Molecular feature-based classification of retroperitoneal liposarcoma: a prospective cohort study.

ABSTRACT:

Background

Retroperitoneal liposarcoma (RPLS) is a critical malignant disease with various clinical outcomes. However, the molecular heterogeneity of RPLS was poorly elucidated, and few biomarkers were proposed to monitor its progression.

Methods

RNA sequencing was performed on a training cohort of 88 RPLS patients to identify dysregulated genes and pathways using clusterProfiler. The GSVA algorithm was utilized to assess signaling pathway levels in each sample, and unsupervised clustering was employed to distinguish RPLS subtypes. Differentially expressed genes (DEGs) between RPLS subtypes were identified to construct a simplified dichotomous clustering via nonnegative matrix factorization. The feasibility of this classification was validated in a separate validation cohort

SUBMITTER: Xiao M 

PROVIDER: S-EPMC12101831 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature