Overexpression of RhoV Promotes the Progression and EGFR-TKI Resistance of Lung Adenocarcinoma

Chen, Hongjin; Xia, Ruixue; Jiang, Long; Zhou, Yong; Xu, Haojun; Peng, Weiwei; Yao, Chengyun; Zhou, Guoren; Zhang, Yijie; Xia, Hongping; Wang, Yongsheng

doi:10.3389/fonc.2021.619013

Cited by 16 publications

(19 citation statements)

References 28 publications

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“…Based on the study by Zhang et al, the RAS homologous family member V (RHOV) is majorly involved in LUAD metastasis and may provide biomarkers for prognosis prediction and LUAD treatment [ 43 ]. Other research has found that overexpression of RhoV in lung adenocarcinoma promotes lung adenocarcinoma occurrence and progression, as well as EGFR-TKI resistance [ 44 ]. CPS1 (carbamoyl phosphate synthase 1) is a rate-limiting enzyme in the first step of the urea cycle and is also required for human liver metabolism [ 45 ].…”

Section: Discussionmentioning

confidence: 99%

Molecular Typing Based on Oxidative Stress Genes and Establishment of Prognostic Characteristics of 7 Genes in Lung Adenocarcinoma

Tang

et al. 2022

Oxidative Medicine and Cellular Longevity

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Oxidative stress could maintain different biological processes in human cancer. However, the effect of oxidative stress on lung adenocarcinoma (LUAD) should be studied. This study analyzed the expression and clinical importance of oxidative stress in LUAD in detail. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were employed for obtaining LUAD expression profiles. Based on oxidative stress-related genes, molecular subtypes substantially correlated with the LUAD prognosis were discovered with ConsensusClusterPlus. Differentially expressed genes (DEGs) among subtypes were found using the Limma software package. Least absolute shrinkage and selection operator- (Lasso-) Cox analysis was employed to create the polygenic risk model. RiskScore and clinically relevant features were used to create nomograms. By utilizing oxidative stress-related genes and reliable clustering, stable molecular subtypes were first discovered. The prognosis, clinical characteristics, route characteristics, and immunological characteristics of these three molecular subtypes were all different. Subsequently, by using differential expression genes among molecular subtypes and Lasso, 7 main genes linked with the oxidative stress phenotype were discovered. A prognostic risk model was also built on the basis of major genes associated with the oxidative stress phenotype. The model demonstrated a high level of resilience and was unaffected by clinical-pathological features. It played a stable predictive role in independent datasets. Ultimately, to improve the prognosis model and survival prediction, RiskScore (RS) was combined with clinicopathological variables, and a decision tree model was used. The model exhibited a high prediction accuracy as well as the ability to predict survival. This research found that oxidative stress-related genes have a major involvement in the onset and progression of LUAD and that they may influence LUAD susceptibility to immunotherapy and standard chemotherapy. Furthermore, the identified risk models for 7 genes linked with oxidative stress exhibited could assist clinical treatment decisions and prognosis prediction. The classifier could be used as a molecular diagnostic tool for assessing LUAD patients’ prognosis risk.

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Section: Discussionmentioning

confidence: 99%

Molecular Typing Based on Oxidative Stress Genes and Establishment of Prognostic Characteristics of 7 Genes in Lung Adenocarcinoma

Tang

et al. 2022

Oxidative Medicine and Cellular Longevity

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“…RHOV has been shown to promote cell differentiation and act as an important regulator of neural crest induction ( Guémar et al, 2007 ; Song et al, 2015 ). RHOV is highly expressed in many lung cancer cell lines and promotes the growth and metastasis of LUAD cells ( Zhang Y. et al, 2020 ; Chen H. et al, 2021 ; Zhang et al, 2021 ). CYP4B1 belongs to the mammalian CYP4 enzyme family and is mainly expressed in human lungs ( Wiek et al, 2015 ).…”

Section: Discussionunclassified

Single-cell RNA sequencing analysis to explore immune cell heterogeneity and novel biomarkers for the prognosis of lung adenocarcinoma

Wang

Liang

et al. 2022

Front. Genet.

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Background: Single-cell RNA sequencing is necessary to understand tumor heterogeneity, and the cell type heterogeneity of lung adenocarcinoma (LUAD) has not been fully studied.Method: We first reduced the dimensionality of the GSE149655 single-cell data. Then, we statistically analysed the subpopulations obtained by cell annotation to find the subpopulations highly enriched in tumor tissues. Monocle was used to predict the development trajectory of five subpopulations; beam was used to find the regulatory genes of five branches; qval was used to screen the key genes; and cellchart was used to analyse cell communication. Next, we used the differentially expressed genes of TCGA-LUAD to screen for overlapping genes and established a prognostic risk model through univariate and multivariate analyses. To identify the independence of the model in clinical application, univariate and multivariate Cox regression were used to analyse the relevant HR, 95% CI of HR and p value. Finally, the novel biomarker genes were verified by qPCR and immunohistochemistry.Results: The single-cell dataset GSE149655 was subjected to quality control, filtration and dimensionality reduction. Finally, 23 subpopulations were screened, and 11-cell subgroups were annotated in 23 subpopulations. Through the statistical analysis of 11 subgroups, five important subgroups were selected, including lung epithelial cells, macrophages, neuroendocrine cells, secret cells and T cells. From the analysis of cell trajectory and cell communication, it is found that the interaction of five subpopulations is very complex and that the communication between them is dense. We believe that these five subpopulations play a very important role in the occurrence and development of LUAD. Downloading the TCGA data, we screened the marker genes of these five subpopulations, which are also the differentially expressed genes in tumorigenesis, with a total of 462 genes, and constructed 10 gene prognostic risk models based on related genes. The 10-gene signature has strong robustness and can achieve stable prediction efficiency in datasets from different platforms. Two new molecular markers related to LUAD, HLA-DRB5 and CCDC50, were verified by qPCR and immunohistochemistry. The results showed that HLA-DRB5 expression was negatively correlated with the risk of LUAD, and CCDC50 expression was positively correlated with the risk of LUAD.Conclusion: Therefore, we identified a prognostic risk model including CCL20, CP, HLA-DRB5, RHOV, CYP4B1, BASP1, ACSL4, GNG7, CCDC50 and SPATS2 as risk biomarkers and verified their predictive value for the prognosis of LUAD, which could serve as a new therapeutic target.

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“…For instance, ANLN is a well-known oncogene that promotes carcinogenesis and therapeutic resistance in multiple types of cancers, such as LUAD ( Long et al, 2018 ; Xu et al, 2019 ; Deng et al, 2021 ), oral cancer ( Wang B et al, 2021 ), colorectal cancer ( Liu et al, 2022 ), breast cancer ( Wang et al, 2020 ; Maryam and Chin, 2021 ), pancreatic cancer ( Wang et al, 2019 ), and head and neck squamous cell carcinoma ( Guo et al, 2021 ). RHOV has been widely studied to promote LUAD cell growth, metastasis, and therapeutic resistance ( Chen H et al, 2021 ; Zhang et al, 2021 ). In addition, KRT6A has been shown to participate in tumor proliferation, invasion, EMT, and cancer stem cell transformation in lung cancer ( Yang et al, 2020 ; Zhou J et al, 2021 ; Che et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

A Four-Gene Prognostic Signature Based on the TEAD4 Differential Expression Predicts Overall Survival and Immune Microenvironment Estimation in Lung Adenocarcinoma

Gong

Sun

et al. 2022

Front. Pharmacol.

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Background: TEA domain transcription factor 4 (TEAD4) is a member of the transcriptional enhancer factor (TEF) family of transcription factors, which is studied to be linked to the tumorigenesis and progression of various forms of cancers, including lung adenocarcinoma (LUAD). However, the specific function of this gene in the progression of LUAD remains to be explored.Method: A total of 19 genes related to the Hippo pathway were analyzed to identify the significant genes involved in LUAD progression. The TCGA-LUAD data (n = 585) from public databases were mined, and the differentially expressed genes (DEGs) in patients with the differential level of TEAD4 were identified. The univariate Cox regression, zero LASSO regression coefficients, and multivariate Cox regression were performed to identify the independent prognostic signatures. The immune microenvironment estimation in the two subgroups, including immune cell infiltration, HLA family genes, and immune checkpoint genes, was assessed. The Gene Set Enrichment Analysis (GSEA) and GO were conducted to analyze the functional enrichment of DEGs between the two risk groups. The potential drugs for the high-risk subtypes were forecasted via the mode of action (moa) module of the connectivity map (CMap) database.Results:TEAD4 was found to be significantly correlated with poor prognosis in LUAD-patients. A total of 102 DEGs in TEAD4-high vs. TEAD4-low groups were identified. Among these DEGs, four genes (CPS1, ANLN, RHOV, and KRT6A) were identified as the independent prognostic signature to conduct the Cox risk model. The immune microenvironment estimation indicated a strong relationship between the high TEAD4 expression and immunotherapeutic resistance. The GSEA and GO showed that pathways, including cell cycle regulation, were enriched in the high-risk group, while immune response-related and metabolism biological processes were enriched in the low-risk group. Several small molecular perturbagens targeting CFTR or PLA2G1B, by the mode of action (moa) modules of the glucocorticoid receptor agonist, cyclooxygenase inhibitor, and NFkB pathway inhibitor, were predicted to be suited for the high-risk subtypes based on the high TEAD4 expression.Conclusion: The current study revealed TEAD4 is an immune regulation–related predictor of prognosis and a novel therapeutic target for LUAD.

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Overexpression of RhoV Promotes the Progression and EGFR-TKI Resistance of Lung Adenocarcinoma

Cited by 16 publications

References 28 publications

Molecular Typing Based on Oxidative Stress Genes and Establishment of Prognostic Characteristics of 7 Genes in Lung Adenocarcinoma

Molecular Typing Based on Oxidative Stress Genes and Establishment of Prognostic Characteristics of 7 Genes in Lung Adenocarcinoma

Single-cell RNA sequencing analysis to explore immune cell heterogeneity and novel biomarkers for the prognosis of lung adenocarcinoma

A Four-Gene Prognostic Signature Based on the TEAD4 Differential Expression Predicts Overall Survival and Immune Microenvironment Estimation in Lung Adenocarcinoma

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