# Identification of DNASE1L3 as a novel biomarker of clinical stage in liver hepatocellular carcinoma

## TL;DR

This study identifies DNASE1L3 as a new biomarker for liver cancer staging, showing its expression decreases with disease progression and predicts poor outcomes.

## Contribution

DNASE1L3 is newly identified as a tissue biomarker intrinsically linked to clinical stage and prognosis in liver hepatocellular carcinoma.

## Key findings

- DNASE1L3 expression decreases with advancing liver cancer stages.
- Low DNASE1L3 levels are an independent predictor of poor prognosis in LIHC.
- DNASE1L3 is part of a key gene module associated with LIHC progression.

## Abstract

Tumor staging is critical for guiding therapeutic decisions and determining prognosis in liver hepatocellular carcinoma (LIHC). This study aimed to identify potential tissue biomarkers intrinsically linked to disease stage to enhance our understanding of LIHC biology.

Transcriptome and clinical data from LIHC patients were obtained from The Cancer Genome Atlas (TCGA) database. Differential expression analysis was conducted using the “limma” package. Weighted gene co-expression network analysis (WGCNA) was used to identify the gene module most strongly associated with LIHC and to extract hub genes. The hub genes then underwent differential expression, prognostic, and clinical staging analyses, immunohistochemical validation, and multivariable Cox regression analysis.

This analysis included data from 373 LIHC tumors and 50 solid tissue normal samples obtained from the TCGA database. Differential expression analysis identified 319 upregulated and 853 downregulated genes in LIHC tumors compared to these normal samples. An enrichment analysis highlighted key pathways, including cell cycle, DNA replication, and base excision repair. Three independent validation datasets confirmed 18 downregulated and 7 upregulated genes. Among them, DNASE1L3, APOF, and FCN3 were consistently identified as core genes within the WGCNA-derived purple module. A further analysis using the UCSC database revealed that DNASE1L3 and APOF were significantly associated with LIHC prognosis. A MEXPRESS analysis showed strong correlations between these genes and clinical stage, which was further supported by a SangerBox-based staging analysis, indicating significant differences in gene expression between early and advanced disease stages. Immunohistochemical data demonstrated that DNASE1L3 levels decreased from stage I to stage III in LIHC. Multivariable Cox regression confirmed that low DNASE1L3 expression is an independent predictor of poor prognosis in LIHC.

Our results identified DNASE1L3 as a promising tissue biomarker. Loss of DNASE1L3 is indicative of advanced and aggressive LIHC, and therefore its expression may offer complementary information to current staging systems to improve prognostic assessment.