Abstract
Colorectal cancer (CRC) is a prevalent and lethal malignancy, with ubiquitination significantly influencing cellular processes involved in cancer progression. However, the contributions of ubiquitination-related genes in CRC remain unclear. This study conducted a detailed analysis of gene expression profiles associated with ubiquitination in CRC, evaluating 1006 genes across 46 pathways. By comparing CRC tissues to adjacent normal tissues, we identified differentially expressed genes and developed a ubiquitination-related pathway gene signature (URPGS) using LASSO regression analysis on genes with prognostic significance. The prognostic capability of the URPGS was validated in independent cohorts, and its associations with clinical characteristics, including post-chemotherapy survival outcomes, were examined. Machine learning techniques identified HSPA1A as a key gene relevant to CRC both in vitro and in vivo. Our analysis revealed 307 differentially expressed ubiquitination-related genes, with 24 significantly associated with patient prognosis. The developed 14-gene URPGS exhibited strong prognostic value, effectively stratifying patients into high-risk and low-risk groups for overall survival. The URPGS correlated with advanced clinical stages, lymph node metastasis, and recurrence, with higher scores linked to poorer post-chemotherapy survival outcomes. Knockdown of HSPA1A significantly inhibited CRC cell proliferation, migration, and invasion in vitro, as well as tumor growth and metastasis in vivo. This research establishes a novel URPGS that effectively predicts prognosis and chemotherapy outcomes in CRC, enhancing our understanding of ubiquitination's role and suggesting personalized treatment strategies.