Cervical cancer (CC) is one of the most common malignant tumors in gynecology. Immunotherapy and targeted therapy are two particularly effective treatments. In this study, weighted gene co-expression network analysis and CIBERSORT algorithm that quantifies the composition of immune cells were used to analyze CC expression data based on the GEO database and identify modules related to T cells. Five candidate hub genes were identified by tumor-infiltrating immune cells estimation and Kaplan-Meier survival analysis according to CC data from The Cancer Genome Atlas (TCGA). Chemotherapeutic response, methylation, and gene mutation analyses were implemented so that the five candidate hub genes identified may be the potential biomarkers and therapeutic targets which were related to T cell infiltration. Moreover, the results of RT-qPCR revealed that CD48 was a tumor suppressor gene, which was negatively correlated with CC stages, lymph node metastasis, and differentiation. Furthermore, the functional study verified that the interference of CD48 was able to boost the proliferation and migration ability in vitro and the growth of transplanted tumors in vivo. Overall, we identified molecular targets related to immune infiltration and prognosis, regarded CD48 as a key molecule involved in the progression of CC, thus providing new insights into the development of molecular therapy and immunotherapeutics against CC.
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