Patient Stratification Based On Radiotherapy And Chemotherapy Responsiveness Provides Guidance For Treatment Of Lower Grade Glioma

Abstract

For a long time, the guidance for adjuvant chemoradiotherapy for lower grade glioma (LGG) lacks instructions on the application timing and order of radiotherapy (RT) and chemotherapy. Faced with this situation, we hope to establish new indicators to guide patient stratification and provide guidance for the use of RT and chemotherapy. For patients who are resistant to both RT and chemotherapy, we aim to study the mechanism of resistance and determine suitable treatments. The TCGA LGG dataset (containing 516 primary LGGs) was selected as the discovery cohort. The CGGA RNAseq_693 (containing 282 primary LGGs) and mRNAseq_325 (containing 144 primary LGGs) datasets were selected as the discovery cohort for the Rscore. By analyzing 942 primary LGG samples from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases, we trained and validated two gene signatures (Rscore and Cscore) that independently predicted the responsiveness to RT and chemotherapy (Rscore AUC = 0.84, Cscore AUC = 0.79) and performed better than a previous signature. When the two scores were combined, we divided patients into four groups with different prognosis after adjuvant chemoradiotherapy: RSCS (RT-sensitive and chemotherapy-sensitive), RSCR (RT-sensitive and chemotherapy-resistant), RRCS (RT-resistant and chemotherapy-sensitive), and RRCR (RT-resistant and chemotherapy-resistant).For OS analysis, the results showed that the 4 groups had significantly different survival rates and that the RRCR and RSCS groups exhibited significantly lower and higher survival rates, respectively, than the other groups. We further found that the RRCR group exhibited a microenvironment with significantly increased T cell inflammation. And both TMB (p = 0.001) and TIS (p<0.0001) were significantly higher in the RRCR group than in the other groups. Patient stratification based on the Rscore and Cscore can be used to guide the clinical application of RT and chemotherapy in patients with LGG. For the patients who show resistance to both RT and chemotherapy, additional checkpoint blockade immunotherapy is recommended.