RESUMO
AIMS: The present study aimed todevelop a prognostic model for HNSCC treatment on the basis of angiogenesis-related signatures. BACKGROUND: Head and Neck Squamous Cell Carcinoma (HNSCC) is the most frequent malignancy with poor prognostic outcomes in the head and neck. Angiogenesis plays a critical role in tumorigenesis and is expected to be an effective therapeutic target. OBJECTIVE: The RNA-seq dataset TCGA-HNSCC and the hallmark gene set were used for angiogenesis-related RiskScore model construction. METHODS: The RNA-seq data was downloaded from The Cancer Genome Atlas (TCGA), and the hallmark gene set was used to measure the angiogenesis score using the GSVA R package. Then, the optimal cutoff point for prognostic classification was calculated by the survminer package, and Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify angiogenesis gene modules . Multi/univariable and Lasso Cox analyses were performed to develop the RiskScore model, and the classifier efficiency was evaluated by the Receiver Operating Characteristic curve (ROC). Furthermore, a nomogram was designed for survival probability prediction, and the immune infiltration and immunotherapy differences among different risk patients were assessed. RESULTS: After calculating the angiogenesis score, we found that this indicator and patients' prognosis were closely correlated, especially when patients with a high angiogenesis score had a poor prognosis. Then, WGCNA identified a blue gene module positively correlated with angiogenesis. Multivariate and Lasso Cox analysis further identified 9 risk model genes for developing a RiskScore, which was used to divide low- and high- -risk groups of patients. Those with a high risk tended to show poor prognosis, immune infiltration, and higher immune escape. Finally, a nomogram was developed to optimize the risk model, and it exhibited excellent short- and long-term survival prediction performance. CONCLUSION: We constructed a reliable RiskScore model for the prognostic prediction of HNSCC patients, contributing to precise therapeutic intervention of the cancer.
RESUMO
Long non-coding RNA nuclear-enriched abundant transcript 1 (Lnc-NEAT1) is a crucial mediator in cancer progression, which is associated with poor prognosis of patients with laryngeal papilloma (LP). Herein, we aimed to determine how Lnc-NEAT1 promotes LP development. q-PCR, MTT, EDU and Western blotting were performed to determine that Lnc-NEAT1 facilitates LP cell proliferation and hinders cell apoptosis. LncBase database, q-PCR, GEPIA online database, Dual luciferase reporter and RIP assays were utilized to confirm that Lnc-NEAT1 sponged miR-577/miR-1224-5p and negatively mediated CCNT2. Western blotting, MTT and EDU were used to confirm that Lnc-NEAT1 promoted LP cell proliferation and inhibited cell apoptosis through CCNT2. Lnc-NEAT1 was highly expressed in LP, and enhanced LP cell proliferation, and it was inhibited by Lnc-NEAT1 depleting. Concerning the underlying mechanism, it was found that Lnc-NEAT1 could functionally sponge microRNA-577 (miR-577) and microRNA-1224-5p (miR-1224-5p) and up-regulate Cyclin T2 (CCNT2) in LP cells. Notably, CCNT2 knockdown blocked Lnc-NEAT1-induced LP cell proliferation, and rescued cell apoptosis, which was specifically indicated by restoration of Bax, Cleaved caspase 3 and Cleaved caspase 9. Lnc-NEAT1 played a carcinogenic role in LP through mediating miR-577 or miR-1224-5p/CCNT2 axis, which may provide promising insights for the treatment of LP.
