Affiliation:
1. Department of Respiratory Medicine, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer Hospital,
Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030082,
China
2. Department of thoracic surgery, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer
Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan,
030082, China
Abstract
Background:
Although cancer stem cells (CSCs) contribute to tumorigenesis, progression, and
drug resistance, stemness-based classification and prognostic signatures of lung squamous cell carcinoma
(LUSC) remain unclarified. This study attempted to identify stemness-based subtypes and develop a
prognostic risk model for LUSC.
Methods:
Based on RNA-seq data from The Cancer Genome Atlas (TCGA), Gene-Expression Omnibus
(GEO) and Progenitor Cell Biology Consortium (PCBC), mRNA expression-based stemness index
(mRNAsi) was calculated by one-class logistic regression (OCLR) algorithm. A weighted gene coexpression
network (WGCNA) was employed to identify stemness subtypes. Differences in mutation, clinical
characteristics, immune cell infiltration, and antitumor therapy responses were determined. We constructed
a prognostic risk model, followed by validations in GEO cohort, pan-cancer and immunotherapy datasets.
Results:
LUSC patients with subtype C2 had a better prognosis, manifested by higher mRNAsi, higher
tumor protein 53 (TP53) and Titin (TTN) mutation frequencies, lower immune scores and decreased immune
checkpoints. Patients with subtype C2 were more sensitive to Imatinib, Pyrimethamine, and
Paclitaxel therapy, whereas those with subtype C1 were more sensitive to Sunitinib, Saracatinib, and Dasatinib.
Moreover, we constructed stemness-based signatures using seven genes (BMI1, CCDC51, CTNS,
EIF1AX, FAM43A, THBD, and TRIM68) and found high-risk patients had a poorer prognosis in the
TCGA cohort. Similar results were found in the GEO cohort. We verified the good performance of risk
scores in prognosis prediction and therapy responses.
Conclusion:
The stemness-based subtypes shed novel insights into the potential roles of LUSC-stemness
in tumor heterogeneity, and our prognostic signatures offer a promising tool for prognosis prediction and
guide therapeutic decisions in LUSC.
Publisher
Bentham Science Publishers Ltd.
Subject
General Medicine,Medicine (miscellaneous)
Cited by
1 articles.
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