The differential expression of AFF3 in cervical cancer and its correlation with clinicopathological features and prognosis.

ABSTRACT

BACKGROUND: Cervical cancer (CC) is the second most common malignancy in women, and identifying biomarkers of CC is crucial for prognosis prediction. Here, we investigated the expression of AF4/FMR2 Family Member 3 (AFF3) in CC and its association with clinicopathological features and prognosis. METHODS: Tumour and adjacent tissues, along with clinicopathological features and follow-up information, were collected from 78 patients. AFF3 expression was assessed using quantitative real-time polymerase chain reaction and Western blotting. The correlation between AFF3 expression and CC symptoms was using chi-square test. The 5-year overall survival (OS) was analysed using the Kaplan-Meier method. The Univariate analysis of prognostic risk factors was conducted using the COX proportional hazards model, followed by multivariate COX regression analysis including variables with p < 0.01. RESULTS: AFF3 expression was downregulated in CC, and its levels were correlated with lymph node metastasis (LNM) and International Federation of Gynaecology and Obstetrics (FIGO) stage. Patients with low AFF3 expression had a lower 5-year OS rate (52.78%, 19/36). Postoperative survival was reduced in patients with histological grade 3 (G3), myometrial invasion (depth ≥ 1/2), lymphovascular space invasion, LNM, and advanced FIGO stage. Low expression of AFF3 (HR 2.848, 95% CI 1.144-7.090) and histological grade G3 (HR 4.393, 95% CI 1.663-11.607) were identified as independent prognostic risk factors in CC patients. CONCLUSION: Low expression of AFF3 and histological G3 are independent predictors of poor prognosis in CC patients, suggesting that AFF3 could serve as a potential biomarker for prognostic assessment in CC.

Cervical cancer is a significant health concern worldwide, responsible for over 300,000 deaths annually and ranking as the fourth most common cancer in women. Existing screening methods have limitations, highlighting the need for innovative therapies. In our research, we identified a specific genetic material that varied significantly among cervical cancer patients with varying survival outcomes, detected in tissue samples obtained post-surgery. Our study demonstrates the considerable potential of this marker for accurately predicting outcomes in our study population. By analysing differences in the expression of this genetic marker, we can forecast the prognosis and progression of cervical cancer. These findings offer valuable insights for advancing cervical cancer treatment strategies, potentially improving outcomes for patients. Early detection and targeted treatment based on this genetic marker could extend patients' lives and prevent fatalities by enabling timely medical intervention and management.