OLFML3, as a potential predictor of prognosis and therapeutic target for glioma, is closely related to immune cell infiltration

The low response rate to immunosuppressant is mainly due the lack of adequate knowledge about tumor microenvironment (TME) and screening biomarkers for gliomas. We aimed identify promising immune new classification glioma. In this study, multiple-immune algorithms were used calculate immune-infiltration scores. Unsupervised supervised machine learning methods perform classification. observed that OLFML3 overexpression was indicated in gliomas linked poor prognosis. knockdown inhibited proliferation, invasion increased sensitivity glioma cells temozolomide. expression could also reflect aberrant status. Based on immune-related signature, patients divided into three subtypes via consensus clustering. Patients with C2 subtype presented poorer prognosis shorter progression free survival than other two subtypes. TME patterns among different. C3 are immune-inflamed immune-desert tumors, respectively. Additionally, compared subtype, C1/C2 more likely respond immunotherapy. pRRophetic algorithm resistant temozolomide, but sensitive paclitaxel cisplatin. To conclude, affects cell invasion, TMZ has been proved be an independent prognostic- biomarker. novel subtype's provide prognostic predictive predictors may guide physicians selecting potential responders.