Exploring prognostic microbiota markers in patients with endometrial carcinoma: Intratumoral insights

• DOI: 10.1016/j.heliyon.2024.e27879
• Publication Date: 2024-03-13T08:28:58Z
• Authors: Jie Liu; Yi Qu; Yang-Yang Li; Ya-Lan Xu; Yi-Fang Yan; Hao Qin
• Keywords: Social sciences (General); H1-99; 0301 basic medicine; Q1-390; 03 medical and health sciences; Science (General); Prognostic signature; Microbial biomarker; Risk score; Endometrial carcinoma; TCGA-UCEC; Research Article

Endometrial cancer, a leading gynecological malignancy, is profoundly influenced by the uterine microbiota, key factor in disease prognosis and treatment. Our study underscores distinct microbial compositions endometrial cancer compared to adjacent non-cancerous tissues, revealing dominant presence of p_Actinobacteria cancerous tissues as opposed p_Firmicutes surrounding areas. Through comprehensive analysis, we identified 485 unique microorganisms 26 which correlate with patient prognosis. Employing univariate Cox regression LASSO analyses, devised risk scoring model, effectively stratifying patients into high low-risk categories, thereby providing predictive insights their overall survival. We further developed nomogram that incorporates score along age, grade, clinical stage, significantly enhancing accuracy our prediction model for cancer. Moreover, delves differential immune landscapes high-risk patients. The group displayed higher prevalence activated B cells increased T cell co-stimulation, indicative robust response. Conversely, showed elevated tumor dysfunction exclusion scores, suggesting less favorable outcomes immunotherapy. Notably, efficacy IPS-CTLA4 PD1/PD-L1/PD-L2 blockers was substantially group, pointing more responsive immunotherapeutic approach. In summary, research elucidates patterns establishes both nomogram. These findings highlight potential microbiota biomarker customizing treatment strategies, enabling precise interventions while preventing overtreatment cases. This emphasizes microbiota's role tailoring immunotherapy, offering novel perspective Significantly, study's expansive sample analysis from TCGA-UCEC cohort, employing linear discriminant effect size methodology, not only validates but also enhances understanding paving way diagnostic therapeutic approaches its management.