EPAS1 promotes peritoneal carcinomatosis of non-small-cell lung cancer by enhancing mesothelial-mesenchymal transition

Targeting EPAS-1/HIF-2α Pathway to Address Endocrine Resistance in Luminal A Type Breast Cancer

BACKGROUND

Tamoxifen is most often used as the first treatment for luminal A breast cancer; however, one-third of the patients are resistant to it. Numerous studies have shown that hypoxia contributes to drug resistance and is related to poor clinical outcomes. Despite this, little is known regarding the key hypoxic mediators involved in tamoxifen resistance.

METHODS

We performed a comprehensive multi-omics analysis using publicly available transcriptomics and whole-exome sequencing data from tamoxifen-sensitive and tamoxifen-resistant luminal A breast cancer patient samples. EPAS1 was identified as a key hypoxic mediator linked to endocrine resistance in luminal A breast cancer. In vitro assays, including Western blotting, hypoxia detection assays, and CCK8 assays, were conducted to validate the association between EPAS1 expression and tamoxifen resistance in cell lines. Additionally, we tested the effect of PT2977 (Belzutifan), an EPAS1 inhibitor, as a potential treatment for tamoxifen resistance using tamoxifen-resistant and control cells, followed by validation in xenograft models of tamoxifen-resistant tumours.

RESULTS

Patient and cell line data revealed that EPAS1 is significantly upregulated in tamoxifen-resistant luminal A breast cancer, which is associated with poor survival outcomes and an altered tumour microenvironment. Further investigation using tamoxifen-resistant cell lines confirmed elevated EPAS1 expression levels. In vitro treatment with the EPAS1 inhibitor PT2977 resulted in a significant decrease in cell viability and modulated hypoxia-related pathways, indicating a potential therapeutic effect. Furthermore, in vivo studies showed that PT2977 reduced the growth of tamoxifen-resistant cells under the experimental conditions used.

CONCLUSION

This study suggests that PT2977, by targeting the hypoxic gene EPAS1, has the potential to inhibit the growth of tamoxifen-resistant luminal A breast cancer. However, while PT2977 demonstrated effectiveness in reducing tumour growth under the experimental conditions used, further studies are necessary to evaluate its role in overcoming hormone resistance and to explore its therapeutic applicability in broader clinical settings and other cancer subtypes.

Association between single nucleotide polymorphisms in EPAS1 and PPARA genes and high altitude polycythemia in Chinese Tibetan population

Background

High altitude polycythemia (HAPC) is a disease with high morbidity and great harm in high altitude populations. It has been shown that Single Nucleotide Polymorphisms (SNPs) correlate with the genetic basis of adaptation to plateau hypoxia in Tibetan populations. The EPAS1 and PPARA genes are involved in hypoxia adaptation by encoding transcription factors in Tibetan populations at high altitude. The aim of this study was to investigate the association of EPAS1 and PPARA gene locus polymorphisms with genetic susceptibility to HAPC in the Chinese Tibetan population.

Methods

We included 78 HAPC patients and 84 healthy controls, and genotyped the EPAS1 gene SNP loci (rs6735530, rs6756667, rs7583392, and rs12467821) and PPARA rs6520015 by using TaqMan polymerase chain reaction. Logistic regression was used to analyze the association between these SNPs and HAPC; interactions between SNPs were also predicted by multifactorial dimensionality reduction (MDR) analysis.

Results

We found that the PPARA rs6520015 polymorphism was not associated with the risk of HAPC in the Chinese Tibetan population; EPAS1 rs6735530, rs6756667, rs7583392, and rs12467821 increased the risk of HAPC in some models. Haplotype TCAGC decreases the risk of HAPC; Haplotype TTGAT increases the risk of HAPC; and EPAS1 rs7583392 is in complete linkage disequilibrium with rs12467821. The best prediction model was the EPAS1 rs6756667 unit point model, but the P value was greater than 0.05 in all three models, which was not statistically significant.

Conclusion

The present findings suggest that among the Tibetan population in China, There is an association between EPAS1 rs6735530, rs6756667, rs7583392, and rs12467821 and the risk of HAPC, and that there is no significant correlation between PPARA rs6520015 and the risk of HAPC.

Putative mechanisms of primary resistance to EGFR-targeted therapies: A retrospective study

BACKGROUNDS

Advanced lung adenocarcinoma (LUAD) patient with EGFR mutations often experience resistance to first-line epidermal growth factor tyrosine kinase inhibitors (EGFR-TKIs) therapy. Nonetheless, the mechanism and biomarkers of primary resistance remain unclear. Further exploration of independent prognostic factors will help clinicians identify patients who may not respond to EGFR-TKIs and select appropriate treatment strategies.

METHODS

A retrospective study involving 124 patients with stage IV LUAD harboring a common sensitizing EGFR mutation (exon 19 deletion or L858R mutation) who received EGFR-TKIs as first-line therapy was performed. All participants were tested by DNA-targeted sequencing in baseline samples, and there were 19 patients with progression-free survival (PFS) ≤ 3 months (cohort 1, C1, primary resistance), 22 patients with 3 < PFS < 8 months (cohort 2, C2, poor response) without known mutations associated with resistance, and 83 patients with PFS ≥ 8 months (cohort 3, C3, normal).

RESULTS

The most commonly mutated genes at baseline in patients prior to treatment within the entire study population. were TP53 (65 %), MYC (19 %), CDKN2A (12 %), MUC16 (12 %) and RBM10 (12 %). The baseline characteristics, except for the proportions of patients with EGFR L858R mutation and exon 19 deletion in C1 plus C2 compared to C3 (p = 0.036), were not significantly different among the cohorts. The frequencies of PIK3C2G, STK11, EPAS1, RARA and BTG2 variation were significantly higher in C1, the primary resistance group. Multivariate Cox analysis revealed that PIK3C2G (HR 15.70 95 % CI 3.24-76.05, p < 0.001), STK11 (HR 17.04, 95 % CI 3.68-78.92, p < 0.001), EPAS1 (HR 11.99, 95 % CI 2.57-56.03, p = 0.002), and BTG2 amplification (HR 9.53, 95 % CI 1.67-54.28, p = 0.011) were significantly associated with shorter PFS.

CONCLUSIONS

The genomic landscape varies significantly among patients with LUAD, which should be considered when making personalized treatment decisions. This information could provide insights into molecular changes and their effects on clinical treatment in diverse patients with LUAD harboring sensitizing EGFR mutations.

Boosting Clear Cell Renal Carcinoma-Specific Drug Discovery Using a Deep Learning Algorithm and Single-Cell Analysis

Clear cell renal carcinoma (ccRCC), the most common subtype of renal cell carcinoma, has the high heterogeneity of a highly complex tumor microenvironment. Existing clinical intervention strategies, such as target therapy and immunotherapy, have failed to achieve good therapeutic effects. In this article, single-cell transcriptome sequencing (scRNA-seq) data from six patients downloaded from the GEO database were adopted to describe the tumor microenvironment (TME) of ccRCC, including its T cells, tumor-associated macrophages (TAMs), endothelial cells (ECs), and cancer-associated fibroblasts (CAFs). Based on the differential typing of the TME, we identified tumor cell-specific regulatory programs that are mediated by three key transcription factors (TFs), whilst the TF EPAS1/HIF-2α was identified via drug virtual screening through our analysis of ccRCC's protein structure. Then, a combined deep graph neural network and machine learning algorithm were used to select anti-ccRCC compounds from bioactive compound libraries, including the FDA-approved drug library, natural product library, and human endogenous metabolite compound library. Finally, five compounds were obtained, including two FDA-approved drugs (flufenamic acid and fludarabine), one endogenous metabolite, one immunology/inflammation-related compound, and one inhibitor of DNA methyltransferase (N4-methylcytidine, a cytosine nucleoside analogue that, like zebularine, has the mechanism of inhibiting DNA methyltransferase). Based on the tumor microenvironment characteristics of ccRCC, five ccRCC-specific compounds were identified, which would give direction of the clinical treatment for ccRCC patients.

The underlying molecular mechanisms and biomarkers between periodontitis and COVID-19

OBJECTIVE

Emerging evidence shows the clinical consequences of patient with COVID-19 and periodontitis are not promising, and periodontitis is a risk factor. Periodontitis and COVID-19 probably have a relationship. Hence, this study aimed to identify the common molecular mechanism that may help to devise potential therapeutic strategies in the future.

MATERIAL AND METHODS

We analyzed two RNA-seq datasets for differential expressed genes, enrichment of biological processes, transcription factors (TFs) and deconvolution-based immune cell types in periodontitis, COVID-19 and healthy controls. Relationships between TFs and mRNA were established by Pearson correlation analysis, and the common TFs-mRNA regulatory network and nine co-upregulated TFs of the two diseases was obtained. The RT-PCR detected the TFs.

RESULTS

A total of 1616 and 10201 differentially expressed gene (DEGs) from periodontitis and COVID-19 are found. Moreover, nine shared TFs and common biological processes associated with lymphocyte activation involved in immune response were identified across periodontitis and COVID-19. The cell type enrichment revealed elevated plasma cells among two diseases. The RT-PCR further confirmed the nine TFs up-regulation in periodontitis.

CONCLUSION

The pathogenesis of periodontitis and COVID-19 is closely related to the expression of TFs and lymphocyte activation, which can provide potential targets for treatment.

A feature selection-based framework to identify biomarkers for cancer diagnosis: A focus on lung adenocarcinoma

Lung cancer (LC) represents most of the cancer incidences in the world. There are many types of LC, but Lung Adenocarcinoma (LUAD) is the most common type. Although RNA-seq and microarray data provide a vast amount of gene expression data, most of the genes are insignificant to clinical diagnosis. Feature selection (FS) techniques overcome the high dimensionality and sparsity issues of the large-scale data. We propose a framework that applies an ensemble of feature selection techniques to identify genes highly correlated to LUAD. Utilizing LUAD RNA-seq data from the Cancer Genome Atlas (TCGA), we employed mutual information (MI) and recursive feature elimination (RFE) feature selection techniques along with support vector machine (SVM) classification model. We have also utilized Random Forest (RF) as an embedded FS technique. The results were integrated and candidate biomarker genes across all techniques were identified. The proposed framework has identified 12 potential biomarkers that are highly correlated with different LC types, especially LUAD. A predictive model has been trained utilizing the identified biomarker expression profiling and performance of 97.99% was achieved. In addition, upon performing differential gene expression analysis, we could find that all 12 genes were significantly differentially expressed between normal and LUAD tissues, and strongly correlated with LUAD according to previous reports. We here propose that using multiple feature selection methods effectively reduces the number of identified biomarkers and directly affects their biological relevance.

EPAS1 Promoter Hypermethylation is a Diagnostic and Prognostic Biomarker for Non-Small Cell Lung Cancer

Background: The importance of promoter methylation in non-small cell lung cancers (NSCLCs) remains to be understood. Thus, we aimed to determine the diagnostic and prognostic value of methylation of the endothelial Per-Arnt-Sim (PAS) domain-containing protein 1 (EPAS1) promoter in NSCLC. Materials and Methods: EPAS1 promoter methylation levels were quantitated by a methylation-specific polymerase chain reaction. Furthermore, we evaluated the expression, promoter methylation, prognostic value, and impact on immune cell infiltration of EPAS1 by analyzing TCGA database or by web-based bioinformatics tools such as GEPIA, UALCAN, and MethSurv. Results: Our results demonstrated that promoter methylation of EPAS1 downregulated its expression in NSCLC tissues. Additionally, an area under the curve value of 0.772 indicated that methylation of the EPAS1 promoter is a potential diagnostic marker for NSCLC. Kaplan-Meier analysis demonstrated that high methylation levels of CpG sites in the EPAS1 promoter were indicative of worse overall survival (OS). Furthermore, EPAS1 expression levels were strongly correlated with infiltration of several types of immune cells, for instance, γδ T cells, T follicular helper cells, CD8+ T cells, and CD4+ T cells. Conclusions: Collectively, our findings demonstrated that methylation of the EPAS1 promoter is a promising prognostic biomarker for NSCLC and EPAS1 potentially plays an important role in immune cell infiltration in NSCLC.

Targeting HIF-2α in the Tumor Microenvironment: Redefining the Role of HIF-2α for Solid Cancer Therapy

Inadequate oxygen supply, or hypoxia, is characteristic of the tumor microenvironment and correlates with poor prognosis and therapeutic resistance. Hypoxia leads to the activation of the hypoxia-inducible factor (HIF) signaling pathway and stabilization of the HIF-α subunit, driving tumor progression. The homologous alpha subunits, HIF-1α and HIF-2α, are responsible for mediating the transcription of a multitude of critical proteins that control proliferation, angiogenic signaling, metastasis, and other oncogenic factors, both differentially and sequentially regulating the hypoxic response. Post-translational modifications of HIF play a central role in its behavior as a mediator of transcription, as well as the temporal transition from HIF-1α to HIF-2α that occurs in response to chronic hypoxia. While it is evident that HIF-α is highly dynamic, HIF-2α remains vastly under-considered. HIF-2α can intensify the behaviors of the most aggressive tumors by adapting the cell to oxidative stress, thereby promoting metastasis, tissue remodeling, angiogenesis, and upregulating cancer stem cell factors. The structure, function, hypoxic response, spatiotemporal dynamics, and roles in the progression and persistence of cancer of this HIF-2α molecule and its EPAS1 gene are highlighted in this review, alongside a discussion of current therapeutics and future directions.

lncRNAfunc: a knowledgebase of lncRNA function in human cancer

The long non-coding RNAs associating with other molecules can coordinate several physiological processes and their dysfunction can impact diverse human diseases. To date, systematic and intensive annotations on diverse interaction regulations of lncRNAs in human cancer were not available. Here, we built lncRNAfunc, a knowledgebase of lncRNA function in human cancer at https://ccsm.uth.edu/lncRNAfunc, aiming to provide a resource and reference for providing therapeutically targetable lncRNAs and intensive interaction regulations. To do this, we collected 15 900 lncRNAs across 33 cancer types from TCGA. For individual lncRNAs, we performed multiple interaction analyses of different biomolecules including DNA, RNA, and protein levels. Our intensive studies of lncRNAs provide diverse potential mechanisms of lncRNAs that regulate gene expression through binding enhancers and 3'-UTRs of genes, competing for miRNA binding sites with mRNAs, recruiting the transcription factors to gene promoters. Furthermore, we investigated lncRNAs that potentially affect the alternative splicing events through interacting with RNA binding Proteins. We also performed multiple functional annotations including cancer stage-associated lncRNAs, RNA A-to-I editing event-associated lncRNAs, and lncRNA expression quantitative trait loci. lncRNAfunc is a unique resource for cancer research communities to help better understand potential lncRNA regulations and therapeutic lncRNA targets.

MicroRNA-383: A tumor suppressor miRNA in human cancer

Downregulated expression of anti-tumor miR-383 has been found in many kinds of cancer. MiR-383 family members can directly target the 3'-untranslated region (3'-UTR) of the mRNA of some pro-tumor genes to attenuate several cancer-related processes, including cell proliferation, invasion, migration, angiogenesis, immunosuppression, epithelial-mesenchymal transition, glycolysis, chemoresistance, and the development of cancer stem cells, whilst promoting apoptosis. Functionally, miR-383 operates as a tumor inhibitor miRNA in many types of cancer, including breast cancer, hepatocellular carcinoma, gastric cancer, pancreatic cancer, colorectal cancer, esophageal cancer, lung cancer, head and neck cancer, glioma, medulloblastoma, melanoma, prostate cancer, cervical cancer, oral squamous cell carcinoma, thyroid cancer, and B-cell lymphoma. Both pro-tumor and anti-tumor effects have been attributed to miR-383 in ovarian cancer. However, only the pro-tumor effects of miR-383 were reported in cholangiocarcinoma. The restoration of miR-383 expression could be considered a possible treatment for cancer. This review discusses the anti-tumor effects of miR-383 in human cancers, emphasizing their downstream target genes and potential treatment approaches.

Pre-Clinical and Clinical Applications of Small Interfering RNAs (siRNA) and Co-Delivery Systems for Pancreatic Cancer Therapy

Pancreatic cancer (PC) is one of the leading causes of death and is the fourth most malignant tumor in men. The epigenetic and genetic alterations appear to be responsible for development of PC. Small interfering RNA (siRNA) is a powerful genetic tool that can bind to its target and reduce expression level of a specific gene. The various critical genes involved in PC progression can be effectively targeted using diverse siRNAs. Moreover, siRNAs can enhance efficacy of chemotherapy and radiotherapy in inhibiting PC progression. However, siRNAs suffer from different off target effects and their degradation by enzymes in serum can diminish their potential in gene silencing. Loading siRNAs on nanoparticles can effectively protect them against degradation and can inhibit off target actions by facilitating targeted delivery. This can lead to enhanced efficacy of siRNAs in PC therapy. Moreover, different kinds of nanoparticles such as polymeric nanoparticles, lipid nanoparticles and metal nanostructures have been applied for optimal delivery of siRNAs that are discussed in this article. This review also reveals that how naked siRNAs and their delivery systems can be exploited in treatment of PC and as siRNAs are currently being applied in clinical trials, significant progress can be made by translating the current findings into the clinical settings.

MiR-182-5p promotes the Metastasis and Epithelial-mesenchymal Transition in Non-small Cell Lung Cancer by Targeting EPAS1

Background: Dysregulation of microRNAs (miRNAs) is associated with the pathogenesis of non-small cell lung cancer (NSCLC). However, the mechanisms through which miR-182-5p regulate NSCLC progression have not been established. This study aimed at evaluating the expression levels of miR-182-5p in human NSCLC and its function in lung cancer cells. Endothelial PAS Domain-containing protein 1 (EPAS1; also referred to as hypoxia-inducing factor 2A, HIF-2α) is a transcription factor that is responsible for induction of genes related to cell survival under hypoxia conditions. Hypoxia, an inherent feature of solid tumors, is associated with aggressive phenotypes, as well as resistance to radiotherapy and chemotherapy, which predict metastasis and poor prognosis. Methods: The Cancer Genome Atlas (TCGA) dataset was used to investigate the association between miR-182-5p expression and clinicopathological characteristics as well as prognosis of NSCLC patients. Target genes of miR-182-5p were identified using the PITA, miRmap, microT, miRanda, PicTar, and TargetScan prediction tools. Transwell assays were performed to determine the potential functions of miR-182-5p in lung cancer cells. Luciferase reporter assays were performed to analyze regulation of the putative target of miR-182-5p while western blot assays were used to validate the luciferase results. Results: miR-182-5p was found to be upregulated in NSCLC tissues and acted as an independent prognostic factor for tumor recurrence in NSCLC patients. Functionally, overexpression of miR-182-5p promoted lung cancer cell migration and invasion. Genome-wide gene expression analysis and luciferase report assays revealed that EPAS1 is a direct target of miR-182-5p. EPAS1 was negatively correlated with miR-182-5p expression in NSCLC tissues. Univariate and multivariate survival analyses identified EPAS1 as an independent prognostic factor for overall survival (OS) in NSCLC. Conclusions: These findings imply that miR-182-5p promotes NSCLC progression by targeting EPAS1 and is, therefore, a potential indicator of tumor recurrence in NSCLC patients.

Computational pan-cancer characterization of model-based quantitative transcription regulations dysregulated in regional lymph node metastasis

Cancer is one of the major causes of mortality worldwide. Regional lymph node metastasis is an important mechanism during the spread of human cancers, in which transcription regulation plays an essential role. This study formulated a regression-model-based quantitative transcription regulation (mqTrans) between one mRNA gene and multiple transcription factors (TFs). Computational pan-cancer screening was carried out to detect the quantitative dysregulation of transcription regulation in the regional lymph node metastasis of 18 cancer types. Only a few metastasis-dysregulated mqTrans models were shared among the cancer types. The mRNA genes of the metastasis-dysregulated mqTrans models were not differentially expressed in regional lymph node metastasis. The experimental data suggested that mqTrans technology provided a complementary approach to the evaluation of transcription regulation mechanisms and may facilitate its quantitative investigation in other phenotypes.

Decreased HLF Expression Predicts Poor Survival in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a type of non-small cell carcinoma. Its pathogenesis is being explored and there is no cure for the disease.

Material/Methods

The Gene Expression Omnibus (GEO) was searched to obtain data on expression of messenger RNA. GEO2R, an interactive web tool, was used to calculate the differentially expressed genes (DEGs) in LUAD. All the DEGs from different datasets were imported into VENNY 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/index.html) to identify the intersection of the DEGs. An online analysis tool, the Database for Annotation, Visualization, and Integrated Discovery (DAVID), was used to help understand the biological meaning of DEG enrichment in LUAD. Cytoscape 3.7.2 was used to perform centrality analysis and visualize hub genes and related networks. Furthermore, the prognostic value of the hub genes was evaluated with the Kaplan-Meier plotter survival analysis tool.

Results

The GEO database was used to obtain RNA sequencing information for LUAD and normal tissue from the GSE118370, GSE136043, and GSE140797 datasets. A total of 376 DEGs were identified from GSE118370, 248 were identified from GSE136403, and 718 DEGs were identified from GSE140797. The 10 genes with the highest degrees of expression – the hub genes – were CAV1, TEK, SLIT2, RHOJ, DGSX, HLF, MEIS1, PTPRD, FOXF1, and ADRB2. In addition, Kaplan-Meier survival evaluation showed that CAV1, TEK, SLIT2, HLF, MEIS1, PTPRD, FOXF1, and ADRB2 were associated with favorable outcomes for LUAD.

Conclusions

CAV1, TEK, SLIT2, HLF, MEIS1, PTPRD, FOXF1, and ADRB2 are hub genes in the DEG interaction network for LUAD and are involved in the development of and prognosis for the disease. The mechanisms underlying these genes should be the subject of further studies.