHC dataset was used to construct and validate prognostic models, and the PubMed database was used to explore genes in the models to identify new markers. The screened genes were subjected to genomic analyses, including differential, prognostic, enrichment, and immunocorrelation analyses. Single-cell RNA (scRNA) data were used to further validate the immunogenetic relationship.

Results: Of 215 RRGs, we identified 75 differentially expressed prognosis-related genes, and a prognostic model incorporating thioredoxin like 4A (TXNL4A) was identified using least absolute shrinkage and selection operator regression analysis. ICGC-LIHC was used as a validation dataset to confirm the validity of the model. PubMed failed to retrieve HCC-related studies on TXNL4A. TXNL4A was highly expressed in most tumors and was associated with HCC survival. Chi-squared analyses indicated that TXNL4A expression positively correlated positively with the clinical features of HCC. Multivariate analyses revealed that high TXNL4A expression was an independent risk factor for HCC. Immunocorrelation and scRNA data analyses indicated that TXNL4A was correlated with CD8 T cell infiltration in HCC.

Conclusion: Therefore, we identified a prognostic and immune-related marker for HCC from the RNA splicing pathway.

Keywords: RNA splicing pathway; TXNL4A; hepatocellular carcinoma; single-cell RNA; tumor immune.

Grants and funding

This study was supported by Science and Technology Foundation of Henan Province (172102310152), Natural Science Foundation of Henan Province (182300410359), Science and Technology Foundation of Henan Province (SBGJ202002097), Science and Technology Foundation of Henan Province (192102310099), Henan Provincial Education Fund (19A320020).