IL-1β and associated molecules as prognostic biomarkers linked with immune cell infiltration in colorectal cancer: an integrated statistical and machine learning approach.

ABSTRACT:

Purpose

Colorectal cancer (CRC) is the third most common cancer globally, necessitating novel biomarkers for early diagnosis and treatment. This study proposes an efficient pipeline leveraging an integrated bioinformatics and machine learning framework to enhance the identification of diagnostic and prognostic biomarkers for CRC.

Methods

A selection of methylated differentially expressed genes (MeDEGs) and features (genes) was made using both statistical and Machine learning (ML) approaches from publically available datasets. These genes were subjected to STRING network construction and hub genes estimation, separately. Also, essential miRNAs (micro-RNAs) and TFs (Transcription factors) as regulatory elements were revealed and findings were validated through scRNA-seq analys

SUBMITTER: Sahoo K 

PROVIDER: S-EPMC11871282 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature