Dysregulation of selected lncRNAs and Hippo/EMT-associated genes in hepatocellular carcinoma patients
Abstract
Background and aim: Liver cancer remains the sixth most common malignancy and the third leading cause of cancer-related death worldwide, with hepatocellular carcinoma accounting for most cases. Long non-coding RNAs regulate hepatocarcinogenesis by modulating proliferation, epithelial–mesenchymal transition, and invasion. This study aimed to characterize the expression of three such transcripts (MALAT1, NEAT1, NKILA) and two protein-coding genes of the Hippo/EMT axis (YAP1, SNAI1) in a single-center Romanian cohort of hepatocellular carcinoma patients and to interpret the resulting pattern in relation to the existing literature. Methods: Tumoral and non-tumoral liver tissue samples were obtained from patients with non-metastatic hepatocellular carcinoma undergoing surgical resection. Total RNA was extracted using TRIzol, reverse-transcribed, and quantified by SYBR Green–based qRT-PCR on a QuantStudio 7 Flex platform. Relative expression was calculated by the ΔΔCt method, normalized to B2M and 18S rRNA, and compared between the two groups using GraphPad Prism; p < 0.05 was considered significant. Results: 39 tumoral and 39 non-tumoral tissue samples were analyzed. MALAT1 (p = 0.0008), YAP1 (p = 0.0016), and SNAI1 (p = 0.0365) were significantly overexpressed in tumoral tissue, whereas NEAT1 was significantly reduced (p = 0.0320). NKILA showed no significant difference between groups (p = 0.3592). Effect sizes were graded, with the strongest separation for MALAT1 and YAP1 and more modest differences for SNAI1 and NEAT1. Conclusion: MALAT1, YAP1, and SNAI1 overexpression in hepatocellular carcinoma was confirmed in a single-center cohort from Romania, including predominantly early-stage subjects. The reduction of NEAT1 diverges from most prior reports and may reflect isoform-specific detection or the molecular abnormality of the cirrhotic tissue comparator. Future work should incorporate isoform-specific assays, etiology-stratified cohorts, and outcome correlation.