ETV4 promotes proliferation and invasion of lung adenocarcinoma by transcriptionally upregulating MSI2

Update on the Progress of Musashi-2 in Malignant Tumors

Since the discovery of the Musashi (MSI) protein, its ability to affect the mitosis of Drosophila progenitor cells has garnered significant interest among scientists. In the following 20 years, it has lived up to expectations. A substantial body of evidence has demonstrated that it is closely related to the development, metastasis, migration, and drug resistance of malignant tumors. In recent years, research on the MSI protein has advanced, and many novel viewpoints and drug resistance attempts have been derived; for example, tumor protein p53 mutations and MSI-binding proteins lead to resistance to protein arginine N-methyltransferase 5-targeted therapy in lymphoma patients. Moreover, the high expression of MSI2 in pancreatic cancer might suppress its development and progression. As a significant member of the MSI family, MSI2 is closely associated with multiple malignant tumors, including hematological disorders, common abdominal tumors, and other tumor types (e.g., glioblastoma, breast cancer). MSI2 is highly expressed in the majority of tumors and is related to a poor disease prognosis. However, its specific expression levels and regulatory mechanisms may differ based on the tumor type. This review summarizes the research progress related to MSI2 in recent years, including its occurrence, migration mechanism, and drug resistance, as well as the prospect of developing tumor immunosuppressants and biomarkers.

Pan-cancer analysis of the potential of PEA3 subfamily genes as tumor markers

Polyomavirus enhancer activator 3 (PEA3), an ETS transcription factor, has been documented to regulate the development and metastasis of human cancers. Nonetheless, a thorough analysis examining the relationship between the PEA3 subfamily members and tumour development, prognosis, and the tumour microenvironment (TME) across various cancer types has not yet been conducted. The expression profiles and prognostic significance of the PEA3 subfamily were evaluated using data from the GEO, TCGA, and PrognoScan databases, in conjunction with COX regression analyses and the Kaplan-Meier Plotter. Furthermore, the relationships between PEA3 subfamily expression, stemness scores, tumor microenvironments, immune subtypes, and drug susceptibility across multiple cancer types were explored. We found that ETV1, ETV4 and ETV5 are highly expressed in cancer, and their biological functions are synergistic. In the prognostic analysis of the Cancer Genome Atlas, the PEA3 subfamily genes were found to be associated with the prognosis of multiple cancers such as Lung adenocarcinoma (LUAD), Liver hepatocellular carcinoma (LIHC), etc., and marked a worse prognosis at different endpoints. In addition, it was significantly correlated with the stromal and immune scores of pan-cancer, and also significantly associated with the RNA stemness score and DNA stemness score of pan-cancer. Expression levels of the PEA3 subfamily genes correlate with immune subtypes of LIHC, LUAD, and Lung squamous cell carcinoma. We also found a variety of drugs with positive and negative associations of ETV1, ETV4 and ETV5. These findings elucidate the role of the PEA3 subfamily gene as a biomarker for carcinogenesis and cancer progression, offering valuable insights for future research into the PEA3 subfamily gene as a potential therapeutic target across various cancer types.

Study on the Mechanism of FOXA2 Activation on Glutathione Metabolic Reprogramming Mediated by ETV4 Transcription to Facilitate Colorectal Cancer Malignant Progression

The metabolic imbalance of glutathione (GSH) has been widely recognized in most cancers, but the specific molecular mechanism of GSH metabolic regulation in the malignant progression of colorectal cancer (CRC) is unexplored. The objective of our project is to elucidate whether ETV4 affects the malignant progression of CRC through GSH metabolic reprogramming. Bioinformatics and molecular experiments measured the expression of ETV4 in CRC, and in vitro experiments explored the impact of ETV4 on CRC malignant progression. The Kyoto Encyclopedia of Genes and Genomes (KEGG) identified the pathway of ETV4 enrichment. The bioinformatics approach identified FOXA2 as an upstream regulatory factor of ETV4. The dual-luciferase assay, chromatin immunoprecipitation (ChIP) and co-immunoprecipitation (Co-IP) experiment verified the binding relationship between ETV4 and FOXA2. Cell viability, migration, and invasion abilities were determined by conducting CCK-8, wound healing, and Transwell assays, respectively. The expression levels of N-cadherin, E-cadherin, and vimentin were determined by utilizing immunofluorescence (IF). Metabolism-related enzymes GCLM, GCLC, and GSTP1 levels were detected to evaluate the GSH metabolism level by analyzing the GSH/GSSG ratio. In vivo experiments were performed to explore the effect of FOXA2/ETV4 on CRC progression, and the expression of related proteins was detected by western blot. ETV4 was highly expressed in CRC. Knocking down ETV4 suppressed CRC cell viability, migration, invasion, and epithelial-mesenchymal transition (EMT) progression in vitro. ETV4 was abundant in the GSH metabolic pathway, and overexpression of ETV4 facilitated CRC malignant progression through activation of the GSH metabolism. In addition, in vitro cellular experiments and in vivo experiments in nude mice confirmed that FOXA2 transcriptionally activated ETV4. Knocking down FOXA2 repressed the malignant phenotype of CRC cells by suppressing GSH metabolism. These effects were reversed by overexpressing ETV4. Our results indicated that FOXA2 transcriptionally activates ETV4 to facilitate CRC malignant progression by modulating the GSH metabolic pathway. Targeting the FOXA2/ETV4 axis or GSH metabolism may be an effective approach for CRC treatment.

Model ensembling as a tool to form interpretable multi-omic predictors of cancer pharmacosensitivity

Stratification of patients diagnosed with cancer has become a major goal in personalized oncology. One important aspect is the accurate prediction of the response to various drugs. It is expected that the molecular characteristics of the cancer cells contain enough information to retrieve specific signatures, allowing for accurate predictions based solely on these multi-omic data. Ideally, these predictions should be explainable to clinicians, in order to be integrated in the patients care. We propose a machine-learning framework based on ensemble learning to integrate multi-omic data and predict sensitivity to an array of commonly used and experimental compounds, including chemotoxic compounds and targeted kinase inhibitors. We trained a set of classifiers on the different parts of our dataset to produce omic-specific signatures, then trained a random forest classifier on these signatures to predict drug responsiveness. We used the Cancer Cell Line Encyclopedia dataset, comprising multi-omic and drug sensitivity measurements for hundreds of cell lines, to build the predictive models, and validated the results using nested cross-validation. Our results show good performance for several compounds (Area under the Receiver-Operating Curve >79%) across the most frequent cancer types. Furthermore, the simplicity of our approach allows to examine which omic layers have a greater importance in the models and identify new putative markers of drug responsiveness. We propose several models based on small subsets of transcriptional markers with the potential to become useful tools in personalized oncology, paving the way for clinicians to use the molecular characteristics of the tumors to predict sensitivity to therapeutic compounds.

Prognostic value of PEA3 subfamily gene expression in cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma (CCA) is a lethal malignancy with limited treatment options and poor prognosis. The PEA3 subfamily of E26 transformation specific genes: ETV1, ETV4, and ETV5 are known to play significant roles in various cancers by influencing cell proliferation, invasion, and metastasis.

AIM

To analyze PEA3 subfamily gene expression levels in CCA and their correlation with clinical parameters to determine their prognostic value for CCA.

METHODS

The expression levels of PEA3 subfamily genes in pan-cancer and CCA data in the cancer genome atlas and genotype-tissue expression project databases were analyzed with R language software. Survival curve and receiver operating characteristic analyses were performed using the SurvMiner, Survival, and Procr language packages. The gene expression profiling interactive analysis 2.0 database was used to analyze the expression levels of PEA3 subfamily genes in different subtypes and stages of CCA. Web Gestalt was used to perform the gene ontology/ Kyoto encyclopedia of genes and genomes (GO/KEGG) analysis, and STRING database analysis was used to determine the genes and proteins related to PEA3 subfamily genes.

RESULTS

ETV1, ETV4, and ETV5 expression levels were significantly increased in CCA. There were significant differences in ETV1, ETV4, and ETV5 expression levels among the different subtypes of CCA, and predictive analysis revealed that only high ETV1 and ETV4 expression levels were significantly associated with shorter overall survival in patients with CCA. GO/KEGG analysis revealed that PEA3 subfamily genes were closely related to transcriptional misregulation in cancer. In vitro and in vivo experiments revealed that PEA3 silencing inhibited the invasion and metastasis of CCA cells.

CONCLUSION

The expression level of ETV4 may be a predictive biomarker of survival in patients with CCA.

ETV4 promotes the progression of cholangiocarcinoma by regulating glycolysis via the TGF-β signaling

BACKGROUND

Considerable studies show that ETS variant 4 (ETV4) plays an important roles in multitudinous tumor. This study investigated its function in cholangiocarcinoma (CCA) progression and revealed the underlying mechanisms.

METHODS

The expression of ETV4 in CCA was evaluated using TCGA database and the single-cell analysis based on GSE189903 dataset. ETV4 expression in CCA human specimens was detected by reverse transcription-quantitative PCR, immunohistochemistry, and western blot. Cell Counting Kit-8, EdU, colony formation, wound healing, and Transwell assays were used to analyze the effects of ETV4. Extracellular acidification rate, oxygen consumption rate, glucose uptake, and lactate production were used to measure glycolysis in CAA cells. Western blot was performed to explore glycolysis-related proteins. Tumor growth was evaluated in mice xenograft tumors.

RESULTS

ETV4 was up-regulated in CCA epithelial cells. The high-expression of ETV4 was associated with poor prognosis of patients with CCA. ETV4 overexpression enhanced the proliferation, migration, invasion, and glycolysis of CCA cells; ETV4 silencing led to the contrary effects. Mechanistically, ETV4 activates TGF-β/Smad2/3 signaling pathway. In mice xenograft mode, ETV4 silencing inhibits the tumor growth, the expression of glycolysis-related proteins and TGF-β/Smad2/3 pathway proteins.

CONCLUSIONS

ETV4 functions as an essential factor in the roles of TGF-β1 in CCA cells, and may be a promising target for TGF-β1-mediated CCA progression.

ETV4 facilitates angiogenesis in hepatocellular carcinoma by upregulating MMP14 expression

Abnormal vascularization plays a crucial role in cell proliferation, tumor invasion and metastasis of hepatocellular carcinoma (HCC). It has been reported that ETV4 functions as an oncogenic gene in driving the carcinogenesis and progression, and promoting invasion and metastasis of HCC. However, the function of ETV4 on angiogenesis in HCC remains unclear. In the current study, immunohistochemistry showed that knockdown of ETV4 reduced angiogenesis in HCC xenograft tumor tissues. In vitro, tube formation assay verified that ETV4 expression promoted angiogenesis through simulating the angiogenic environment in HCC cells. Transcriptome sequencing indicated that MMP14 was one of the differentially expressed genes enriched in angiogenesis process. Subsequently, it was confirmed that MMP14 was regulated by ETV4 at the transcription level in HCC cells, clinical tissue samples and online databases. Further, we demonstrated that MMP14 induced angiogenesis in ETV4-mediated HCC microenvironment. Collectively, this research further reveals the biological mechanism of ETV4 in promoting the migration and invasion of HCC, and provides novel mechanistic insights and strategic guidance for anti-angiogenic therapy in HCC.

ETV4 facilitates proliferation, migration, and invasion of liver cancer by mediating TGF-β signal transduction through activation of B3GNT3

BACKGROUND

Metastasis of liver cancer (LC) is the main cause of its high mortality. ETV4 is a critical regulatory factor in promoting LC progression, but the mechanism that ETV4 impacts LC proliferation, migration, and invasion is poorly understood.

OBJECTIVE

Investigation of the molecular mechanism of LC metastasis is conducive to developing effective drugs that prevent LC metastasis.

METHODS

Expression of ETV4 and its target gene B3GNT3 in LC tissue was analyzed by bioinformatics, and the result was further verified in LC cells by qRT-PCR. In vitro cellular assays evaluated the impact of ETV4 on the proliferation, migration, and invasion of LC cells. Chromatin immunoprecipitation (ChIP) and dual-luciferase reporter gene assay were conducted to analyze the interaction between B3GNT3 and ETV4. SB525334 suppressor was used to treat and access the activation of ETV4 on the TGF-β pathway.

RESULTS

We discovered that ETV4 and B3GNT3 were evidently up-regulated in LC, and high expression of ETV4 was coupled to the increase of proliferation, migration, and invasion of LC cells and epithelial-mesenchymal transition ability. Besides, ETV4 could bind to the B3GNT3 promoter and activate its transcription. Knockdown of B3GNT3 could prominently suppress the effect of up-regulated ETV4 on LC cells. Meanwhile, ETV4 could activate the TGF-β signaling pathway via B3GNT3, while SB525334 treatment notably repressed the functions of ETV4.

CONCLUSION

ETV4 emerges as a driven oncogene in LC, and the ETV4/B3GNT3-TGF-β pathway promotes proliferation, migration, invasion, and epithelial-mesenchymal transition progress of LC. Inhibition of the pathway may provide an underlying method for the prevention and treatment of LC metastasis.

Based on the Cancer Genome Atlas Database Development of a prognostic model of RNA binding protein in stomach adenocarcinoma

The purpose of this study was to identify potential RNA binding proteins associated with the survival of gastric adenocarcinoma, as well as the corresponding biological characteristics and signaling pathways of these RNA binding proteins. RNA sequencing and clinical data were obtained from the cancer genome map (N = 32, T = 375) and the comprehensive gene expression database (GSE84437, N = 433). The samples in The Cancer Genome Atlas were randomly divided into a development group and a test group. A total of 1495 RNA binding protein related genes were extracted. Using nonparametric tests to analyze the difference of RNA binding protein related genes, 296 differential RNA binding proteins were obtained, 166 were up-regulated and 130 were down regulated. Twenty prognosis-related RNA binding proteins were screened using Cox regression, including 14 high-risk genes (hazard ratio > 1.0) and 6 low-risk genes (hazard ratio < 1.0). Seven RNA binding protein related genes were screened from the final prognostic model and used to construct a new prognostic model. Using the development group and test group, the model was verified with survival analysis, receiver operating characteristics curves and prognosis analysis curves. A prediction nomogram was finally developed and showed good prediction performance.

Transcription Activation of Rab8A by PEA3 Augments Progression of Esophagus Cancer by Activating the Wnt/β-Catenin Signaling Pathway

Background

Rab8A has been reported as an oncogenic gene in breast and cervical cancer. However, the function and molecular mechanism of Rab8A in esophagus cancer has not been reported.

Methods

Rab8A expression was detected by qPCR and western blotting assays, small interference RNA (siRNA) was applied to reduce Rab8A expression, and the biological behaviors of esophagus cancer cells were estimated by cell counting kit-8, colony formation, and transwell and western blotting assays. The transcriptional factor of Rab8A was verified by dual-luciferase assay and chromatin immunoprecipitation assay. The protein expression of key genes in the Wnt/β-catenin signaling pathway was determined by western blotting assay. M435-1279 was used to suppress the Wnt/β-catenin signaling pathway.

Results

A significant increase of Rab8A expression has been found in esophagus cancer cells. Knockdown of Rab8A suppressed the viability, colony formation, migration, and invasion abilities of esophagus cancer cells and induced apoptosis. PEA3 transcriptionally regulated Rab8A expression and promoted the viability, colony formation, migration, and invasion abilities of esophagus cancer cells and blocked apoptosis, which were diminished by si-Rab8A transfection. Additionally, the expression levels of key genes related to the Wnt/β-catenin signaling pathway were strengthened by PEA3 overexpression, which were reduced by si-Rab8A transfection. M435-1279 treatment significantly reduced the viability and colony formation of esophagus cancer cells.

Conclusions

The data showed that Rab8A was transcriptionally regulated by PEA3 and promoted the malignant behaviors of esophagus cancer cells by activating the Wnt/β-catenin pathway. The above results indicated that Rab8A may be considered as a promising biomarker for diagnosis and precision treatment in esophagus cancer.

Targeting PEA3 transcription factors to mitigate small cell lung cancer progression

Small cell lung cancer (SCLC) remains a lethal disease with a dismal overall survival rate of 6% despite promising responses to upfront combination chemotherapy. The key drivers of such rapid mortality include early metastatic dissemination in the natural course of the disease and the near guaranteed emergence of chemoresistant disease. Here, we found that we could model the regression and relapse seen in clinical SCLC in vitro. We utilized time-course resolved RNA-sequencing to globally profile transcriptome changes as SCLC cells responded to a combination of cisplatin and etoposide-the standard-of-care in SCLC. Comparisons across time points demonstrated a distinct transient transcriptional state resembling embryonic diapause. Differential gene expression analysis revealed that expression of the PEA3 transcription factors ETV4 and ETV5 were transiently upregulated in the surviving fraction of cells which we determined to be necessary for efficient clonogenic expansion following chemotherapy. The FGFR-PEA3 signaling axis guided the identification of a pan-FGFR inhibitor demonstrating in vitro and in vivo efficacy in delaying progression following combination chemotherapy, observed inhibition of phosphorylation of the FGFR adaptor FRS2 and corresponding downstream MAPK and PI3K-Akt signaling pathways. Taken together, these data nominate PEA3 transcription factors as key mediators of relapse progression in SCLC and identify a clinically actionable small molecule candidate for delaying relapse of SCLC.

Comprehensive analysis of prediction of the EGFR mutation and subtypes based on the spinal metastasis from primary lung adenocarcinoma

Purpose

To investigate the use of multiparameter MRI-based radiomics in the in-depth prediction of epidermal growth factor receptor (EGFR) mutation and subtypes based on the spinal metastasis in patients with primary lung adenocarcinoma.

Methods

A primary cohort was conducted with 257 patients who pathologically confirmed spinal bone metastasis from the first center between Feb. 2016 and Oct. 2020. An external cohort was developed with 42 patients from the second center between Apr. 2017 and Jun. 2021. All patients underwent sagittal T1-weighted imaging (T1W) and sagittal fat-suppressed T2-weight imaging (T2FS) MRI imaging. Radiomics features were extracted and selected to build radiomics signatures (RSs). Machine learning classify with 5-fold cross-validation were used to establish radiomics models for predicting the EGFR mutation and subtypes. Clinical characteristics were analyzed with Mann-Whitney U and Chi-Square tests to identify the most important factors. Nomogram models were developed integrating the RSs and important clinical factors.

Results

The RSs derived from T1W showed better performance for predicting the EGFR mutation and subtypes compared with those from T2FS in terms of AUC, accuracy and specificity. The nomogram models integrating RSs from combination of the two MRI sequences and important clinical factors achieved the best prediction capabilities in the training (AUCs, EGFR vs. Exon 19 vs. Exon 21, 0.829 vs. 0.885 vs.0.919), internal validation (AUCs, EGFR vs. Exon 19 vs. Exon 21, 0.760 vs. 0.777 vs.0.811), external validation (AUCs, EGFR vs. Exon 19 vs. Exon 21, 0.780 vs. 0.846 vs.0.818). DCA curves indicated potential clinical values of the radiomics models.

Conclusions

This study indicated potentials of multi-parametric MRI-based radiomics to assess the EGFR mutation and subtypes. The proposed clinical-radiomics nomogram models can be considered as non-invasive tools to assist clinicians in making individual treatment plans.

Oncogenic role and drug sensitivity of ETV4 in human tumors: a pan-cancer analysis

Background

Increasing evidence supports a relationship between E twenty-six variant transcription factor 4 (ETV4) and several cancers, but no pan-cancer analysis has been reported.

Methods

The present study surveyed the effects of ETV4 on cancer using RNA sequencing data obtained from The Cancer Genome Atlas and GTEx, and further explored its role in drug sensitivity using data from Cellminer. Differential expression analyses were conducted for multiple cancers using R software. Cox regression and survival analysis were employed to calculate correlations between ETV4 levels and survival outcomes in multiple cancers using the online tool Sangerbox. ETV4 expression was also compared with immunity, heterogeneity, stemness, mismatch repair genes, and DNA methylation among different cancers.

Results

ETV4 was found to be significantly upregulated in 28 tumors. Upregulation of ETV4 was associated with poor overall survival, progression free interval, disease-free-interval, and disease specific survival in several cancer types. Expression of ETV4 was also remarkably correlated with immune cell infiltration, tumor heterogeneity, mismatch repair gene expression, DNA methylation, and tumor stemness. Furthermore, ETV4 expression seemed to affect sensitivity to a number of anticancer drugs.

Conclusions

These results suggest that ETV4 may be useful as a prognostic factor and therapeutic target.

E2F5 promotes proliferation and invasion of gastric cancer through directly upregulating UBE2T transcription

The underlying mechanisms of E2F5 upregulation and its pro-tumor functions have not been elucidated in gastric cancer (GC). Here, the expression, prognostic value, mutation status, and promoter methylation of E2F5 were evaluated. The effects of E2F5 depletion on cell proliferation and invasion in GC, were also assessed through in vitro experiments. Additionally, gene set enrichment analysis (GSEA) was applied to analyze the potential downstream regulator of E2F5. The study also assessed the correlation and transcription regulation between E2F5 and UBE2T. Finally, the roles of UBE2T in E2F5-related pro-tumor functions were examined. The findings revealed that E2F5 was upregulated and showed remarkable association with pathological variables and prognosis. Hypomethylation of the E2F5 promoter predicted poor prognosis and partially caused E2F5 upregulation in GC. E2F5 knockdown significantly inhibited the proliferation and invasion of GC cells. E2F5 had a significant positive correlation with UBE2T in GC. Mechanistically, E2F5 promoted UBE2T transcription and UBE2T overexpression reversed the effects of E2F5 depletion on the proliferation and invasion of cells in GC. Taken together, this study originally confirmed the upregulation of E2F5 in GC, revealed that E2F5 can directly upregulate UBE2T transcription, and subsequently promote the malignant progression, which highlights that the E2F5/UBE2T axis can potentially be used in the diagnosis and treatment of GC.

Identification of condition-specific regulatory mechanisms in normal and cancerous human lung tissue

Background

Lung cancer is the leading cause of cancer death in both men and women. The most common lung cancer subtype is non-small cell lung carcinoma (NSCLC) comprising about 85% of all cases. NSCLC can be further divided into three subtypes: adenocarcinoma (LUAD), squamous cell carcinoma (LUSC), and large cell lung carcinoma. Specific genetic mutations and epigenetic aberrations play an important role in the developmental transition to a specific tumor subtype. The elucidation of normal lung versus lung tumor gene expression patterns and regulatory targets yields biomarker systems that discriminate lung phenotypes (i.e., biomarkers) and provide a foundation for the discovery of normal and aberrant gene regulatory mechanisms.

Results

We built condition-specific gene co-expression networks (csGCNs) for normal lung, LUAD, and LUSC conditions. Then, we integrated normal lung tissue-specific gene regulatory networks (tsGRNs) to elucidate control-target biomarker systems for normal and cancerous lung tissue. We characterized co-expressed gene edges, possibly under common regulatory control, for relevance in lung cancer.

Conclusions

Our approach demonstrates the ability to elucidate csGCN:tsGRN merged biomarker systems based on gene expression correlation and regulation. The biomarker systems we describe can be used to classify and further describe lung specimens. Our approach is generalizable and can be used to discover and interpret complex gene expression patterns for any condition or species.

Supplementary Information

The online version contains available at 10.1186/s12864-022-08591-9.

MRI-Based Radiomics Nomogram as a Potential Biomarker to Predict the EGFR Mutations in Exon 19 and 21 Based on Thoracic Spinal Metastases in Lung Adenocarcinoma

RATIONALE AND OBJECTIVES

Preoperative identifications of epidermal growth factor receptor (EGFR) mutation subtypes based on the MRI image of spinal metastases are needed to provide individualized therapy, but has not been previously investigated. This study aims to develop and evaluate an MRI-based radiomics nomogram for differentiating the exon 19 and 21 in EGFR mutation from spinal bone metastases in patients with primary lung adenocarcinoma.

MATERIALS AND METHODS

A total of 76 patients underwent T1-weighted and T2-weighted fat-suppressed MRI scans were enrolled in this study, 38 were positive for EGFR mutation in exon 19 and 38 were in exon 21.MRI imaging features were extracted and selected from each MRI pulse sequence, and used to form the radiomics signature. A radiomics nomogram was developed integrating the radiomics signature and important clinical factors with receiver operating characteristic, calibration and decision curve analysis to assess the nomogram. Clinical characteristics were analyzed with Mann-Whitney U and Chi-Square tests to identify the most important factors.

RESULTS

A total of 6 features were selected as the most discriminative predictors from the two MRI pulse sequences. The nomogram integrating the combined radiomics signature, age and CEA level generated good prediction performance in the training (AUCs, nomogram vs. combined radiomics signature vs. clinical model, 0.90 vs. 0.87 vs. 0.59) and validation (AUCs, nomogram vs. combined radiomics signature vs. clinical model, 0.88 vs. 0.86 vs. 0.72) cohort. DCA analysis confirmed the potential clinical utility of the nomogram.

CONCLUSION

This study demonstrated that MRI features from spinal bone metastases can be used to prognosticate EGFR mutation subtypes in exon 19 and 21. The developed pre-treatment nomogram can potentially guide treatments for lung adenocarcinoma patients.

ETV4 mediated lncRNA C2CD4D-AS1 overexpression contributes to the malignant phenotype of lung adenocarcinoma cells via miR-3681-3p/NEK2 axis

Lung adenocarcinoma (LUAD) is originated from the mucus-producing glands of the lungs. The involvement of long noncoding RNAs (lncRNAs) has been discovered in multiple diseases. In the present research, we aimed to unmask the role of C2CD4D and THEM5 antisense RNA 1 (C2CD4D-AS1) in LUAD. RT-qPCR or western blot analysis was respectively applied in the detection of RNA or protein expressions. The function of C2CD4D-AS1 in LUAD was assessed by functional assays. Through ChIP, RNA pull down, DNA pull down, RIP and luciferase reporter assays, the in-depth regulatory mechanism of C2CD4D-AS1 in LUAD was explored. C2CD4D-AS1 was dramatically overexpressed in LUAD tissues and cell lines. As a result, depletion of C2CD4D-AS1 significantly repressed cell proliferation, migration, invasion and stimulated cell apoptosis in LUAD. Mechanistically, ETS variant transcription factor 4 (ETV4) activated the transcription of C2CD4D-AS1 and stimulated its up-regulation in LUAD cells, thus affecting LUAD cell biological functions. Furthermore, C2CD4D-AS1 sponged microRNA-3681-3p (miR-3681-3p) and regulated NIMA-related kinase 2 (NEK2), thus participating in modulating LUAD cell biological behaviors. To conclude, C2CD4D-AS1 up-regulation induced by ETV4 enhanced NEK2 expression by sequestering miR-3681-3p to contribute to the malignant behaviors of LUAD cells.

E26 transformation-specific variant 4 as a tumor promotor in human cancers through specific molecular mechanisms

E26 transformation-specific (ETS) variant 4 (ETV4) is an important transcription factor that belongs to the ETS transcription factor family and is essential for much cellular physiology. Recent evidence has revealed that ETV4 is aberrantly expressed in many types of tumors, and its overexpression is related to poor prognosis of cancer patients. Additionally, increasing studies have identified that ETV4 promotes cancer growth, invasion, metastasis, and drug resistance. Mechanistically, the level of ETV4 is regulated by some post-translation modulations in a broad spectrum of cancers. However, little progress has been made to comprehensively summarize the critical roles of ETV4 in different human cancers. Hence, this review mainly focuses on the physiological functions of ETV4 in various human tumors. In addition, the molecular mechanisms of ETV4-mediated cancer progression were elucidated, including how ETV4 modulates its downstream signaling pathways and how ETV4 is regulated by some factors. On this basis, the present review may provide a valuable therapeutics strategy for future cancer treatment by targeting ETV4-related pathways.

The Knockdown of ETV4 Inhibits the Papillary Thyroid Cancer Development by Promoting Ferroptosis Upon SLC7A11 Downregulation

Papillary thyroid cancer (PTC) is one of the most prevalent endocrine malignancies. Herein, we aimed to provide a new viewpoint for the PTC progression and explore a new target for the effective therapy for PTC. We found that E26 transformation specific (ETS) variant 4 (ETV4, an ETS family transcription factor) was upregulated in PTC tissues and cells. In vitro experiments exhibited that silencing ETV4 suppressed PTC cell proliferation and cell cycle progression, while the overexpression of ETV4 gained the opposite results. Dual-luciferase reporter assay highlighted that ETV4 could upregulate the solute carrier family 7 member 11 (SLC7A11, a key role for cysteine uptake in ferroptosis) transcription by binding to its promoter region directly. Moreover, the viability inhibition of PTC cells induced by the knockdown of ETV4 was at least partly through the promotion of ferroptosis upon the downregulation of SLC7A11. In in vivo experiment, the results showed that the downregulation of ETV4 repressed the tumor development through the low expression of SLC7A11, and the ETV4 overexpression obtained the contrary effects. Overall, the data suggested that the knockdown of ETV4 suppressed the PTC progression by promoting ferroptosis upon SLC7A11 downregulation.

ETV4 mediates the wnt/β-catenin pathway through transcriptional activation of ANXA2 to promote hepatitis B virus-associated liver hepatocellular carcinoma progression

ETS variant 4 (ETV4) has been implicated in the development of various cancers. However, the molecular events mediated by ETV4 in liver cancer are poorly understood, especially in Hepatitis B virus (HBV)-associated liver hepatocellular carcinoma (LIHC). Here, we aimed to identify the target involved in ETV4-driven hepatocarcinogenesis. Bioinformatics analysis revealed that ETV4 was highly expressed in patients with HBV-associated LIHC, and HBV infection promoted the expression of ETV4 in LIHC cells. Inhibition of ETV4 repressed the proliferation, migration, invasion of LIHC cells and suppressed the secretion of HBV and the replication of HBV DNA. ANXA2 expression in LIHC patients was positively correlated with ETV4 expression. ChIP and dual-luciferase reporter assays revealed that ETV4 elevated the ANXA2 expression at the transcriptional level by binding to the ANXA2 promoter. Overexpression of ANXA2 reversed the inhibitory effect of sh-ETV4 on the malignant biological behaviors of HBV-infected LIHC cells by activating the Wnt/β-catenin pathway. In conclusion, ETV4 mediates the activation of Wnt/β-catenin pathway through transcriptional activation of ANXA2 expression to promote HBV-associated LIHC progression.

Identification of potential diagnostic biomarkers in MMPs for pancreatic carcinoma

Pancreatic cancer (PC) is a malignant tumor which ranks fourth in cancer-related death. However, the specificity and sensitivity of traditional biomarkers such as carbohydrate antigen 19-9 no longer meet the clinical requirements.Tools as ONCOMINE and Gene Expression Profiling Interactive Analysis (GEPIA) were used to analyze the differential expression of matrix metalloproteinases (MMPs) in PC and adjacent tissues. For further analysis, we adopted database for annotation, visualization and integrated discovery (DAVID 6.8), transcriptional regulatory relationships unraveled by sentence-based text (TRRUST) and other tools. We also identified drugs targeted the selected MMPs.Eight MMPs (MMP1, MMP2, MMP7, MMP9, MMP11, MMP12, MMP14, and MMP28) were differentially expressed in PC and adjacent tissue. MMP1 (P = .0189), MMP7 (P = .000216), MMP11 (P = .0209), MMP14 (P = .00611) were correlated with the pathological stages of PC. Patients with higher expression of MMP1 (P = .0011), MMP2 (P = .011), MMP7 (P = .0081), MMP9 (P = .046), MMP11 (P = .0019), MMP12 (P = .0011), MMP14 (P = .0011), and MMP28 (P = 6.3e-06) showed poor prognosis. Ten transcription factors were associated with the up-regulation of selected MMPs. Marimastat (DB00786) was found to target selected MMPs.Our research revealed that selected MMPs played an important role in the early diagnosis and prognosis of PC.

Potential Role of Musashi-2 RNA-Binding Protein in Cancer EMT

Local invasion and distant metastasis are the key hallmarks in the aggressive progression of malignant tumors, including the ability of cancer cells to detach from the extracellular matrix overcome apoptosis, and disseminate into distant sites. It is generally believed that this malignant behavior is stimulated by epithelial-mesenchymal transition (EMT). Musashi (MSI) RNA-binding proteins, belonging to the evolutionarily conserved RNA-binding proteins (RBP) family, were originally discovered to regulate asymmetric cell division during embryonic development. Recently, Musashi-2 (MSI2), as a key member of MSI family, has been prevalently reported to be tightly associated with the advanced clinical stage of several cancers. Multiple oncogenic signaling pathways mediated by MSI2 play vital roles in EMT. Here, we systematically reviewed the detailed role and signal networks of MSI2 in regulating cancer development, especially in EMT signal transduction, involving EGF, TGF-β, Notch, and Wnt pathways.

3D radiomics predicts EGFR mutation, exon-19 deletion and exon-21 L858R mutation in lung adenocarcinoma

BACKGROUND

To establish a radiomic approach to identify epidermal growth factor receptor (EGFR) mutation status in lung adenocarcinoma patients based on CT images, and to distinguish exon-19 deletion and exon-21 L858R mutation.

METHODS

Two hundred sixty-three patients who underwent pre-surgical contrast-enhanced CT and molecular testing were included, and randomly divided into the training (80%) and test (20%) cohort. Tumor images were three-dimensionally segmented to extract 1,672 radiomic features. Clinical features (age, gender, and smoking history) were added to build classification models together with radiomic features. Subsequently, the top-10 most relevant features were used to establish classifiers. For the classifying tasks including EGFR mutation, exon-19 deletion, and exon-21 L858R mutation, four logistic regression models were established for each task.

RESULTS

The training and test cohort consisted of 210 and 53 patients, respectively. Among the established models, the highest accuracy and sensitivity among the four models were 75.5% (61.7-86.2%) and 92.9% (76.5-99.1%) to classify EGFR mutation, respectively. The highest specificity values were 86.7% (69.3-96.2%) and 70.4% (49.8-86.3%) to classify exon-19 deletion and exon-21 L858R mutation, respectively.

CONCLUSIONS

CT radiomics can sensitively identify the presence of EGFR mutation, and increase the certainty of distinguishing exon-19 deletion and exon-21 L858R mutation in lung adenocarcinoma patients. CT radiomics may become a helpful non-invasive biomarker to select EGFR mutation patients for invasive sampling.

Identifying critical state of complex diseases by single-sample Kullback-Leibler divergence

Background

Developing effective strategies for signaling the pre-disease state of complex diseases, a state with high susceptibility before the disease onset or deterioration, is urgently needed because such state usually followed by a catastrophic transition into a worse stage of disease. However, it is a challenging task to identify such pre-disease state or tipping point in clinics, where only one single sample is available and thus results in the failure of most statistic approaches.

Methods

In this study, we presented a single-sample-based computational method to detect the early-warning signal of critical transition during the progression of complex diseases. Specifically, given a set of reference samples which were regarded as background, a novel index called single-sample Kullback–Leibler divergence (sKLD), was proposed to explore and quantify the disturbance on the background caused by a case sample. The pre-disease state is then signaled by the significant change of sKLD.

Results

The novel algorithm was developed and applied to both numerical simulation and real datasets, including lung squamous cell carcinoma, lung adenocarcinoma, stomach adenocarcinoma, thyroid carcinoma, colon adenocarcinoma, and acute lung injury. The successful identification of pre-disease states and the corresponding dynamical network biomarkers for all six datasets validated the effectiveness and accuracy of our method.

Conclusions

The proposed method effectively explores and quantifies the disturbance on the background caused by a case sample, and thus characterizes the criticality of a biological system. Our method not only identifies the critical state or tipping point at a single sample level, but also provides the sKLD-signaling markers for further practical application. It is therefore of great potential in personalized pre-disease diagnosis.

ETV4 overexpression promotes progression of non-small cell lung cancer by upregulating PXN and MMP1 transcriptionally

ETS variant 4 (ETV4), together with ETV1 and ETV5, constitute the PEA3 subfamily of ETS transcription factors, which are implicated in the progression of many cancers. However, the clinicopathologic significance and molecular events regulated by ETV4 in lung cancer are still poorly understood, especially in squamous cell carcinoma of the lung. Here, we aimed to identify functional targets involved in ETV4-driven lung tumorigenesis. Microarray analysis and validation data revealed that ETV4 was the most preponderant PEA3 factor, which was significantly related to the advanced stage, lymph node metastasis, and poor prognosis of non-small cell lung cancers (NSCLCs; all P < .001). Reduced ETV4 expression suppressed the growth and metastasis of NSCLC both in vivo and in vitro. Microarray, gain, or loss of function and luciferase report assays revealed the direct regulatory effect of ETV4 on the expression of focal adhesion gene PXN and matrix metalloproteinase 1 (MMP1), and PXN and/or MMP1 inhibition partially abolished cell proliferation and migration induced by ETV4. Kaplan-Meier analysis indicated that ETV4 and PXN or MMP1 co-overexpression is associated with poor prognosis in human NSCLCs. In conclusion, the ETV4-PXN and ETV4-MMP1 axes are useful biomarkers of tumor progression and worse outcomes in NSCLCs.