Comprehensive Analysis of Immune Implications and Prognostic Value of SPI1 in Gastric Cancer

The transcription factor Spi-1 proto-oncogene (SPI1, also known as PU.1) is a key regulator of signal communication in the immune system and is essential for the development of myeloid cells and lymphocytes. However, the potential role of SPI1 in gastric cancer (GC) and the correlations between SPI1 and immune infiltration remain unclear.

In the present study, multiple databases including ONCOMINE, TIMER, Kaplan-Meier Plotter, and The Cancer Genome Atlas were used to explore the expression levels and prognostic value of SPI1 in GC. cBioPortal was used to explore the possible reasons for the increased expression of SPI1 in GC. The correlations between SPI1 expression and tumor-infiltrating immune cells (TICs) were analyzed using CIBERSORT and TIMER. Gene set enrichment analysis was used to determine the biological function of SPI1 in the development of GC. In addition, a risk signature based on SPI1-related immunomodulators was constructed to accurately evaluate the prognosis of patients with GC. The upregulation of SPI1 expression in GC was further confirmed through immunohistochemistry, western blotting, and real-time quantitative PCR (RT-qPCR) assay.

The expression of SPI1 was increased significantly in GC according to multiple databases, and high expression of SPI1 was related to poor prognosis and progression of GC. The main factor influencing the high expression of SPI1 mRNA in GC may be diploidy, not DNA methylation. Moreover, immunohistochemistry, western blotting, and RT-qPCR assays also confirmed the upregulated expression of SPI1 in GC. CIBERSORT analysis revealed that SPI1 expression was correlated with seven types of TICs (naive B cells, resting memory CD4 T cells, activated memory CD4 T cells, activated natural killer cells, resting natural killer cells, M2 macrophages, and resting dendritic cells). Gene set enrichment analysis indicated that SPI1 might be related to immune activation in GC and participate in cell cycle regulation. In addition, based on SPI1-related immunomodulators, we developed multiple-gene risk prediction signatures and constructed a nomogram that can independently predict the clinical outcome of GC.

The results of the present study suggest that SPI1 has a critical role in determining the prognosis of GC patients and may be a potential immunotherapeutic target.