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Gene signatures characterizing driver mutations in lung squamous carcinoma are predictive of the progression of pre-cancer lesions.

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International journal of cancer 📖 저널 OA 49.1% 2022: 0/3 OA 2023: 1/3 OA 2024: 6/16 OA 2025: 32/61 OA 2026: 130/241 OA 2022~2026 2025
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유사 논문
P · Population 대상 환자/모집단
환자: lung squamous cell carcinoma (LUSC) are often diagnosed at advanced stages, limiting opportunities for early intervention
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
We found many of these signatures increased progressively across lesion stages, reflecting roles in early tumorigenesis.

Lin Y, Mekala V, Li J, Wang X, Aminu M, Wu J, Zhang J, Ripley RT, Amos CI, Cheng C

📝 환자 설명용 한 줄

Patients with lung squamous cell carcinoma (LUSC) are often diagnosed at advanced stages, limiting opportunities for early intervention.

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↓ .bib ↓ .ris
APA Lin Y, Mekala V, et al. (2025). Gene signatures characterizing driver mutations in lung squamous carcinoma are predictive of the progression of pre-cancer lesions.. International journal of cancer. https://doi.org/10.1002/ijc.70269
MLA Lin Y, et al.. "Gene signatures characterizing driver mutations in lung squamous carcinoma are predictive of the progression of pre-cancer lesions.." International journal of cancer, 2025.
PMID 41402247 ↗
DOI 10.1002/ijc.70269

Abstract

Patients with lung squamous cell carcinoma (LUSC) are often diagnosed at advanced stages, limiting opportunities for early intervention. LUSC develops through multistep progression from low-grade lesions to high-grade lesions, including carcinoma in situ (CIS), of which about half progress to invasive cancer while the other half regress. Although frequent mutations and copy number alterations have been documented in LUSC and observed in precursor lesions, their prognostic significance in precancers remains largely unexplored. In this study, we leveraged gene expression data from LUSC tumors in The Cancer Genome Atlas to derive transcriptional signatures corresponding to 34 key driver genomic aberrations, including mutations, amplifications, and deletions. These tumor-derived signatures were applied to precancerous datasets to assess their ability to characterize developmental stages and predict progression risk. We found many of these signatures increased progressively across lesion stages, reflecting roles in early tumorigenesis. In particular, several signatures accurately predicted which CIS lesions would progress to invasive cancer. Furthermore, these signature scores were more strongly associated with prognosis in LUSC than the presence of genomic aberrations alone. We also examined relationships between driver-associated signatures and the tumor immune microenvironment. Signature scores were significantly correlated with immune features such as immune cell infiltration and immune checkpoint gene expression, including CD274 (PD-L1). These associations varied across stages, indicating dynamic immune interactions during cancer evolution. Together, our findings demonstrate that tumor-derived driver gene expression signatures provide valuable insight into the biology and progression risk of precancerous lesions, offering potential utility for early detection and intervention in LUSC.

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