Analysis of lncRNA-mRNA networks after MEK1/2 inhibition based on WGCNA in pancreatic ductal adenocarcinoma

Weighted gene co-expression network indicates that the DYNLL2 is an important regulator of chicken breast muscle development and is regulated by miR-148a-3p

Background

The characteristics of muscle fibers determine the growth and meat quality of poultry. In this study, we performed a weighted gene co-expression network analysis (WGCNA) on the muscle fiber characteristics and transcriptome profile of the breast muscle tissue of Gushi chicken at 6, 14, 22, and 30 weeks.

Results

A total of 27 coexpressed biological functional modules were identified, of which the midnight blue module had the strongest correlation with muscle fiber and diameter. In addition, 7 hub genes were found from the midnight blue module, including LC8 dynein light chain 2 (DYNLL2). Combined with miRNA transcriptome data, miR-148a-3p was found to be a potential target miRNA of DYNLL2. Experiments on chicken primary myoblasts (CPMs) demonstrated that miR-148a-3p promotes the expression of myosin heavy chain (MYHC) protein by targeting DYNLL2, proving that it can promote differentiation of myoblasts.

Conclusions

This study proved that the hub gene DYNLL2 and its target miR-148-3p are important regulators in chicken myogenesis. These results provide novel insights for understanding the molecular regulation mechanisms related to the development of chicken breast muscle.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08522-8.

Revealing the Role of lncRNA CCDC144NL-AS1 and LINC01614 in Gastric Cancer via Integrative Bioinformatics Analysis and Experimental Validation

Long non-coding RNAs (lncRNAs) are key regulators in the pathophysiology of gastric cancer, and lncRNAs have been regarded as potential biomarkers and therapeutic targets for gastric cancer. The present study performed the WGCNA analysis of the GSE70880 dataset and aimed to identify novel lncRNAs associated with gastric cancer progression. Based on the WGCNA, the lncRNAs and mRNA co-expression network were constructed. A total of four modules were identified and the eigengenes in different modules were involved in various key signaling pathways. Furthermore, the co-expression networks were constructed between the lncRNAs and mRNA; this leads to the identification of 6 modules, which participated in various cellular pathways. The survival analysis showed that high expression of CCDC144NL antisense RNA 1 (CCDC144NL-AS1) and LINC01614 was positively correlated with the poor prognosis of patients with gastric cancer. The in vitro validation results showed that CCDC144NL-AS1 and LINC01614 were both up-regulated in the gastric cancer cells. Silence of CCDC144NL-AS1 and LINC01614 both significantly suppressed the cell proliferation and migration of gastric cancer cells, and also promoted the chemosensitivity of gastric cancer cells to 5-fluorouracil. Collectively, our results suggested that the newly identified two lncRNAs (CCDC144NL-AS1 and LINC01614) may act as oncogenes in gastric cancer.

High-Throughput In Vitro Gene Expression Profile to Screen of Natural Herbals for Breast Cancer Treatment

Breast cancer has surpassed lung cancer as the most commonly diagnosed cancer in women worldwide. Some therapeutic drugs and approaches could cause side effects and weaken the immune system. The combination of conventional therapies and traditional Chinese medicine (TCM) significantly improves treatment efficacy in breast cancer. However, the chemical composition and underlying anti-tumor mechanisms of TCM still need to be investigated. The primary aim of this study is to provide unique insights to screen the natural components for breast cancer therapy using high-throughput transcriptome analysis. Differentially expressed genes were identified based on two conditions: single samples and groups were classified according to their pharmaceutical effect. Subsequently, the sample treated with E. cochinchinensis Lour. generated the most significant DEGs set, including 1,459 DEGs, 805 upregulated and 654 downregulated. Similarly, group 3 treatment contained the most DEGs (414 DEGs, 311 upregulated and 103 downregulated). KEGG pathway analyses showed five significant pathways associated with the inflammatory and metastasis processes in cancer, which include the TNF, IL−17, NF-kappa B, MAPK signaling pathways, and transcriptional misregulation in cancer. Samples were classified into 13 groups based on their pharmaceutical effects. The results of the KEGG pathway analyses remained consistent with signal samples; group 3 presents a high significance. A total of 21 genes were significantly regulated in these five pathways, interestingly, IL6, TNFAIP3, and BRIC3 were enriched on at least two pathways, seven genes (FOSL1, S100A9, CXCL12, ID2, PRS6KA3, AREG, and DUSP6) have been reported as the target biomarkers and even the diagnostic tools in cancer therapy. In addition, weighted correlation network analysis (WGCNA) was used to identify 18 modules. Among them, blue and thistle2 were the most relevant modules. A total of 26 hub genes in blue and thistle2 modules were identified as the hub genes. In conclusion, we screened out three new TCM (R. communis L., E. cochinchinensis Lour., and B. fruticosa) that have the potential to develop natural drugs for breast cancer therapy, and obtained the therapeutic targets.

High-Throughput Screen of Natural Compounds and Biomarkers for NSCLC Treatment by Differential Expression and Weighted Gene Coexpression Network Analysis (WGCNA)

Lung cancer is known as the leading cause which presents the highest fatality rate worldwide; non-small-cell lung cancer (NSCLC) is the most prevalent type of lung carcinoma with high severity and affects 80% of patients with lung malignancies. Up to now, the general treatment for NSCLC includes surgery, chemotherapy, and radiotherapy; however, some therapeutic drugs and approaches could cause side effects and weaken the immune system. The combination of conventional therapies and traditional Chinese medicine (TCM) significantly improves treatment efficacy in lung cancer. Therefore, it is necessary to investigate the chemical composition and underlying antitumor mechanisms of TCM, so as to get a better understanding of the potential natural ingredient for lung cancer treatment. In this study, we selected 78 TCM to treat NSCLC cell line (A549) and obtained 92 transcriptome data; differential expression and WGCNA were applied to screen the potential natural ingredient and target genes. The sample which was treated with A. pierreana generated the most significant DEG set, including 6130 DEGs, 2479 upregulated, and 3651 downregulated. KEGG pathway analyses found that four pathways (MAPK, NF-kappa B, p53, and TGF-beta signaling pathway) were significantly enriched; 16 genes were significantly regulated in these four pathways. Interestingly, some of them such as EGFR, DUSP4, IL1R1, IL1B, MDM2, CDKNIA, and IDs have been used as the target biomarkers for cancer diagnosis and therapy. In addition, classified samples into 14 groups based on their pharmaceutical effects, WGCNA was used to identify 27 modules. Among them, green and darkgrey were the most relevant modules. Eight genes in the green module and four in darkgrey were identified as hub genes. In conclusion, we screened out three new TCM (B. fruticose, A. pierreana, and S. scandens) that have the potential to develop natural anticancer drugs and obtained the therapeutic targets for NSCLC therapy. Our study provides unique insights to screen the natural components for NSCLC therapy using high-throughput transcriptome analysis.

NEAT1/miR-101-dependent Up-regulation of DNA-PKcs Enhances Malignant Behaviors of Pancreatic Ductal Adenocarcinoma Cells

Background: Although we previously revealed that DNA-dependent protein kinase catalytic subunit (DNA-PKcs) is overexpressed in pancreatic ductal adenocarcinoma (PDAC) and important for gemcitabine resistance, the role of DNA-PKcs in the progression and metastasis of PDAC remain unclear. To date, the upstream signaling events stimulating DNA-PKcs overexpression in PDAC are still not well characterized.

Methods: Expression of DNA-PKcs was measured by western blot. The levels of miRNA-101 and lncRNA nuclear paraspeckle assembly transcript 1 (NEAT1) were detected by real-time PCR. Cell viability was determined by CCK-8. Cell migration and cell invasion were measured by transwell assay. The regulatory relationship between NEAT1 and miR-101 was determined by a luciferase assay.

Results: DNA-PKcs expression was significantly elevated in human PDAC tissues and cells. DNA-PKcs overexpression was correlated with TNM stage and lymph node metastasis. Higher expression of DNA-PKcs was closely correlated with patients of worse overall survival (OS). DNA-PKcs knockdown suppresses malignant behaviors of PDAC cells. Further study showed that miRNA-101 level was decreased in PDAC tissues and cells, which could be responsible for DNA-PKcs overexpression and DNA-PKcs mediated oncogenic actions in PDAC cells. Moreover, NEAT1 functions as an oncogene influencing cell proliferation, migration and invasion in part by serving as a competing endogenous RNA (ceRNAs) modulating miR-101 expression, leading to up-regulation of DNA-PKcs.

Conclusion: These findings suggest that NEAT1/miR-101-dependent up-regulation of DNA-PKcs promotes the malignant behaviors of PDAC cells. The NEAT1/miR-101/DNA-PKcs axis may serve as a viable prognostic marker and therapeutic target for PDAC.

Weighted gene co-expression network analysis (WGCNA) to explore genes responsive to Streptococcus oralis biofilm and immune infiltration analysis in human gingival fibroblasts cells

The correlation between oral bacteria and dental implants failure has been reported. However, the effect and mechanism of bacteria during dental implants is unclear. In this study, we explored key genes and candidate gene clusters in human gingival fibroblasts (HGF) cells in response to Streptococcus oralis biofilm through weighted gene co-expression network analysis (WGCNA) and differential genes analysis using gene expression matrix, GSE134481, downloaded from the Gene Expression Omnibus (GEO) database. We obtained 325 genes in the module significantly associated with S. oralis infection and 113 differentially expressed genes (DEGs) in the S. oralis biofilm; 62 DEGs indicated significant correlation with S. oralis injury. Multiple immune pathways, such as the tumor necrosis factor (TNF) signaling pathway, were considerably enriched. We obtained a candidate genes cluster containing 12 genes – IL6, JUN, FOS, CSF2, HBEGF, EDN1, CCL2, MYC, NGF, SOCS3, CXCL1, and CXCL2; we observed 5 candidate hub genes associated with S. oralis infection – JUN, IL6, FOS, MYC, and CCL2. The fraction of macrophage M0 cells was significantly increased in biofilm treatment compared with control; expression of FOS and MYC was significantly positively correlated with macrophage M0 cells. Our findings present a fierce inflammation changes in the transcript level of HGF in response to S. oralis.

Crosstalk between noncoding RNAs and ferroptosis: new dawn for overcoming cancer progression

Cancer progression including proliferation, metastasis, and chemoresistance has become a serious hindrance to cancer therapy. This phenomenon mainly derives from the innate insensitive or acquired resistance of cancer cells to apoptosis. Ferroptosis is a newly discovered mechanism of programmed cell death characterized by peroxidation of the lipid membrane induced by reactive oxygen species. Ferroptosis has been confirmed to eliminate cancer cells in an apoptosis-independent manner, however, the specific regulatory mechanism of ferroptosis is still unknown. The use of ferroptosis for overcoming cancer progression is limited. Noncoding RNAs have been found to play an important roles in cancer. They regulate gene expression to affect biological processes of cancer cells such as proliferation, cell cycle, and cell death. Thus far, the functions of ncRNAs in ferroptosis of cancer cells have been examined, and the specific mechanisms by which noncoding RNAs regulate ferroptosis have been partially discovered. However, there is no summary of ferroptosis associated noncoding RNAs and their functions in different cancer types. In this review, we discuss the roles of ferroptosis-associated noncoding RNAs in detail. Moreover, future work regarding the interaction between noncoding RNAs and ferroptosis is proposed, the possible obstacles are predicted and associated solutions are put forward. This review will deepen our understanding of the relationship between noncoding RNAs and ferroptosis, and provide new insights in targeting noncoding RNAs in ferroptosis associated therapeutic strategies.

Analysis of lncRNA-mRNA networks after MEK1/2 inhibition based on WGCNA in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDA) responds poorly to treatment. Efforts have been exerted to prolong the survival time of PDA, but the 5-year survival rates remain disappointing. Understanding the molecular mechanisms of PDA development is significant. MEK/ERK pathway signaling has been proven to be important in PDA. lncRNA-mRNA networks have become a vital part of molecular mechanisms in the MEK/ERK pathway. Herein, weighted gene coexpression network analysis was used to investigate the coexpressed lncRNA-mRNA networks in the MEK/ERK pathway based on GSE45765. Differently expressed long noncoding RNA (lncRNA) and messenger RNA (mRNA) were found and 10 modules were identified based on coexpression profiles. Gene ontology and Kyoto Encyclopedia of Genes and Genomes were then performed to analyze the coexpressed lncRNA and mRNA in different modules. PDA cells and tissues were used to validate the analysis results. Finally, we found that NONHSAT185150.1 and B4GALT6 were negatively correlated with MEK1/2. By analyzing GSE45765, the genome-wide profiles of lncRNA-mRNA network after MEK1/2 was established, which might aid the development of drug-targeting MEK1/2 and the investigation of diagnostic markers.