학술논문

Elucidating Hedgehog pathway's role in HNSCC progression: insights from a 6-gene signature.
Document Type
Article
Source
Scientific Reports. 2/26/2024, Vol. 14 Issue 1, p1-13. 13p.
Subject
*HEDGEHOG signaling proteins
*DISEASE risk factors
*SQUAMOUS cell carcinoma
*GENE regulatory networks
*DRUG metabolism
Language
ISSN
2045-2322
Abstract
With the emergence of targeted inhibition strategies for Hedgehog signaling in cancer, multiple Hedgehog signaling pathway-related biomarkers have become the focus of research. SsGSEA algorithm was employed to analyze the Hedgehog pathway scores of samples in TCGA-HNSC dataset and divide them into two groups. Weighted co-expression network analysis was performed to identify modules strongly associated with the Hedgehog pathway. Differentially up-regulated genes in tumor samples in comparison to the normal ones were screened by Limma, in which genes belonging to modules strongly related to Hedgehog pathway were further filtered by LASSO reduction and multivariate Cox regression analysis to develop a model. ESTIMATE and CIBERSORT were served to characterize the tumor microenvironment (TME). TIDE assessed immunotherapy response. Hedgehog pathway activity was significantly higher in head and neck squamous cell carcinoma (HNSCC) tissues than in normal tissues and was correlated with HNSCC survival, glycan, cofactors and vitamins, drug metabolism, and matrix scores. Six genes (SLC2A3, EFNB2, OAF, COX4I2, MT2A and TXNRD1) were captured to form a Hedgehog associated 6-gene signature, and the resulting risk score was an independent indicator of HNSCC prognosis. It was significantly positively correlated with stromal score, metabolism, angiogenesis and inflammatory response. Patients in low-risk group with a low TIDE score had higher immunotherapy sensitivity relative to those in high-risk group. This study revealed novel findings of the Hedgehog pathway in HNSCC progression and opened up a Hedgehog pathology-related signature to help identify risk factors contributing to HNSCC progression and help predict immunotherapy outcomes. [ABSTRACT FROM AUTHOR]