Dysregulated lncRNA-miRNA-mRNA Network Reveals Patient Survival-Associated Modules and RNA Binding Proteins in Invasive Breast Carcinoma

Pan-Cancer Methylated Dysregulation of Long Non-coding RNAs Reveals Epigenetic Biomarkers

Different cancer types not only have common characteristics but also have their own characteristics respectively. The mechanism of these specific and common characteristics is still unclear. Pan-cancer analysis can help understand the similarities and differences among cancer types by systematically describing different patterns in cancers and identifying cancer-specific and cancer-common molecular biomarkers. While long non-coding RNAs (lncRNAs) are key cancer modulators, there is still a lack of pan-cancer analysis for lncRNA methylation dysregulation. In this study, we integrated lncRNA methylation, lncRNA expression and mRNA expression data to illuminate specific and common lncRNA methylation patterns in 23 cancer types. Then, we screened aberrantly methylated lncRNAs that negatively regulated lncRNA expression and mapped them to the ceRNA relationship for further validation. 29 lncRNAs were identified as diagnostic biomarkers for their corresponding cancer types, with lncRNA AC027601 was identified as a new KIRC-associated biomarker, and lncRNA ACTA2-AS1 was regarded as a carcinogenic factor of KIRP. Two lncRNAs HOXA-AS2 and AC007228 were identified as pan-cancer biomarkers. In general, the cancer-specific and cancer-common lncRNA biomarkers identified in this study may aid in cancer diagnosis and treatment.

Long non-coding RNA FOXD3 antisense RNA 1 augments anti-estrogen resistance in breast cancer cells through the microRNA-363/ trefoil factor 1/ phosphatidylinositol 3-kinase/protein kinase B axis

Long non-coding RNA (lncRNA) FOXD3 antisense RNA 1 (FOXD3-AS1) has been reported to participate in multiple processes that contribute toward the development of cancer. The present study aimed to explore the effect of lncRNA FOXD3-AS1 on anti-estrogen resistance in breast cancer (BC) cells. FOXD3-AS1 was found to be highly expressed in BC cell lines. Moreover, FOXD3-AS1 was highly expressed in estrogen receptor-negative (ER^-) cells compared to the ER-positive (ER⁺) cells. FOXD3-AS1 overexpression in T47D and MCF-7 (ER⁺) cells enhanced the resistance of cells to tamoxifen (TMX), whereas FOX3-AS1 downregulation reduced the TMX resistance in MDA-MB-231 (ER^-) cells. Similar results were reproduced in vivo that FOXD3-AS1 inhibition reduced the growth of xenograft tumors formed by MDA-MB-231 cells following TMX treatment whereas FOXD3-AS1 overexpression in T47D cells facilitated tumor growth. The bioinformatic analysis and luciferase assays indicated that FOXD3-AS1 sponged microRNA-363 (miR-363) to restore expression of trefoil factor 1 (TFF1) mRNA. Overexpression of miR-363 reduced T47D cell proliferation induced by FOXD3-AS1, whereas overexpression of TFF1 restored growth of MDA-MB-231 cells reduced after FOXD3-AS1 silencing. The phosphorylation of phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) was increased by FOXD3-AS1 but attenuated by miR-363. Inhibition of PI3K/Akt blocked the role of FOXD3-AS1 and reduced the TMX resistance in T47D and MCF-7 cells. Taken together, the present study suggested that FOXD3-AS1 sponges miR-363 to upregulate TFF1 expression, leading to PI3K/Akt signaling activation and anti-estrogen resistance in BC cells.

Development and validation of prognostic model based on the analysis of autophagy-related genes in colon cancer

BACKGROUND

Autophagy, a process of self-digestion, is closely related to multiple biological processes of colon cancer. This study aimed to construct and evaluate prognostic signature of autophagy-related genes (ARGs) to predict overall survival (OS) in colon cancer patients.

MATERIALS AND METHODS

First, a total of 234 ARGs were downloaded via The Cancer Genome Atlas (TCGA) database. Based on the TCGA dataset, differentially expressed ARGs were identified in colon cancer. The univariate and multivariate Cox regression analysis was performed to screen prognostic ARGs to construct the prognostic model. The feasibility of the prognostic model was evaluated using receiver operating characteristic curves and Kaplan-Meier curves. A prognostic model integrating the gene signature with clinical parameters was established with a nomogram.

RESULTS

We developed an autophagy risk signature based on the 6 ARGs (ULK3, ATG101, MAP1LC3C, TSC1, DAPK1, and SERPINA1). The risk score was positively correlated with poor outcome and could independently predict prognosis. Furthermore, the autophagy-related signature could effectively reflect the levels of immune cell type fractions and indicate an immunosuppressive microenvironment.

CONCLUSION

We innovatively identified and validated 6 autophagy-related gene signature that can independently predict prognosis and reflect overall immune response intensity in the colon cancer microenvironment.

Immune and Metabolic Dysregulated Coding and Non-coding RNAs Reveal Survival Association in Uterine Corpus Endometrial Carcinoma

Uterine corpus endometrial carcinoma (UCEC) is one of the most common gynecologic malignancies, but only a few biomarkers have been proven to be effective in clinical practice. Previous studies have demonstrated the important roles of non-coding RNAs (ncRNAs) in diagnosis, prognosis, and therapy selection in UCEC and suggested the significance of integrating molecules at different levels for interpreting the underlying molecular mechanism. In this study, we collected transcriptome data, including long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs), of 570 samples, which were comprised of 537 UCEC samples and 33 normal samples. First, differentially expressed lncRNAs, miRNAs, and mRNAs, which distinguished invasive carcinoma samples from normal samples, were identified, and further analysis showed that cancer- and metabolism-related functions were enriched by these RNAs. Next, an integrated, dysregulated, and scale-free biological network consisting of differentially expressed lncRNAs, miRNAs, and mRNAs was constructed. Protein-coding and ncRNA genes in this network showed potential immune and metabolic functions. A further analysis revealed two clinic-related modules that showed a close correlation with metabolic and immune functions. RNAs in the two modules were functionally validated to be associated with UCEC. The findings of this study demonstrate an important clinical application for improving outcome prediction for UCEC.

Shared Molecular Mechanisms between Alzheimer's Disease and Periodontitis Revealed by Transcriptomic Analysis

OBJECTIVE

To investigate the genetic crosstalk mechanisms that link periodontitis and Alzheimer's disease (AD).

BACKGROUND

Periodontitis, a common oral infectious disease, is associated with Alzheimer's disease (AD) and considered a putative contributory factor to its progression. However, a comprehensive investigation of potential shared genetic mechanisms between these diseases has not yet been reported.

METHODS

Gene expression datasets related to periodontitis were downloaded from the Gene Expression Omnibus (GEO) database, and differential expression analysis was performed to identify differentially expressed genes (DEGs). Genes associated with AD were downloaded from the DisGeNET database. Overlapping genes among the DEGs in periodontitis and the AD-related genes were defined as crosstalk genes between periodontitis and AD. The Boruta algorithm was applied to perform feature selection from these crosstalk genes, and representative crosstalk genes were thus obtained. In addition, a support vector machine (SVM) model was constructed by using the scikit-learn algorithm in Python. Next, the crosstalk gene-TF network and crosstalk gene-DEP (differentially expressed pathway) network were each constructed. As a final step, shared genes among the crosstalk genes and periodontitis-related genes in DisGeNET were identified and denoted as the core crosstalk genes.

RESULTS

Four datasets (GSE23586, GSE16134, GSE10334, and GSE79705) pertaining to periodontitis were included in the analysis. A total of 48 representative crosstalk genes were identified by using the Boruta algorithm. Three TFs (FOS, MEF2C, and USF2) and several pathways (i.e., JAK-STAT, MAPK, NF-kappa B, and natural killer cell-mediated cytotoxicity) were identified as regulators of these crosstalk genes. Among these 48 crosstalk genes and the chronic periodontitis-related genes in DisGeNET, C4A, C4B, CXCL12, FCGR3A, IL1B, and MMP3 were shared and identified as the most pivotal candidate links between periodontitis and AD.

CONCLUSIONS

Exploration of available transcriptomic datasets revealed C4A, C4B, CXCL12, FCGR3A, IL1B, and MMP3 as the top candidate molecular linkage genes between periodontitis and AD.

BaBao Dan Suppresses Tumor Growth of Pancreatic Cancer Through Modulating Transcriptional Reprogramming of Cancer-Related Genes

Background and Aims

Pancreatic ductal adenocarcinoma (PDAC) is one of refractory malignancies without efficient therapeutics. Babao Dan (BBD) was partially effective to suppress tumor growth of PDAC in clinical practice. However, the molecular mechanisms were unclear.

Methods

We established PDAC mice models and treated them with BBD through intragastric administration. Treatment and control groups were then subjected to high-throughput RNA sequencing. We presented the transcriptional changes upon BBD treatment by using computational analysis comparing BBD treatment and control groups. Functional enrichment analysis was employed to investigate the biological processes or pathways that BBD modulates.

Results

BBD treatment showed strong suppression on tumor growth of PDAC, even stronger than Gemcitabine. Through differential analysis comparing BBD treatment and control groups, we identified 638 up-regulated and 259 down-regulated genes in the BBD treatment group. BBD was found to activate tumor suppressor genes, such as MTUS1, PDGFB, SOD3, and UCHL1. Furthermore, we revealed that BBD treatment inhibited cancer-related pathways and elevated activities of metabolism-related processes. The BBD-modulated metabolic genes were further showed to be associated with patient survival in an independent cohort with pancreatic cancer.

Conclusion

BBD repressed the tumor growth of PDAC. BBD treatment modulated expression of cancer-related genes in PDAC. BBD suppressed cancer-related pathways and activated metabolic processes in PDAC. Our study suggests BBD treatment as potential effective therapeutics for patients with pancreatic cancer.

Machine Learning Based Network Analysis Determined Clinically Relevant miRNAs in Breast Cancer

BACKGROUND AND AIMS

MicroRNAs (miRNAs) have been shown to play important roles in many cancers, including breast cancer. The majority of previous studies employed network analysis to identify key miRNAs in cancer progression. However, most of dysregulated miRNA networks were constructed based on the expression variation of miRNAs and target genes.

METHODS

The relations between miRNAs and target genes were computed by Spearman correlation separately in breast cancer and normal breast samples. We calculated dysregulated scores based on the dysregulation of miRNA-mRNA regulatory relations. A dysregulated miRNA target network (DMTN) was constructed from the miRNA-mRNA pairs with significant dysregulated scores. SVM classifier was employed to predict breast cancer risk miRNAs from the DMTN. Hypermetric test was utilized to calculate the significance of overlap between different gene sets. Pearson correlation was used to evaluate associations between miRNAs/genes and drug response.

RESULTS

The DMTN comprised 511 miRNAs and was similar to common biological networks. Based on miRNAs and target genes in DMTN, we predicted 90 breast cancer risk miRNAs by using SVM classifier. Predicted risk miRNAs and one-step neighbor genes were significantly overlapping with differential miRNAs, cancer-related and housekeeping genes in breast cancer. These risk miRNAs were involved in many cancer-related and immune-related processes. In addition, most risk miRNAs were able to predict survival of breast cancer patients. More interestingly, some risk miRNAs and one-step neighbor genes were remarkably associated with immune cell infiltration. For example, high expression of hsa-miR-155 indicates high abundance of activated CD4+ T cells but low level of M2 macrophage infiltration. Furthermore, we identified 588 miRNA-drug and 3,146 gene-drug pairs, wherein the expression level of miRNAs/genes could indicate the sensitivity of cancer cells to anti-cancer drugs.

CONCLUSION

We predicted 90 breast cancer risk miRNAs based on proposed DMTN by using SVM classifier. Predicted risk miRNAs are biologically and clinically relevant in breast cancer. Risk miRNAs and one-step neighbor genes could serve as biomarkers for immune cell infiltration and anti-cancer drug response, which sheds lights on immunotherapy or targeted therapy for patients with breast cancer.

Integrated analysis identifies a pathway-related competing endogenous RNA network in the progression of pancreatic cancer

BACKGROUND

It is well acknowledged that cancer-related pathways play pivotal roles in the progression of pancreatic cancer (PC). Employing Integrated analysis, we aim to identify the pathway-related ceRNA network associated with PC progression.

METHODS

We divided eight GEO datasets into three groups according to their platform, and combined TCGA and GTEx databases as a group. Additionally, we screened out the differentially expressed genes (DEGs) and performed functional enrichment analysis in each group, and recognized the top hub genes in the most enriched pathway. Furthermore, the upstream of miRNAs and lncRNAs were predicted and validated according to their expression and prognostic roles. Finally, the co-expression analysis was applied to identify a pathway-related ceRNA network in the progression of PC.

RESULTS

A total of 51 significant pathways that common enriched in all groups were spotted. Enrichment analysis indicated that pathway in cancer was greatly linked with tumor formation and progression. Next, the top 20 hug genes in this pathway were recognized, and stepwise prediction and validation from mRNA to lncRNA, including 11 hub genes, 4 key miRNAs, and 2 key lncRNAs, were applied to identify a meaningful ceRNA network according to ceRNA rules. Ultimately, we identified the PVT1/miR-20b/CCND1 axis as a promising pathway-related ceRNA axis in the progression of PC.

CONCLUSION

Overall, we elucidate the pathway-related ceRNA regulatory network of PVT1/miR-20b/CCND1 in the progression of PC, which can be considered as therapeutic targets and encouraging prognostic biomarkers for PC.

The Long Non-coding RNA LINC01705 Regulates the Development of Breast Cancer by Sponging miR-186-5p to Mediate TPR Expression as a Competitive Endogenous RNA

Long non-coding RNAs (lncRNAs) may be a regulatory factor of tumorigenesis. However, it is unclear what its biomechanisms are in breast cancer. In this study, different lncRNAs were detected in breast cancer through microarray analysis (GSE119233) and LINC01705 was selected for further study. qRT-PCR was then utilized for the detection of LINC01705 expression in breast cancer cells. A transwell assay, flow cytometry, 5-ethynyl-2'-deoxyuridine (EdU), a cell counting Kit-8 (CCK-8), and a wound-healing assay were performed to determine cell migration, invasion, apoptosis, and proliferation in breast cancer, respectively. For the identification of potential targets of LINC01705, dual-luciferase reporter gene and bioinformatics assays were conducted. Moreover, for the clarification of their interaction and roles in the regulation of the occurrence of breast cancer, Western blotting and RIP assays were conducted. Our findings revealed high LINC01705 expression in breast cancer tissues relative to adjacent non-cancerous tissues (n = 40, P < 0.001). Overexpression of LINC01705 notably enhanced cell migration and proliferation in breast cancer. In addition, LINC01705 positively regulated the translocated promoter region, nuclear basket protein (TPR) through competition with miR-186-5p. In conclusion, our results suggest that LINC01705 is implicated in the progression of breast cancer via competitively binding to miR-186-5p as a competing endogenous RNA (ceRNA), thereby regulating TPR expression.

Emerging Roles and Therapeutic Interventions of Aerobic Glycolysis in Glioma

Glioma is the most common type of intracranial malignant tumor, with a great recurrence rate due to its infiltrative growth, treatment resistance, intra- and intertumoral genetic heterogeneity. Recently, accumulating studies have illustrated that activated aerobic glycolysis participated in various cellular and clinical activities of glioma, thus influencing the efficacy of radiotherapy and chemotherapy. However, the glycolytic process is too complicated and ambiguous to serve as a novel therapy for glioma. In this review, we generalized the implication of key enzymes, glucose transporters (GLUTs), signalings and transcription factors in the glycolytic process of glioma. In addition, we summarized therapeutic interventions via the above aspects and discussed promising clinical applications for glioma.