Interest in metformin as a potential anticancer agent for colorectal cancer (CRC) has increased. However, compelling epidemiological links and strong preclinical evidence suggest that metformin has variable efficacy in patients with CRC. This variability highlights the need to identify the patients who are most likely to benefit from effective stratification. We aimed to review the evidence concerning the diverse roles of metformin in CRC prevention and treatment, focusing on identifying and validating the predictive biomarkers essential for selecting patient subgroups that are likely to respond positively. We explored the various molecular pathways through which metformin acts and investigated how these diverse mechanisms might explain the observed differences in patient responses. Epidemiological studies and large meta-analyses have consistently reported reduced CRC incidence and improved survival among patients with diabetes treated with metformin. However, successfully extending these benefits broadly across all patients with CRC or achieving predictable outcomes in advanced disease settings remains a significant challenge. This review consolidates the current knowledge, highlights how different mechanisms interact, critically assesses clinical evidence in light of patient heterogeneity, and advocates for the development and implementation of biomarker-guided personalized therapeutic strategies as key to optimally utilizing the potential of metformin in CRC management. The current challenges and vital future research priorities in this critical area are also outlined.

The LPS-induced inflammation model is widely used for studying inflammatory processes due to its cost-effectiveness, reproducibility, and faithful representation of key hallmarks. While researchers often validate this model using clinical cytokine markers, a comprehensive understanding of gene regulatory mechanisms requires extending investigation beyond these hallmarks. Our study leveraged multiple whole-blood bulk RNA-seq datasets to rigorously compare the transcriptional profiles of the well-established LPS-induced inflammation model with those of several human diseases characterized by systemic inflammation. Beyond conventional inflammation-associated systems, we explored additional systems indirectly associated with inflammatory responses (i.e., ISR, RAAS, and UPR) using a customized core inflammatory gene list. Our cross-condition-validation approach spanned four distinct conditions: systemic lupus erythematosus (SLE) patients, dengue infection, candidemia infection, and staphylococcus aureus exposure. This analysis approach, utilizing the core gene list aimed to assess the model’s suitability for understanding the gene regulatory mechanisms underlying inflammatory processes triggered by diverse factors. Our analysis resulted in elevated expressions of innate immune-associated genes, coinciding with suppressed expressions of adaptive immune-associated genes. Also, upregulation of genes associated with cellular stresses and mitochondrial innate immune responses underscored oxidative stress as a central driver of the corresponding inflammatory processes in both the LPS-induced and other inflammatory contexts.

Basal cell carcinoma (BCC), the most common skin cancer, is primarily driven by Hedgehog (Hh) and TP53 pathway alterations. Although additional pathways were implicated, the mutational landscape in Asian populations, particularly Koreans, remains underexplored. We performed whole-exome sequencing of BCC tumor tissues from Korean patients and analyzed mutations in 11 established BCC driver genes (PTCH1, SMO, GLI1, TP53, CSMD1/2, NOTCH1/2, ITIH2, DPP10, and STEAP4). Mutational profiles were compared with Caucasian cohort profiles to identify ethnicity-specific variants. Ultraviolet (UV)-exposed and non-UV-exposed tumor sites were compared; genes unique to non-UV-exposed tumors were further analyzed with protein–protein interaction analysis. BCCs in Koreans exhibited distinct features, including fewer truncating and more intronic variants compared to Caucasians. Korean-specific mutations in SMO, PTCH1, TP53, and NOTCH2 overlapped with oncogenic gain-of-function/loss-of-function (GOF/LOF) variants annotated in OncoKB, with some occurring at hotspot sites. BCCs in non-exposed areas showed recurrent mutations in CSMD1, PTCH1, and NOTCH1, suggesting a UV-independent mechanism. Novel mutations in TAS1R2 and ADCY10 were exclusive to non-exposed BCCs, with protein–protein interaction analysis linking them to TP53 and NOTCH2. We found unique ethnic-specific and UV-independent mutational profiles of BCCs in Koreans. TAS1R2 and ADCY10 may contribute to tumorigenesis of BCC in non-exposed areas, supporting the need for population-specific precision oncology.