Analysis of the Interaction Network of Hub miRNAs-Hub Genes, Being Involved in Idiopathic Pulmonary Fibers and Its Emerging Role in Non-small Cell Lung Cancer

Role and mechanism of COL3A1 in regulating the growth, metastasis, and drug sensitivity in cisplatin-resistant non-small cell lung cancer cells

Non-small cell lung cancer (NSCLC) is among the most difficult malignancies to treat. Type III collagen (COL3A1) can affect the progression and chemoresistance development of NSCLC. We herein explored the mechanism that drives COL3A1 dysregulation in NSCLC. Potential RNA-binding proteins (RBPs) and transcription factors (TFs) that could bind to COL3A1 were searched by bioinformatics. mRNA expression was detected by quantitative PCR. Protein expression was evaluated using immunoblotting and immunohistochemistry. The effects of the variables were assessed by gauging cell growth, invasiveness, migratory capacity, apoptosis, and cisplatin (DDP) sensitivity. The direct YY1/COL3A1 relationship was confirmed by ChIP and luciferase reporter experiments. Xenograft experiments were done to examine COL3A1's function in DDP efficacy. COL3A1 showed enhanced expression in DDP-resistant NSCLC. In H460/DDP and A549/DDP cells, downregulation of COL3A1 exerted inhibitory functions in cell growth, invasiveness, and migration, as well as promoting effects on cell DDP sensitivity and apoptosis. Mechanistically, ELAV-like RNA binding protein 1 (ELAVL1) enhanced the mRNA stability and expression of COL3A1, and Yin Yang 1 (YY1) promoted the transcription and expression of COL3A1. Furthermore, upregulation of COL3A1 reversed ELAVL1 inhibition- or YY1 deficiency-mediated functions in DDP-resistant NSCLC cells. Additionally, COL3A1 downregulation enhanced the anti-tumor efficacy of DDP in vivo. Our investigation demonstrates that COL3A1 upregulation, induced by both RBP ELAVL1 and TF YY1, exerts important functions in phenotypes of NSCLC cells with DDP resistance, offering an innovative opportunity in the treatment of drug-resistant NSCLC.

Systems Biology and Machine Learning Identify Genetic Overlaps Between Lung Cancer and Gastroesophageal Reflux Disease

One Health and planetary health place emphasis on the common molecular mechanisms that connect several complex human diseases as well as human and planetary ecosystem health. For example, not only lung cancer (LC) and gastroesophageal reflux disease (GERD) pose a significant burden on planetary health, but also the coexistence of GERD in patients with LC is often associated with a poor prognosis. This study reports on the genetic overlaps between these two conditions using systems biology-driven bioinformatics and machine learning-based algorithms. A total of nine hub genes including IGHV1-3, COL3A1, ITGA11, COL1A1, MS4A1, SPP1, MMP9, MMP7, and LOC102723407 were found to be significantly altered in both LC and GERD as compared with controls and with pathway analyses suggesting a significant association with the matrix remodeling pathway. The expression of these genes was validated in two additional datasets. Random forest and K-nearest neighbor, two machine learning-based algorithms, achieved accuracies of 89% and 85% for distinguishing LC and GERD, respectively, from controls using these hub genes. Additionally, potential drug targets were identified, with molecular docking confirming the binding affinity of doxycycline to matrix metalloproteinase 7 (binding affinity: -6.8 kcal/mol). The present study is the first of its kind that combines in silico and machine learning algorithms to identify the gene signatures that relate to both LC and GERD and promising drug candidates that warrant further research in relation to therapeutic innovation in LC and GERD. Finally, this study also suggests upstream regulators, including microRNAs and transcription factors, that can inform future mechanistic research on LC and GERD.

Suppression of OGN in lung myofibroblasts attenuates pulmonary fibrosis by inhibiting integrin αv-mediated TGF-β/Smad pathway activation

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) represents a severe and progressive manifestation of idiopathic interstitial pneumonia marked by an uncertain etiology along with an unfavorable prognosis. Osteoglycin (OGN), belonging to the small leucine-rich proteoglycans family, assumes pivotal functions in both tissue formation and damage response. However, the roles and potential mechanisms of OGN in the context of lung fibrosis remain unexplored.

METHODS

The assessment of OGN expression levels in fibrotic lungs was conducted across various experimental lung fibrosis mouse models. To elucidate the effects of OGN on the differentiation of lung myofibroblasts, both OGN knockdown and OGN overexpression were employed in vitro. The expression of integrin αv, along with its colocalization with lysosomes and latency-associated peptide (LAP), was monitored in OGN-knockdown lung myofibroblasts. Furthermore, the role of OGN in lung fibrosis was investigated through OGN knockdown utilizing adeno-related virus serotype 6 (AAV6)-mediated delivery.

RESULTS

OGN exhibited upregulation in both lungs and myofibroblasts across diverse lung fibrosis mouse models. And laboratory experiments in vitro demonstrated that OGN knockdown inhibited the TGF-β/Smad signaling pathway in lung myofibroblasts. Conversely, OGN overexpression promoted TGF-β/Smad pathway in these cells. Mechanistic insights revealed that OGN knockdown facilitated lysosome-mediated degradation of integrin αv while inhibiting its binding to latency-associated peptide (LAP). Remarkably, AAV6-targeted OGN knockdown ameliorated the extent of lung fibrosis in experimental mouse models.

CONCLUSION

Our results indicate that inhibiting OGN signaling could serve as a promising therapeutic way for lung fibrosis.

Pan-cancer analysis of COL15A1: an immunological and prognostic biomarker

Collagen, type XV, alpha 1 (COL15A1) belongs to the collagen superfamily, which can influence disease progression by modulating immune pathways. Although the growing number of investigations demonstrating the indispensable role of COL15A1 in the progression of certain tumors, no pan-cancer assessment of COL15A1 is accessible to date. Therefore, the available data was used to explore the role of COL15A1 in 33 types of tumors and to investigate their potential immune function. Numerous bioinformatics approaches were used to research the potential oncogenic role of COL15A1, including analysis of tumor prognosis, microsatellite instability (MSI), tumor mutational burden (TMB), single nucleotide polymorphism (SNP), drug sensitivity, immune cell infiltration, and the correlation between cancer stem cells (CSCs) and COL15A1 expression. The outcome implies that most tumors had a high expression of COL15A1, and COL15A1 manifested different relationships with prognosis in different tumors, including both positive and negative correlations. COL15A1 was also found to have a significant correlation with MSI, TMB, and immune infiltrating cells. Our study suggests that COL15A1 may serve as a prognostic marker for malignancy because of its differential expression in tissues and their function in tumor immunity.

The prognostic impact of pathogenic stromal cell-associated genes in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) stands as the most prevalent subtype among lung cancers. Interactions between stromal and cancer cells influence tumor growth, invasion, and metastasis. However, the regulatory mechanisms of stromal cells in the lung adenocarcinoma tumor microenvironment remain unclear. This study seeks to elucidate the regulatory connections among critical pathogenic genes and their associated expression variations within distinct stromal cell subtypes.

METHOD

Analysis and investigation were conducted on a total of 114,019 single-cell RNA data and 346 The Cancer Genome Atlas (TCGA) LUAD-related samples using bioinformatics and statistical algorithms. Differential gene expression analysis was performed for tumor samples and controls, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Differential genes between stromal cells and other cell clusters were identified and intersected with the differential genes from TCGA. We employed a combination of LASSO regression and multivariable Cox regression to identify the ultimate set of pathogenic gene. Survival models were trained to predict the relationship between patient survival and these pathogenic genes. Analysis of transcription factor (TF) cell specificity and pseudotime trajectories within stromal cell subpopulations revealed that vascular endothelial cells (ECs) and matrix cancer-associated fibroblasts (CAFs) are key in regulation of the prognosis-associated genes CAV2, COL1A1, TIMP1, ETS2, AKAP12, ID1 and COL1A2.

RESULTS

Seven pathogenic genes associated with LUAD in stromal cells were identified and used to develop a survival model. High expression of these genes is linked to a greater risk of poor survival. Stromal cells were categorized into eight subtypes and one unannotated cluster. Mesothelial cells, vascular endothelial cells (ECs), and matrix cancer-associated fibroblasts (CAFs) showed cell-specific regulation of the pathogenic genes.

CONCLUSIONS

The seven disease-causing genes in vascular ECs and matrix CAFs can be used to detect the survival status of LUAD patients, providing new directions for future targeted drug design.

MicroRNA (let-7b-5p)-targeted DARS2 regulates lung adenocarcinoma growth by PI3K/AKT signaling pathway

Background

The aberrant intracellular expression of a mitochondrial aspartyl-tRNA synthetase 2 (DARS2) has been reported in human cancers. Nevertheless, its critical role and detailed mechanism in lung adenocarcinoma (LUAD) remain unexplored.

Methods

Initially, The Cancer Genome Atlas (TCGA)-based Gene Expression Profiling Interactive Analysis (GEPIA) database (http://gepia.cancer-pku.cn/) was used to analyze the prognostic relevance of DARS2 expression in LUAD. Further, cell counting kit (CCK)-8, immunostaining, and transwell invasion assays in LUAD cell lines in vitro, as well as DARS2 silence on LUAD by tumorigenicity experiments in vivo in nude mice, were performed. Besides, we analyzed the expression levels of p-PI3K (phosphorylated-Phosphotylinosital3 kinase), PI3K, AKT (Protein Kinase B), p-AKT (phosphorylated-Protein Kinase B), PCNA (proliferating cell nuclear antigen), cleaved-caspase 3, E-cadherin, and N-cadherin proteins using the Western blot analysis.

Results

LUAD tissues showed higher DARS2 expression compared to normal tissues. Upregulation of DARS2 could be related to Tumor-Node-Metastasis (TNM) stage, high lymph node metastasis, and inferior prognosis. DARS2 silence decreased the proliferation, migration, and invasion abilities of LUAD cells. In addition, the DARS2 downregulation decreased the PCNA and N-cadherin expression and increased cleaved-caspase 3 and E-cadherin expressions in LUAD cells, coupled with the inactivation of the PI3K/AKT signaling pathway. Moreover, DARS2 silence impaired the tumorigenicity of LUAD in vivo. Interestingly, let-7b-5p could recognize DARS2 through a complementary sequence. Mechanistically, the increased let-7b-5p expression attenuated the promo-oncogenic action of DARS2 during LUAD progression, which were inversely correlated to each other in the LUAD tissues.

Conclusion

In summary, let-7b-5p downregulated DARS2 expression, regulating the progression of LUAD cells by the PI3K/AKT signaling pathway.

Prediction and analysis of genetic effect in idiopathic pulmonary fibrosis and gastroesophageal reflux disease

With increasing research on idiopathic pulmonary fibrosis (IPF) and gastroesophageal reflux disease (GERD), more and more studies have indicated that GERD is associated with IPF, but the underlying pathological mechanisms remain unclear. The aim of the present study is to identify and analyse the differentially expressed genes (DEGs) between IPF and GERD and explore the relevant molecular mechanisms via bioinformatics analysis. Four GEO datasets (GSE24206, GSE53845, GSE26886, and GSE39491) were downloaded from the GEO database, and DEGs between IPF and GERD were identified with the online tool GEO2R. Subsequently, a series of bioinformatics analyses are conducted, including Kyoto Encyclopaedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analyses, the PPI network, biological characteristics, TF-gene interactions, TF-miRNA coregulatory networks, and the prediction of drug molecules. Totally, 71 genes were identified as DEGs in IPF and GERD. Five KEGG pathways, including Amoebiasis, Protein digestion and absorption, Relaxin signalling pathway, AGE-RAGE signalling pathway in diabetic complications, and Drug metabolism - cytochrome P450, were significantly enriched. In addition, eight hub genes, including POSTN, MMP1, COL3A1, COL1A2, CXCL12, TIMP3, VCAM1, and COL1A1 were selected from the PPI network by Cytoscape software. Then, five hub genes (MMP1, POSTN, COL3A1, COL1A2, and COL1A1) with high diagnostic values for IPF and GERD were validated by GEO datasets. Finally, TF-gene and miRNA interaction was identified with hub genes and predicted drug molecules for the IPF and GERD. And the results suggest that cetirizine, luteolin, and pempidine may have great potential therapeutic value in IPF and GERD. This study will provide novel strategies for the identification of potential biomarkers and valuable therapeutic targets for IPF and GERD.

Logic-based modeling and drug repurposing for the prediction of novel therapeutic targets and combination regimens against E2F1-driven melanoma progression

Melanoma presents increasing prevalence and poor outcomes. Progression to aggressive stages is characterized by overexpression of the transcription factor E2F1 and activation of downstream prometastatic gene regulatory networks (GRNs). Appropriate therapeutic manipulation of the E2F1-governed GRNs holds the potential to prevent metastasis however, these networks entail complex feedback and feedforward regulatory motifs among various regulatory layers, which make it difficult to identify druggable components. To this end, computational approaches such as mathematical modeling and virtual screening are important tools to unveil the dynamics of these signaling networks and identify critical components that could be further explored as therapeutic targets. Herein, we integrated a well-established E2F1-mediated epithelial-mesenchymal transition (EMT) map with transcriptomics data from E2F1-expressing melanoma cells to reconstruct a core regulatory network underlying aggressive melanoma. Using logic-based in silico perturbation experiments of a core regulatory network, we identified that simultaneous perturbation of Protein kinase B (AKT1) and oncoprotein murine double minute 2 (MDM2) drastically reduces EMT in melanoma. Using the structures of the two protein signatures, virtual screening strategies were performed with the FDA-approved drug library. Furthermore, by combining drug repurposing and computer-aided drug design techniques, followed by molecular dynamics simulation analysis, we identified two potent drugs (Tadalafil and Finasteride) that can efficiently inhibit AKT1 and MDM2 proteins. We propose that these two drugs could be considered for the development of therapeutic strategies for the management of aggressive melanoma.

Plasma exosomal miR-1290 and miR-29c-3p as diagnostic biomarkers for lung cancer

Background

Enhancing the diagnostic efficacy of early-stage lung cancer is crucial for improving prognosis. The objective of this study was to ascertain dependable exosomal miRNAs as biomarkers for the diagnosis of lung cancer.

Methods

Exosomal miRNA candidates were identified through miRNA sequencing and subsequently validated in various case-control sets using real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR). The correlation between the expression of exosomal miRNAs and the clinicopathological features of lung cancer was investigated. To assess the diagnostic efficacy of exosomal miRNAs for lung cancer, the receiver operating characteristic (ROC) curve analysis was conducted. The optimal cutoff value of exosomal miRNAs was determined in the testing cohort and subsequently confirmed in the validation cohort.

Results

The results showed that the expression of exosomal miR-1290 was significantly elevated, while that of miR-29c-3p was significantly decreased in the plasma of lung cancer patients, especially in those with early-stage lung cancer, compared to individuals with benign lung conditions (P < 0.01). Exosomal miR-1290 and miR-29c-3p demonstrated superior diagnostic efficacy compared to conventional tumor biomarkers in distinguishing between lung cancer and benign lung diseases, as evidenced by their respective area under the curve (AUC) values of 0.934 and 0.868. Furthermore, exosomal miR-1290 and miR-29c-3p exhibited higher diagnostic efficiency in early-stage lung cancer than traditional tumor markers, with AUC values of 0.947 and 0.895, respectively. Notably, both exosomal miR-1290 and miR-29c-3p displayed substantial discriminatory capacity in distinguishing between non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), as indicated by their respective AUC values of 0.810 and 0.842.

Conclusions

The findings of this study provided evidence that exosomal miR-1290 and miR-29c-3p hold significant potential as biomarkers for the early detection of lung cancer, as well as for differentiating between NSCLC and SCLC.

Relationship between asporin and extracellular matrix behavior: A literature review

Asporin (ASPN), as a member of the small leucine-rich repeat proteoglycan family, is a type of protein that is found in the extracellular matrix. Collagen deposition or transformation is involved in a variety of pathological processes. ASPN is identified in cancerous tissue, pathological cardiac tissue, articular cartilage, keloid, and fibrotic lung tissue, and it has a role in the development of cancer, cardiovascular, bone and joint, keloid, and pulmonary fibrosis by interfering with collagen metabolism. This review article summarizes the data on ASPN expressions in mouse and human and highlights that overexpress of ASPN might play a role in a variety of diseases. Although our knowledge of ASPN is currently limited, these instances may help us better understand how it interacts with diseases.

Exosomal microRNAs Targeting TP53 Gene as Promising Prognostic Markers for Head and Neck Squamous Cell Carcinoma

Statement of Problem  MicroRNAs are small non-coding RNAs that regulate an array of functions by targeting crucial genes. A significant dysregulation in the TP53 profile has been observed in the head and neck squamous cell carcinoma (HNSCC) patients. Hence, the present in silico study was designed to identify those microRNAs which target TP53 gene and demonstrate their differential expression in HNSCC cases. Materials and Methods  The study was extended further to explore their exosomal location using database such as EVmiRNA and ExoCarta. The study follows an observational in silico design. Computational tool miRDB was used identify the microRNA targets of TP53 gene. The UALCAN server was used to ascertain the expression of microRNA in HNSCC cases derived from the Cancer Gene Atlas dataset. The survival of HNSCC patients based on the differential expression microRNA markers were recorded. Further, each of the microRNA was queried for their exosomal presence using EVmiRNA. Results  About 102 microRNA targets of TP53 gene with a target score in the range of 95-50 were identified. The differential expression data for 52 microRNAs was retrieved from the UALCAN database. The microRNAs hsa-miR-421, hsa-miR-548f-5p, and hsa-let-7c-5p were found to be differentially expressed with marked influence over the survival of HNSCC patients. Furthermore, hsa-miR-421 and hsa-let-7c-5p were found to have an exosomal origin especially in body fluids such as blood and saliva. Conclusion  The results accumulated from the present study identified three microRNAs which can affect the functions of TP53 gene and bring about serious outcomes in HNSCC patients. The microRNAs of exosomal origin targeting TP53 gene in HNSCC patients can be a promising prognostic marker, which can be further used as a therapeutic lead by designing inhibitors.

Integrated analysis to identify the AC005154.6/hsa-miR-29c-3p/CCNL2 axis as a novel prognostic biomarker associated with immune infiltration in prostate cancer

Background

Prostate cancer (PCa) is currently the major malignancy in men. It is becoming increasingly clear that competitive endogenous RNA (ceRNA) regulation networks are important in a wide variety of cancers. Nevertheless, there is still much to learn about the biological functions of the ceRNA network in prostate cancer.

Methods

The ceRNA network was constructed using the "GDCRNATools" package. Based on survival analysis, we obtained AC005154.6/hsa-miR-29c-3p/CCNL2 for further analysis. The prognostic model based on this ceRNA network was constructed by univariate and multivariate Cox regression methods. Furthermore, functional enrichment analysis, mutation landscape analysis, immune infiltration analysis, drug sensitivity analysis, methylation analysis, pan-cancer analysis, and molecular experiments of CCNL2 were carried out to investigate the role of CCNL2 in tumorigenesis.

Results

We identified the AC005154.6/CCNL2 axis as a risk factor that can promote the progression of prostate cancer by bioinformatics analysis and molecular experiments. Immune infiltration analysis suggested that CCNL2 may act as a novel biomarker for treatment decisions. The methylation level of CCNL2 was significantly decreased in tumor samples, possibly contributing to the upregulation of CCNL2 in prostate cancer. Moreover, CCNL2 is differentially expressed in multiple cancers and is tightly correlated with immune infiltration.

Conclusion

The current study constructed a ceRNA network, AC005154.6/hsa-miR-29c-3p/CCNL2. Potentially, this biomarker can be used for early diagnosis and decision-making about prostate cancer treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02779-5.

Integrating Expression Data-Based Deep Neural Network Models with Biological Networks to Identify Regulatory Modules for Lung Adenocarcinoma

Simple Summary

The growing evidence suggested that competing endogenous RNAs (ceRNAs) have significant associations with tumor occurrence and progression, yet the regulatory mechanism of them in lung adenocarcinoma remains unclear. Identification of the regulatory modules for lung adenocarcinoma is a critical and fundamental step towards understanding the regulatory mechanisms during carcinogenesis. Deep neural network (DNN) models have become a powerful tool to intelligently recognize the sophisticated relationships of ceRNAs appropriately. In this paper, multiple deep neural network models were constructed using the expression data to identify regulatory modules for lung adenocarcinoma in biological networks. Three identified regulatory modules association with lung adenocarcinoma were validated from three aspects, i.e., literature review, functional enrichment analysis, and an independent dataset. The regulatory relationships between RNAs were validated in various datasets, including CPTAC, TCGA and an expression profile from the GEO database. Our study will contribute to improving the understanding of regulatory mechanisms in the carcinogenesis of lung adenocarcinoma and provide schemes for identifying novel regulatory modules of other cancers.

Abstract

Lung adenocarcinoma is the most common type of primary lung cancer, but the regulatory mechanisms during carcinogenesis remain unclear. The identification of regulatory modules for lung adenocarcinoma has become one of the hotspots of bioinformatics. In this paper, multiple deep neural network (DNN) models were constructed using the expression data to identify regulatory modules for lung adenocarcinoma in biological networks. First, the mRNAs, lncRNAs and miRNAs with significant differences in the expression levels between tumor and non-tumor tissues were obtained. MRNA DNN models were established and optimized to mine candidate mRNAs that significantly contributed to the DNN models and were in the center of an interaction network. Another DNN model was then constructed and potential ceRNAs were screened out based on the contribution of each RNA to the model. Finally, three modules comprised of miRNAs and their regulated mRNAs and lncRNAs with the same regulation direction were identified as regulatory modules that regulated the initiation of lung adenocarcinoma through ceRNAs relationships. They were validated by literature and functional enrichment analysis. The effectiveness of these regulatory modules was evaluated in an independent lung adenocarcinoma dataset. Regulatory modules for lung adenocarcinoma identified in this study provided a reference for regulatory mechanisms during carcinogenesis.

MiRNA-144-5p down-modulates CDCA3 to regulate proliferation and apoptosis of lung adenocarcinoma cells

BACKGROUND

Lung adenocarcinoma (LUAD) belongs to non-small cell lung cancer. In addition to surgical resection, chemotherapy and radiotherapy cause great side effects and low 5-year survival rates. MiRNAs are closely related to cancer development. This study aimed to analyze the molecular mechanism of miRNA-144-5p targeting CDCA3 to inhibit LUAD proliferation.

METHODS

MiRNA and mRNA data were downloaded from TCGA-LUAD dataset for differential expression analysis. TargetScan and miRTarBase databases were adopted to predict the target genes of miRNA, and the signaling pathways involved were analyzed by gene set enrichment analysis. The functions of LUAD cells were analyzed by CCK-8, colony formation assay, stem cell spheroidization assay, and flow cytometry. The expression levels of CDCA3, p53, and cell cycle-associated proteins were evaluated by Western blot.

RESULTS

The expression of miRNA-144-5p was significantly down-regulated in LUAD, but overexpression of it repressed proliferation and spheroidization, and promoted apoptosis of LUAD cells. By bioinformatics prediction and dual-luciferase reporter assay, miRNA-144-5p was validated to target CDCA3, thereby regulating proliferation of LUAD cells. Besides, the results of cell experiments showed that miRNA-144-5p targeting CDCA3 affected cell proliferation and apoptosis in LUAD by regulating cell cycles, and miRNA-144-5p/CDCA3 mediated the p53 signaling pathway to affect the growth of LUAD cells.

SIGNIFICANCE

Through the study of the pathogenesis of miRNA-144-5p regulating LUAD, we can better understand the molecular mechanism underlying LUAD development.

Identification of Hub Genes in Idiopathic Pulmonary Fibrosis and NSCLC Progression:Evidence From Bioinformatics Analysis

Background: Lung cancer is the most common comorbidity of idiopathic pulmonary fibrosis. Thus there is an urgent need for the research of IPF and carcinogenesis

Objective: The objective of this study was to explore hub genes which are common in pulmonary fibrosis and lung cancer progression through bioinformatic analysis.

Methods: All the analysis was performed in R software. Differentially expressed genes (DEGs) were explored by comparing gene expression profiles between IPF tissues and healthy lung tissues from GSE24206, GSE53845, GSE101286 and GSE110147 datasets. Venn Diagram analysis was used to identify the overlapping genes, while GO and KEGG pathway enrichment analysis were used to explore the biological functions of the DEGs using clusterprofiler package. Hub genes were identified by analyzing protein-protein interaction networks using Cytoscape software. Nomogram was constructed using the rms package. Tumor immune dysfunction and exclusion (TIDE) and Genomics of Drug Sensitivity in Cancer (GDSC) analysis was used to quantify the immunotherapy and chemotherapy sensitivity of non-small cell lung cancer (NSCLC) patients.

Results:COL1A1, COL3A1, MMP1, POSTN1 and TIMP3 were identified as the top five hub genes. The five hub genes were used to construct a diagnostic nomogram that was validated in another IPF dataset. Since the hub genes were also associated with lung cancer progression, we found that the nomogram also had diagnostic value in NSCLC patients. These five genes achieved a statistically difference of overall survival in NSCLC patients (p < 0.05). The expression of the five hub genes was mostly enriched in fibroblasts. Fibroblasts and the hub genes also showed significant ability to predict the susceptibility of NSCLC patients to chemotherapy and immunotherapy.

Conclusion: We identified five hub genes as potential biomarkers of IPF and NSCLC progression. This finding may give insight into the underlying molecular mechanisms of IPF and lung cancer progression and provides potential targets for developing new therapeutic agents for IPF patients.

Long Non-coding RNA HOXA11-AS Facilitates Proliferation of Lung Adenocarcinoma Cells via Targeting the Let-7c-5p/IGF2BP1 Axis

Objective: This study investigates the relationship between the HOXA11-AS/let-7c-5p/IGF2BP1 regulatory axis and lung adenocarcinoma.

Methods: The expression levels of HOXA11-AS, let-7c-5p, and IGF2BP1 were evaluated in LUAD tissue and cell lines. Subcellular fractionation detection assay was adopted to verify the HOXA11-AS distribution in LUAD cells. The interaction relationship between let-7c-5p and HOXA11-AS or IGF2BP1 was validated by dual-luciferase reporter detection. In RNA binding protein immunoprecipitation assay, the binding relationship between HOXA11-AS and let-7c-5p was identified. The cell viability of transfected cells was tested by the Cell Counting Kit-8 assay. The mouse xenograft model was used to identify the effect of HOXA11-AS on tumor growth in vivo.

Results: Upregulation of lncRNA HOXA11-AS was found in LUAD, and suppression of HOXA11-AS could suppress the proliferative ability of LUAD cells. The let-7c-5p was expressed to be downregulated, which played an inhibitory role in LUAD cell proliferation. Let-7c-5p was negatively regulated by HOXA11-AS. HOXA11-AS promoted LUAD cell proliferation, while let-7c-5p had an inverse effect. Besides, IGF2BP1, regulated by let-7c-5p, had a positive relation with HOXA11-AS, while overexpression of IGF2BP1 could suppress the inhibition of silencing HOXA11-AS on LUAD cell proliferation. Experiments on mice confirmed that HOXA11-AS facilitated LUAD cell growth in vivo through regulating the let-7c-5p/IGF2BP1 axis.

Conclusion: HOXA11-AS promoted LUAD cell proliferation by targeting let-7c-5p/IGF2BP1, which could be potential molecular targets for LUAD.

Radix ranunculus temate saponins sensitizes ovarian cancer to Taxol via upregulation of miR‑let‑7b

A common cause of treatment failure in ovarian cancer is acquired drug resistance. Therefore, effective novel drugs against chemoresistance need to be developed. MicroRNAs (miRNAs or miRs) serve key regulatory roles in tumorigenesis and chemoresistance. The objective of the present study was to explore the role of miR-let-7b in ovarian cancer chemoresistance, and to develop novel strategy for the treatment of drug-resistant ovarian cancer. For this purpose, reverse transcription-quantitative PCR was performed to evaluate the expression level of miR-let-7b in fresh ovarian cancer tissues and cell lines. miR-let-7b mimic was transfected into ovarian cancer cell lines. Functional experiments, cell apoptosis and cell viability assays were carried out to identify the tumor-suppressor function of miR-let-7b. The treatment effect of Radix ranunculus temate saponins (RRTS), one of the primary constituents extracted from the traditional Chinese medicine radix Ranunculi ternati, was identified in vitro and in vivo. The results revealed that miR-let-7b was downregulated significantly in chemoresistant ovarian cancer patients. miR-let-7b overexpression suppressed cell growth and invasion and enhanced sensitivity to Taxol of ovarian cancer cells. Furthermore, miR-let-7b levels in ovarian cancer tissue were inversely associated with collagen type III α1 chain (COL3A1) levels. COL3A1, a non-fibrillar collagen associated with chemoresistance, was targeted by miR-let-7b. RRTS showed cytotoxic effects on ovarian cancer cells through inducing miR-let-7b expression and decreasing COL3A1 expression. In addition, RRTS sensitized ovarian cancer to Taxol both in vitro and in vivo. In conclusion, the present results revealed synergistic cytotoxicity of RRTS and Taxol on against ovarian cancer cells via upregulating expression of miR-let-7b. Combination of Taxol and RRTS may be a novel treatment strategy for patients with TR ovarian cancer.

Bioinformatics approach to identify common gene signatures of patients with coronavirus 2019 and lung adenocarcinoma

Coronavirus disease 2019 (COVID-19) continues as a global pandemic. Patients with lung cancer infected with COVID-19 may develop severe disease or die. Treating such patients severely burdens overwhelmed healthcare systems. Here, we identified potential pathological mechanisms shared between patients with COVID-19 and lung adenocarcinoma (LUAD). Co-expressed, differentially expressed genes (DEGs) in patients with COVID-19 and LUAD were identified and used to construct a protein-protein interaction (PPI) network and to perform enrichment analysis. We used the NetworkAnalyst platform to establish a co-regulatory of the co-expressed DEGs, and we used Spearman's correlation to evaluate the significance of associations of hub genes with immune infiltration and immune checkpoints. Analysis of three datasets identified 112 shared DEGs, which were used to construct a protein-PPI network. Subsequent enrichment analysis revealed co-expressed genes related to biological process (BP), molecular function (MF), and cellular component (CC) as well as to pathways, specific organs, cells, and diseases. Ten co-expressed hub genes were employed to construct a gene-miRNA, transcription factor (TF)-gene, and TF-miRNA network. Hub genes were significantly associated with immune infiltration and immune checkpoints. Finally, methylation level of hub genes in LUAD was obtained via UALCAN database. The present multi-dimensional study reveals commonality in specific gene expression by patients with COVID-19 and LUAD. These findings provide insights into developing strategies for optimising the management and treatment of patients with LUAD with COVID-19.

The Regulation of let-7c-5p on the Biological Characteristics of Lung Adenocarcinoma Cells by Targeting AURKB

To study the modulatory mechanism of let-7c-5p on the biological characteristics of lung adenocarcinoma (LUAD) cells by targeting AURKB. Differentially expressed genes (DEGs) were screened by bioinformatics analysis. CCK-8, colony formation, scratch healing, Transwell, and flow cytometry assays were employed to test biological functions of LUAD cells. Western Blot was undertaken to assay the protein level of AURKB, and qRT-PCR was undertaken to test AURKB mRNA and let-7c-5p expression. Dual-luciferase reporter gene method was applied to detect the interaction between AURKB and let-7c-5p. Let-7c-5p was much likely to target AURKB expression. Let-7c-5p was poorly expressed in LUAD cells and suppressed AURKB. Silencing AURKB or overexpressing let-7c-5p both could suppress proliferation, migration, and invasion and stimulate apoptosis, while overexpressing the two simultaneously could reverse such effect. Forced expression of let-7c-5p inhibited proliferation, migration, and invasion and accelerated apoptosis of LUAD cells by inhibiting AURKB, which may provide a new way to understand the malignant progression of LUAD.

An 11-Gene Signature Risk-Prediction Model Based on Prognosis-Related miRNAs and Their Target Genes in Lung Adenocarcinoma

Aberrant expression of microRNAs may affect tumorigenesis and progression by regulating their target genes. This study aimed to construct a risk model for predicting the prognosis of patients with lung adenocarcinoma (LUAD) based on differentially expressed microRNA-regulated target genes. The miRNA sequencing data, RNA sequencing data, and patients’ LUAD clinical data were downloaded from the The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs and genes were screened out by combining differential analysis with LASSO regression analysis to further screen out miRNAs associated with patients’ prognosis, and target gene prediction was performed for these miRNAs using a target gene database. Overlapping gene screening was performed for target genes and differentially expressed genes. LASSO regression analysis and survival analysis were then used to identify key genes. Risk score equations for prognostic models were established using multifactorial COX regression analysis to construct survival prognostic models, and the accuracy of the models was evaluated using subject working characteristic curves. The groups were divided into high- and low-risk groups according to the median risk score, and the correlation with the clinicopathological characteristics of the patients was observed. A total of 123 up-regulated miRNAs and 22 down-regulated miRNAs were obtained in this study. Five prognosis-related miRNAs were screened using LASSO regression analysis and Kaplan-Meier method validation, and their target genes were screened with the overlap of differentially expressed genes before multifactorial COX analysis finally resulted in an 11-gene risk model for predicting patient prognosis. The area under the ROC curve proved that the model has high accuracy. The 11-gene risk-prediction model constructed in this study may be an effective predictor of prognosis.

Cell Behavior of Non-Small Cell Lung Cancer Is at EGFR and MicroRNAs Hands

Lung cancer is a complex disease associated with gene mutations, particularly mutations of Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS) and epidermal growth factor receptor (EGFR). Non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) are the two major types of lung cancer. The former includes most lung cancers (85%) and are commonly associated with EGFR mutations. Several EGFR-tyrosine kinase inhibitors (EGFR-TKIs), including erlotinib, gefitinib, and osimertinib, are effective therapeutic agents in EGFR-mutated NSCLC. However, their effectiveness is limited by the development (acquired) or presence of intrinsic drug resistance. MicroRNAs (miRNAs) are key gene regulators that play a profound role in the development and outcomes for NSCLC via their role as oncogenes or oncosuppressors. The regulatory role of miRNA-dependent EGFR crosstalk depends on EGFR signaling pathway, including Rat Sarcoma/Rapidly Accelerated Fibrosarcoma/Mitogen-Activated Protein Kinase/Extracellular Signal-Regulated Kinase 1/2 (Ras/Raf/MEK/ERK1/2), Signal Transducer and Activator of Transcription (STAT), Nuclear Factor Kappa-Light-Chain-Enhancer of Activated B Cells (NF-kB), phosphoinositide 3-kinase/protein kinase B (PI3K/AKT), Janus kinase 1 (JAK1), and growth factor receptor-bound protein 2 (GRB2). Dysregulated expression of miRNAs affects sensitivity to treatment with EGFR-TKIs. Thus, abnormalities in miRNA-dependent EGFR crosstalk can be used as diagnostic and prognostic markers, as well as therapeutic targets in NSCLC. In this review, we present an overview of miRNA-dependent EGFR expression regulation, which modulates the behavior and progression of NSCLC.

Silencing lncRNA GAS5 alleviates apoptosis and fibrosis in diabetic cardiomyopathy by targeting miR-26a/b-5p

BACKGROUND

LncRNA GAS5 is associated with high glucose-induced cardiomyocyte injury, but its role in diabetic cardiomyopathy (DCM) remains unclear.

METHODS

Mice were administered with streptozotocin to construct the diabetic model (DM). Primary mouse cardiomyocytes were isolated and treated with 30 mmol/L high glucose to mimic the diabetic condition in vitro. GAS5 expression was detected by quantitative reverse transcription polymerase chain reaction. The relationship between GAS5 and miR-26a/b-5p was determined by bioinformatic prediction, luciferase reporter assay and RNA immunoprecipitation assay. The cardiac function of diabetic mice was evaluated by two-dimensional echocardiography.

RESULTS

GAS5 was significantly upregulated in diabetic cardiomyopathy both in vitro and in vivo. GAS5 knockdown and miR-26a/b-5p overexpression not only effectively attenuated myocardial fibrosis of diabetic mice in vivo but also inhibited high glucose-induced cardiomyocyte injury in vitro. miR-26a/b-5p was identified as a target of GAS5. GAS5 knockdown efficiently attenuated myocardial fibrosis and high glucose-induced cardiomyocyte injury through negatively regulating miR-26a/b-p.

CONCLUSION

Our study showed that GAS5 promotes DCM progression by regulating miR-26a/b-5p, suggesting that GAS5 might be a potential therapeutic target for DCM.

Identification of Hub Genes and Pathways Associated With Idiopathic Pulmonary Fibrosis via Bioinformatics Analysis

Idiopathic pulmonary fibrosis (IPF) is a progressive disease whose etiology remains unknown. The purpose of this study was to explore hub genes and pathways related to IPF development and prognosis. Multiple gene expression datasets were downloaded from the Gene Expression Omnibus database. Weighted correlation network analysis (WGCNA) was performed and differentially expressed genes (DEGs) identified to investigate Hub modules and genes correlated with IPF. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interaction (PPI) network analysis were performed on selected key genes. In the PPI network and cytoHubba plugin, 11 hub genes were identified, including ASPN, CDH2, COL1A1, COL1A2, COL3A1, COL14A1, CTSK, MMP1, MMP7, POSTN, and SPP1. Correlation between hub genes was displayed and validated. Expression levels of hub genes were verified using quantitative real-time PCR (qRT-PCR). Dysregulated expression of these genes and their crosstalk might impact the development of IPF through modulating IPF-related biological processes and signaling pathways. Among these genes, expression levels of COL1A1, COL3A1, CTSK, MMP1, MMP7, POSTN, and SPP1 were positively correlated with IPF prognosis. The present study provides further insights into individualized treatment and prognosis for IPF.

Evaluation of the severity of nonalcoholic fatty liver disease through analysis of serum exosomal miRNA expression

Noninvasive techniques for evaluating the severity of nonalcoholic fatty liver disease (NAFLD) have shown limited diagnostic performance. MicroRNAs (miRNAs) are useful biomarkers for diagnosing and monitoring the progression and treatment response to several diseases. Here, we evaluated whether serum exosomal miRNAs could be used for the diagnosis and prognosis of NAFLD severity. Exosomal miRNAs were isolated from the sera of 41 patients with NAFLD (diagnosed using liver biopsy) for microarray profiling. The degree of NAFLD severity was determined using inflammation, steatosis, and ballooning scores and the NAFLD activity score (NAS). Correlations between miRNA expression, clinical and biochemical parameters, and mRNA expression were analyzed. Overall, 25, 11, 13, and 14 miRNAs correlated with the inflammation score, steatosis score, ballooning score, and NAS, respectively, with 33 significant correlations observed between 27 miRNAs and six clinical variables. Eight miRNAs (let-7b-5p, miR-378h, -1184, -3613-3p, -877-5p, -602, -133b, and 509-3p) showed anticorrelated patterns with the corresponding mRNA expression. In fibrosis, 52 and 30 interactions corresponding to high miRNA-low mRNA and low miRNA-high mRNA expression, respectively, were observed. The present results therefore suggest that serum exosomal miRNAs can be used to evaluate NAFLD severity and identify potential targets for NAFLD treatment.

Identification and Validation of Potential Biomarkers and Pathways for Idiopathic Pulmonary Fibrosis by Comprehensive Bioinformatics Analysis

Objective

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, irreversible, high-mortality lung disease, but its pathogenesis is still unclear. Our purpose was to explore potential genes and molecular mechanisms underlying IPF.

Methods

IPF-related data were obtained from the GSE99621 dataset. Differentially expressed genes (DEGs) were identified between IPF and controls. Their biological functions were analyzed. The relationships between DEGs and microRNAs (miRNAs) were predicted. DEGs and pathways were validated in a microarray dataset. A protein-protein interaction (PPI) network was constructed based on these common DEGs. Western blot was used to validate hub genes in IPF cell models by western blot.

Results

DEGs were identified for IPF than controls in the RNA-seq dataset. Functional enrichment analysis showed that these DEGs were mainly enriched in immune and inflammatory response, chemokine-mediated signaling pathway, cell adhesion, and other biological processes. In the miRNA-target network based on RNA-seq dataset, we found several miRNA targets among all DEGs, like RAB11FIP1, TGFBR3, and SPP1. We identified 304 upregulated genes and 282 downregulated genes in IPF compared to controls both in the microarray and RNA-seq datasets. These common DEGs were mainly involved in cell adhesion, extracellular matrix organization, oxidation-reduction process, and lung vasculature development. In the PPI network, 3 upregulated and 4 downregulated genes could be considered hub genes, which were confirmed in the IPF cell models.

Conclusion

Our study identified several IPF-related DEGs that could become potential biomarkers for IPF. Large-scale multicentric studies are eagerly needed to confirm the utility of these biomarkers.

Integrated analysis of the molecular mechanisms in idiopathic pulmonary fibrosis

Rationale: Idiopathic pulmonary fibrosis (IPF) is one of the most aggressive forms of idiopathic interstitial pneumonia. Some miRNAs may be associated with IPF and may affect the occurrence and development of IPF in various pathways. Many miRNAs and genes that may be involved in the development of IPF have been discovered using chip and high throughput technologies. Methods: We analyzed one miRNA and four mRNA databases. We identified hub genes and pathways related to IPF using GO, KEGG enrichment analysis, gene set variation analysis (GSVA), PPI network construction, and hub gene analysis. A comprehensive analysis of differentially expressed miRNAs (DEMs), predicted miRNA target genes, and differentially expressed genes (DEGs) led to the creation of a miRNA-mRNA regulatory network in IPF. Results: We found 203 DEGs and 165 DEMs that were associated with IPF. The findings of enrichment analyses showed that these DEGs were mainly involved in antimicrobial humoral response, antimicrobial humoral immune response mediated by antimicrobial peptide, extracellular matrix organization, cell killing, and organ or tissue specific immune response. The VEGFA, CDH5, and WNT3A genes overlapped between hub genes and the miRNA-mRNA regulatory network. The miRNAs including miR-199b-5p, miR-140-5p, miR-199a-5p, miR-125A-5p, and miR-107 that we predicted would regulate the VEGFA, CDH5, and WNT3A genes, which were also associated with IPF or other fibrosis-related diseases. GSVA indicated that metabolic processes of UTP and IMP, immune response, regulation of Th2 cell cytokine production, and positive regulation of NK cell-mediated immunity are associated with the pathogenesis and treatment of IPF. These pathways also interact with VEGFA, CDH5, and WNT3A. Conclusion: These findings provide a new research direction for the diagnosis and treatment of IPF.