Synergistic Impact of ARSB, TP53, and Maspin Gene Expressions on Survival Outcomes in Colorectal Cancer: A Comprehensive Clinicopathological Analysis

(1) Background: Colorectal cancer (CRC) remains a significant cause of morbidity and mortality worldwide, with its prognosis influenced by genetic and clinicopathological factors. This study investigates the associations between the gene expressions of Arylsulfatase B (ARSB), TP53, and Maspin, alongside traditional clinicopathological features, and their impact on CRC survival outcomes. (2) Methods: 70 consecutive CRC cases were analyzed for ARSB, TP53, and Maspin gene expression using RT-qPCR, and their protein levels were assessed through immunohistochemistry. Clinicopathological parameters—age, gender, tumor localization, macroscopic and microscopic aspects, lymph node ratio, pT stage, and tumor budding—were evaluated for their prognostic significance. Kaplan–Meier survival analysis with Cox proportional hazards regression was used to determine their impact on overall survival. (3) Results: No significant survival differences were observed based on age, gender, tumor localization, and macroscopic aspect. The microscopic aspect and pT stage showed significant associations with survival, with poorer outcomes in G3 and pT3/pT4 stages, respectively. Immunohistochemical positivity for ARSB and Maspin indicated a longer survival, while TP53 protein expression alone did not significantly impact the prognosis. Dual high gene expression (ARSB + TP53, TP53 + Maspin) and triple high gene expression (ARSB + TP53 + Maspin) were significantly associated with better survival outcomes. (4) Conclusions: The combined gene expression profile of ARSB, TP53, and Maspin presents a novel prognostic marker in CRC, offering insights into the molecular dynamics of cancer cells and potential therapeutic targets. These findings emphasize the importance of integrating molecular markers with traditional clinicopathological factors for a more accurate prognostication and personalized treatment approach in CRC.