Deciphering the Role of SLFN12: A Novel Biomarker for Predicting Immunotherapy Outcomes in Glioma Patients Through Artificial Intelligence.

Gliomas are the most prevalent form of primary brain tumours. Recently, targeting the PD-1 pathway with immunotherapies has shown promise as a novel glioma treatment. However, not all patients experience long-lasting benefits, underscoring the necessity to discover reliable biomarkers for predicting treatment outcomes. This study applied a range of advanced artificial intelligence methods to identify a new biomarker linked to the effectiveness of anti-PD-1 immunotherapy in glioma patients. Through an extensive analysis of single-cell RNA sequencing and bulk transcriptomic data from over 3000 patients, the gene SLFN12 emerged as a significant and independent predictor of immunotherapy response. Our results indicate that elevated SLFN12 expression is associated with worse overall survival across various glioma cohorts. Notably, we found that patients with high SLFN12 levels are less likely to respond favourably to anti-PD-1 treatment, positioning SLFN12 as a clinically valuable biomarker for personalised treatment decisions. Functional studies revealed that SLFN12 is involved in key immune-related pathways, shedding light on its potential role in altering the tumour microenvironment and impacting immunotherapy outcomes. Additional laboratory experiments confirmed the role of SLFN12 in promoting glioma cell proliferation, migration and macrophage recruitment. In summary, this study identifies SLFN12 as a novel biomarker for predicting immunotherapy response in glioma patients, offering new insights for precision immunotherapy approaches.