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

Induction of necroptosis in lung adenocarcinoma by miR‑10b‑5p through modulation of the PKP3/RIPK3/MLKL cascade

Globally, lung adenocarcinoma (LUAD) remains the leading cause of cancer‑related mortality, highlighting the urgent need for innovative therapeutic approaches. Necroptosis has been recognized as a crucial mechanism for inhibiting cancer progression. Research has revealed a significant association between microRNA (miRNA)‑mediated necroptosis and tumor progression. The present study aimed to elucidate the role and underlying mechanisms of miR‑10b‑5p in regulating necroptosis in the context of LUAD. In an investigation of LUAD, miRNA sequencing was conducted on both LUAD and adjacent non‑tumor tissues, followed by the integration of external database information to identify specific target miRNAs. The expression of miR‑10b‑5p was verified in LUAD tissues and corresponding adjacent non‑cancerous tissues using immunohistochemistry. In vitro experiments, utilizing LUAD cell lines engineered to modulate miR‑10b‑5p levels, assessed its effects on cellular activities and necroptosis. The inhibition of PKP3 by miR‑10b‑5p was determined using a dual luciferase reporter system. Furthermore, alterations in miR‑10b‑5p levels were found to affect PKP3 expression and inhibit the RIPK3/MLKL signaling pathway, as evidenced by western blot analysis in LUAD cell lines. The effect of PKP3 knockdown on cell activity and necroptosis in LUAD cell lines with low miR‑10b‑5p expression levels was assessed using cell function assays. Finally, a nude mouse xenograft model was used to investigate the effect of miR‑10b‑5p on LUAD growth in vivo and its specific mechanism of action. It has been revealed that miR‑10b‑5p levels are significantly elevated in LUAD specimens. Further investigations demonstrated that an increase in miR‑10b‑5p enhances the proliferation of LUAD cells and suppresses the progression of necroptosis, as evidenced by in vitro experiments. Through dual luciferase reporter assays, PKP3 was confirmed as a direct target negatively regulated by miR‑10b‑5p, leading to reduced expression levels. Western blot analysis indicated that miR‑10b‑5p inhibits the RIPK3/MLKL pathway activation through downregulation of PKP3, which leads to increased cell proliferation and decreased necroptosis. However, knockdown of PKP3 reversed the inhibitory effect of miR‑10b‑5p inhibitors on cellular activity and inhibited necrosis by suppressing the RIPK3/MLKL signalling pathway. In addition, animal model studies demonstrated that inhibition of miR‑10b‑5p activated the RIPK3/MLKL pathway by promoting PKP3 expression and significantly reduced LUAD growth by promoting necroptosis. In conclusion, our studies have revealed that the miR‑10b‑5p functions as a tumorigenic factor, enhancing various cellular activities in LUAD cells and suppressing necroptosis by specifically targeting PKP3, thereby inhibiting activation of the RIPK3/MLKL pathway. Importantly, interventions using inhibitors that specifically target miR‑10b‑5p have shown significant success in impeding the progression of LUAD by promoting necroptosis in both cellular and animal models. Thus, targeting miR‑10b‑5p holds considerable potential as a therapeutic strategy for LUAD.

A prognostic model for lung adenocarcinoma based on cuproptosis and disulfidptosis related genes revealing the key prognostic role of FURIN

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Despite advances in treatment, the prognosis remains poor due to late diagnosis. Cuproptosis (driven by copper ion accumulation) and disulfidptosis (driven by disulfide bond accumulation) are novel forms of programmed cell death, closely linked to tumor initiation, progression, and resistance. However, the specific roles of these mechanisms in LUAD remain inadequately studied. This study integrated multi-omics data from TCGA and GEO databases to systematically evaluate the differential expression and prognostic significance of copper and disulfide-related genes (DCRGs), identify two DCRG molecular subtypes, and construct a DCRG scoring model based on four key genes. Multi-omics analysis results revealed that the DCRG score not only accurately predicts prognosis in LUAD patients but is also closely associated with immune cell infiltration patterns and EGFR inhibitor responses. RT-qPCR validated the high expression of FURIN and RHOV in LUAD cells, supporting their role as potential therapeutic targets. Further Mendelian randomization analysis confirmed the causal relationship between FURIN and LUAD development. These findings provide novel biomarkers for the prognosis evaluation of LUAD based on cuproptosis and disulfidptosis mechanisms and offer a theoretical basis for targeting FURIN in LUAD treatment.

Spatially resolved gene expression profiling of tumor microenvironment reveals key steps of lung adenocarcinoma development

The interaction of tumor cells and their microenvironment is thought to be a key factor in tumor development. We present spatial RNA profiles obtained from 30 lung adenocarcinoma patients at the non-invasive and later invasive stages. We use spatial transcriptome sequencing data in conjunction with in situ RNA profiling to conduct higher resolution analyses. The detailed examination of each case, as well as the subsequent computational analyses based on the observed diverse profiles, reveals that significant changes in the phenotypic appearances of tumor cells are frequently associated with changes in immune cell features. The phenomenon coincides with the induction of a series of cellular expression programs that enable tumor cells to transform and break through the immune cell barrier, allowing them to progress further. The study shows how lung tumors develop through interaction in their microenvironments.

Oxidative stress gene signature construction to identify subtypes and prognosis of patients with lung adenocarcinoma

Background

Although oxidative stress and malignancies are intimately connected, it is unknown how lung adenocarcinoma (LUAD) is affected by oxidative stress response-related genes (OSRGs).Our goal in this work was to create a genetic signature based on OSRGs that might both predict prognosis and hint to potential treatment options for LUAD.

Methods

Clinicopathological and transcriptome information on LUAD patients was obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A model for predicting risk was created using LASSO regression. The TCGA, GSE72094, and GSE41271 cohorts all demonstrated the risk model's prediction ability. Immune cell infiltration was measured using the CIBERSORT method, and the TIDE platform was implemented to evaluate the therapeutic efficacy of immune checkpoint inhibition (ICI). Chemotherapy sensitivity was predicted using drug activity data by the Genomics of Drug Sensitivity. An investigation into gene expression was conducted using qRT-PCR. CCK-8 and transwell assays were employed to look into how DKK1 affected the migration and proliferation of LUAD cells.

Results

A gene signature consisting of ANLN, FAM83A, DKK1, LOXL2, RHOV, IGFBP1, CCR2, GNG7, and C11orf16 was efficiently determined and used to calculate a patient-specific risk score, this functioned as a stand-alone biomarker for prediction. Correlations were found between risk scores and immune cell infiltration frequency, ICI therapy response rate, estimated chemotherapeutic drug susceptibility and autophagy-related genes.Furthermore, DKK1 knockdown reduced the ability of LUAD cells to multiply and migrate.

Conclusion

Our thorough transcriptome study of OSRGs generated a biological framework effective in forecasting outcome and responsiveness to therapy in LUAD patients.

Fatty acid metabolism prognostic signature predicts tumor immune microenvironment and immunotherapy, and identifies tumorigenic role of MOGAT2 in lung adenocarcinoma

Background

Aberrant fatty acid metabolism (FAM) plays a critical role in the tumorigenesis of human malignancies. However, studies on its impact in lung adenocarcinoma (LUAD) are limited.

Methods

We developed a prognostic signature comprising 10 FAM-related genes (GPR115, SOAT2, CDH17, MOGAT2, COL11A1, TCN1, LGR5, SLC34A2, RHOV, and DKK1) using data from LUAD patients in The Cancer Genome Atlas (TCGA). This signature was validated using six independent LUAD datasets from the Gene Expression Omnibus (GEO). Patients were classified into high- and low-risk groups, and overall survival (OS) was compared by Kaplan-Meier analysis. The signature's independence as a prognostic indicator was assessed after adjusting for clinicopathological features. Receiver operating characteristic (ROC) analysis validated the signature. Tumor immune microenvironment (TIME) was analyzed using ESTIMATE and multiple deconvolution algorithms. Functional assays, including CCK8, cell cycle, apoptosis, transwell, and wound healing assays, were performed on MOGAT2-silenced H1299 cells using CRISPR/Cas9 technology.

Results

Low-risk group patients exhibited decreased OS. The signature was an independent prognostic indicator and demonstrated strong risk-stratification utility for disease relapse/progression. ROC analysis confirmed the signature's validity across validation sets. TIME analysis revealed higher infiltration of CD8+ T cells, natural killers, and B cells, and lower tumor purity, stemness index, and tumor mutation burden (TMB) in low-risk patients. These patients also showed elevated T cell receptor richness and diversity, along with reduced immune cell senescence. High-risk patients exhibited enrichment in pathways related to resistance to immune checkpoint blockades, such as DNA repair, hypoxia, epithelial-mesenchymal transition, and the G2M checkpoint. LUAD patients receiving anti-PD-1 treatment had lower risk scores among responders compared to non-responders. MOGAT2 was expressed at higher levels in low-risk LUAD patients. Functional assays revealed that MOGAT2 knockdown in H1299 cells promoted proliferation and migration, induced G2 cell cycle arrest, and decreased apoptosis.

Conclusions

This FAM-related gene signature provides a valuable tool for prognostic stratification and monitoring of TIME and immunotherapy responses in LUAD. MOGAT2 is identified as a potential anti-tumor regulator, offering new insights into its role in LUAD pathogenesis.

Atypical RhoUV GTPases in development and disease

RhoU and RhoV are members of the Rho family of small GTPases that comprise their own subfamily. RhoUV GTPases are classified as atypical due to the kinetics of their GTP/GDP binding cycles. They also possess unique N- and C-termini that regulate their subcellular localization and activity. RhoU and RhoV have been linked to cytoskeletal regulation, cell adhesion, and cell migration. They each exhibit distinct expression patterns during embryonic development and diseases such as cancer metastasis, suggesting they have specialized functions. In this review, we will discuss the known functions of RhoU and RhoV, with a focus on their roles in early development, organogenesis, and disease.

Molecular basis and current insights of atypical Rho small GTPase in cancer

Atypical Rho GTPases are a subtype of the Rho GTPase family that are involved in diverse cellular processes. The typical Rho GTPases, led by RhoA, Rac1 and Cdc42, have been well studied, while relative studies on atypical Rho GTPases are relatively still limited and have great exploration potential. With the increase in studies, current evidence suggests that atypical Rho GTPases regulate multiple biological processes and play important roles in the occurrence and development of human cancers. Therefore, this review mainly discusses the molecular basis of atypical Rho GTPases and their roles in cancer. We summarize the sequence characteristics, subcellular localization and biological functions of each atypical Rho GTPase. Moreover, we review the recent advances and potential mechanisms of atypical Rho GTPases in the development of multiple cancers. A comprehensive understanding and extensive exploration of the biological functions of atypical Rho GTPases and their molecular mechanisms in tumors will provide important insights into the pathophysiology of tumors and the development of cancer therapeutic strategies.

Prognostic significance of the rho GTPase RHOV and its role in tumor immune cell infiltration: a comprehensive pan-cancer analysis

Ras homolog gene family member V (RHOV) is an atypical Rho GTPase that participates in various important cellular processes. Although RHOV has been identified to play an oncogenic role in lung cancer and triple-negative breast cancer, its role in other types of tumors remains unknown. In this study, we investigated the expression of RHOV in pan-cancer analysis using The Cancer Genome Atlas (TCGA) and Gene-Tissue Expression datasets. RHOV mRNA levels were dysregulated in several types of tumors. RHOV expression was identified as an independent prognostic factor in 7 of 33 types of tumors; however, the relationship varied according to tumor type. Higher RHOV expression was associated with a favorable prognosis in kidney renal cell carcinoma and prostate adenocarcinoma, for which RHOV expression was downregulated, whereas RHOV expression was associated with a poor prognosis for patients with adenoid cystic carcinoma, lung adenocarcinoma, pancreatic ductal adenocarcinoma, skin cutaneous melanoma, and uveal melanoma with upregulated RHOV expression. Furthermore, RHOV expression was associated with various clinicopathological parameters in these tumors. RHOV expression showed varied associations with different types of tumor-infiltrating immune cells and demonstrated a potential impact on the response to immunotherapy depending on the cancer type. Additionally, functional enrichment analysis of RHOV-related genes demonstrated a role in a wide range of developmental and immune-related processes. This study provides valuable insights into the role of RHOV in pan-cancer development, indicating its role as a tumor suppressor or oncogene according to the cancer type and tumor microenvironment.

Intratumor microbiome derived glycolysis-lactate signatures depicts immune heterogeneity in lung adenocarcinoma by integration of microbiomic, transcriptomic, proteomic and single-cell data

Introduction

Microbiome plays roles in lung adenocarcinoma (LUAD) development and anti-tumor treatment efficacy. Aberrant glycolysis in tumor might promote lactate production that alter tumor microenvironment, affecting microbiome, cancer cells and immune cells. We aimed to construct intratumor microbiome score to predict prognosis of LUAD patients and thoroughly investigate glycolysis and lactate signature's association with LUAD immune cell infiltration.

Methods

The Cancer Genome Atlas-LUAD (TCGA-LUAD) microbiome data was downloaded from cBioPortal and analyzed to examine its association with overall survival to create a prognostic scoring model. Gene Set Enrichment Analysis (GSEA) was used to find each group's major mechanisms involved. Our study then investigated the glycolysis and lactate pattern in LUAD patients based on 19 genes, which were correlated with the tumor microenvironment (TME) phenotypes and immunotherapy outcomes. We developed a glycolysis-lactate risk score and signature to accurately predict TME phenotypes, prognosis, and response to immunotherapy.

Results

Using the univariate Cox regression analysis, the abundance of 38 genera were identified with prognostic values and a lung-resident microbial score (LMS) was then developed from the TCGA-LUAD-microbiome dataset. Glycolysis hallmark pathway was significantly enriched in high-LMS group and three distinct glycolysis-lactate patterns were generated. Patients in Cluster1 exhibited unfavorable outcomes and might be insensitive to immunotherapy. Glycolysis-lactate score was constructed for predicting prognosis with high accuracy and validated in external cohorts. Gene signature was developed and this signature was elevated in epithelial cells especially in tumor mass on single-cell level. Finally, we found that the glycolysis-lactate signature levels were consistent with the malignancy of histological subtypes.

Discussion

Our study demonstrated that an 18-microbe prognostic score and a 19-gene glycolysis-lactate signature for predicting prognosis of LUAD patients. Our LMS, glycolysis-lactate score and glycolysis-lactate signature have potential roles in precision therapy of LUAD patients.

Identification of lung adenocarcinoma subtypes and predictive signature for prognosis, immune features, and immunotherapy based on immune checkpoint genes

Background: Lung adenocarcinoma (LUAD) is the most common variant of non-small cell lung cancer (NSCLC) across the world. Recently, the rapid development of immunotherapy has brought a new dawn for LUAD patients. Closely related to the tumor immune microenvironment and immune cell functions, more and more new immune checkpoints have been discovered, and various cancer treatment studies targeting these novel immune checkpoints are currently in full swing. However, studies on the phenotype and clinical significance of novel immune checkpoints in LUAD are still limited, and only a minority of patients with LUAD can benefit from immunotherapy. Methods: The LUAD datasets were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, and the immune checkpoints score of each sample were calculated based on the expression of the 82 immune checkpoints-related genes (ICGs). The weighted gene co-expression network analysis (WGCNA) was used to obtain the gene modules closely related to the score and two different LUAD clusters were identified based on these module genes by the Non-negative Matrix Factorization (NMF) Algorithm. The differentially expressed genes between the two clusters were further used to construct a predictive signature for prognosis, immune features, and the response to immunotherapy for LUAD patients through a series of regression analyses. Results: A new immune checkpoints-related signature was finally established according to the expression of 7 genes (FCER2, CD200R1, RHOV, TNNT2, WT1, AHSG, and KRTAP5-8). This signature can stratify patients into high-risk and low-risk groups with different survival outcomes and sensitivity to immunotherapy, and the signature has been well validated in different clinical subgroups and validation cohorts. Conclusion: We constructed a novel immune checkpoints-related LUAD risk assessment system, which has a good predictive ability and significance for guiding immunotherapy. We believe that these findings will not only aid in the clinical management of LUAD patients but also provide some insights into screening appropriate patients for immunotherapy.

Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma

Background: Studies have reported that coppers are involved in the tumorigenesis and development of tumor. In herein, we aimed to construct a prognostic classification system for lung adenocarcinoma (LUAD) associated with cuproptosis. Methods: Samples information of LUAD were acquired from The Cancer Genome Atlas (TCGA) and GSE31210 dataset. Cuproptosis-related genes were screened from previous research. ConsensusClusterPlus was applied to determine molecular subtypes, which evaluated by genome analysis, tumor immune microenvironment analysis, immunotherapy, functional enrichment analysis. Furthermore, univariate Cox analysis combined with Lasso analysis were employed to construct a cuproptosis-related risk model for LUAD. Results: 14 genes related to cuproptosis phenotype were identified, and 2 clusters (C1 and C2) were determined. Among which, C1 had better survival outcome, less advanced stages, enhanced immune infiltration and enriched in TCA related pathways. A 7 cuproptosis-associated genes risk model was constructed, and the performance was verified in the GSE31210 dataset. A higher RiskScore was significantly correlated with worse overall survival, advanced stages. Cox survival analysis showed that RiskScore was an independent predictor. High-risk group patients had weakened immune infiltration, less likely to benefit from immunotherapy and was more sensitived to immunotherapy. Conclusion: The cuproptosis-related gene signature could serve as potential prognostic predictors for LUAD patients and may provide clues for the intervention of cuproptosis induced harm and targeted anti-tumor application.

Development and validation of a TRP-related gene signature for overall survival prediction in lung adenocarcinoma

The transient receptor potential (TRP) channel is a type of channel protein widely distributed in peripheral and central nervous systems. Genes encoding TRP can be regulated by natural aromatic substances and serve as a therapeutic target for many diseases. However, the role of TRP-related genes in lung adenocarcinoma (LUAD) remains unclear. In this study, we used data from TCGA to screen and identify 17 TRP-related genes that are differentially expressed between LUAD and normal lung tissues. Based on these differentially expressed genes (DEGs), we classified all patients with LUAD into two subtypes. Significant differences in prognosis, clinical features, and immune cell infiltration characteristics were observed between the two subtypes. Subsequently, a prognostic signature with 12 genes was established by applying the least absolute shrinkage and selection operator (LASSO) Cox regression method, and all patients with LUAD were classified into low- and high-risk groups. Patients with LUAD in the low-risk group had a significantly longer survival time than those in the high-risk group (p < 0.001), which was confirmed by LUAD data from the GSE72094 and GSE68571 validation datasets. Combined with clinical characteristics, the risk score was found to be an independent predictor of overall survival (OS) in patients with LUAD. Additionally, patients with high TRP scores exhibited poorer clinical characteristics and immune status while showing a sensitive response to chemotherapeutic agents. In conclusion, the TRP score is a promising biomarker for determining the prognosis, molecular subtype, tumor microenvironment, and guiding personalized treatment in patients with LUAD.

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

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.

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

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.

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

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.

The Role of Fast-Cycling Atypical RHO GTPases in Cancer

Simple Summary

For many years, cancer-associated mutations in RHO GTPases were not identified and observations suggesting roles for RHO GTPases in cancer were sparse. Instead, RHO GTPases were considered primarily to regulate cell morphology and cell migration, processes that rely on the dynamic behavior of the cytoskeleton. This notion is in contrast to the RAS proteins, which are famous oncogenes and found to be mutated at high incidence in human cancers. Recent advancements in the tools for large-scale genome analysis have resulted in a paradigm shift and RHO GTPases are today found altered in many cancer types. This review article deals with the recent views on the roles of RHO GTPases in cancer, with a focus on the so-called fast-cycling RHO GTPases.

Abstract

The RHO GTPases comprise a subfamily within the RAS superfamily of small GTP-hydrolyzing enzymes and have primarily been ascribed roles in regulation of cytoskeletal dynamics in eukaryotic cells. An oncogenic role for the RHO GTPases has been disregarded, as no activating point mutations were found for genes encoding RHO GTPases. Instead, dysregulated expression of RHO GTPases and their regulators have been identified in cancer, often in the context of increased tumor cell migration and invasion. In the new landscape of cancer genomics, activating point mutations in members of the RHO GTPases have been identified, in particular in RAC1, RHOA, and CDC42, which has suggested that RHO GTPases can indeed serve as oncogenes in certain cancer types. This review describes the current knowledge of these cancer-associated mutant RHO GTPases, with a focus on how their altered kinetics can contribute to cancer progression.