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 Development of alternative splicing signature in lung squamous cell carcinoma

2021 ◽  
Vol 38 (5) ◽  
Author(s):  
Jia-qing Yan ◽  
Min Liu ◽  
Ying-lin Ma ◽  
Kai-di Le ◽  
Bin Dong ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Alternative Splicing ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Predictive Accuracy ◽  
Risk Group ◽  
Lung Squamous Cell Carcinoma ◽  
Prognostic Models ◽  
Prognostic Indicators

AbstractIncreasing evidence demonstrated that alternative splicing (AS) plays a vital role in tumorigenesis and clinical outcome of patient. However, systematical analysis of AS in lung squamous cell carcinoma (LUSC) is lacking and greatly necessary. Thus, this study was to systematically estimate the function of AS events served as prognostic indicators in LUSC. Among 31,345 mRNA AS events in 9633 genes, we detected 1996 AS in 1409 genes which have significant connection with overall survival (OS) of LUSC patients. Then, prognostic model based on seven types of AS events was established and we further constructed a combined prognostic model. The Kaplan–Meier curve results suggested that seven types of AS signatures and the combined prognostic model could exhibit robust performance in predicting prognosis. Patients in the high-risk group had significantly shorter OS than those in the low-risk group. The ROC showed all prognostic models had high accuracy and powerful predictive performance with different AUC ranging from 0.837 to 0.978. Moreover, the combined prognostic model had highest performance in risk stratification and predictive accuracy than single prognostic models and had higher accuracy than other mRNA model. Finally, a significant correlation network between survival-related AS genes and prognostic splicing factors (SFs) was established. In conclusion, our study provided several potential prognostic AS models and constructed splicing network between AS and SFs in LUSC, which could be used as potential indicators and treatment targets for LUSC patients.

scholarly journals Development of alternative splicing signature in lung squamous cell carcinoma

2021 ◽  
Author(s):  
Jia-qing Yan ◽  
Min Liu ◽  
Yin-lin Ma ◽  
Kai-di Le ◽  
Bin Dong ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Alternative Splicing ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Predictive Accuracy ◽  
Risk Group ◽  
Lung Squamous Cell Carcinoma ◽  
Prognostic Models ◽  
Prognostic Indicators

Abstract Increasing evidence demonstrated that alternative splicing (AS) played a vital role in tumorigenesis and clinical outcome of patient. However, systematically analysis of AS in lung squamous cell carcinoma (LUSC) is lacking and greatly necessary. Thus, this study was to systematically estimate the function of AS events served as prognostic indicators in LUSC. Among 31,345 mRNA AS events in 9,633 genes, we detected 1,996 AS in 1,409 genes which have significantly connection with overall survival (OS) of LUSC patients. Then, prognostic model based on seven types of AS events were established and we further constructed a combined prognostic model. The Kaplan-Meier curve results suggested that seven types of AS signatures and the combined prognostic model could exhibit robust performance in predicting prognosis. Patients in the high risk group had significantly shorter OS than those in the low risk group. The ROC showed all prognostic models had high accuracy and powerful predictive performance with different AUC ranging from 0.837 to 0.978. Moreover, the combined prognostic model had highest performance in risk stratification and predictive accuracy than single prognostic models. Finally, a significant correlation network between survival-related AS genes and prognostic splicing factors (SFs) was established. In conclusion, our study provided several potential prognostic AS models and constructed splicing network between AS and SFs in LUSC, which could be used as potential indicators and treatment targets for LUSC patients.

scholarly journals Development and validation of an individualized immune prognostic model in stage I–III lung squamous cell carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qi-Fan Yang ◽  
Di Wu ◽  
Jian Wang ◽  
Li Ba ◽  
Chen Tian ◽  
...  
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Lung Squamous Cell Carcinoma ◽  
Risk Groups ◽  
Stage I ◽  
Tissue Samples ◽  
Mutation Burden

AbstractLung squamous cell carcinoma (LUSC) possesses a poor prognosis even for stages I–III resected patients. Reliable prognostic biomarkers that can stratify and predict clinical outcomes for stage I–III resected LUSC patients are urgently needed. Based on gene expression of LUSC tissue samples from five public datasets, consisting of 687 cases, we developed an immune-related prognostic model (IPM) according to immune genes from ImmPort database. Then, we comprehensively analyzed the immune microenvironment and mutation burden that are significantly associated with this model. According to the IPM, patients were stratified into high- and low-risk groups with markedly distinct survival benefits. We found that patients with high immune risk possessed a higher proportion of immunosuppressive cells such as macrophages M0, and presented higher expression of CD47, CD73, SIRPA, and TIM-3. Moreover, When further stratified based on the tumor mutation burden (TMB) and risk score, patients with high TMB and low immune risk had a remarkable prolonged overall survival compared to patients with low TMB and high immune risk. Finally, a nomogram combing the IPM with clinical factors was established to provide a more precise evaluation of prognosis. The proposed immune relevant model is a promising biomarker for predicting overall survival in stage I–III LUSC. Thus, it may shed light on identifying patient subset at high risk of adverse prognosis from an immunological perspective.

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 Significance of mucin type glucosaminyl (N-acetyl) transferase 3 expression in lung squamous cell carcinoma

2021 ◽  
Author(s):  
Yu-Jun Chen ◽  
Li Gao ◽  
Rui Zhang ◽  
Gang Chen ◽  
Zhen-bo Feng ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Methylation Level ◽  
Lung Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Progression Free Survival ◽  
Genetic Mutation ◽  
Functional Enrichment ◽  
Standard Mean Difference

Abstract Background: The clinical significance and role of glycan synthase glucosamine (N-acetyl) transferase 3 (GCNT3) has not been investigated in lung squamous cell carcinoma (LUSC).Materials & Methods: In the present study, multiple detection technologies including tissue microarrays, external microarrays and RNA-seq were adopted for evaluating the clinic-pathological significance of GCNT3 in 1632 LUSC samples and 1478 non-cancer samples. Standard mean difference and hazard ratio value were calculated from all included datasets for assessing differential expression and prognostic value of GCNT3 in LUSC. The molecular basis underlying GCNT3 in LUSC was also explored through methylation level, genetic mutation and functional enrichment analysis of GCNT3-correlated genes in LUSC. Results: GCNT3 was obviously upregulated in LUSC samples. GCNT3 overexpression exerted unfavorable impact on the progression-free survival and overall survival of LUSC patients from GSE29013. The mRNA expression of GCNT3 was negatively correlated with methylation level of GCNT3 in LUSC and the predominant type of genetic alteration for GCNT3 in LUSC was mRNA high. Genes correlated with GCNT3 in LUSC mainly assembled in pathways such as adherens junction, p53 signaling pathway, protein digestion and absorption pathway. Conclusions: In conclusion, overexpressed GCNT3 had clinical potential as therapeutic target for LUSC.

Mine TCGA Database for Tumor Microenvironment-Related Genes of Prognostic value in lung squamous cell carcinoma

2020 ◽  
Author(s):  
Xiao Chen ◽  
Rui Li ◽  
Yun-Hong Yin ◽  
Xiao Liu ◽  
Xi-Jia Zhou ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Cells ◽  
Lung Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Hub Genes

Abstract Background: Tumor microenvironment (TME) plays a significant role in the development of cancer. However, the roles of TME in lung squamous cell carcinoma (LUSC) are not well studied. In our study, we aimed to identify differentially expressed tumor microenvironment-related genes as biomarker for predicting the prognosis of LUSC.Methods: We combined The Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissue using Expression data (ESTIMATE) datasets to identified differentially expressed genes in lung squamous cell carcinoma microenvironment. Then, functional enrichment analysis and protein-protein interaction (PPI) network were conducted. The top six genes in the PPI network were regarded as tumor microenvironment-related hub genes. Finally, the relationship between hub genes and tumor-infiltrating immune cells was deciphered using TIMER.Results: Our study revealed that immune and stromal scores are associated with specific clinicopathologic variables in LUSC. These variables include gender, age, distant metastasis and prognosis. In addition, a total of 874 upregulated and 72 downregulated genes were identified. Functional enrichment analysis demonstrated a correlation between DEGs and the tumor microenvironment, tumor immune cells differentiation and activation. C3AR1, CSF1R, CCL2, CCR1, TYROBP, CD14were selected as the hub genes. A positive correlation was obtained between the expression of hub genes and the abundance of six immune cells.Conclusions: The results of the present study showed that ESTIMATE algorithm-based stromal and immune scores may be a reference indicator of cancer prognosis. We identified five TME-related genes, which could be used to predict the prognosis of LUSC patients.

scholarly journals Competitive Endogenous RNA Network Construction and Comparison of Lung Squamous Cell Carcinoma in Smokers and Nonsmokers

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yan Yao ◽  
Tingting Zhang ◽  
Lingyu Qi ◽  
Ruijuan Liu ◽  
Gongxi Liu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
Differential Expression Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cerna Network

Background. Lung squamous cell carcinoma (LUSC) is a subtype of highly malignant lung cancer with poor prognosis, for which smoking is the main risk factor. However, the underlying genetic and molecular mechanisms of smoking-related LUSC remain largely unknown. Methods. We mined existing LUSC-related mRNA, miRNA, and lncRNA transcriptome data and corresponding clinical data from The Cancer Genome Atlas (TCGA) database and divided them into smoking and nonsmoking groups, followed by differential expression analysis. Functional enrichment analysis of the unique differentially expressed mRNAs of the two groups was performed using the DAVID database. Subsequently, the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network of LUSC in smoking and nonsmoking groups was constructed. Finally, survival analyses were performed to determine the effects of differentially expressed lncRNAs/mRNAs/miRNAs that were involved in the ceRNA network on overall survival and to discover the hub genes. Results. A total of 1696 lncRNAs, 125 miRNAs, and 3246 mRNAs and 1784 lncRNAs, 96 miRNAs, and 3229 mRNAs with differentially expressed profiles were identified in the smoking and nonsmoking groups, respectively. The ceRNA network and survival analysis revealed four lncRNAs (LINC00466, DLX6-AS1, LINC00261, and AGBL1), one miRNA (hsa-mir-210), and two mRNAs (CITED2 and ENPP4), with the potential as biomarkers for smoking-related LUSC diagnosis and prognosis. Conclusion. Taken together, our research has identified the differences in the ceRNA regulatory networks between smoking and nonsmoking LUSC, which could lay the foundation for future clinical research.

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