Integrated transcriptomic analysis identifies Paternally Expressed Gene 10 as a novel candidate biomarker associated with aggressive features in liposarcoma
Abstract Background Liposarcoma is a rare cancer, comprising four major histological subtypes: well-differentiated, dedifferentiated, myxoid and pleomorphic liposarcoma. Therapeutic options remain limited for advanced disease, and additional biomarkers that may support biological characterization, diagnosis, or risk stratification are needed. Methods Bulk RNA sequencing (RNA-seq) was performed on paired tumour and adjacent non-tumour tissues from an analysable subset of 16 patients (22 tumour specimens) within a clinicopathological cohort of 21 patients. Differential gene expression analysis, principal component analysis, gene set enrichment (GSEA) analysis and single-sample GSEA (ssGSEA) were used to define subtype-specific transcriptional programs and imprinted-gene dysregulation. PEG10 expression was validated by RT-qPCR and RNA fluorescence in situ hybridization (FISH), and its cellular localization was explored by combined FISH and immunofluorescence for P53, vimentin, Ki67, and CD34. PEG10 expression in liposarcoma was further investigated in an external single-cell RNA-sequencing dataset of dedifferentiated liposarcoma. An exploratory survival analysis was performed in the pan-sarcoma TCGA-SARC cohort. Results Transcriptomic profiling identified distinct subtype-specific gene expression patterns and broad dysregulation of imprinted genes in liposarcoma compared with adjacent non-tumour tissue. Among all the imprinted genes, PEG10 showed a marked tumour-to-normal expression difference and good discriminatory performance between tumour and normal tissues in the discovery cohort (AUC=0.867). In the TCGA sarcoma cohort high PEG10 expression was associated with shorter overall survival. Immuno-FISH and single-cell analyses revealed that PEG10 was predominantly detected in tumour and proliferating cell populations. Importantly, PEG10 expression was higher in high-grade tumours. In bulk RNA-seq data, PEG10 expression correlated with hypoxia, extracellular matrix remodelling and invasion ssGSEA signatures. In the external single-cell RNA-seq dataset PEG10high tumours showed a reduced immune cell infiltration. Conclusions This study provides an integrated transcriptomic characterisation of liposarcoma and identifies PEG10 as a candidate tumour-associated biomarker linked to aggressive disease features. The diagnostic and prognostic value of PEG10 requires validation in larger, independent, subtype-balanced liposarcoma cohorts, and its potential therapeutic relevance requires direct functional investigation.