Machine learning–based new classification for immune infiltration of gliomas
We developed a highly reliable model for predicting different immune subtypes of glioma by ML. Then, we comprehensively analyzed the immune infiltration, molecular and clinical features of different immune subtypes of gliomas and defined gliomas into four subtypes: immunogenic subtype, adaptive immune resistance subtype, mesenchymal subtype, and immune tolerance subtype, which represent different TMEs and different stages of tumor development.
Authors
- Yangchun Hu (ORCID: https://orcid.org/0000-0002-0989-2696)
- Feng Yuan (ORCID: https://orcid.org/0000-0002-8132-9224)
- Yingshuai Wang (ORCID: https://orcid.org/0000-0001-5457-3240)
- Hongwei Cheng (ORCID: https://orcid.org/0009-0000-8749-5912)
- Lei Ye (ORCID: https://orcid.org/0000-0002-6529-6178)
- Lei Yuan (ORCID: https://orcid.org/0000-0003-0826-648X)
- Yan Li (ORCID: https://orcid.org/0000-0001-7068-5680)
Institutions
- Anhui Medical University (CN)
- First Affiliated Hospital of Anhui Medical University (CN)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- PLoS ONE
- Published
- 2024-10-25
- DOI
- https://doi.org/10.1371/journal.pone.0312071
- Citations
- 4
- Primary Topic
- Glioma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.75