FAM3B 过表达与结直肠癌不良预后和免疫失调相关：来自生物信息学和孟德尔随机化分析的见解

Colorectal cancer (CRC) ranks third in global cancer diagnoses and is the second leading cause of cancer-related deaths. Identifying novel therapeutic targets and effective prognostic markers is crucial to improve CRC outcomes. This study aimed to investigate the role of FAM3B in relation to clinicopathological features, prognosis, tumor microenvironment, and immune infiltration of CRC.

We obtained data from bioinformatics databases, immunohistochemical experiments, and two-sample Mendelian randomization analyses. Differential expression analysis, survival analysis, Cox regression, and tumor microenvironment/immune infiltration evaluation were performed. FAM3B expression patterns were validated by immunohistochemistry. The causal relationship between FAM3B and CRC risk was explored using SNP data obtained from IEU GWAS and FinnGen by calculating the MR-Egger regression, weighted median, and inverse-variance weighting estimations.

FAM3B was significantly upregulated in CRC tissues compared to normal tissues (p < 0.001). High FAM3B expression was associated with poor prognosis (HR: 1.59, 95% CI 1.00-2.54, p < 0.05), advanced tumor stages, and metastasis. Patients with high FAM3B expression had lower overall survival rates compared to those with low expression. High FAM3B levels were correlated with increased tumor cell purity and specific immune infiltration, including higher levels of M1 macrophages and lower levels of CD8+ T cells, resting NK cells, and monocytes (p < 0.05). The multivariate Cox regression analysis confirmed FAM3B as an independent prognostic factor. Mendelian randomization analysis indicated a causal relationship between FAM3B and CRC risk (IVW method OR = 1.07, 95% CI 1.00-1.14, p = 0.035).

High FAM3B expression levels are correlated with poor prognosis and advanced tumor stages in CRC patients, likely influencing CRC development by regulating the tumor microenvironment characteristics. These findings suggest that FAM3B could be a potential CRC therapeutic target, and the constructed clinical predictive model offers new insights for the diagnosis and treatment of CRC patients.