A diagnostic signature derived from NK cell related genes in prostate cancer: insights from integrated scRNA-seq and bulk RNA-seq analyses with functional validation of KIT.

BACKGROUND

Prostate cancer is one of the most common malignant tumors of the male genitourinary system. The impaired activity of natural killer (NK) cells observed in prostate cancer may contribute to immune evasion. This study aimed to develop robust NK cell-related diagnostic signatures.

METHODS

Based on NK related genes identified by scRNA-seq analysis, weighted gene co-expression network analysis, least absolute shrinkage and selection operator regression analysis, and machine learning algorithms were used to develop a novel diagnostic model. The expression of diagnostic genes was validated using tumor and adjacent normal tissues collected from prostate cancer patients. The biological functions of KIT as an NK cell related gene were further evaluated in prostate cancer cells.

RESULTS

A nine-gene NK cell-related diagnostic signature was developed, including HSPD1, HSPE1, CLU, KIT, LAPTM4A, SLC18A2, TUBA4A, VWA5A, and ZFP36L1. These genes were validated in independent datasets and showed strong predictive ability for prostate cancer diagnosis (AUC >0.8). Based on the expression profiles of these genes, nine compounds were identified that may influence drug sensitivity in prostate cancer. Furthermore, the expressions of CLU, TUBA4A, and KIT were successfully validated in collected prostate cancer tissue samples. Functional experiments demonstrated that KIT overexpression enhanced the cytotoxicity of NK-92 cells against prostate cancer PC-3 cells, inhibited cancer cell viability, cell migration and invasion, and increased the secretion of cytokines such as IFN-γ, Gzms-A, Gzms-B, and Perforin, as well as the degranulation marker CD107a.

CONCLUSION

This study provides a new understanding of NK cell related gene signatures in prostate cancer diagnosis and highlights KIT as a promising candidate for future therapeutic investigation. Further research is needed to explore the mechanisms underlying the expression of these genes and their roles in the tumor microenvironment.