MicroRNA and transcription factor co-regulatory networks and subtype classification of seminoma and non-seminoma in testicular germ cell tumors

Unveiling cell-type-specific microRNA networks through alternative polyadenylation in glioblastoma

BACKGROUND

Glioblastoma multiforme (GBM) is characterized by its cellular complexity, with a microenvironment consisting of diverse cell types, including oligodendrocyte precursor cells (OPCs) and neoplastic CD133 + radial glia-like cells. This study focuses on exploring the distinct cellular transitions in GBM, emphasizing the role of alternative polyadenylation (APA) in modulating microRNA-binding and post-transcriptional regulation.

RESULTS

Our research identified unique APA profiles that signify the transitional phases between neoplastic cells and OPCs, underscoring the importance of APA in cellular identity and transformation in GBM. A significant finding was the disconnection between differential APA events and gene expression alterations, indicating that APA operates as an independent regulatory mechanism. We also highlighted the specific genes in neoplastic cells and OPCs that lose microRNA-binding sites due to APA, which are crucial for maintaining stem cell characteristics and DNA repair, respectively. The constructed networks of microRNA-transcription factor-target genes provide insights into the cellular mechanisms influencing cancer cell survival and therapeutic resistance.

CONCLUSIONS

This study elucidates the APA-driven regulatory framework within GBM, spotlighting its influence on cell state transitions and microRNA network dynamics. Our comprehensive analysis using single-cell RNA sequencing data to investigate the microRNA-binding sites altered by APA profiles offers a robust foundation for future research, presenting a novel approach to understanding and potentially targeting the complex molecular interplay in GBM.

An Integrated Framework to Identify Prognostic Biomarkers and Novel Therapeutic Targets in Hepatocellular Carcinoma-Based Disabilities

Hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors globally, significantly affecting liver functions, thus necessitating the identification of biomarkers and effective therapeutics to improve HCC-based disabilities. This study aimed to identify prognostic biomarkers, signaling cascades, and candidate drugs for the treatment of HCC through integrated bioinformatics approaches such as functional enrichment analysis, survival analysis, molecular docking, and simulation. Differential expression and functional enrichment analyses revealed 176 common differentially expressed genes from two microarray datasets, GSE29721 and GSE49515, significantly involved in HCC development and progression. Topological analyses revealed 12 hub genes exhibiting elevated expression in patients with higher tumor stages and grades. Survival analyses indicated that 11 hub genes (CCNB1, AURKA, RACGAP1, CEP55, SMC4, RRM2, PRC1, CKAP2, SMC2, UHRF1, and FANCI) and three transcription factors (E2F1, CREB1, and NFYA) are strongly linked to poor patient survival. Finally, molecular docking and simulation identified seven candidate drugs with stable complexes to their target proteins: tozasertib (-9.8 kcal/mol), tamatinib (-9.6 kcal/mol), ilorasertib (-9.5 kcal/mol), hesperidin (-9.5 kcal/mol), PF-562271 (-9.3 kcal/mol), coumestrol (-8.4 kcal/mol), and clofarabine (-7.7 kcal/mol). These findings suggest that the identified hub genes and TFs could serve as valuable prognostic biomarkers and therapeutic targets for HCC-based disabilities.

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.

Knowledge graphs facilitate prediction of drug response for acute myeloid leukemia

Acute myeloid leukemia (AML) is a highly aggressive and heterogeneous disease, underscoring the need for improved therapeutic options and methods to optimally predict responses. With the wealth of available data resources, including clinical features, multiomics analysis, and ex vivo drug screening from AML patients, development of drug response prediction models has become feasible. Knowledge graphs (KGs) embed the relationships between different entities or features, allowing for explanation of a wide breadth of drug sensitivity and resistance mechanisms. We designed AML drug response prediction models guided by KGs. Our models included engineered features, relative gene expression between marker genes for each drug and regulators (e.g., transcription factors). We identified relative gene expression of FGD4-MIR4519, NPC2-GATA2, and BCL2-NFKB2 as predictive features for venetoclax ex vivo drug response. The KG-guided models provided high accuracy in independent test sets, overcame potential platform batch effects, and provided candidate drug sensitivity biomarkers for further validation.

Pan-cancer integrative analyses dissect the remodeling of endothelial cells in human cancers

Therapeutics targeting tumor endothelial cells (TECs) have been explored for decades, with only suboptimal efficacy achieved, partly due to an insufficient understanding of the TEC heterogeneity across cancer patients. We integrated single-cell RNA-seq data of 575 cancer patients from 19 solid tumor types, comprehensively charting the TEC phenotypic diversities. Our analyses uncovered underappreciated compositional and functional heterogeneity in TECs from a pan-cancer perspective. Two subsets, CXCR4 + tip cells and SELE + veins, represented the prominent angiogenic and proinflammatory phenotypes of TECs, respectively. They exhibited distinct spatial organization patterns, and compared to adjacent non-tumor tissues, tumor tissue showed an increased prevalence of CXCR4 + tip cells, yet with SELE + veins depleted. Such functional and spatial characteristics underlie their differential associations with the response of anti-angiogenic therapies and immunotherapies. Our integrative resources and findings open new avenues to understand and clinically intervene in the tumor vasculature.

Expression and Functional Analysis of Immuno-Micro-RNAs mir-146a and mir-326 in Colorectal Cancer

Micro-RNAs (miRNAs) are non-coding RNAs with importance in the development of cancer. They are involved in both tumor development and immune processes in tumors. The present study aims to characterize the behavior of two miRNAs, the proinflammatory miR-326-5p and the anti-inflammatory miR-146a-5p, in colorectal cancer (CRC), to decipher the mechanisms that regulate their expression, and to study potential applications. Tissue levels of miR-326-5p and miR-146a-5p were determined by qrt-PCR (real-time quantitative reverse transcription polymerase chain reaction) in 45 patients with colorectal cancer in tumoral and normal adjacent tissue. Subsequent bioinformatic analysis was performed to characterize the transcriptional networks that control the expression of the two miRNAs. The biomarker potential of miRNAs was assessed. The expression of miR-325-5p and miR-146a-5p was decreased in tumors compared to normal tissue. The two miRNAs are regulated through a transcriptional network, which originates in the inflammatory and proliferative pathways and regulates a set of cellular functions related to immunity, proliferation, and differentiation. The miRNAs coordinate distinct modules in the network. There is good biomarker potential of miR-326 with an AUC (Area under the curve) of 0.827, 0.911 sensitivity (Sn), and 0.689 specificity (Sp), and of the combination miR-326-miR-146a, with an AUC of 0.845, Sn of 0.75, and Sp of 0.89. The miRNAs are downregulated in the tumor tissue. They are regulated by a transcriptional network in which they coordinate distinct modules. The structure of the network highlights possible therapeutic approaches. MiR-326 and the combination of the two miRNAs may serve as biomarkers in CRC.

NANOG controls testicular germ cell tumour stemness through regulation of MIR9-2

BACKGROUND

Testicular germ cell tumours (TGCTs) represent a clinical challenge; they are most prevalent in young individuals and are triggered by molecular mechanisms that are not fully understood. The origin of TGCTs can be traced back to primordial germ cells that fail to mature during embryonic development. These cells express high levels of pluripotency factors, including the transcription factor NANOG which is highly expressed in TGCTs. Gain or amplification of the NANOG locus is common in advanced tumours, suggesting a key role for this master regulator of pluripotency in TGCT stemness and malignancy.

METHODS

In this study, we analysed the expression of microRNAs (miRNAs) that are regulated by NANOG in TGCTs via integrated bioinformatic analyses of data from The Cancer Genome Atlas and NANOG chromatin immunoprecipitation in human embryonic stem cells. Through gain-of-function experiments, MIR9-2 was further investigated as a novel tumour suppressor regulated by NANOG. After transfection with MIR9-2 mimics, TGCT cells were analysed for cell proliferation, invasion, sensitivity to cisplatin, and gene expression signatures by RNA sequencing.

RESULTS

For the first time, we identified 86 miRNAs regulated by NANOG in TGCTs. Among these, 37 miRNAs were differentially expressed in NANOG-high tumours, and they clustered TGCTs according to their subtypes. Binding of NANOG within 2 kb upstream of the MIR9-2 locus was associated with a negative regulation. Low expression of MIR9-2 was associated with tumour progression and MIR9-2-5p was found to play a role in the control of tumour stemness. A gain of function of MIR9-2-5p was associated with reduced proliferation, invasion, and sensitivity to cisplatin in both embryonal carcinoma and seminoma tumours. MIR9-2-5p expression in TGCT cells significantly reduced the expression of genes regulating pluripotency and cell division, consistent with its functional effect on reducing cancer stemness.

CONCLUSIONS

This study provides new molecular insights into the role of NANOG as a key determinant of pluripotency in TGCTs through the regulation of MIR9-2-5p, a novel epigenetic modulator of cancer stemness. Our data also highlight the potential negative feedback mediated by MIR9-2-5p on NANOG expression, which could be exploited as a therapeutic strategy for the treatment of TGCTs.

Astrocytic transcription factors REST, YY1, and putative microRNAs in Parkinson's disease and advanced therapeutic strategies

Transcription factors (TF) and microRNAs are regulatory factors in astrocytes and are linked to several Parkinson's disease (PD) progression causes, such as disruption of glutamine transporters in astrocytes and concomitant disrupted glutamine uptake and inflammation. REST, a crucial TF, has been documented as an epigenetic repressor that limits the expression of neuronal genes in non-neural cells. REST activity is significantly linked to its corepressors in astrocytes, specifically histone deacetylases (HDACs), CoREST, and MECP2. Another REST-regulating TF, YY1, has been studied in astrocytes, and its interaction with REST has been investigated. In this review, the molecular processes that support the astrocytic control of REST and YY1 in terms of the regulation of glutamate transporter EAAT2 were addressed in a more detailed and comprehensive manner. Both TFs' function in astrocytes and how astrocyte abnormalities cause PD is still a mystery. Moreover, microRNAs (short non-coding RNAs) are key regulators that have been correlated to the expression and regulation of numerous genes linked to PD. The identification of numerous miRs that are engaged in astrocyte dysfunction that triggers PD has been shown. The term "Gut-brain axis" refers to the two systems' mutual communication. Gut microbial dysbiosis, which mediates an imbalance of the gut-brain axis, might contribute to neurodegenerative illnesses through altered astrocytic regulation. New treatment approaches to modify the gut-brain axis and prevent astrocytic repercussions have also been investigated in this review.

Leveraging a disulfidptosis‑related lncRNAs signature for predicting the prognosis and immunotherapy of glioma

BACKGROUND

Gliomas, a prevalent form of primary brain tumors, are linked with a high mortality rate and unfavorable prognoses. Disulfidptosis, an innovative form of programmed cell death, has received scant attention concerning disulfidptosis-related lncRNAs (DRLs). The objective of this investigation was to ascertain a prognostic signature utilizing DRLs to forecast the prognosis and treatment targets of glioma patients.

METHODS

RNA-seq data were procured from The Cancer Genome Atlas database. Disulfidptosis-related genes were compiled from prior research. An analysis of multivariate Cox regression and the least absolute selection operator was used to construct a risk model using six DRLs. The risk signature's performance was evaluated via Kaplan-Meier survival curves and receiver operating characteristic curves. Additionally, functional analysis was carried out using GO, KEGG, and single-sample GSEA to investigate the biological functions and immune infiltration. The research also evaluated tumor mutational burden, therapeutic drug sensitivity, and consensus cluster analysis. Reverse transcription quantitative PCR was conducted to validate the expression level of DRLs.

RESULTS

A prognostic signature comprising six DRLs was developed to predict the prognosis of glioma patients. High-risk patients had significantly shorter overall survival than low-risk patients. The robustness of the risk model was validated by receiver operating characteristic curves and subgroup survival analysis. Risk model was used independently as a prognostic indicator for the glioma patients. Notably, the low-risk patients displayed a substantial decrease in the immune checkpoints, the proportion of immune cells, ESTIMATE and immune score. IC50 values from the different risk groups allowed us to discern three drugs for the treatment of glioma patients. Lastly, the potential clinical significance of six DRLs was determined.

CONCLUSIONS

A novel six DRLs signature was developed to predict prognosis and may provide valuable insights for patients with glioma seeking novel immunotherapy and targeted therapy.

Diverse activity of miR-150 in Tumor development: shedding light on the potential mechanisms

There is a growing interest to understand the role and mechanism of action of microRNAs (miRNAs) in cancer. The miRNAs are defined as short non-coding RNAs (18-22nt) that regulate fundamental cellular processes through mRNA targeting in multicellular organisms. The miR-150 is one of the miRNAs that have a crucial role during tumor cell progression and metastasis. Based on accumulated evidence, miR-150 acts as a double-edged sword in malignant cells, leading to either tumor-suppressive or oncogenic function. An overview of miR-150 function and interactions with regulatory and signaling pathways helps to elucidate these inconsistent effects in metastatic cells. Aberrant levels of miR-150 are detectable in metastatic cells that are closely related to cancer cell migration, invasion, and angiogenesis. The ability of miR-150 in regulating of epithelial-mesenchymal transition (EMT) process, a critical stage in tumor cell migration and metastasis, has been highlighted. Depending on the cancer cells type and gene expression profile, levels of miR-150 and potential target genes in the fundamental cellular process can be different. Interaction between miR-150 and other non-coding RNAs, such as long non-coding RNAs and circular RNAs, can have a profound effect on the behavior of metastatic cells. MiR-150 plays a significant role in cancer metastasis and may be a potential therapeutic target for preventing or treating metastatic cancer.

Epigenetic Factors and ncRNAs in Testicular Cancer

Testicular cancer is the most prevalent tumor among males aged 15 to 35, resulting in a significant number of newly diagnosed cases and fatalities annually. Non-coding RNAs (ncRNAs) have emerged as key regulators in various cellular processes and pathologies, including testicular cancer. Their involvement in gene regulation, coding, decoding, and overall gene expression control suggests their potential as targets for alternative treatment approaches for this type of cancer. Furthermore, epigenetic modifications, such as histone modifications, DNA methylation, and the regulation by microRNA (miRNA), have been implicated in testicular tumor progression and treatment response. Epigenetics may also offer critical insights for prognostic evaluation and targeted therapies in patients with testicular germ cell tumors (TGCT). This comprehensive review aims to present the latest discoveries regarding the involvement of some proteins and ncRNAs, mainly miRNAs and lncRNA, in the epigenetic aspect of testicular cancer, emphasizing their relevance in pathogenesis and their potential, given the fact that their specific expression holds promise for prognostic evaluation and targeted therapies.

Noncoding RNAs in oral cancer

Oral cancer (OC) is the most prevalent subtype of cancer arising in the head and neck region. OC risk is mainly attributed to behavioral risk factors such as exposure to tobacco and excessive alcohol consumption, and a lesser extent to viral infections such as human papillomaviruses and Epstein-Barr viruses. In addition to these acquired risk factors, heritable genetic factors have shown to be associated with OC risk. Despite the high incidence, biomarkers for OC diagnosis are lacking and consequently, patients are often diagnosed in advanced stages. This delay in diagnosis is reflected by poor overall outcomes of OC patients, where 5-year overall survival is around 50%. Among the biomarkers proposed for cancer detection, noncoding RNA (ncRNA) can be considered as one of the most promising categories of biomarkers due to their role in virtually all cellular processes. Similar to other cancer types, changes in expressions of ncRNAs have been reported in OC and a number of ncRNAs have diagnostic, prognostic, and therapeutic potential. Moreover, some ncRNAs are capable of regulating gene expression by various mechanisms. Therefore, elucidating the current literature on the four main types of ncRNAs namely, microRNA, lncRNA, snoRNA, piwi-RNA, and circular RNA in the context of OC pathogenesis is timely and would enable further improvements and innovations in diagnosis, prognosis, and treatment of OC. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development.

Transcriptomic analysis of esophageal cancer reveals hub genes and networks involved in cancer progression

Esophageal carcinoma (ESCA) has a 5-year survival rate of fewer than 20%. The study aimed to identify new predictive biomarkers for ESCA through transcriptomics meta-analysis to address the problems of ineffective cancer therapy, lack of efficient diagnostic tools, and costly screening and contribute to developing more efficient cancer screening and treatments by identifying new marker genes. Nine GEO datasets of three kinds of esophageal carcinoma were analyzed, and 20 differentially expressed genes were detected in carcinogenic pathways. Network analysis revealed four hub genes, namely RAR Related Orphan Receptor A (RORA), lysine acetyltransferase 2B (KAT2B), Cell Division Cycle 25B (CDC25B), and Epithelial Cell Transforming 2 (ECT2). Overexpression of RORA, KAT2B, and ECT2 was identified with a bad prognosis. These hub genes modulate immune cell infiltration. These hub genes modulate immune cell infiltration. Although this research needs lab confirmation, we found interesting biomarkers in ESCA that may aid in diagnosis and treatment.

Genome-Wide Characterization and Expression Analysis of Transcription Factor Families in Desert Moss Syntrichia caninervis under Abiotic Stresses

Transcription factor (TF) families play important roles in plant stress responses. S. caninervis is a new model moss for plant desiccation tolerance studies. Here, we report a high-confidence identification and characterization of 591 TFs representing 52 families that covered all chromosomes in S. caninervis. GO term and KEGG pathway analysis showed that TFs were involved in the regulation of transcription, DNA-templated, gene expression, binding activities, plant hormone signal transduction, and circadian rhythm. A number of TF promoter regions have a mixture of various hormones-related cis-regulatory elements. AP2/ERF, bHLH, MYB, and C2H2-zinc finger TFs were the overrepresented TF families in S. caninervis, and the detailed classification of each family is performed based on structural features. Transcriptome analysis revealed the transcript abundances of some ScAP2/ERF, bHLH, MYB, and C2H2 genes were accumulated in the treated S. caninervis under cold, dehydration, and rehydration stresses. The RT-qPCR results strongly agreed with RNA-seq analysis, indicating these TFs might play a key role in S. caninervis response to abiotic stress. Our comparative TF characterization and classification provide the foundations for functional investigations of the dominant TF genes involved in S. caninervis stress response, as well as excellent stress tolerance gene resources for plant stress resistance breeding.

MicroRNA-Transcription factor regulatory networks in the early strobilar development of Echinococcus granulosus protoscoleces

BACKGROUND

Echinococcus granulosus sensu lato has a complex developmental biology with a variety of factors relating to both intermediate and final hosts. To achieve maximum parasite adaptability, the development of the cestode is dependent on essential changes in transcript regulation. Transcription factors (TFs) and miRNAs are known as master regulators that affect the expression of downstream genes through a wide range of metabolic and signaling pathways. In this study, we aimed to develop a regulatory miRNA-Transcription factor (miRNA-TF) network across early developmental stages of E. granulosus protoscoleces by performing in silico analysis, and to experimentally validate TFs expression in protoscoleces obtained from in vitro culture, and from in vivo experiments.

RESULTS

We obtained list of 394 unique E. granulosus TFs and matched them with 818 differentially expressed genes which identified 41 predicted TFs with differential expression. These TFs were used to predict the potential targets of 31 differentially expressed miRNAs. As a result, eight miRNAs and eight TFs were found, and the predicted network was constructed using Cytoscape. At least four miRNAs (egr-miR-124a, egr-miR-124b-3p, egr-miR-745-3p, and egr-miR-87-3p) and their corresponding differentially expressed TFs (Zinc finger protein 45, Early growth response protein 3, Ecdysone induced protein 78c and ETS transcription factor elf 2) were highlighted in this investigation. The expression of predicted differentially expressed TFs obtained from in vitro and in vivo experiments, were experimentally validated by quantitative polymerase chain reaction. This confirmed findings of RNA-seq data.

CONCLUSION

miRNA-TF networks presented in this study control some of the most important metabolic and signaling pathways in the development and life cycle of E. granulosus, providing a potential approach for disrupting the early hours of dog infection and preventing the development of the helminth in the final host.

MicroRNA-profiling of miR-371~373- and miR-302/367-clusters in serum and cerebrospinal fluid identify patients with intracranial germ cell tumors

PURPOSE

Intracranial germ cell tumors (iGCT) comprise germinoma and non-germinoma. Their diagnosis predominantly relies on biopsy as only one-fifth of patients present with elevated biomarkers (AFP/ß-HCG) in serum or cerebrospinal fluid (CSF). MicroRNAs (miR/miRNA) have emerged as non-invasive biomarkers in extracranial GCT and may potentially facilitate non-invasive diagnosis in iGCT.

METHODS

We analyzed eight miRNAs in serum and CSF from the miR-371~373- and miR-302/367-clusters and four miRNAs differentially expressed in iGCT tissue (miR-142-5p/miR-146a-5p/miR-335-5p/miR-654-3p) from eight iGCT patients (age 10-33 years) and 12 control subjects by pre-amplified RT-qPCR. MiR-30b-5p (serum) and miR-204-5p (CSF) acted as reference genes. ΔCt-values were expressed as [Formula: see text] after standardization against controls.

RESULTS

Between iGCT and control patients' serum ΔCt-values of miR-371a-3p (p = 0.0159), miR-372-3p (p= 0.0095, miR-367 (p = 0.0190), miR-302a (p = 0.0381) and miR-302d-3p (p = 0.0159) differed significantly. Discriminatory pattern in CSF was similar to serum as miR-371a (p = 0.0286), miR-372-3p (p = 0.0028), miR-367-3p (p = 0.0167) and miR-302d-3p (p = 0.0061) distinguished between patients and controls. Abundant [Formula: see text] levels of each of these miRNAs were found across all serum and CSF samples including biomarker-negative patients.

CONCLUSION

With the largest data set so far, we underline the suitability of miR-371a, miR-372, miR-367 and miR-302d in serum and CSF for diagnosis of iGCT, particularly in biomarker-negative germinoma. Diagnosis of iGCT by miRNA analysis is a feasible and valid approach, particularly as serum can be readily obtained by a less invasive procedure. MiRNA analysis may discriminate iGCT from other tumors with similar radiological findings and may allow to monitor response to therapy as well as early relapse during follow-up.

Identification of a survival associated gene trio in chemical induced breast cancer

Sporadic cases of breast cancer being more prevalent than the hereditary cases, can be largely attributed to environmental pollutants like polycyclic aromatic hydrocarbons (PAHs). The aim of the present study was to identify gene dysregulations and the associations in DMBA (a PAH) induced breast cancer. A breast cancer model was developed in Wistar rats (n = 40), using DMBA. Serum proteomics (2D electrophoresis and MALDI-TOF MS) followed by relative gene expression analysis in mammary glands were conducted to reach to the differential gene signatures. The candidate genes were subjected to survival analysis (by GEPIA2 and KM plotter) and infiltration analysis (by ImmuCellAI) for correlating gene expression with patient survival and immune cell infiltration respectively. Further, the regulatory network investigation (by Cytoscape) was performed to find out the transcription factors (TFs) and miRNAs of the concerned genes. A gene trio (ANXA5, MTG1, PPP2R5B), expressing differentially in early mammary carcinogenesis at 4 months (precancerous stage) till full-fledged cancerous stage (post 6 months) was identified. The altered gene expression was associated with less survival among breast cancer patients (n = 4019). The dysregulated expression also has a correlation with enhanced mammary infiltration of immune cells. Moreover, a regulatory network (comprising of 77 transcription factors and 50 miRNAs) involved in the regulation of candidate genes was also deciphered. The deregulated target genes can therefore be explored for reregulation via identified TFs and miRNAs, and survival thereby improved.

Receptors that bind to PEDF and their therapeutic roles in retinal diseases

Retinal neovascular, neurodegenerative, and inflammatory diseases represented by diabetic retinopathy are the main types of blinding eye disorders that continually cause the increased burden worldwide. Pigment epithelium-derived factor (PEDF) is an endogenous factor with multiple effects including neurotrophic activity, anti-angiogenesis, anti-tumorigenesis, and anti-inflammatory activity. PEDF activity depends on the interaction with the proteins on the cell surface. At present, seven independent receptors, including adipose triglyceride lipase, laminin receptor, lipoprotein receptor-related protein, plexin domain-containing 1, plexin domain-containing 2, F1-ATP synthase, and vascular endothelial growth factor receptor 2, have been demonstrated and confirmed to be high affinity receptors for PEDF. Understanding the interactions between PEDF and PEDF receptors, their roles in normal cellular metabolism and the response the initiate in disease will be accommodating for elucidating the ways in which inflammation, angiogenesis, and neurodegeneration exacerbate disease pathology. In this review, we firstly introduce PEDF receptors comprehensively, focusing particularly on their expression pattern, ligands, related diseases, and signal transduction pathways, respectively. We also discuss the interactive ways of PEDF and receptors to expand the prospective understanding of PEDF receptors in the diagnosis and treatment of retinal diseases.

Development of Computational Correlations among Known Drug Scaffolds and their Target-Specific Non-Coding RNA Scaffolds of Alzheimer's Disease

BACKGROUND

Alzheimer's disease is the most common neurodegenerative disorder. Recent development in sciences has also identified the pivotal role of microRNAs (miRNAs) in AD pathogenesis.

OBJECTIVES

We proposed a novel method to identify AD pathway-specific statistically significant miRNAs from the targets of known AD drugs. Moreover, microRNA scaffolds and corresponding drug scaffolds of different pathways were also discovered.

MATERIAL AND METHODS

A Wilcoxon signed-rank test was performed to identify pathway-specific significant miRNAs. We generated feed-forward loop regulations of microRNA-TF-gene-based networks, studied the minimum free energy structures of pre-microRNA sequences, and clustered those microRNAs with their corresponding structural motifs of robust transcription factors. Conservation analyses of significant microRNAs were done, and the phylogenetic trees were constructed. We identified 3'UTR binding sites and chromosome locations of these significant microRNAs.

RESULTS

In this study, hsa-miR-4261, hsa-miR-153-5p, hsa-miR-6766, and hsa-miR-4319 were identified as key miRNAs for the ACHE pathway and hsa-miR-326, hsa-miR-6133, hsa-miR-4251, hsa-miR-3148, hsa-miR-10527-5p, hsa-miR-527, and hsa-miR-518a were identified as regulatory miRNAs for the NMDA pathway. These miRNAs were regulated by several AD-specific TFs, namely RAD21, FOXA1, and ESR1. It has been observed that anisole and adamantane are important chemical scaffolds to regulate these significant miRNAs.

CONCLUSION

This is the first study that developed a detailed correlation between known AD drug scaffolds and their AD target-specific miRNA scaffolds. This study identified chromosomal locations of microRNAs and corresponding structural scaffolds of transcription factors that may be responsible for miRNA co-regulation for Alzheimer's disease. Our study provides hope for therapeutic improvements in the existing microRNAs by regulating pathways and targets.

Metabolic reprogramming by miRNAs in the tumor microenvironment: Focused on immunometabolism

MicroRNAs (miRNAs) are emerging as a significant modulator of immunity, and their abnormal expression/activity has been linked to numerous human disorders, such as cancer. It is now known that miRNAs potentially modulate the production of several metabolic processes in tumor-associated immune cells and indirectly via different metabolic enzymes that affect tumor-associated signaling cascades. For instance, Let-7 has been identified as a crucial modulator for the long-lasting survival of CD8+ T cells (naive phenotypes) in cancer by altering their metabolism. Furthermore, in T cells, it has been found that enhancer of zeste homolog 2 (EZH2) expression is controlled via glycolytic metabolism through miRNAs in patients with ovarian cancer. On the other hand, immunometabolism has shown us that cellular metabolic reactions and processes not only generate ATP and biosynthetic intermediates but also modulate the immune system and inflammatory processes. Based on recent studies, new and encouraging approaches to cancer involving the modification of miRNAs in immune cell metabolism are currently being investigated, providing insight into promising targets for therapeutic strategies based on the pivotal role of immunometabolism in cancer. Throughout this overview, we explore and describe the significance of miRNAs in cancer and immune cell metabolism.

A comparative mRNA- and miRNA transcriptomics reveals novel molecular signatures associated with metastatic prostate cancers

Background: Prostate cancer (PC) is a fatally aggressive urogenital cancer killing millions of men, globally. Thus, this study aims to identify key miRNAs, target genes, and drug targets associated with prostate cancer metastasis.

Methods: The miRNA and mRNA expression datasets of 148 prostate tissue biopsies (39 tumours and 109 normal tissues), were analysed by differential gene expression analysis, protein interactome mapping, biological pathway analysis, miRNA-mRNA networking, drug target analysis, and survival curve analysis.

Results: The dysregulated expression of 53 miRNAs and their 250 target genes involved in Hedgehog, ErbB, and cAMP signalling pathways connected to cell growth, migration, and proliferation of prostate cancer cells was detected. The subsequent miRNA-mRNA network and expression status analysis have helped us in narrowing down their number to 3 hub miRNAs (hsa-miR-455-3p, hsa-miR-548c-3p, and hsa-miR-582-5p) and 9 hub genes (NFIB, DICER1, GSK3B, DCAF7, FGFR1OP, ABHD2, NACC2, NR3C1, and FGF2). Further investigations with different systems biology methods have prioritized NR3C1, ABHD2, and GSK3B as potential genes involved in prostate cancer metastasis owing to their high mutation load and expression status. Interestingly, down regulation of NR3C1 seems to improve the prostate cancer patient survival rate beyond 150 months. The NR3C1, ABHD2, and GSK3B genes are predicted to be targeted by hsa-miR-582-5p, besides some antibodies, PROTACs and inhibitory molecules.

Conclusion: This study identified key miRNAs (miR-548c-3p and miR-582-5p) and target genes (NR3C1, ABHD2, and GSK3B) as potential biomarkers for metastatic prostate cancers from large-scale gene expression data using systems biology approaches.

Discovering Common Pathogenic Mechanisms of COVID-19 and Parkinson Disease: An Integrated Bioinformatics Analysis

Coronavirus disease 2019 (COVID-19) has emerged since December 2019 and was later characterized as a pandemic by WHO, imposing a major public health threat globally. Our study aimed to identify common signatures from different biological levels to enlighten the current unclear association between COVID-19 and Parkinson's disease (PD) as a number of possible links, and hypotheses were reported in the literature. We have analyzed transcriptome data from peripheral blood mononuclear cells (PBMCs) of both COVID-19 and PD patients, resulting in a total of 81 common differentially expressed genes (DEGs). The functional enrichment analysis of common DEGs are mostly involved in the complement system, type II interferon gamma (IFNG) signaling pathway, oxidative damage, microglia pathogen phagocytosis pathway, and GABAergic synapse. The protein-protein interaction network (PPIN) construction was carried out followed by hub detection, revealing 10 hub genes (MX1, IFI27, C1QC, C1QA, IFI6, NFIX, C1S, XAF1, IFI35, and ELANE). Some of the hub genes were associated with molecular mechanisms such as Lewy bodies-induced inflammation, microglia activation, and cytokine storm. We investigated regulatory elements of hub genes at transcription factor and miRNA levels. The major transcription factors regulating hub genes are SOX2, XAF1, RUNX1, MITF, and SPI1. We propose that these events may have important roles in the onset or progression of PD. To sum up, our analysis describes possible mechanisms linking COVID-19 and PD, elucidating some unknown clues in between.

Transcriptome and Metabolome Analysis of Color Changes during Fruit Development of Pepper (Capsicum baccatum)

Fruit color is one of the most critical characteristics of pepper. In this study, pepper (Capsicum baccatum L.) fruits with four trans-coloring periods were used as experimental materials to explore the color conversion mechanism of pepper fruit. By transcriptome and metabolome analysis, we identified a total of 307 flavonoid metabolites, 68 carotenoid metabolites, 29 DEGs associated with flavonoid biosynthesis, and 30 DEGs related to carotenoid biosynthesis. Through WGCNA (weighted gene co-expression network analysis) analysis, positively correlated modules with flavonoids and carotenoids were identified, and hub genes associated with flavonoid and carotenoid synthesis and transport were anticipated. We identified Pinobanksin, Naringenin Chalcone, and Naringenin as key metabolites in the flavonoid biosynthetic pathway catalyzed by the key genes chalcone synthase (CHS CQW23_29123, CQW23_29380, CQW23_12748), cinnamic acid 4-hydroxylase (C4H CQW23_16085, CQW23_16084), cytochrome P450 (CYP450 CQW23_19845, CQW23_24900). In addition, phytoene synthase (PSY CQW23_09483), phytoene dehydrogenase (PDS CQW23_11317), zeta-carotene desaturase (ZDS CQW23_19986), lycopene beta cyclase (LYC CQW23_09027), zeaxanthin epoxidase (ZEP CQW23_05387), 9-cis-epoxycarotenoid dioxygenase (NCED CQW23_17736), capsanthin/capsorubin synthase (CCS CQW23_30321) are key genes in the carotenoid biosynthetic pathway, catalyzing the synthesis of key metabolites such as Phytoene, Lycopene, β-carotene and ε-carotene. We also found that transcription factor families such as p450 and NBARC could play important roles in the biosynthesis of flavonoids and carotenoids in pepper fruits. These results provide new insights into the interaction mechanisms of genes and metabolites involved in the biosynthesis of flavonoids and carotenoids in pepper fruit leading to color changes in pepper fruit.

PTTG1/ZEB1 Axis Regulates E-Cadherin Expression in Human Seminoma

Simple Summary

Seminoma represents one of the most common neoplasms in Caucasian males between 15 and 40 years old. The molecular pathways underlying its clinical behavior are far from being understood yet. We previously demonstrated that nuclear Pituitary-tumor transforming-gene 1 (PTTG1), overexpressed in several neoplasms, promotes invasiveness through its transcriptional target matrix-metalloproteinase-2 (MMP2). PTTG1 sustains the migratory and invasive properties of cancer cells through the induction of the epithelial-to-mesenchymal transition (EMT). E-Cadherin (E-CAD) repression is the first step of EMT. Therefore, we investigated the role of PTTG1 in EMT in human seminoma using an in vitro and in vivo model and through Atlas database interrogation. Our data showed a PTTG1-mediated E-CAD transcriptional repression through Zinc finger E-box binding homeobox 1 (ZEB1), a master regulator of the EMT process. Our data provide insights into the molecular characterization of seminoma, promoting PTTG1 as a prognostic marker useful in human seminoma clinical management.

Abstract

(1) Background: PTTG1 sustains the EMT process and the invasiveness of several neoplasms. We previously showed the role of nuclear PTTG1 in promoting invasiveness, through its transcriptional target MMP2, in seminoma in vitro models. Here, we investigated the key players involved in PTTG1-mediated EMT in human seminoma. (2) Methods: Two seminoma cell lines and four human seminoma tumor specimens were used. E-Cadherin gene regulation was investigated using Western blot, real-time PCR, and luciferase assay. Immunoprecipitation, ChIP, RE-ChIP, and confocal microscopy analysis were performed to evaluate the interplay between PTTG1 and ZEB1. Matrigel invasion and spheroid formation assays were applied to functionally investigate PTTG1 involvement in the EMT of seminoma cell lines. RNA depletion and overexpression experiments were performed to verify the role of PTTG1/ZEB1 in E-Cadherin repression and seminoma invasiveness. E-Cadherin and ZEB1 levels were analyzed in human testicular tumors from the Atlas database. (3) Results: PTTG1 transcriptionally represses E-Cadherin in seminoma cell lines through ZEB1. The cooperation of PTTG1 with ZEB1 has a significant impact on cell growth/invasion properties involving the EMT process. Analysis of the Atlas database of testicular tumors showed significantly lower E-Cadherin levels in seminoma, where PTTG1 showed nuclear staining. Finally, PTTG1 and ZEB1 strongly localize together in the periphery of the tumors. (4) Conclusions: These results strengthen the evidence for a role of PTTG1 in the EMT process in human seminomas through its cooperation with the transcriptional repressor ZEB1 on the E-Cadherin gene. Our data enrich the molecular characterization of seminoma, suggesting that PTTG1 is a prognostic factor in seminoma clinical management.

Deciphering the role of predicted miRNAs of polyomaviruses in carcinogenesis

Human polyomaviruses are relatively common in the general population. Polyomaviruses maintain a persistent infection after initial infection in childhood, acting as an opportunistic pathogen in immunocompromised populations and their association has been linked to carcinogenesis. A comprehensive understanding of the underlying molecular mechanisms of carcinogenesis in consequence of polyomavirus infection remains elusive. However, the critical role of viral miRNAs and their potential targets in modifying the transcriptome profile of the host remains largely unknown. Polyomavirus-derived miRNAs have the potential to play a substantial role in carcinogenesis. Employing computational approaches, putative viral miRNAs along with their target genes have been predicted and possible roles of the targeted genes in many significant biological processes have been obtained. Polyomaviruses have been observed to target intracellular signal transduction pathways through miRNA-mediated epigenetic regulation, which may contribute to cancer development. In addition, BKPyV-infected human renal cell microarray data was coupled with predicted target genes and analysis of the downregulated genes indicated that viruses target multiple signaling pathways (e.g. MAPK signaling pathway, PI3K-Akt signaling pathway, PPAR signaling pathway) in the host as well as turning off several tumor suppression genes (e.g. FGGY, EPHX2, CACNA2D3, CDH16) through miRNA-induced mechanisms, assuring cell transformation. This study provides a conceptual framework for the underlying molecular mechanisms involved in the course of carcinogenesis upon polyomavirus infection.

Genomic variants disrupt miRNA-mRNA regulation

Micro RNA (miRNA) and its regulatory effect on messenger RNA (mRNA) gene expression are a major focus in cancer research. Disruption in the normal miRNA-mRNA regulation network can result in serious cascading biological repercussions. In this study, we curated miRNA-related variants from major genomic consortiums and thoroughly evaluated how these variants could exert their effects by cross-validating with independent functional knowledge bases. Nearly all known variants (more than 664 million) categorized by type (germline, somatic, epigenetic) were mapped to the genomic regions involved in miRNA-mRNA binding (miRNA seeds and miRNA-mRNA 3'-UTR binding sequence). Subsets of miRNA-related variants supported by additional functional evidence, such as expression Quantitative Trait Loci (eQTL) and Genome-Wide Association Study (GWAS), were identified and scrutinized. Our results show that variants in miRNA seeds can substantially alter the composition of an miRNA's target mRNA set. Various functional analyses converged to reveal a post-transcriptional complex regulatory network where miRNA, eQTL, and RNA-binding protein intertwined to disseminate the impact of genomic variants. These results may potentially explain how certain variants affect disease/trait risks in genome wide association studies.

Upregulated GATA3/miR205-5p Axis Inhibits MFNG Transcription and Reduces the Malignancy of Triple-Negative Breast Cancer

Simple Summary

Triple-negative cancer (TNBC) is a deadly disease that presents a potential health threat to women worldwide. It is the most aggressive and presents a poor prognosis among all breast cancer subgroups. We previously demonstrated that the elevated expression of manic fringe (MFNG) plays a pivotal role in breast cancer. However, the mechanism through which MFNG is regulated remains obscure. The study presented here set out to determine the mechanism by which MFNG expression is regulated in TNBC. Our findings revealed that GATA3 and miR-205-p cooperatively block the transcription of MFNG leading to the inhibition of cell migration and tumor growth in vitro and in vivo. Our study uncovers a novel GATA3/miR-205-p/MFNG feed-forward loop and miR205-5p could be adopted as a potential therapeutic strategy of TNBC.

Abstract

Triple-negative breast cancer (TNBC) accounts for approximately 20% of all breast carcinomas and has the worst prognosis of all breast cancer subtypes due to the lack of an effective target. Therefore, understanding the molecular mechanism underpinning TNBC progression could explore a new target for therapy. While the Notch pathway is critical in the development process, its dysregulation leads to TNBC initiation. Previously, we found that manic fringe (MFNG) activates the Notch signaling and induces breast cancer progression. However, the underlying molecular mechanism of MFNG upstream remains unknown. In this study, we explore the regulatory mechanisms of MFNG in TNBC. We show that the increased expression of MFNG in TNBC is associated with poor clinical prognosis and significantly promotes cell growth and migration, as well as Notch signaling activation. The mechanistic studies reveal that MFNG is a direct target of GATA3 and miR205-5p and demonstrate that GATA3 and miR205-5p overexpression attenuate MFNG oncogenic effects, while GATA3 knockdown mimics MFNG phenotype to promote TNBC progression. Moreover, we illustrate that GATA3 is required for miR205-5p activation to inhibit MFNG transcription by binding to the 3′ UTR region of its mRNA, which forms the GATA3/miR205-5p/MFNG feed-forward loop. Additionally, our in vivo data show that the miR205-5p mimic combined with polyetherimide-black phosphorus (PEI-BP) nanoparticle remarkably inhibits the growth of TNBC-derived tumors which lack GATA3 expression. Collectively, our study uncovers a novel GATA3/miR205-5p/MFNG feed-forward loop as a pathway that could be a potential therapeutic target for TNBC.

Esrrb Regulates Specific Feed-Forward Loops to Transit From Pluripotency Into Early Stages of Differentiation

Characterization of pluripotent states, in which cells can both self-renew or differentiate, with the irreversible loss of pluripotency, are important research areas in developmental biology. Although microRNAs (miRNAs) have been shown to play a relevant role in cellular differentiation, the role of miRNAs integrated into gene regulatory networks and its dynamic changes during these early stages of embryonic stem cell (ESC) differentiation remain elusive. Here we describe the dynamic transcriptional regulatory circuitry of stem cells that incorporate protein-coding and miRNA genes based on miRNA array expression and quantitative sequencing of short transcripts upon the downregulation of the Estrogen Related Receptor Beta (Esrrb). The data reveals how Esrrb, a key stem cell transcription factor, regulates a specific stem cell miRNA expression program and integrates dynamic changes of feed-forward loops contributing to the early stages of cell differentiation upon its downregulation. Together these findings provide new insights on the architecture of the combined transcriptional post-transcriptional regulatory network in embryonic stem cells.

Potential Small Molecules for Therapy of Lupus Nephritis Based on Genetic Effect and Immune Infiltration

Lupus nephritis (LN) is the most common and significant complication of systemic lupus erythematosus (SLE) due to its poor prognosis and mortality rates in SLE patients. There is a critical need for new drugs as the pathogenesis of LN remains to be elucidated and immunosuppressive therapy comes with many deficiencies. In this study, 23 hub genes (IFI6, PLSCR1, XAF1, IFI16, IFI44, MX1, IFI44L, IFIT3, IFIT2, IFI27, DDX58, EIF2AK2, IFITM1, RTP4, IFITM3, TRIM22, PARP12, IFIH1, OAS1, HERC6, RSAD2, DDX60, and MX2) were identified through bioinformatics and network analysis and are closely related to interferon production and function. Interestingly, immune cell infiltration analysis and correlation analysis demonstrate a positive correlation between the expression of 23 hub genes and monocyte infiltration in glomeruli and M2 macrophage infiltration in the tubulointerstitium of LN patients. Additionally, the CTD database, DsigDB database, and DREIMT database were used to explore the bridging role of genes in chemicals and LN as well as the potential influence of these chemicals on immune cells. After comparison and discussion, six small molecules (Acetohexamide, Suloctidil, Terfenadine, Prochlorperazine, Mefloquine, and Triprolidine) were selected for their potential ability in treating lupus nephritis.

A Deep Learning-Based Framework for Supporting Clinical Diagnosis of Glioblastoma Subtypes

Understanding molecular features that facilitate aggressive phenotypes in glioblastoma multiforme (GBM) remains a major clinical challenge. Accurate diagnosis of GBM subtypes, namely classical, proneural, and mesenchymal, and identification of specific molecular features are crucial for clinicians for systematic treatment. We develop a biologically interpretable and highly efficient deep learning framework based on a convolutional neural network for subtype identification. The classifiers were generated from high-throughput data of different molecular levels, i.e., transcriptome and methylome. Furthermore, an integrated subsystem of transcriptome and methylome data was also used to build the biologically relevant model. Our results show that deep learning model outperforms the traditional machine learning algorithms. Furthermore, to evaluate the biological and clinical applicability of the classification, we performed weighted gene correlation network analysis, gene set enrichment, and survival analysis of the feature genes. We identified the genotype-phenotype relationship of GBM subtypes and the subtype-specific predictive biomarkers for potential diagnosis and treatment.

Integrative global co-expression analysis identifies Key MicroRNA-target gene networks as key blood biomarkers for obesity

Obesity is associated with the quantitative changes in miRNAs and their target genes. However, the molecular basis of their dysregulation and expression status correlations is incompletely understood. Therefore, this study aims to examine the shared differentially expressed miRNAs and their target genes between blood and adipose tissues of obese individuals to identify potential blood-based biomarkers. In this study, 3 gene expression datasets (two mRNA and one miRNA), generated from blood and adipose tissues of 68 obese and 39 lean individuals, were analyzed by a series of robust computational concepts, like protein interactome mapping, functional enrichment of biological pathways and construction of miRNA-mRNA and transcription factor gene networks. The comparison of blood versus tissue datasets has revealed the shared differential expression of 210 genes (59.5% upregulated) involved in lipid metabolism and inflammatory reactions. The blood miRNA (GSE25470) analysis has identified 79 differentially expressed miRNAs (71% downregulated). The miRNA-target gene scan identified regulation of 30 shared genes by 22miRNAs. The gene network analysis has identified the inverse expression correlation between 8 target genes (TP53, DYSF, GAB2, GFRA2, NACC2, FAM53C, JNK and GAB2) and 3 key miRNAs (hsa-mir-940, hsa-mir-765, hsa-mir-612), which are further regulated by 24 key transcription factors. This study identifies potential obesity related blood biomarkers from largescale gene expression data by computational miRNA-target gene interactome and transcription factor network construction methods.

A Novel Graph Topology-Based GO-Similarity Measure for Signature Detection From Multi-Omics Data and its Application to Other Problems

Large scale multi-omics data analysis and signature prediction have been a topic of interest in the last two decades. While various traditional clustering/correlation-based methods have been proposed, but the overall prediction is not always satisfactory. To solve these challenges, in this article, we propose a new approach by leveraging the Gene Ontology (GO)similarity combined with multiomics data. In this article, a new GO similarity measure, ModSchlicker, is proposed and the effectiveness of the proposed measure along with other standardized measures are reviewed while using various graph topology-based Information Content (IC)values of GO-term. The proposed measure is deployed to PPI prediction. Furthermore, by involving GO similarity, we propose a new framework for stronger disease-based gene signature detection from the multi-omics data. For the first objective, we predict interaction from various benchmark PPI datasets of Yeast and Human species. For the latter, the gene expression and methylation profiles are used to identify Differentially Expressed and Methylated (DEM)genes. Thereafter, the GO similarity score along with a statistical method are used to determine the potential gene signature. Interestingly, the proposed method produces a better performance ( 0.9 avg. accuracy and 0.95 AUC)as compared to the other existing related methods during the classification of the participating features (genes)of the signature. Moreover, the proposed method is highly useful in other prediction/classification problems for any kind of large scale omics data.

Association of pigment epithelium derived factor expression with cancer progression and prognosis: a meta-analysis study

BACKGROUND

Pigment epithelium derived factor (PEDF) is a secreted protein that strongly suppresses angiogenesis and directly inhibits cancer cells proliferation. The differential expression of PEDF has been observed in multiple types of human tumors. However, it is unclear as to how PEDF expression is associated with cancer progression and if PEDF could serve as a prognostic marker for cancer patients.

METHODS

We performed a comprehensive search for the studies on PEDF expression in 14 top-ranked types of solid tumor cancer with the highest incidence. A systemic approach was used to screen for qualified studies and to extract data. Meta-analysis was performed to investigate if PEDF expression is associated with the TNM staging, tumor size, lymph node invasion, distal metastasis and pathological grade of tumor in a pan-cancer manner. A Kaplan-Meier curve was plotted with the digitally-reconstituted patient survival data to study the effect of PEDF expression on the prognosis of cancer patients.

RESULTS

A total of nine studies were selected, reviewed and analyzed. Meta-analysis suggested that decreased PEDF protein expression was associated with higher TNM staging (OR = 2.13, 95% CI: 1.61-2.81), larger tumor size (OR = 1.42, 95% CI: 1.1-1.84), larger possibility of lymph node invasion (OR = 1.68, 95% CI: 1.26-2.22) and higher pathological grade (OR = 1.6, 95% CI: 1.2-2.13). No correlation was found between PEDF expression and tumor distal metastasis, gender or age. In addition, low PEDF protein level in tumor tissue is correlated with shorter overall survival (P < 0.05).

CONCLUSIONS

Low PEDF protein expression in cancer is significantly associated with more advanced cancer progression and significantly poorer survival. The differential clinical outcome among patients with various PEDF expression suggests its prognostic value.

In-Silico Analysis of rSNPsin miRNA:mRNA Duplex Involved in Insulin Signaling Genes Shows a Possible Pathogenesis of Insulin Resistance

BACKGROUND

Insulin resistance is a condition in which the body produces insulin but is unable to use it effectively. Aberrations in insulin signaling are known to play a crucial role in pathogenesis of this disease state. Eventually patients will have glucose build up in their blood instead of being absorbed by the cells, leading to type 2 diabetes.

OBJECTIVE

In the current study we focus on understanding the role of rSNP mediated miRNA:mRNA dysregulation and its impact on the above metabolic condition.

METHODS

More than 30 genes involved in insulin signaling pathway were found using KEGG database. The 3'UTR end of genes was studied by using RegRNA and Ensembl, whereas TargetScan along with miRbase were used to identify their target miRNAs.Binding free energy was used as a parameter to analyze the affect of polymorphism on the miRNA:mRNA duplex formation.Further, UNA fold was used to determine the heat capacity changes.

RESULTS

The following genes INSR, INS, GLUT4, FOXO1, IL6, TRIB3 and SREBF1 were selected for analysis. Multiple miRNAs, hsa-miR-16-5p, hsa-miR-15a-15p were identified in the SNP occurring region for INSR. INS too showed similar results.INSR, INS and TRIB3 were found to have the maximum change in their binding free energy due to rSNP variation. A destabilisation in the heat capacity values was observed too, contributed due to rSNP induction.

CONCLUSION

A direct relationship between miRNA target polymorphism and the stability of the miRNA:mRNA duplex was observed. The current methodology used to study insulin resistance pathogenesis could elaborate on our existing knowledge of miRNA mediated disease states.

Identifying Hub Genes, Key Pathways and Immune Cell Infiltration Characteristics in Pediatric and Adult Ulcerative Colitis by Integrated Bioinformatic Analysis

BACKGROUND AND AIMS

In the present study, we investigated the differentially expressed genes (DEGs), pathways and immune cell infiltration characteristics of pediatric and adult ulcerative colitis (UC).

METHODS

We conducted DEG analysis using the microarray dataset GSE87473 containing 19 pediatric and 87 adult UC samples downloaded from the Gene Expression Omnibus. Gene ontology and pathway enrichment analyses were conducted using Metascape. We constructed the protein-protein interaction (PPI) network and the drug-target interaction network of DEGs and identified hub modules and genes using Cytoscape and analyzed immune cell infiltration in pediatric and adult UC using CIBERSORT.

RESULTS

In total, 1700 DEGs were screened from the dataset. These genes were enriched mainly in inter-cellular items relating to cell junctions, cell adhesion, actin cytoskeleton and transmembrane receptor signaling pathways and intra-cellular items relating to the splicing, metabolism and localization of RNA. CDC42, POLR2A, RAC1, PIK3R1, MAPK1 and SRC were identified as hub DEGs. Immune cell infiltration analysis revealed higher proportions of naive B cells, resting memory T helper cells, regulatory T cells, monocytes, M0 macrophages and activated mast cells in pediatric UC, along with lower proportions of memory B cells, follicular helper T cells, γδ T cells, M2 macrophages, and activated dendritic cells.

CONCLUSIONS

Our study suggested that hub genes CDC42, POLR2A, RAC1, PIK3R1, MAPK1 and SRC and immune cells including B cells, T cells, monocytes, macrophages and mast cells play vital roles in the pathological differences between pediatric and adult UC and may serve as potential biomarkers in the diagnosis and treatment of UC.

Whole-exome sequencing reveals potential germline and somatic mutations in 60 malignant ovarian germ cell tumors†

Malignant ovarian germ cell tumors (MOGCTs) are rare and heterogeneous ovary tumors. We aimed to identify potential germline mutations and somatic mutations in MOGCTs by whole-exome sequencing. The peripheral blood and tumor samples from these patients were used to identify germline mutations and somatic mutations, respectively. For those genes with copy number alterations (deletion and duplication region), functional annotation was performed. Immunohistochemistry was performed to evaluate the expression of mutated genes corresponding to CNA deletion region and duplication region. In peripheral blood, copy number loss and gain were mostly found in yolk sac tumors (YSTs). Moreover, POU5F1 was the most significant mutated gene with mutation frequency >10% in both CNA deletion and duplication region. In addition, strong cytoplasm staining of POU5F1 (corresponding to CNA deletion region and duplication region) was found in two YST and nuclear staining in two dysgerminomas tumor samples. Genes corresponding to CNA deletion region were significantly enriched in the signaling pathway of regulating pluripotency of stem cells. In addition, genes corresponding to CNA duplication region were significantly enriched in the signaling pathways of RIG-I (DExD/H-box helicase 58)-like receptor, Toll-like receptor and nuclear factor (NF)-kappa. Keratin 4 (KRT4), ribosomal protein L14 (RPL14), proprotein convertase subtilisin/kexin type 6 (PCSK6), poly(A)-binding protein cytoplasmic 3 (PABPC3), and sterile alpha and TIR motif containing 1 (SARM1) mutations were detected in both peripheral blood and tumor samples. Identification of potential germline mutations and somatic mutations in MOGCTs may provide a new field in understanding the genetic feature of the rare biological tumor type in the ovary.

Computational learning of features for automated colonic polyp classification

Shape, texture, and color are critical features for assessing the degree of dysplasia in colonic polyps. A comprehensive analysis of these features is presented in this paper. Shape features are extracted using generic Fourier descriptor. The nonsubsampled contourlet transform is used as texture and color feature descriptor, with different combinations of filters. Analysis of variance (ANOVA) is applied to measure statistical significance of the contribution of different descriptors between two colonic polyps: non-neoplastic and neoplastic. Final descriptors selected after ANOVA are optimized using the fuzzy entropy-based feature ranking algorithm. Finally, classification is performed using Least Square Support Vector Machine and Multi-layer Perceptron with five-fold cross-validation to avoid overfitting. Evaluation of our analytical approach using two datasets suggested that the feature descriptors could efficiently designate a colonic polyp, which subsequently can help the early detection of colorectal carcinoma. Based on the comparison with four deep learning models, we demonstrate that the proposed approach out-performs the existing feature-based methods of colonic polyp identification.

Mechanistic dissection of diabetic retinopathy using the protein-metabolite interactome

Purpose

The current study aims to determine the molecular mechanisms of diabetic retinopathy (DR) using the protein-protein interactome and metabolome map. We examined the protein network of novel biomarkers of DR for direct (physical) and indirect (functional) interactions using clinical target proteins in different models.

Methods

We used proteomic tools including 2-dimensional gel electrophoresis, mass spectrometry analysis, and database search for biomarker identification using in vivo murine and human model of diabetic retinopathy and in vitro model of oxidative stress. For the protein interactome and metabolome mapping, various bioinformatic tools that include STRING and OmicsNet were used.

Results

We uncovered new diabetic biomarkers including prohibitin (PHB), dynamin 1, microtubule-actin crosslinking factor 1, Toll-like receptor (TLR 7), complement activation, as well as hypothetical proteins that include a disintegrin and metalloproteinase (ADAM18), vimentin III, and calcium-binding C2 domain-containing phospholipid-binding switch (CAC2PBS) using a proteomic approach. Proteome networks of protein interactions with diabetic biomarkers were established using known DR-related proteome data. DR metabolites were interconnected to establish the metabolome map. Our results showed that mitochondrial protein interactions were changed during hyperglycemic conditions in the streptozotocin-treated murine model and diabetic human tissue.

Conclusions

Our interactome mapping suggests that mitochondrial dysfunction could be tightly linked to various phases of DR pathogenesis including altered visual cycle, cytoskeletal remodeling, altered lipid concentration, inflammation, PHB depletion, tubulin phosphorylation, and altered energy metabolism. The protein-metabolite interactions in the current network demonstrate the etiology of retinal degeneration and suggest the potential therapeutic approach to treat DR.

Nuclear Localization of PTTG1 Promotes Migration and Invasion of Seminoma Tumor through Activation of MMP-2

Simple Summary

Seminoma is the most common subtype of testicular germ cell tumors (TGCTs) and its molecular patterns have not been clarified. The pituitary tumor-transforming gene 1 (PTTG1) is a securin and its overexpression is reported in many cancers. We previously demonstrated that PTTG1 is mainly localized at the neoplasm periphery and infiltration area of seminoma. Therefore, we aim to investigate in vitro the role of PTTG1 on the invasive properties of seminoma. Our results elucidate the role of nuclear PTTG1 in promoting invasiveness and the metastatic process of these cells through its transcriptional target matrix-metalloproteinase-2 (MMP-2). Analysis of human testicular tumors from the Atlas database revealed an exclusive PTTG1 nuclear localization and a concomitant increase of MMP-2 levels in seminoma compared to non-seminoma tumors. Our data provide insights into the molecular characterization of seminoma, promoting PTTG1 as a prognostic marker useful in human seminoma clinical management.

Abstract

(1) Background: PTTG1 sustains the invasiveness of several cancer types. We previously reported that in seminomas, PTTG1 was detected in the peripheral area of the tumor and in the leading infiltrative edge. Here, we investigate the PTTG1 role on the invasive properties of seminoma. (2) Methods: three seminoma cell lines were used as in vitro model. PTTG1 levels and localization were investigated by biochemical and immunofluorescence analyses. Wound-healing, Matrigel invasion assays, and zymography were applied to study migratory and invasive capability of the cell lines. RNA interference and overexpression experiments were performed to address the PTTG1 role in seminoma invasiveness. PTTG1 and its target MMP-2 were analyzed in human testicular tumors using the Atlas database. (3) Results: PTTG1 was highly and differentially expressed in the seminoma cell lines. Nuclear PTTG1 was positively correlated to the aggressive phenotype. Its modulation confirms these results. Atlas database analysis revealed that PTTG1 was localized in the nucleus in seminoma compared with non-seminoma tumors, and that MMP-2 levels were significantly higher in seminomas. (4) Conclusions: nuclear PTTG1 promotes invasiveness of seminoma cell lines. Atlas database supported these results. These data lead to the hypothesis that nuclear PTTG1 is an eligible prognostic factor in seminomas.

In silico ranking of phenolics for therapeutic effectiveness on cancer stem cells

BACKGROUND

Cancer stem cells (CSCs) have features such as the ability to self-renew, differentiate into defined progenies and initiate the tumor growth. Treatments of cancer include drugs, chemotherapy and radiotherapy or a combination. However, treatment of cancer by various therapeutic strategies often fail. One possible reason is that the nature of CSCs, which has stem-like properties, make it more dynamic and complex and may cause the therapeutic resistance. Another limitation is the side effects associated with the treatment of chemotherapy or radiotherapy. To explore better or alternative treatment options the current study aims to investigate the natural drug-like molecules that can be used as CSC-targeted therapy. Among various natural products, anticancer potential of phenolics is well established. We collected the 21 phytochemicals from phenolic group and their interacting CSC genes from the publicly available databases. Then a bipartite graph is constructed from the collected CSC genes along with their interacting phytochemicals from phenolic group as other. The bipartite graph is then transformed into weighted bipartite graph by considering the interaction strength between the phenolics and the CSC genes. The CSC genes are also weighted by two scores, namely, DSI (Disease Specificity Index) and DPI (Disease Pleiotropy Index). For each gene, its DSI score reflects the specific relationship with the disease and DPI score reflects the association with multiple diseases. Finally, a ranking technique is developed based on PageRank (PR) algorithm for ranking the phenolics.

RESULTS

We collected 21 phytochemicals from phenolic group and 1118 CSC genes. The top ranked phenolics were evaluated by their molecular and pharmacokinetics properties and disease association networks. We selected top five ranked phenolics (Resveratrol, Curcumin, Quercetin, Epigallocatechin Gallate, and Genistein) for further examination of their oral bioavailability through molecular properties, drug likeness through pharmacokinetic properties, and associated network with CSC genes.

CONCLUSION

Our PR ranking based approach is useful to rank the phenolics that are associated with CSC genes. Our results suggested some phenolics are potential molecules for CSC-related cancer treatment.

A Linear Regression and Deep Learning Approach for Detecting Reliable Genetic Alterations in Cancer Using DNA Methylation and Gene Expression Data

DNA methylation change has been useful for cancer biomarker discovery, classification, and potential treatment development. So far, existing methods use either differentially methylated CpG sites or combined CpG sites, namely differentially methylated regions, that can be mapped to genes. However, such methylation signal mapping has limitations. To address these limitations, in this study, we introduced a combinatorial framework using linear regression, differential expression, deep learning method for accurate biological interpretation of DNA methylation through integrating DNA methylation data and corresponding TCGA gene expression data. We demonstrated it for uterine cervical cancer. First, we pre-filtered outliers from the data set and then determined the predicted gene expression value from the pre-filtered methylation data through linear regression. We identified differentially expressed genes (DEGs) by Empirical Bayes test using Limma. Then we applied a deep learning method, "nnet" to classify the cervical cancer label of those DEGs to determine all classification metrics including accuracy and area under curve (AUC) through 10-fold cross validation. We applied our approach to uterine cervical cancer DNA methylation dataset (NCBI accession ID: GSE30760, 27,578 features covering 63 tumor and 152 matched normal samples). After linear regression and differential expression analysis, we obtained 6287 DEGs with false discovery rate (FDR) <0.001. After performing deep learning analysis, we obtained average classification accuracy 90.69% (±1.97%) of the uterine cervical cancerous labels. This performance is better than that of other peer methods. We performed in-degree and out-degree hub gene network analysis using Cytoscape. We reported five top in-degree genes (PAIP2, GRWD1, VPS4B, CRADD and LLPH) and five top out-degree genes (MRPL35, FAM177A1, STAT4, ASPSCR1 and FABP7). After that, we performed KEGG pathway and Gene Ontology enrichment analysis of DEGs using tool WebGestalt(WEB-based Gene SeT AnaLysis Toolkit). In summary, our proposed framework that integrated linear regression, differential expression, deep learning provides a robust approach to better interpret DNA methylation analysis and gene expression data in disease study.

Molecular signatures identified by integrating gene expression and methylation in non-seminoma and seminoma of testicular germ cell tumours

Testicular germ cell tumours (TGCTs) are the most common cancer in young male adults (aged 15 to 40). Unlike most other cancer types, identification of molecular signatures in TGCT has rarely reported. In this study, we developed a novel integrative analysis framework to identify co-methylated and co-expressed genes [mRNAs and microRNAs (miRNAs)] modules in two TGCT subtypes: non-seminoma (NSE) and seminoma (SE). We first integrated DNA methylation and mRNA/miRNA expression data and then used a statistical method, CoMEx (Combined score of DNA Methylation and Expression), to assess differentially expressed and methylated (DEM) genes/miRNAs. Next, we identified co-methylation and co-expression modules by applying WGCNA (Weighted Gene Correlation Network Analysis) tool to these DEM genes/miRNAs. The module with the highest average Pearson's Correlation Coefficient (PCC) after considering all pair-wise molecules (genes/miRNAs) included 91 molecules. By integrating both transcription factor and miRNA regulations, we constructed subtype-specific regulatory networks for NSE and SE. We identified four hub miRNAs (miR-182-5p, miR-520b, miR-520c-3p, and miR-7-5p), two hub TFs (MYC and SP1), and two genes (RECK and TERT) in the NSE-specific regulatory network, and two hub miRNAs (miR-182-5p and miR-338-3p), five hub TFs (ETS1, HIF1A, HNF1A, MYC, and SP1), and three hub genes (CDH1, CXCR4, and SNAI1) in the SE-specific regulatory network. miRNA (miR-182-5p) and two TFs (MYC and SP1) were common hubs of NSE and SE. We further examined pathways enriched in these subtype-specific networks. Our study provides a comprehensive view of the molecular signatures and co-regulation in two TGCT subtypes.

SPANXN2 functions a cell migration inhibitor in testicular germ cell tumor cells

Background

SPANX family members are thought to play an important role in cancer progression. The SPANXN2 is a gene expressed mainly in normal testis, but its role in testicular germ cell tumors (TGCTs) has yet to be investigated. TGCT is one of the most common solid tumors in young men and is associated with poor prognosis; however, effective prognostic indicators remain elusive. Therefore, we investigated the role of SPANXN2 in TGCT development.

Methods

SPANXN2 expression levels were validated by quantitative real-time polymerase chain reaction (qRT-PCR) analyses of 14 TGCT samples and five adjacent normal tissue samples. SPANXN2 was transiently overexpressed in TGCT cells to study the consequences for cell function. The effects of SPANXN2 on cell migration were evaluated in transwell and wound healing assays. The effects on cloning ability were evaluated in colony formation assays. MTT assays and cell cycle analysis were used to detect the effects of SPANXN2 on cell proliferation. The expression levels of EMT- and AKT-related proteins in cells overexpressing SPANXN2 were analyzed by Western blotting.

Results

Compared with adjacent normal tissues, the Gene Expression Profiling Interactive Analysis database showed SPANXN2 expression was downregulated in TGCTs which was consistent with the qRT-PCR analysis. SPANXN2 overexpression reduced cell migration and colony formation capability and downregulated expression of EMT- and AKT-related proteins, Vimentin, Snail, AKT, and p-AKT.

Conclusion

Our results suggest that SPANXN2 regulates TGCT cell migration via EMT- and AKT-related proteins although its role in the occurrence and development of TGCT remains to be fully elucidated.