A Ferroptosis-Related Gene Prognostic Index to Predict Temozolomide Sensitivity and Immune Checkpoint Inhibitor Response for Glioma - Cai, Yonghua; Liang, Xianqiu; Zhan, Zhengming; Zeng, Yu; Lin, Jie; Xu, Anqi; Xue, Shuaishuai; Xu, Wei; Chai, Peng; Mao, Yangqi; Song, Zibin; Han, Lei; et al. (Frontiers in Cell and Developmental Biology, 2022)
Background: Glioma is the most lethal solid tumor of all brain cancers. Despite a multimodality therapy with surgery, radiotherapy, chemotherapy, and immunotherapy, Glioma prognosis remains poor. Ferroptosis is a crucial tumor suppressor mechanism that has proven to be effective in anticancer therapy. However, the implications of ferroptosis on the clinical prognosis, chemotherapy, and immune checkpoint inhibitor (ICI) therapy for patients with glioma remain to be elucidated. Methods: Consensus clustering identified two distinct ferroptosis-related subtypes based on the Cancer Genome Atlas (TCGA) glioma dataset (n=663). Subsequently, the ferroptosis-related gene prognostic index (FRGPI) was constructed by weighted gene co-expression network analysis (WGCNA) and “stepAIC” algorithms and validated with the Chinese Glioma Genome Atlas (CGGA) dataset (n =404). Subsequently, the correlation between clinical, molecular, and immune features and FRGPI was analyzed. After that, the temozolomide sensitivity and the ICI response for glioma were predicted by the “pRRophetic” and “TIDE” algorithms, respectively. Finally, candidate small molecular drugs were discovered using the connectivity map database based on FRGPI. Results: The FRGPI was established based on the HMOX1, TFRC, JUN, and SOCS1 genes. The distribution of FRGPI varied significantly among the different ferroptosis-related subtypes. Patients with high FRGPI had a worse overall prognosis than Patients with low FRGPI, consistent with the results in the CGGA dataset. The complete results showed that high FRGPI was characterized by more aggressive phenotypes, high PD-L1 expression, high tumor mutational burden score, and enhanced temozolomide sensitivity; low FRGPI was associated with less aggressive phenotypes, high microsatellite instability score, and stronger response to immune checkpoint blockade. In addition, the infiltration of memory resting CD4+ T cells, regulatory T cells, M1 macrophage, M2 macrophage, and neutrophils were positively correlated with FRGPI. In contrast, plasma B cells and naïve CD4+ T cells were negatively correlated. A total of 15 potential small molecule compounds (such as depactin, physostigmine, and phenacetin) were identified. Conclusion: FRGPI is a promising gene panel for predicting the prognosis, immune characteristics, temozolomide sensitivity, and ICI response in patients with glioma.