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Development and validation of a hypoxia-related gene pair signature to predict overall survival in head and neck squamous cell carcinoma

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机构: [1]Clinical Medical College, Dali University, Dali, 671000, Yunnan, China. [2]Department of Otolaryngology, The First Affiliated Hospital of Dali University, Dali, 671000, Yunnan, China.
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Head and neck squamous cell carcinoma (HNSCC) are a highly aggressive tumor with an extremely poor prognosis. Thus, we aimed to develop and validate a robust prognostic signature that can estimate the prognosis for HNSCC.Data on gene expressions and clinical were downloaded from TCGA and GEO database. To develop the best prognosis signature, a LASSO Cox Regression model was employed. Time-dependent receiver-operating characteristic (ROC) was used to determine the best cut-off value. Patients were divided into high-risk and low-risk hypoxia groups according to cut-off value. Survival differences were evaluated by log-rank test, while multivariate analysis was performed by a Cox proportional hazards model.A 17-HRGPs composed of 24 unique genes was constructed, which was significantly related to OS. In the TCGA and GEO datasets, patients in the high hypoxia risk group have a poor prognosis (TCGA: P < 0.001, GEO: P < 0.05). After adjusting for other clinicopathological parameters, the 17-HRGP signature was independent prognostic factors in patients with HNSCC (P < 0.05). Functional analysis revealed that mRNA binding, gene silencing by RNA, RNA binding involved in posttranscriptional gene silencing signaling pathway were enriched in the low-risk groups. For this model, C-index was 0.684, which was higher than that of many established risk models. Macrophages M0, Mast cells activated, NK cells resting, T cells CD4 memory resting, etc. were significantly higher in the high-risk group, and B cells memory, Plasma cells, T cells follicular helper, T cells gamma delta, T cells CD8, etc. were significantly higher in the low-risk group.In summary, our study constructed a robust HRGPs signature as molecular markers for predicting the outcome of HNSCC patients.

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出版当年[2021]版:
大类 | 4 区 医学
小类 | 3 区 耳鼻喉科学
最新[2023]版:
大类 | 3 区 医学
小类 | 3 区 耳鼻喉科学
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第一作者机构: [1]Clinical Medical College, Dali University, Dali, 671000, Yunnan, China.
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