scholarly journals MiR-497-5p down-regulates CDCA4 to restrains lung squamous cell carcinoma progression

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Jiangwei Hu ◽  
Xinqin Xiang ◽  
Wei Guan ◽  
Weihua Lou ◽  
Junming He ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Cancer Progression ◽  
Squamous Cell ◽  
Bioinformatics Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
Cell Behaviors ◽  
Qrt Pcr ◽  
Related Cell ◽  
Rescue Experiment

Abstract Background So far, few have concerned miR-497-5p in lung squamous cell carcinoma (LUSC). Methods MiR-497-5p expression in LUSC was measured by qRT-PCR. Its impacts on tumor-related cell behaviors were investigated by CCK8 assay, scratch healing assay, flow cytometry and Transwell invasion methods. In addition, interaction between miR-497-5p and CDCA4 in LUSC was also elucidated through rescue experiment, western blot, dual-luciferase, and bioinformatics analysis. Results Low level of miR-497-5p was confirmed in LUSC tissue and cells. Overexpressed miR-497-5p markedly inhibited cancer progression. miR-497-5p restrained CDCA4 expression. Rescue assay showed that overexpressing miR-497-5p eliminated effect of overexpressed CDCA4. Conclusion By targeting CDCA4, miR-497-5p restrained development of LUSC.

scholarly journals Identification of reference genes for qRT-PCR in human lung squamous-cell carcinoma by RNA-Seq

2014 ◽  
Vol 46 (4) ◽  
pp. 330-337 ◽  
Author(s):  
Cheng Zhan ◽  
Yongxing Zhang ◽  
Jun Ma ◽  
Lin Wang ◽  
Wei Jiang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Reference Genes ◽  
Human Lung ◽  
Lung Squamous Cell Carcinoma ◽  
Rna Seq ◽  
Qrt Pcr

scholarly journals The Oncogenic Role and Immune Infiltration for CARM1 Identified by Pancancer Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Kui Liu ◽  
Jing Ma ◽  
Jiao Ao ◽  
Lili Mu ◽  
Yixian Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Cancer Progression ◽  
Squamous Cell ◽  
Immune Modulation ◽  
Lung Squamous Cell Carcinoma ◽  
Predictive Biomarker ◽  
Protein Arginine Methyltransferases ◽  
Immune Infiltration ◽  
T Cell Infiltration

Chromatin-modifying enzymes, especially protein arginine methyltransferases (PRMTs), have been identified as candidate targets for cancer. Cellular or animal-based evidence has suggested an association between coactivator-linked arginine methyltransferase 1 (CARM1) and cancer progression. However, the relationship between CARM1 and patient prognosis and immune infiltration in pancancer patients is unknown. On the basis of the GEO and TCGA databases, we first investigated the possible oncogenic functions of CARM1 in thirty-three tumor types. CARM1 expression was elevated in many types of tumors. In addition, there was a significant association between CARM1 expression and the survival rate of tumor patients. Uterine corpus endometrial carcinoma (UCES) samples had the highest CARM1 mutation frequency of all cancer types. In head and neck squamous cell carcinoma (HNSC) and lung squamous cell carcinoma (LUSC), CARM1 expression was associated with the level of CD8+ T cell infiltration, and cancer-associated fibroblast infiltration was also observed in other tumors including kidney renal papillary cell carcinoma (KIRC) and prostate adenocarcinoma (PRAD). CARM1 was involved in immune modulation and played an important role in the tumor microenvironment (TME). Furthermore, activities associated with RNA transport and its metabolism were included in the possible mechanisms of CARM1. Herein, our first pancancer research explores the oncogenic role of CARM1 in various tumors. CARM1 is associated with immune infiltrates and can be employed as a predictive biomarker in pancancer.

scholarly journals Diagnosis value of aberrantly expressed microRNA profiles in lung squamous cell carcinoma: a study based on the Cancer Genome Atlas

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e4101 ◽  
Author(s):  
Sheng Yang ◽  
Jing Sui ◽  
Geyu Liang
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Bioinformatics Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background Lung cancer is considered as one of the most frequent and deadly cancers with high mortality all around the world. It is critical to find new biomarkers for early diagnosis of lung cancer, especially lung squamous cell carcinoma (LUSC). The Cancer Genome Atlas (TCGA) is a database which provides both cancer and clinical information. This study is a comprehensive analysis of a novel diagnostic biomarker for LUSC, based on TCGA. Methods and Results The present study investigated LUSC-specific key microRNAs (miRNAs) from large-scale samples in TCGA. According to exclusion criteria and inclusion criteria, the expression profiles of miRNAs with related clinical information of 332 LUSC patients were obtained. Most aberrantly expressed miRNAs were identified between tumor and normal samples. Forty-two LUSC-specific intersection miRNAs (fold change >2, p < 0.05) were obtained by an integrative computational method, among them six miRNAs were found to be aberrantly expressed concerning characteristics of patients (gender, lymphatic metastasis, patient outcome assessment) through Student t-test. Five miRNAs correlated with overall survival (log-rank p < 0.05) were obtained through the univariate Cox proportional hazards regression model and Mantel–Haenszel test. Then, five miRNAs were randomly selected to validate the expression in 47 LUSC patient tissues using quantitative real-time polymerase chain reaction. The results showed that the test findings were consistent with the TCGA findings. Also, the diagnostic value of the specific key miRNAs was determined by areas under receiver operating characteristic curves. Finally, 577 interaction mRNAs as the targets of 42 LUSC-specific intersection miRNAs were selected for further bioinformatics analysis. Conclusion This study indicates that this novel microRNA expression signature may be a useful biomarker of the diagnosis for LUSC patients, based on bioinformatics analysis.

scholarly journals Switched alternative splicing events as attractive features in lung squamous cell carcinoma

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Boxue He ◽  
Cong Wei ◽  
Qidong Cai ◽  
Pengfei Zhang ◽  
Shuai Shi ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Alternative Splicing ◽  
Correlation Analysis ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Lung Squamous Cell Carcinoma ◽  
Functional Enrichment ◽  
Spearman Correlation ◽  
Qrt Pcr

Abstract Background Alternative splicing (AS) plays important roles in transcriptome and proteome diversity. Its dysregulation has a close affiliation with oncogenic processes. This study aimed to evaluate AS-based biomarkers by machine learning algorithms for lung squamous cell carcinoma (LUSC) patients. Method The Cancer Genome Atlas (TCGA) database and TCGA SpliceSeq database were utilized. After data composition balancing, Boruta feature selection and Spearman correlation analysis were used for differentially expressed AS events. Random forests and a nested fivefold cross-validation were applied for lymph node metastasis (LNM) classifier building. Random survival forest combined with Cox regression model was performed for a prognostic model, based on which a nomogram was developed. Functional enrichment analysis and Spearman correlation analysis were also conducted to explore underlying mechanisms. The expression of some switch-involved AS events along with parent genes was verified by qRT-PCR with 20 pairs of normal and LUSC tissues. Results We found 16 pairs of splicing events from same parent genes which were strongly related to the splicing switch (intrapair correlation coefficient = − 1). Next, we built a reliable LNM classifier based on 13 AS events as well as a nice prognostic model, in which switched AS events behaved prominently. The qRT-PCR presented consistent results with previous bioinformatics analysis, and some AS events like ITIH5-10715-AT and QKI-78404-AT showed remarkable detection efficiency for LUSC. Conclusion AS events, especially switched ones from the same parent genes, could provide new insights into the molecular diagnosis and therapeutic drug design of LUSC.

scholarly journals Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis

2020 ◽  
Vol 21 (8) ◽  
pp. 2994
Author(s):  
Miaomiao Gao ◽  
Weikaixin Kong ◽  
Zhuo Huang ◽  
Zhengwei Xie
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Bioinformatics Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Good Prediction ◽  
Good Prediction Accuracy ◽  
Key Genes

Lung squamous cell carcinoma (LUSC) is often diagnosed at the advanced stage with poor prognosis. The mechanisms of its pathogenesis and prognosis require urgent elucidation. This study was performed to screen potential biomarkers related to the occurrence, development and prognosis of LUSC to reveal unknown physiological and pathological processes. Using bioinformatics analysis, the lung squamous cell carcinoma microarray datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were analyzed to identify differentially expressed genes (DEGs). Furthermore, PPI and WGCNA network analysis were integrated to identify the key genes closely related to the process of LUSC development. In addition, survival analysis was performed to achieve a prognostic model that accomplished good prediction accuracy. Three hundred and thirty–seven up–regulated and 119 down-regulated genes were identified, in which four genes have been found to play vital roles in LUSC development, namely CCNA2, AURKA, AURKB, and FEN1. The prognostic model contained 5 genes, which were all detrimental to prognosis. The AUC of the established prognostic model for predicting the survival of patients at 1, 3, and 5 years was 0.692, 0.722, and 0.651 in the test data, respectively. In conclusion, this study identified several biomarkers of significant interest for additional investigation of the therapies and methods of prognosis of lung squamous cell carcinoma.

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