Journal
BOSNIAN JOURNAL OF BASIC MEDICAL SCIENCES
Volume 22, Issue 5, Pages 728-750Publisher
ASSOC BASIC MEDICAL SCI FEDERATION BOSNIA & HERZEGOVINA SARAJEVO
DOI: 10.17305/bjbms.2021.6888
Keywords
Ferroptosis; pyroptosis; prognostic signature; immunotherapy; low-grade glioma
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Funding
- National Natural Science Foundation of China [81672968]
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Accumulating evidence suggests that ferroptosis and pyroptosis play important roles in the tumorigenesis of low-grade glioma (LGG). This research aimed to classify molecular subtypes of LGG and identify a novel multigene signature based on ferroptosis- and pyroptosis-related genes. The study found that the FPRGs had prognostic value and developed a six-gene prognostic signature that outperformed other recognized signatures in predicting the survival probability of LGG patients.
Accumulating evidence reveals that ferroptosis and pyroptosis play pivotal roles in tumorigenesis of low-grade glioma (LGG). In this research, we aimed to classify molecular subtypes and further identify and verify a novel multigene signature in LGG on the basis of ferroptosis-and pyroptosis-related genes (FPRGs). Raw sequencing data and corresponding clinical data of LGG samples retrieved from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases were obtained for the training and validation datasets. Non-negative matrix factorization (NMF) clustering defined by FPRGs associated with prognosis was performed to classify molecular subtypes of LGG patients. Least absolute shrinkage and selection operator-support vector machine-random forest analysis was carried out to develop a FPRG signature to predict the survival and benefit of immunotherapy of LGG patients. NMF clustering defined by FPRGs with prognostic values acted to categorize LGG patients into two molecular subtypes with different prognosis, clinical traits, and immune microenvironments. A six-FPRG prognostic signa-ture was constructed, accompanied by the optimal p-value. The AUC values of our signature exhibited great prognostic performances. Our signature was superior to other four well-recognized signatures in predicting the survival probability of LGG patients. Immune characteristics, tumor mutation profile, tumor stemness indices, MGMT methylation, and immunotherapy response biomarkers showed significant differ-ences between high-and low-risk populations. Finally, a nomogram was created for quantitative prediction of the survival probability of LGG patients, with the AUC values of the nomogram being 0.916, 0.888, and 0.836 for 1-, 3-, and 5-year survival, sequentially. Overall, the FPRG signature may function as an effective indicator for the prognosis prediction and immunotherapy response of LGG patients.
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