Liquid-liquid phase separation-driven molecular subtyping and prognostic modeling in colorectal cancer

TL;DR

This study explores how liquid-liquid phase separation influences colorectal cancer progression and develops a prognostic model to predict patient outcomes.

Contribution

The paper introduces a novel LLPS-related gene signature for risk stratification and prognosis in colorectal cancer.

Findings

430 LLPS-related differentially expressed genes were identified in colorectal cancer samples.

A five-gene LLPS-associated risk signature was developed to distinguish high- and low-risk patient groups.

The model revealed differences in prognosis, mutations, pathways, and drug sensitivity between risk groups.

Abstract

Liquid–liquid phase separation (LLPS) orchestrates the spatiotemporal organization of biomolecular condensates and regulates numerous biological processes. However, the extent to which dysregulated LLPS facilitates the progression of colorectal cancer (CRC) has not been elucidated. Elucidating how LLPS influences CRC possibly offers valuable insights into diagnosis and therapeutic intervention.

Differentially expressed genes (DEGs) were identified from 566 CRC samples and 19 normal controls in the GSE39582 dataset. LLPS-linked genes were collected from the DrLLPS database. Prognostically significant genes were identified via univariate Cox regression, least absolute shrinkage and selection operator regression, and stepwise akaike information criterion algorithm. The risk score was derived utilizing the LLPS-linked gene signature. Patient characteristics were evaluated concerning the computed risk scores. The biological and clinical distinctions across high-risk and low-risk cohorts were further investigated, leveraging the COAD, READ, and GSE17536 validation cohorts. The expression and spatial distribution of the five prognostic genes were examined via the GSE166555 dataset and spatial transcriptomics analysis. The hydroxyacyl-coenzyme A dehydrogenase (HADH) expression-related enrichment pathways were further analysed via weighted gene coexpression network analysis combined with Metascape. The expression and biological functions of HADH were verified in vitro.

A total of 430 LLPS-related DEGs were identified, from which five prognostic genes were selected to construct the LLPS-associated risk signature. Marked differences in gene expression profiles, overall prognosis, clinicopathological attributes, somatic mutations, signaling pathway activity, tumor microenvironment composition, and drug sensitivity were noted across the high-risk and low-risk populations. Furthermore, the expression of the five prognostic genes and biological functions of HADH were validated through in vitro experiments.

An LLPS-related prognostic model was created, enabling the stratification of the CRC population according to risk and informing individualized therapeutic strategies.

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