Identification of Prognostic Genes Associated with Innate Lymphoid Cells in Cervical Cancer Through Bioinformatics Analyses and Experimental Assays

The functions of innate lymphoid cells (ILCs) remain ambiguous in cervical cancer (CC). Thus, this study sought to pinpoint prognostic genes linked to ILCs in CC through both bioinformaticis analyses and experiments. First, single-cell analysis was conducted to identify ILCs, subsequently followed by hdWGCNA to identify key module genes, and Least absolute shrinkage and selection operator (Lasso)+StepCox [both] was determined to the optimum model. Subsequently, differential expression analysis coupled with univariate Cox regression was used to discover CC survival-related genes, which were then intersected with key module genes. A prognostic model was identified using 101 combinations derived from 10 machine learning algorithms, AGPAT4, UCP2, NDUFB7, SELL, TNF, WDR45, TFRC, FCRL3, TBX21, and AKNA were identified as prognostic genes. The area under the curve (AUC) for prognostic model exceeded 0.7, and Kaplan-Meier curve demonstrated that the low-risk cohort had an extended survival duration, suggesting the prognostic model’s predictive capacity for CC survival. Additionally, reverse transcription real-time polymerase chain reaction (RT-qPCR) and Western blot were employed to verify prognostic gene expression in tissue samples. Expression study revealed that FCRL3 shown significantly increased expression in CC samples at the levels of bioinformatics, mRNA, and protein. This study identified ten ILC-related prognostic genes in CC, which offer preliminary candidate molecular markers for CC survival stratification, further large-scale clinical validation and functional research are required prior to clinical prognostic or therapeutic translation.