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pmid:37713826
Identification of prognostic immune subtypes of lung squamous cell carcinoma by unsupervised consistent clustering.
Yuhan Wang · Litie Hou · Miao Yang · Jinyan Fan · Yanbo Wang · Liping Sun
Medicine · 2023 doi:10.1097/MD.0000000000035123
Paper
complete
Experiment
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Data
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Analysis
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Execution
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Complete file
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TCGA-LUSC and GSE30219 data of lung squamous cell carcinoma were obtained from TCGA and GEO databases. Prognostic-associated subtypes were identified by unsupervised consensus clustering (UCC). Using ssGSEA analysis to calculate the level of immune cells of different subtypes, obtain the connection between subtypes and immunity, identify the gene signatures recognized by subtypes, and verify this group of gene signatures through GSE30219. We effectively identified 2 subtypes that were significantly associated with prognostic survival by UCC, and calculated according to ssGSEA, the 2 subtypes were significantly different at the level of immune cells, followed by introducing a This weighted thinking computes a set of gene signatures that are significantly associated with subtype 1. During validation, this set of gene signatures could efficiently and robustly identify distinct prognostic immune subtypes, demonstrated the validity of this set of gene signatures, as well as 2 subtypes of lung squamous cell carcinoma. 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