The Expression and Effection of MicroRNA-499a in High-Tobacco Exposed Head and Neck Squamous Cell Carcinoma: A Bioinformatic Analysis

Gong, Shi-Cai; Xu, Meng; Xiang, Ming; Shan, Yijun; Zhang, Hao

doi:10.3389/fonc.2019.00678

Cited by 11 publications

(6 citation statements)

References 37 publications

(39 reference statements)

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“…Correlation and P-values between the module and clinical characteristics were evaluated by calculating the MEs. In the correlation between the module and clinical characteristics, red represented positive correlation with clinical characteristics, and green represented negative correlation with clinical characteristics (Gong et al, 2019).…”

Section: Identification Of Clinically Significant Modulesmentioning

confidence: 99%

The Prognostic Signature and Potential Target Genes of Six Long Non-coding RNA in Laryngeal Squamous Cell Carcinoma

Gong

Zhang

et al. 2020

Front. Genet.

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Studies have shown that long non-coding RNA (lncRNA) may act as the carcinogenic factor or tumor suppressor of laryngeal squamous cell carcinoma (LSCC). This study aims to identify the prognostic value and potential target protein-coding genes (PCGs) of lncRNAs in LSCC. The LSCC datasets were collected from The Cancer Genome Atlas (TCGA). Statistical and bioinformatic methods were used to establish and evaluate the prognostic model, identify the correlation between lncRNAs and clinical characteristics, and screen for PCGs co-expressed with lncRNAs. Weighted gene coexpression network analysis (WGCNA) identified PCG modules associated with clinical characteristics. The expression of lncRNAs and PCGs was analyzed using our LSCC patients by RT-qPCR. LINC02154, LINC00528, SPRY4-AS1, TTTY14, LNCSRLR, and KLHL7-DT were selected to establish the prognostic model. The overall survival (OS) of low-risk patients forecasted by the model was significantly better than highrisk patients. Receiver operating characteristic (ROC) curve and concordance index (C-index) validated the accuracy of the prognostic model. Chi-square test showed that six lncRNAs were associated with one of the clinical characteristics, i.e., gender, clinical stage, T and N stage, respectively. WGCNA identified PCG modules associated with gender, clinical stage, T and N stage. We took the intersection of the PCG modules of WGCNA, the differentially expressed PCGs between LSCC and normal samples, and the PCGs co-expressed with six lncRNAs. The intersection PCGs survival analysis showed that four PCGs, i.e., STC2, TSPAN9, SMS, and TCEA3 affected the OS of LSCC. More importantly, the differential expression of six lncRNAs and four PCGs between LSCC and normal samples was verified by our LSCC patients. In conclusion, we successfully established a prognostic model based on six-lncRNA RiskScore and initially screened the potential target PCGs of six lncRNAs for further basic and clinical research.

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Section: Identification Of Clinically Significant Modulesmentioning

confidence: 99%

The Prognostic Signature and Potential Target Genes of Six Long Non-coding RNA in Laryngeal Squamous Cell Carcinoma

Gong

Zhang

et al. 2020

Front. Genet.

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“…The weighed gene co-expression network analysis (WGCNA) algorithm was considered by establishing the scale-free co-expression network to explore the correlation between biologically meaningful gene modules and clinical characteristics ( 14 ). In this study, the R package “WGCNA” was run to calculate Pearson’s correlation matrices and adjacency function of all 309 human AGs.…”

Section: Methodsmentioning

confidence: 99%

Identification of an Aging-Related Gene Signature in Predicting Prognosis and Indicating Tumor Immune Microenvironment in Breast Cancer

Zhao

Tan

et al. 2021

Front. Oncol.

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Breast cancer (BC) is the most commonly diagnosed malignancy accompanied by high invasion and metastasis features. Importantly, emerging studies have supported that aging is a key clue that participates in the immune state and development of BC. Nevertheless, there are no studies concerning the aging-related genes (AGs) in constructing the prognosis signature of BC. Here, to address this issue, we initially performed a systematic investigation of the associations between AGs and BC prognosis and accordingly constructed a prognosis risk model with 10 AGs including PLAU, JUND, IL2RG, PCMT1, PTK2, HSPA8, NFKBIA, GCLC, PIK3CA, and DGAT1 by using the least absolute shrinkage and selection operator (LASSO) regression and Cox regression analysis. Meanwhile, our analysis further confirmed that the nomogram possessed a robust performance signature for predicting prognosis compared to clinical characteristics of BC patients, including age, clinical stage, and TNM staging. Moreover, the risk score was confirmed as an independent prognostic index of BC patients and was potentially correlated with immune scores, estimate score, immune cell infiltration level, tumor microenvironment, immunotherapy effect, and drug sensitivity. Furthermore, in the external clinical sample validation, AGs were expressed differentially in patients from different risk groups, and tumor-associated macrophage markers were elevated in high-risk BC tissues with more co-localization of AGs. In addition, the proliferation, transwell, and wound healing assays also confirmed the promoting effect of DGAT1 in BC cell proliferation and migration. Therefore, this well-established risk model could be used for predicting prognosis and immunotherapy in BC, thus providing a powerful instrument for combating BC.

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“…Gong et al demonstrated that high expression of miR-499a was associated with lower overall survival and N stage in high tobacco exposed HNSCC patients [145].…”

Section: Smoking Tobacco and Alcoholic Beveragementioning

confidence: 99%

Insight toward the MicroRNA Profiling of Laryngeal Cancers: Biological Role and Clinical Impact

Takeuchi

Kawasaki

Luce

et al. 2020

IJMS

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Head and neck squamous cell carcinoma (HNSCC), a heterogeneous disease arising from various anatomical locations including the larynx, is a leading cause of death worldwide. Despite advances in multimodality treatment, the overall survival rate of the disease is still largely dismal. Early and accurate diagnosis of HNSCC is urgently demanded in order to prevent cancer progression and to improve the quality of the patient’s life. Recently, microRNAs (miRNAs), a family of small non-coding RNAs, have been widely reported as new robust tools for prediction, diagnosis, prognosis, and therapeutic approaches of human diseases. Abnormally expressed miRNAs are strongly associated with cancer development, resistance to chemo-/radiotherapy, and metastatic potential through targeting a large variety of genes. In this review, we summarize on the recent reports that emphasize the pivotal biological roles of miRNAs in regulating carcinogenesis of HNSCC, particularly laryngeal cancer. In more detail, we report the characterized miRNAs with an evident either oncogenic or tumor suppressive role in the cancers. In addition, we also focus on the correlation between miRNA deregulation and clinical relevance in cancer patients. On the basis of intriguing findings, the study of miRNAs will provide a new great opportunity to access better clinical management of the malignancies.

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The Expression and Effection of MicroRNA-499a in High-Tobacco Exposed Head and Neck Squamous Cell Carcinoma: A Bioinformatic Analysis

Cited by 11 publications

References 37 publications

The Prognostic Signature and Potential Target Genes of Six Long Non-coding RNA in Laryngeal Squamous Cell Carcinoma

The Prognostic Signature and Potential Target Genes of Six Long Non-coding RNA in Laryngeal Squamous Cell Carcinoma

Identification of an Aging-Related Gene Signature in Predicting Prognosis and Indicating Tumor Immune Microenvironment in Breast Cancer

Insight toward the MicroRNA Profiling of Laryngeal Cancers: Biological Role and Clinical Impact

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