EXT1 methylation promotes proliferation and migration and predicts the clinical outcome of non-small cell lung carcinoma via WNT signalling pathway

EXT1 and Its Methylation Involved in the Progression of Uterine Corpus Endometrial Carcinoma Pathogenesis

Uterine corpus endometrial carcinoma (UCEC) is one of the most common gynecologic tumors. Due to the high recurrence and metastasis of UCEC, it is crucial for patients to find new biomarkers for diagnosis and therapy. In this study, R software and the TCGA database were used to screen candidate UCEC predictive markers. Western blot and RT-qPCR were performed to detect protein and mRNA expression of EXT1 in UCEC cell lines. In addition, MTT assay, flow cytometry, transwell assay, and wound healing assay were conducted to assess the cell viability, apoptosis, invasion, and migration in UCEC cells. Overlap-extension PCR technique was employed to construct the vector targeting the deletion of the methylated segment of EXT1. The results showed that a total of 11 candidate genes were obtained and EXT1 was identified as a potential target. The expression and methylation levels of EXT1 were both increased in UCEC tissues and cell lines, as well as elevated EXT1 was closely related to the poor prognosis of patients. Besides, the knockdown of EXT1 significantly inhibited the malignant biological behaviors in UCEC cells. Additionally, the current study also found that the deletion of 1559-2146 bp CpG island segment upregulated EXT1 expression and promoted malignant biological behaviors in UCEC cells. Furthermore, the presence of m7G RNA methylation in UCEC cells also was found. In conclusion, the methylation of EXT1 influenced the gene expression, thereby affecting the malignant biological behaviors in UCEC cells and regulating the pathological progression of UCEC.

TOP2A inhibition and its cellular effects related to cell cycle checkpoint adaptation pathway

In this study, we investigate the G2 checkpoint activated by chromosome entanglements, the so-called Decatenation Checkpoint (DC), which can be activated by TOP2A catalytic inhibition. Specifically, we focus on the spontaneous ability of cells to bypass or override this checkpoint, referred to as checkpoint adaptation. Some factors involved in adapting to this checkpoint are p53 and MCPH1. Using cellular models depleted of p53 or both p53 and MCPH1 in hTERT-RPE1 cells, we analyzed cell cycle dynamics and adaptation, segregation defects, apoptosis rate, and transcriptional changes related to prolonged exposure to TOP2A inhibitors. Our findings reveal that cell cycle dynamics are altered in MCPH1-depleted cells compared to control cells. We found that MCPH1 depletion can restore the robustness of the DC in a p53-negative background. Furthermore, this research highlights the differential effects of TOP2A poisons and catalytic inhibitors on cellular outcomes and transcriptional profiles. By examining the different mechanisms of TOP2A inhibition and their impact on cellular processes, this study contributes to a deeper understanding of the regulation and physiological implications of the DC and checkpoint adaptation in non-carcinogenic cell lines.

Wnt/β-catenin signaling in the development and therapeutic resistance of non-small cell lung cancer

Wnt/β-catenin signaling is a critical pathway that influences development and therapeutic response of non-small cell lung cancer (NSCLC). In recent years, many Wnt regulators, including proteins, miRNAs, lncRNAs, and circRNAs, have been found to promote or inhibit signaling by acting on Wnt proteins, receptors, signal transducers and transcriptional effectors. The identification of these regulators and their underlying molecular mechanisms provides important implications for how to target this pathway therapeutically. In this review, we summarize recent studies of Wnt regulators in the development and therapeutic response of NSCLC.

Cancer invasion and metastasis: Insights from murine pubertal mammary gland morphogenesis

Cancer invasion and metastasis accounts for the majority of cancer related mortality. A better understanding of the players that drive the aberrant invasion and migration of tumors cells will provide critical targets to inhibit metastasis. Postnatal pubertal mammary gland morphogenesis is characterized by highly proliferative, invasive, and migratory normal epithelial cells. Identifying the molecular regulators of pubertal gland development is a promising strategy since tumorigenesis and metastasis is postulated to be a consequence of aberrant reactivation of developmental stages. In this review, we summarize the pubertal morphogenesis regulators that are involved in cancer metastasis and revisit pubertal mammary gland transcriptome profiling to uncover both known and unknown metastasis genes. Our updated list of pubertal morphogenesis regulators shows that most are implicated in invasion and metastasis. This review highlights molecular linkages between development and metastasis and provides a guide for exploring novel metastatic drivers.

Heparan sulfate proteoglycans in cancer: Pathogenesis and therapeutic potential

The heparan sulfate proteoglycans (HSPGs) are glycoproteins that consist of a proteoglycan "core" protein and covalently attached heparan sulfate (HS) chain. HSPGs are ubiquitously expressed in mammalian cells on the cell surface and in the extracellular matrix (ECM) and secretory vesicles. Within HSPGs, the protein cores determine when and where HSPG expression takes place, and the HS chains mediate most of HSPG's biological roles through binding various protein ligands, including cytokines, chemokines, growth factors and receptors, morphogens, proteases, protease inhibitors, and ECM proteins. Through these interactions, HSPGs modulate cell proliferation, adhesion, migration, invasion, and angiogenesis to display essential functions in physiology and pathology. Under physiological conditions, the expression and localization of HSPGs are finely regulated to orchestrate their physiological functions, and this is disrupted in cancer. The HSPG dysregulation elicits multiple oncogenic signaling, including growth factor signaling, ECM and Integrin signaling, chemokine and immune signaling, cancer stem cell, cell differentiation, apoptosis, and senescence, to prompt cell transformation, proliferation, tumor invasion and metastasis, tumor angiogenesis and inflammation, and immunotolerance. These oncogenic roles make HSPGs an attractive pharmacological target for anti-cancer therapy. Several therapeutic strategies have been under development, including anti-HSPG antibodies, peptides and HS mimetics, synthetic xylosides, and heparinase inhibitors, and shown promising anti-cancer efficacy. Therefore, much progress has been made in this line of study. However, it needs to bear in mind that the roles of HSPGs in cancer can be either oncogenic or tumor-suppressive, depending on the HSPG and the cancer cell type with the underlying mechanisms that remain obscure. Further studies need to address these to fill the knowledge gap and rationalize more efficient therapeutic targeting.

Novel hypoxia-related gene signature for predicting prognoses that correlate with the tumor immune microenvironment in NSCLC

Background: Intratumoral hypoxia is widely associated with the development of malignancy, treatment resistance, and worse prognoses. The global influence of hypoxia-related genes (HRGs) on prognostic significance, tumor microenvironment characteristics, and therapeutic response is unclear in patients with non-small cell lung cancer (NSCLC). Method: RNA-seq and clinical data for NSCLC patients were derived from The Cancer Genome Atlas (TCGA) database, and a group of HRGs was obtained from the MSigDB. The differentially expressed HRGs were determined using the limma package; prognostic HRGs were identified via univariate Cox regression. Using the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression, an optimized prognostic model consisting of nine HRGs was constructed. The prognostic model's capacity was evaluated by Kaplan‒Meier survival curve analysis and receiver operating characteristic (ROC) curve analysis in the TCGA (training set) and GEO (validation set) cohorts. Moreover, a potential biological pathway and immune infiltration differences were explained. Results: A prognostic model containing nine HRGs (STC2, ALDOA, MIF, LDHA, EXT1, PGM2, ENO3, INHA, and RORA) was developed. NSCLC patients were separated into two risk categories according to the risk score generated by the hypoxia model. The model-based risk score had better predictive power than the clinicopathological method. Patients in the high-risk category had poor recurrence-free survival in the TCGA (HR: 1.426; 95% CI: 0.997-2.042; p = 0.046) and GEO (HR: 2.4; 95% CI: 1.7-3.2; p < 0.0001) cohorts. The overall survival of the high-risk category was also inferior to that of the low-risk category in the TCGA (HR: 1.8; 95% CI: 1.5-2.2; p < 0.0001) and GEO (HR: 1.8; 95% CI: 1.4-2.3; p < 0.0001) cohorts. Additionally, we discovered a notable distinction in the enrichment of immune-related pathways, immune cell abundance, and immune checkpoint gene expression between the two subcategories. Conclusion: The proposed 9-HRG signature is a promising indicator for predicting NSCLC patient prognosis and may be potentially applicable in checkpoint therapy efficiency prediction.

Investigating and modeling the differential DNA methylation for early lung adenocarcinoma diagnosis

Background: Aberrant DNA methylations serve as rich sources of diagnostic biomarkers, but a further improvement in their accuracy and clinical utility is warranted. Methods: Large panel bisulfite sequencing were performed on paired normal and stage I/IV tumors from 226 lung adenocarcinoma cancer patients to characterize the differentially methylated regions (DMRs). Results: Random forest model achieved high prediction accuracy (sensitivity 96% and specificity 97.56%) to separate normal controls from both early and advanced cancer samples, which is superior to most previous prediction models tested in lung adenocarcinoma. Conclusion: Our results suggest that combining the random forest model with targeted bisulfite sequencing have great clinical potentials to accurately predict and early diagnose lung adenocarcinoma during cancer screening.

Exploration of dilated cardiomyopathy for biomarkers and immune microenvironment: evidence from RNA-seq

Background

The pathogenic mechanism of dilated cardiomyopathy (DCM) remains to be defined. This study aimed to identify hub genes and immune cells that could serve as potential therapeutic targets for DCM.

Methods

We downloaded four datasets from the Gene Expression Omnibus (GEO) database: GSE141910, GSE3585, GSE42955 and GSE79962. Weighted gene coexpression network analysis (WGCNA) and differential expression analysis were performed to identify gene panels related to DCM. Meanwhile, the CIBERSORT algorithm was used to estimate the immune cells in DCM tissues. Multiple machine learning approaches were used to screen the hub genes and immune cells. Finally, the diagnostic value of the hub genes was assessed by receiver operating characteristic (ROC) analysis. An experimental mouse model of dilated cardiomyopathy was used to validate the bioinformatics results.

Results

FRZB and EXT1 were identified as hub biomarkers, and the ROC curves suggested an excellent diagnostic ability of the above genes for DCM. In addition, naive B cells were upregulated in DCM tissues, while eosinophils, M2 macrophages, and memory CD4 T cells were downregulated in DCM tissues. The increase in two hub genes and naive B cells was validated in animal experiments.

Conclusion

These results indicated that FRZB and EXT1 could be used as promising biomarkers, and eosinophils, M2 macrophages, resting memory CD4 T cells and naive B cells may also affect the occurrence of DCM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-022-02759-7.

Interfering with ITGB1-DT expression delays cancer progression and promotes cell sensitivity of NSCLC to cisplatin by inhibiting the MAPK/ERK pathway

Long non-coding RNA ITGB1-DT is involved in the regulation of cancer growth and metastasis. However, the roles of ITGB1-DT in non-small cell lung cancer (NSCLC) progression and sensitivity to cisplatin has not been elucidated. ITGB1-DT expression in NSCLC tissues, and the relationship between ITGB1-DT expression with NSCLC diagnosis, prognosis, clinicopathological features, and immune cell infiltration were investigated in The Cancer Gene Atlas (TCGA) database. The roles and mechanisms of ITGB1-DT in cell growth, migration, and drug sensitivity of NSCLC cells were explored in the cell model. The prognostic nomograms of ITGB1-DT-related genes were evaluated using bioinformatics. ITGB1-DT was overexpressed in NSCLC. Elevated ITGB1-DT expression was related to the late T stage, N stage, M stage, short overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) of NSCLC patients. ITGB1-DT was the independent risk factors for poor prognosis, and had diagnostic value for NSCLC patients. Interfering with the ITGB1-DT expression can inhibit the proliferation, migration, and invasion of A549, H1299, and drug-resistant A549/DDP, possibly due to the inhibition of p38 MAPK and ERK phosphorylation levels. ITGB1-DT expression was correlated with the levels of NSCLC immune infiltration cells, such as the TReg, Th, and NK cells. ITGB1-DT-related gene nomograms were associated with the prognosis, and were expected to evaluate the prognosis of NSCLC patients. In conclusion, inhibition of ITGB1-DT expression delayed the growth and metastasis of NSCLC using the MAPK/ERK signaling mechanism and enhanced the sensitivity of NSCLC to cisplatin drugs. These results indicate that ITGB1-DT might be a biomarker for evaluating the diagnosis and prognosis of NSCLC patients.

Prognostic Ability of Enhancer RNAs in Metastasis of Non-Small Cell Lung Cancer

(1) Background: Non-small cell lung cancer (NSCLC) is the most common lung cancer. Enhancer RNA (eRNA) has potential utility in the diagnosis, prognosis and treatment of cancer, but the role of eRNAs in NSCLC metastasis is not clear; (2) Methods: Differentially expressed transcription factors (DETFs), enhancer RNAs (DEEs), and target genes (DETGs) between primary NSCLC and metastatic NSCLC were identified. Prognostic DEEs (PDEEs) were screened by Cox regression analyses and a predicting model for metastatic NSCLC was constructed. We identified DEE interactions with DETFs, DETGs, reverse phase protein arrays (RPPA) protein chips, immunocytes, and pathways to construct a regulation network using Pearson correlation. Finally, the mechanisms and clinical significance were explained using multi-dimensional validation unambiguously; (3) Results: A total of 255 DEEs were identified, and 24 PDEEs were selected into the multivariate Cox regression model (AUC = 0.699). Additionally, the NSCLC metastasis-specific regulation network was constructed, and six key PDEEs were defined (ANXA8L1, CASTOR2, CYP4B1, GTF2H2C, PSMF1 and TNS4); (4) Conclusions: This study focused on the exploration of the prognostic value of eRNAs in the metastasis of NSCLC. Finally, six eRNAs were identified as potential markers for the prediction of metastasis of NSCLC.

KIF2C is a Biomarker Correlated With Prognosis and Immunosuppressive Microenvironment in Human Tumors

Kinesin superfamily member 2C (KIF2C) is an essential regulator of the cell cycle and its aberrant expression can promote tumor progression. However, the mechanism of KIF2C in pan-cancer is unclear.Data were obtained from public databases, including The Cancer Genome Atlas (TCGA), UALCAN, TIMER and CellMiner. The data came from public databases such as The Cancer Genome Atlas (TCGA), UALCAN, TIMER, and CellMiner. We analyzed the correlation of KIF2C with expression, prognosis, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repairs (MMR), immune infiltration and anticancer drug sensitivity by R language.KIF2C was highly expressed in several tumors and correlated with poor prognosis. KIF2C expression was significantly correlated with TMB, MSI, MMRs, and immune checkpoint genes, and with the level of immune cell infiltration such as tumor-associated macrophage (TAM), cancer-associated fibroblasts (CAFs), myeloid-derived suppressor cells (MDSCs) and Tregs. The GO and KEGG results suggest that KIF2C is involved in immune regulation in addition to cell cycle regulation.In addition, KIF2C is associated with DNA methylation, m6A modifications and m7G modifications. Our data suggest that KIF2C is a prognostic biomarker linked to immunosuppression, targeting KIF2C may improve the outcome of immunotherapy. Our findings indicate that KIF2C is a prognostic biomarker associated with immunosuppression, and that targeting KIF2C may improve the outcome of immunotherapy.

Circular RNA circβ-catenin aggravates the malignant phenotype of non-small-cell lung cancer via encoding a peptide

Background

More and more evidences demonstrate that circular RNAs (circNRAs) can encode protein. As a circRNA with translation capabilities, outcomes of circβ‐catenin in non‐small cell lung cancer (NSCLC) still need to be explored.

Method

The research methods of circβ‐catenin in the article include qRT‐PCR, wound healing assay, CCK‐8, colony formation, and Transwell assay. Western blotting and immunofluorescence were provided to detect protein expression levels and peptide encoded by circβ‐catenin, respectively.

Results

A prominently higher circβ‐catenin expression was found in NSCLC tissues. Silencing of circβ‐catenin was able to inhibit NSCLC cell migrating, invasive, and proliferative phenotypes. Overexpression of circβ‐catenin could enhance the migrating, invasive, and proliferative phenotypes of NSCLC cells. Importantly, circβ‐catenin was found to encode a peptide in NSCLC cells. Silencing or overexpression of circβ‐catenin could reduce or increase β‐catenin protein expression via suppressing the degradation of β‐catenin.

Conclusion

Circβ‐catenin could promote NSCLC cell malignant phenotypes via peptide‐regulated β‐catenin pathway. Our study provided a new understanding for the mechanisms of NSCLC.

EXT1 methylation promotes proliferation and migration and predicts the clinical outcome of non-small cell lung carcinoma via WNT signalling pathway

DNA methylation is important for lung cancer prognosis. In this work, it is aimed to seek novel biomarkers with DNA methylation‐expression‐pathway pattern and explore its underlying mechanism. Prognostic DNA methylation sites and mRNAs were screened in NSCLC data set from TCGA, and further validated using the samples retrospectively collected, and EXT1 was identified as a potential target. Gene body methylation of three CpG sites (cg03276982, cg11592677, cg16286281) on EXT1 was significantly associated with clinical outcome, and the EXT1 gene expression also predicted prognosis. The expression level of EXT1 was also correlated with its DNA methylation level. This observation was further validated in a new data set consist of 170 samples. Knocking down of EXT1 resulted in decreased proliferation and migration. EXT1 targets were analysed using GSEA. It is found that the WNT signalling is the potential downstream target of EXT1. Further analyses revealed that the EXT1 targets the beta‐catenin and effect migration rate of NSCLC cell lines. The WNT signalling inhibitor, XAV‐939, effectively disrupted the migration promotion effect induced by EXT1. In summary, EXT1 methylation regulates the gene expression, effects the proliferation and migration via WNT pathway and predicted a poor prognosis for NSCLC.