Abstract

Simple SummaryHepatocellular carcinoma (HCC) is the most common type of primary liver cancer, which is more prevalent in adults. Herein, we established the first immuno-autophagy-related long non-coding RNA (IARlncRNA) signature displaying a prognostic ability among HCC patient groups.Background: The dysregulation of autophagy and immunological processes has been linked to various pathophysiological conditions, including cancer. Most notably, their particular involvement in hepatocellular carcinoma (HCC) is becoming increasingly evident. This has led to the possibility of developing a prognostic signature based on immuno-autophagy-related (IAR) genes. Given that long non-coding RNAs (lncRNAs) also play a special role in HCC, a combined signature utilizing IAR genes and HCC-associated long noncoding RNAs (as IARlncRNA) may potentially help in the clinical scenario. Method: We used Pearson correlation analysis, Kaplan–Meier survival curves, univariate and multivariate Cox regression, and ROC curves to generate and validate a prognostic immuno-autophagy-related long non-coding RNA (IARlncRNA) signature. The Chi-squared test was utilized to investigate the correlation between the obtained signature and the clinical characteristics. CIBERSORT algorithms and the Wilcoxon rank sum test were applied to investigate the correlation between signature and infiltrating immune cells. GO and KEGG analyses were performed to derived signature-dependent pathways. Results: Herein, we build an IAR-lncRNA signature (as first in the literature) and demonstrate its prognostic ability in hepatocellular carcinoma. Primarily, we identified three IARlncRNAs (MIR210HG, AC099850.3 and CYTOR) as unfavorable prognostic determinants. The obtained signature predicted the high-risk HCC group with shorter overall survival, and was further associated with clinical characteristics such as tumor grade (t = 10.918, p = 0.001). Additionally, several infiltrating immune cells showed varied fractions between the low-risk group and the high-risk HCC groups in association with the obtained signature. In addition, pathways analysis described by the signature clearly distinguishes both risk groups in HCC. Conclusions: The immuno-autophagy-related long non-coding RNA (IARlncRNA) signature we established exhibits a prognostic ability in hepatocellular carcinoma. To our knowledge, this is the first attempt in the literature to combine three determinants (immune, autophagy and LnRNAs), thus requiring molecular validation of this obtained signature in clinical samples.

Highlights

  • Autophagy as a conserved process captures and degrades intracellular components primarily to maintain metabolism and cellular homeostasis

  • Pearson correlation was used to confirm the correlation between autophagic genes and long non-coding RNAs (lncRNAs) (|R| > 0.4 and p-value < 0.01), in addition to the correlation between immune-related genes and lncRNA (|R| > 0.6 and p-value < 0.01)

  • The analysis revealed three immunoautophagy-related lncRNAs (MIR210HG, AC099850.3, and CYTOR) as the strongest candidates with prognostic potential (Table S1)

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Summary

Introduction

Autophagy as a conserved process captures and degrades intracellular components primarily to maintain metabolism and cellular homeostasis. The dysregulation of autophagy and immunological processes has been linked to various pathophysiological conditions, including cancer Most notably, their particular involvement in hepatocellular carcinoma (HCC) is becoming increasingly evident. Their particular involvement in hepatocellular carcinoma (HCC) is becoming increasingly evident This has led to the possibility of developing a prognostic signature based on immuno-autophagy-related (IAR) genes. Conclusions: The immuno-autophagy-related long non-coding RNA (IARlncRNA) signature we established exhibits a prognostic ability in hepatocellular carcinoma. To our knowledge, this is the first attempt in the literature to combine three determinants (immune, autophagy and LnRNAs), requiring molecular validation of this obtained signature in clinical samples

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