Affiliation: | 1. Department of Oncology, Shanxi Province Academy of Traditional Chinese Medicine, Shanxi Province Hospital of Traditional Chinese Medicine, Taiyuan, China;2. Department of Anesthesiology, Shanxi Provincial People's Hospital, Taiyuan, China;3. Department of Oncology, Shanxi Province Academy of Traditional Chinese Medicine, Shanxi Province Hospital of Traditional Chinese Medicine, Taiyuan, China Contribution: Data curation (equal), Investigation (equal), Methodology (equal), Software (equal);4. Department of Oncology, Shanxi Province Academy of Traditional Chinese Medicine, Shanxi Province Hospital of Traditional Chinese Medicine, Taiyuan, China Contribution: Investigation (equal), Software (equal), Validation (equal);5. Department of Oncology, Shanxi Province Academy of Traditional Chinese Medicine, Shanxi Province Hospital of Traditional Chinese Medicine, Taiyuan, China Contribution: Software (equal), Validation (equal);6. Department of Integrated Traditional Chinese and Western Medicine, Institute of Integrative Medicine, Xiangya Hospital, Central South University, Changsha, China |
Abstract: | Low-grade glioma (LGG) poses significant management challenges and has a dismal prognosis. While immunotherapy has shown significant promise in cancer treatment, its progress in glioma has confronted with challenges. In our study, we aimed to develop an immune-related gene prognostic index (IRGPI) which could be used to evaluate the response and efficacy of LGG patients with immunotherapy. We included a total of 529 LGG samples from TCGA database and 1152 normal brain tissue samples from the GTEx database. Immune-related differentially expressed genes (DEGs) were screened. Then, we used weighted gene co-expression network analysis (WGCNA) to identify immune-related hub genes in LGG patients and performed Cox regression analysis to construct an IRGPI. The median IRGPI was used as the cut-off value to categorize LGG patients into IRGPI-high and low subgroups, and the molecular and immune mechanism in IRGPI-defined subgroups were analysed. Finally, we explored the relationship between IRGPI-defined subgroups and immunotherapy related indicators in patients after immunotherapy. Three genes (RHOA, NFKBIA and CCL3) were selected to construct the IRGPI. In a survival analysis using TCGA cohort as a training set, patients in the IRGPI-low subgroup had a better OS than those in IRGPI-high subgroup, consistent with the results in CGGA cohort. The comprehensive results showed that IRGPI-low subgroup had a more abundant activated immune cell population and lower TIDE score, higher MSI, higher TMB score, lower T cell dysfunction score, more likely benefit from ICIs therapy. IRGPI is a promising biomarker in the field of LGG ICIs therapy to distinguish the prognosis, the molecular and immunological characteristics of patients. |