Prognostic significance of epigenetic regulatory gene expression in patients with non-small-cell lung cancer

In-silico discovery of common molecular signatures for which SARS-CoV-2 infections and lung diseases stimulate each other, and drug repurposing

COVID-19 caused by SARS-CoV-2 is a global health issue. It is yet a severe risk factor to the patients, who are also suffering from one or more chronic diseases including different lung diseases. In this study, we explored common molecular signatures for which SARS-CoV-2 infections and different lung diseases stimulate each other, and associated candidate drug molecules. We identified both SARS-CoV-2 infections and different lung diseases (Asthma, Tuberculosis, Cystic Fibrosis, Pneumonia, Emphysema, Bronchitis, IPF, ILD, and COPD) causing top-ranked 11 shared genes (STAT1, TLR4, CXCL10, CCL2, JUN, DDX58, IRF7, ICAM1, MX2, IRF9 and ISG15) as the hub of the shared differentially expressed genes (hub-sDEGs). The gene ontology (GO) and pathway enrichment analyses of hub-sDEGs revealed some crucial common pathogenetic processes of SARS-CoV-2 infections and different lung diseases. The regulatory network analysis of hub-sDEGs detected top-ranked 6 TFs proteins and 6 micro RNAs as the key transcriptional and post-transcriptional regulatory factors of hub-sDEGs, respectively. Then we proposed hub-sDEGs guided top-ranked three repurposable drug molecules (Entrectinib, Imatinib, and Nilotinib), for the treatment against COVID-19 with different lung diseases. This recommendation is based on the results obtained from molecular docking analysis using the AutoDock Vina and GLIDE module of Schrödinger. The selected drug molecules were optimized through density functional theory (DFT) and observing their good chemical stability. Finally, we explored the binding stability of the highest-ranked receptor protein RELA with top-ordered three drugs (Entrectinib, Imatinib, and Nilotinib) through 100 ns molecular dynamic (MD) simulations with YASARA and Desmond module of Schrödinger and observed their consistent performance. Therefore, the findings of this study might be useful resources for the diagnosis and therapies of COVID-19 patients who are also suffering from one or more lung diseases.

Overexpression of RAD54L attenuates osteoarthritis by suppressing the HIF-1α/VEGF signaling pathway: Bioinformatics analysis and experimental validation

Osteoarthritis (OA) is a widespread chronic, progressive, degenerative joint disease that causes pain and disability. Current treatments for OA have limited effectiveness and new biomarkers need to be identified. Bioinformatics analysis was conducted to explore differentially expressed genes and DNA repair/recombination protein 54 L (RAD54L) was selected. We firstly overexpressed RAD54L in interleukin-1β (IL-1β)-induced human articular chondrocytes or in OA rats to investigate its effect on OA. Chondrocyte viability and apoptotic rate were measured by Cell Counting Kit-8 and flow cytometry, respectively. Then we evaluated OA severity in vivo by Hematoxylin-eosin staining and Osteoarthritis Research Society International standards. The expression of inflammatory mediators was tested by enzyme-linked immunosorbent assay. Finally, western blot was performed to determine the relative expression level of hypoxia-inducible factors 1α (HIF-1α) and vascular endothelial growth factor (VEGF). Overexpression of RAD54L promoted cell viability and attenuated apoptosis in IL-1β-induced human chondrocytes. A lower Osteoarthritis Research Society International score and a remarkable alleviation of chondrocyte disordering and infiltration of inflammatory cells were found in cartilage tissues of OA rats after overexpressing RAD54L. The inflammatory response induced by OA was decreased by RAD54L overexpression in vitro and in vivo. In addition, RAD54L overexpression decreased the relative expression level of HIF-1α and VEGF. Overexpression of RAD54L could attenuate OA by suppressing the HIF-1α/VEGF signaling pathway, indicating that RAD54L may be a potential treatment target for OA.

Discovery of potent small molecule inhibitors of histone lysine methyltransferase NSDs

Nuclear receptor binding SET domain (NSD) proteins are a class of histone lysine methyltransferases and implicated in multiple cancer types with aberrant expression and involvement of cancer related signaling pathways. In this study, a series of small-molecule compounds including compound 2 and 3 are identified against the SET domain of NSDs through structure-based virtual screening. Our lead compound 3 exhibits potent inhibitory activities in vitro towards the NSD2-SET and NSD3-SET with an IC50 of 0.81 μM and 0.84 μM, respectively, and efficiently inhibits histone H3 lysine 36 dimethylation and decreases the expression of NSDs-targeted genes in non-small cell lung cancer cells at 100 nM. Compound 3 suppresses cell proliferation and reduces the clonogenicity in H460 and H1299 non-small cell lung cancer cells, and induces s-phase cell cycle arrest and apoptosis. These data establish our compounds as a valuable tool-kit for the study of the biological roles of NSDs in cancer.

LC-MS/MS platform-based serum untargeted screening reveals the diagnostic biomarker panel and molecular mechanism of breast cancer

BACKGROUND

Breast cancer (BC), the most common form of malignant cancer affecting women worldwide, was characterized by heterogeneous metabolic disorder and lack of effective biomarkers for diagnosis. The purpose of this study is to search for reliable metabolite biomarkers of BC as well as triple-negative breast cancer (TNBC) using serum metabolomics approach.

METHODS

In this study, an untargeted metabolomics technique based on ultra-high performance liquid chromatography combined with mass spectrometry (UHPLC-MS) was utilized to investigate the differences in serum metabolic profile between the BC group (n = 53) and non-BC group (n = 57), as well as between TNBC patients (n = 23) and non-TNBC subjects (n = 30). The multivariate data analysis, determination of the fold change and the Mann-Whitney U test were used to screen out the differential metabolites. Additionally, machine learning methods including receiver operating curve analysis and logistic regression analysis were conducted to establish diagnostic biomarker panels.

RESULTS

There were 36 metabolites found to be significantly different between BC and non-BC groups, and 12 metabolites discovered to be significantly different between TNBC and non-TNBC patients. Results also showed that four metabolites, including N-acetyl-D-tryptophan, 2-arachidonoylglycerol, pipecolic acid and oxoglutaric acid, were considered as vital biomarkers for the diagnosis of BC and non-BC with an area under the curve (AUC) of 0.995. Another two-metabolite panel of N-acetyl-D-tryptophan and 2-arachidonoylglycerol was discovered to discriminate TNBC from non-TNBC and produced an AUC of 0.965.

CONCLUSION

This study demonstrated that serum metabolomics can be used to identify BC specifically and identified promising serum metabolic markers for TNBC diagnosis.

Inhibitory role of bone marrow mesenchymal stem cells-derived exosome in non-small-cell lung cancer: microRNA-30b-5p, EZH2 and PI3K/AKT pathway

Exosomal microRNA (miRNA) exerts potential roles in non-small-cell lung cancer (NSCLC). The current study elucidated the role of miR-30b-5p shuttled by bone marrow mesenchymal stem cells (BMSCs)-derived exosomes in treating NSCLC. Bioinformatics analysis was performed with NSCLC-related miRNA microarray GSE169587 and mRNA data GSE74706 obtained for collection of the differentially expressed miRNAs and mRNAs. The relationship between miR-30b-5p and EZH2 was predicted and confirmed. Exosomes were isolated from BMSCs and identified. BMSCs-derived exosomes overexpressing miR-30b-5p were used to establish subcutaneous tumorigenesis models to study the effects of miR-30b-5p, EZH2 and PI3K/AKT signalling pathway on tumour growth. A total of 86 BMSC-exo-miRNAs were differentially expressed in NSCLC. Bioinfomatics analysis found that BMSC-exo-miR-30b-5p could regulate NSCLC progression by targeting EZH2, which was verified by in vitro cell experiments. Besides, the target genes of miR-30b-5p were enriched in PI3K/AKT signalling pathway. Animal experiments validated that BMSC-exo-miR-30b-5p promoted NSCLC cell apoptosis and prevented tumorigenesis in nude mice via EZH2/PI3K/AKT axis. Collectively, the inhibitory role of BMSC-derived exosomes-loaded miR-30b-5p in NSCLC was achieved through blocking the EZH2/PI3K/AKT axis.

UHRF1 plays an oncogenic role in small cell lung cancer

Small cell lung cancer (SCLC) is a malignant tumor characterized by aggressiveness and dismal prognosis. The specific role of ubiquitin-like PHD and RING finger domain (UHRF1), a frequently overexpressed cancer-promoting gene in various tumors, is poorly understood in SCLC. Herein, we explored the potential carcinogenic role of UHRF1 in SCLC. First, public databases were used to analyze the expression of UHRF1 in SCLC, and tissue specimens in our center were examined to confirm the results while clinical outcomes were collected to analyze its relationship with UHRF1. Then, UHRF1 knockdown and overexpression cell lines were established to evaluate the carcinogenic function of UHRF1 in vitro and in vivo. The mechanism of the biological consequences was determined by co-inmunoprecipitation. Moreover, we also analyzed the influence of UHRF1 on cisplatin (DDP) sensitivity of SCLC. The expression of UHRF1 was significantly higher in SCLC tissues than in normal tissues, and high levels of UHRF1 suggested a poor prognosis for SCLC. Mechanistically, UHRF1 promoted SCLC growth through yes-associated protein 1 (YAP1). Specifically, UHRF1 bound to YAP1 and inhibited YAP1 ubiquitin degradation, thus stabilizing the YAP1 protein in SCLC cells. UHRF1 downregulation enhanced DDP sensitivity in SCLC cells and was correlated with a favorable prognosis in patients with SCLC treated with platinum-based chemotherapy. UHRF1 plays an oncogenic role in SCLC by modulating YAP1. Therefore, UHRF1 could be used as a biomarker to predict the prognosis of SCLC patients and serve as a potential therapeutic target for SCLC patients.

Epigenetic Alterations and Inflammation as Emerging Use for the Advancement of Treatment in Non-Small Cell Lung Cancer

Lung cancer remains one of the most common malignancies in the world. Nowadays, the most common lung cancer is non-small cell lung cancer (NSCLC), namely, adenocarcinoma, squamous cell carcinoma, and large cell lung carcinoma. Epigenetic alterations that refer to DNA methylation, histone modifications, and noncoding RNA expression, are now suggested to drive the genesis and development of NSCLC. Additionally, inflammation-related tumorigenesis also plays a vital role in cancer research and efforts have been attempted to reverse such condition. During the occurrence and development of inflammatory diseases, the immune component of inflammation may cause epigenetic changes, but it is not always certain whether the immune component itself or the stimulated host cells cause epigenetic changes. Moreover, the links between epigenetic alterations and cancer-related inflammation and their influences on the human cancer are not clear so far. Therefore, the connection between epigenetic drivers, inflammation, and NSCLC will be summarized. Investigation on such topic is most likely to shed light on the molecular and immunological mechanisms of epigenetic and inflammatory factors and promote the application of epigenetics in the innovative diagnostic and therapeutic strategies for NSCLC.

Development of a novel embryonic germline gene-related prognostic model of lung adenocarcinoma

Background

Emerging evidence implicates the correlation of embryonic germline genes with the tumor progress and patient's outcome. However, the prognostic value of these genes in lung adenocarcinoma (LUAD) has not been fully studied. Here we systematically evaluated this issue, and constructed a novel signature and a nomogram associated with embryonic germline genes for predicting the outcomes of lung adenocarcinoma.

Methods

The LUAD cohorts retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were used as training set and testing set, respectively. The embryonic germline genes were downloaded from the website https://venn.lodder.dev. Then, the differentially expressed embryonic germline genes (DEGGs) between the tumor and normal samples were identified by limma package. The functional enrichment and pathway analyses were also performed by clusterProfiler package. The prognostic model was constructed by the least absolute shrinkage and selection operator (LASSO)-Cox regression method. Survival and Receiver Operating Characteristic (ROC) analyses were performed to validate the model using training set and four testing GEO datasets. Finally, a prognostic nomogram based on the signature genes was constructed using multivariate regression method.

Results

Among the identified 269 DEGGs, 249 were up-regulated and 20 were down-regulated. GO and KEGG analyses revealed that these DEGGs were mainly enriched in the process of cell proliferation and DNA damage repair. Then, 103 DEGGs with prognostic value were identified by univariate Cox regression and further filtered by LASSO method. The resulting sixteen DEGGs were included in step multivariate Cox regression and an eleven embryonic germline gene related signature (EGRS) was constructed. The model could robustly stratify the LUAD patients into high-risk and low-risk groups in both training and testing sets, and low-risk patients had much better outcomes. The multi-ROC analysis also showed that the EGRS model had the best predictive efficacy compared with other common clinicopathological factors. The EGRS model also showed robust predictive ability in four independent external datasets, and the area under curve (AUC) was 0.726 (GSE30219), 0.764 (GSE50081), 0.657 (GSE37745) and 0.668 (GSE72094). More importantly, the expression level of some genes in EGRS has a significant correlation with the progression of LUAD clinicopathology, suggesting these genes might play an important role in the progression of LUAD. Finally, based on EGRS genes, we built and calibrated a nomogram for conveniently evaluating patients' outcomes.