https://orcid.org/0000-0002-6804-1111
Abstract
Purpose
mRNA vaccines represent a promising and innovative strategy within the realm of cancer immunotherapy. However, their efficacy in treating lower-grade glioma (LGG) requires evaluation. Ferroptosis exhibits close associations with the initiation, evolution, and suppression of cancer. In this study, we explored the landscape of the ferroptosis-associated tumor microenvironment to facilitate the development of mRNA vaccines for LGG patients.
Patients and Methods
Genomic and clinical data of the LGG patients was obtained from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Ferroptosis-related tumor antigens were identified based on differential expression, mutation status, correlation with antigen-presenting cells, and prognosis, relevance to immunogenic cell death (ICD). Antigen expression levels in LGG specimens and cell lines were validated using real time-polymerase chain reaction (RT-PCR). Consensus clustering was employed for patient classification. The immune landscapes of ferroptosis subtypes were further characterized, including immune responses, prognostic ability, tumor microenvironment, and tumor-related signatures.
Results
Five tumor antigens, namely, HOTAIR, IDO1, KIF20A, NR5A2, and RRM2 were identified in LGG. RT-PCR demonstrated higher expression of these genes in LGG compared to the control. Twelve gene modules and four ferroptosis subtypes (FS1-FS4) of LGG were defined. FS2 and FS4, characterized as “cold” tumors due to their decreased tumor mutation burden (TMB) and immune checkpoint proteins (ICPs), were deemed appropriate candidates for the mRNA vaccine.
Conclusion
HOTAIR, IDO1, KIF20A, NR5A2, and RRM2 were identified as promising candidate antigens for the development of an LGG mRNA vaccine, particularly offering potential benefits to FS2 and FS4 patients.
Abbreviations
FBS, fetal bovine serum; OS, Overall survival; ICP, immune checkpoint; CAR-T, chimeric antigen receptor T cell therapy; PCA, Principal Component Analysis; CGGA, Chinese Glioma Genome Atlas; GO, Gene ontology; FRGs, ferroptosis-related genes; ICD, immunogenic cell death; GEPIA, Gene Expression Profiling Interactive Analysis; PFS, Progression-free survival; TIME, tumor immune microenvironment; TMB, Tumor mutation burden; TIMER, Tumor Immune Estimation Resource; F-subtypes, Ferroptosis-subtypes; CDF, Cumulative distribution function; LGG, Lower grade glioma; WGCNA, Weight gene co-expression network analysis; APCs, antigen-presenting cells; TCGA, The Cancer Genome Atlas; MSI, Microsatellite instability; RT-PCR, real time-polymerase chain reaction; cBioPortal, cBio Cancer Genology Portal; DEGs, differentially expressed genes; DMEM, Dulbecco’s modified Eagle’s medium; KEGG, Kyoto Encyclopedia of Genes and Genomes.
Data Sharing Statement
The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.
Ethics Approval and Consent to Participate
This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of The Fourth Hospital of Hebei Medical University (2020KY303).
Consent for Publication
All authors have given consent for publication.
Acknowledgments
The authors gratefully acknowledge contributions from the CGGA and TCGA databases.
Author Contributions
All authors made a significant contribution to the work reported, whether in study conception, design, and execution; data acquisition, analysis, and interpretation; or all these areas. All authors were involved in drafting, revising, or critically reviewing the article; gave final approval for the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Disclosure
The authors declare that they have no competing interests in this work.