scholarly journals Micro RNA Transcriptome Profile in Canine Oral Melanoma

2019 ◽  
Author(s):  
Md. Mahfuzur Rahman ◽  
Yu-Chang Lai ◽  
Al Asmaul Husna ◽  
Hui-wen Chen ◽  
Yuiko Tanaka ◽  
...  
Keyword(s):  
Human Study ◽  
In Silico Analysis ◽  
Enrichment Analysis ◽  
Micro Rna ◽  
Therapeutic Interventions ◽  
Mirna Profile ◽  
Oral Melanoma ◽  
Cancer Pathogenesis ◽  
Metastatic Cells ◽  
Oncogenic Mirnas

MicroRNAs (miRNAs) dysregulation contribute the cancer pathogenesis. However, the miRNA profile of canine oral melanoma (COM), one of the frequent malignant melanoma in dog is still unrevealed. The aim of this study is to reveal the miRNA profile in canine oral melanoma. MicroRNAs profile of oral tissues from normal healthy dogs and COM patients were compared by next-generation sequencing. Along with tumour suppressor microRNAs (miRNAs), we report 30 oncogenic miRNAs in COM. Expression of miRNAs were further confirmed by quantitative real-time PCR (qPCR). Pathway analysis showed that deregulated miRNAs impact on cancer and signalling pathways. Three oncogenic miRNAs targets (miR-450b, 301a, and 223) from human study also were down-regulated in COM and had significant negative co-relation with their respective miRNA. Furthermore, we found that miR-450b expression is higher in metastatic cells and regulated MMP9 expression through a PAX9-BMP4-MMP9 axis. In silico analysis indicated that miR-126, miR-20b, and miR-106a regulated the highest numbers of differentially expressed transcription factors in respect to human melanoma. Chromosomal enrichment analysis revealed the X chromosome was enriched with oncogenic miRNAs. We comprehensively analyzed the miRNA’s profile in COM which will be a useful resource for developing therapeutic interventions in both species.

scholarly journals Micro RNA Transcriptome Profile in Canine Oral Melanoma

2019 ◽  
Vol 20 (19) ◽  
pp. 4832 ◽  
Author(s):  
Md. Mahfuzur Rahman ◽  
Yu-Chang Lai ◽  
Al Asmaul Husna ◽  
Hui-wen Chen ◽  
Yuiko Tanaka ◽  
...  
Keyword(s):  
Human Study ◽  
In Silico Analysis ◽  
Enrichment Analysis ◽  
Significant Negative Correlation ◽  
Micro Rna ◽  
Therapeutic Interventions ◽  
Mirna Profile ◽  
Oral Melanoma ◽  
Cancer Pathogenesis ◽  
Oncogenic Mirnas

MicroRNAs (miRNAs) dysregulation contribute the cancer pathogenesis. However, the miRNA profile of canine oral melanoma (COM), one of the frequent malignant melanoma in dogs is still unrevealed. The aim of this study is to reveal the miRNA profile in canine oral melanoma. MiRNAs profile of oral tissues from normal healthy dogs and COM patients were compared by next-generation sequencing. Along with tumour suppressor miRNAs, we report 30 oncogenic miRNAs in COM. The expressions of miRNAs were further confirmed by quantitative real-time PCR (qPCR). Pathway analysis showed that deregulated miRNAs impact on cancer and signalling pathways. Three oncogenic miRNAs targets (miR-450b, 301a, and 223) from human study also were down-regulated in COM and had a significant negative correlation with their respective miRNA. Furthermore, we found that miR-450b expression is higher in metastatic cells and regulated MMP9 expression through a PAX9-BMP4-MMP9 axis. In silico analysis indicated that miR-126, miR-20b, and miR-106a regulated the highest numbers of differentially expressed transcription factors with respect to human melanoma. Chromosomal enrichment analysis revealed the X chromosome was enriched with oncogenic miRNAs. We comprehensively analyzed the miRNA’s profile in COM which will be a useful resource for developing therapeutic interventions in both species.

scholarly journals ImReLnc: Identifying Immune-Related LncRNA Characteristics in Human Cancers Based on Heuristic Correlation Optimization

2022 ◽  
Vol 12 ◽  
Author(s):  
Meihong Gao ◽  
Shuhui Liu ◽  
Yang Qi ◽  
Xinpeng Guo ◽  
Xuequn Shang
Keyword(s):  
Correlation Coefficient ◽  
Enrichment Analysis ◽  
Highly Pathogenic ◽  
Prognostic Effect ◽  
Human Cancers ◽  
Cancer Pathogenesis ◽  
Specific Cancer ◽  
Cancer Types ◽  
Non Coding Rnas ◽  
The Relationship

Long non-coding RNAs (lncRNAs) play critical roles in cancer through gene expression and immune regulation. Identifying immune-related lncRNA (irlncRNA) characteristics would contribute to dissecting the mechanism of cancer pathogenesis. Some computational methods have been proposed to identify irlncRNA characteristics in human cancers, but most of them are aimed at identifying irlncRNA characteristics in specific cancer. Here, we proposed a new method, ImReLnc, to recognize irlncRNA characteristics for 33 human cancers and predict the pathogenicity levels of these irlncRNAs across cancer types. We first calculated the heuristic correlation coefficient between lncRNAs and mRNAs for immune-related enrichment analysis. Especially, we analyzed the relationship between lncRNAs and 17 immune-related pathways in 33 cancers to recognize the irlncRNA characteristics of each cancer. Then, we calculated the Pscore of the irlncRNA characteristics to evaluate their pathogenicity levels. The results showed that highly pathogenic irlncRNAs appeared in a higher proportion of known disease databases and had a significant prognostic effect on cancer. In addition, it was found that the expression of irlncRNAs in immune cells was higher than that of non-irlncRNAs, and the proportion of irlncRNAs related to the levels of immune infiltration was much higher than that of non-irlncRNAs. Overall, ImReLnc accurately identified the irlncRNA characteristics in multiple cancers based on the heuristic correlation coefficient. More importantly, ImReLnc effectively evaluated the pathogenicity levels of irlncRNAs across cancer types. ImReLnc is freely available at https://github.com/meihonggao/ImReLnc.

scholarly journals COVID-19 Mortality is Associated with Impaired Innate Immunity in Pre-existing Health Conditions

2021 ◽  
Author(s):  
Matthew E Lee ◽  
Yung Chang ◽  
Navid Ahmadinejad ◽  
Crista E Johnson-Agbakwu ◽  
Celeste Bailey ◽  
...  
Keyword(s):  
Risk Factors ◽  
Innate Immunity ◽  
Viral Infections ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Therapeutic Interventions ◽  
Health Conditions ◽  
Molecular Abnormalities ◽  
Hazard Ratios ◽  
Increased Risk

Background: COVID-19 poses a life-threatening endangerment to individuals with chronic diseases. However, not all comorbidities affect COVID-19 prognosis equally. Some increase the risk of COVID-19 related death by more than six folds while others show little to no impact. To prevent severe outcomes, it is critical that we comprehend pre-existing molecular abnormalities in common health conditions that predispose patients to poor prognoses. In this study, we aim to discover some of these molecular risk factors by associating gene expression dysregulations in common health conditions with COVID-19 mortality rates in different cohorts. Methods: We focused on fourteen pre-existing health conditions, for which age-and-sex-adjusted hazard ratios of COVID-19 mortality have been documented. For each health condition, we analyzed existing transcriptomics data to identify differentially expressed genes (DEGs) between affected individuals and unaffected individuals. We then tested if fold changes of any DEG in these pre-existing conditions were correlated with hazard ratios of COVID-19 mortality to discover molecular risk factors. We performed gene set enrichment analysis to identify functional groups overrepresented in these risk factor genes and examined their relationships with the COVID-19 disease pathway. Results: We found that upregulated expression of 70 genes and downregulated expression of 181 genes in pre-existing health conditions were correlated with increased risk of COVID-19 related death. These genes were significantly enriched with endoplasmic reticulum (ER) function, proinflammatory reaction, and interferon production that participate in viral transcription and immune responses to viral infections. Conclusions: Impaired innate immunity in pre-existing health conditions are associated with increased hazard of COVID-19 mortality. The discovered molecular risk factors are potential prognostic biomarkers and targets for therapeutic interventions.

scholarly journals MicroRNA-based regulation of genomics and transcriptomics of inflammatory cytokines in COVID-19

2021 ◽  
Author(s):  
Manoj Khokhar ◽  
Sojit Tomo ◽  
Purvi Purohit
Keyword(s):  
Transcription Factors ◽  
Inflammatory Response ◽  
In Silico ◽  
Wide Spectrum ◽  
Interaction Network ◽  
In Silico Analysis ◽  
Enrichment Analysis ◽  
Microarray Dataset ◽  
Therapeutic Strategies ◽  
Protein Protein Interaction

Background: Coronavirus disease 2019 is characterized by the elevation of a wide spectrum of inflammatory mediators which are associated with poor disease outcomes. We aimed at an in-silico analysis of regulatory microRNA and their transcription factors (TF) for these inflammatory genes that may help to devise potential therapeutic strategies in the future. Methods: The cytokine regulating immune-expressed genes (CRIEG) were sorted from literature and GEO microarray dataset and their co-differentially expressed miRNA and transcription factors were predicted from publicly available databases. Enrichment analysis was done through mienturnet, MiEAA, and Gene Ontology, and pathways predicted by KEGG and Reactome pathways. The functional and regulatory features were analyzed and visualized through Cytoscape. Results: Sixteen CRIEG were observed to have a significant protein-protein interaction network. The ontological analysis revealed significantly enriched pathways for biological processes, molecular functions, and cellular components. The search performed in the miRNA database yielded 10 miRNAs that are significantly involved in the regulation of these genes and their transcription factors. Conclusion: An In-Silico representation of a network involving miRNAs, CRIEGs, and TF which take part in the inflammatory response in COVID-19 has been elucidated. These regulatory factors may have potentially critical roles in the inflammatory response in COVID-19 and may be explored further for the development of targeted therapeutic strategies and mechanistic validation.

In Silico Analysis of Micro-RNA Sequencing Data

2021 ◽  
pp. 231-251
Author(s):  
Ernesto Aparicio-Puerta ◽  
Bastian Fromm ◽  
Michael Hackenberg ◽  
Marc K. Halushka
Keyword(s):  
Rna Sequencing ◽  
In Silico ◽  
In Silico Analysis ◽  
Micro Rna ◽  
Sequencing Data ◽  
Silico Analysis

Moving Immune Therapy Forward Targeting TME

2020 ◽  
Author(s):  
Kayla F Goliwas ◽  
Jessy S. Deshane ◽  
Craig A Elmets ◽  
Mohammad Athar
Keyword(s):  
Immune System ◽  
Targeted Therapies ◽  
Immune Therapy ◽  
Clinical Trial Design ◽  
Therapeutic Interventions ◽  
Host Immune System ◽  
Host Immune Responses ◽  
Metabolic Plasticity ◽  
Cancer Pathogenesis ◽  
Immune Therapies

The host immune system shapes the fate of tumor progression. Hence, manipulating patients' immune system to activate host immune responses against cancer pathogenesis is a promising strategy to develop effective therapeutic interventions for metastatic and drug resistant cancers. Understanding the dynamic mechanisms within the tumor microenvironment (TME) that contribute to heterogeneity and metabolic plasticity is essential to enhance the patients' responsiveness to immune targeted therapies. Riera-Domingo et. al. describe the immune landscape within the TME, and highlight the significance of metabolic and hypoxic signatures that impact immune function and response to immunotherapy. Current literature in this field confirms that targeting tumor metabolism and the acidic microenvironment commonly associated with tumors may present as viable strategies to modulate the host immune system in favor of developing highly effective immune targeted therapies. However, development of better tools to understand tumor-immune interactions and identify mechanisms driving non-responders, more innovative clinical trial design, and new therapies will need to be identified to move the field forward. Personalized immune therapies incorporating metabolic and microbiome-based gene signatures to influence the therapeutic response and novel methods to generate immunologically "hot" tumors are at the forefront of immunotherapy currently. The combination of these approaches with clinically approved immunotherapies will also be valuable moving forward.

scholarly journals A Pipeline to Call Multilevel Expression Changes between Cancer and Normal Tissues and Its Applications in Repurposing Drugs Effective for Gastric Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Wei Gao ◽  
Jianwei Yang ◽  
Changhua Zhuo ◽  
Sha Huang ◽  
Jinyuan Lin ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Interleukin 4 ◽  
Data Quality Control ◽  
Expression Change ◽  
Normal Tissues ◽  
Differential Coexpression ◽  
Cancer Pathogenesis ◽  
Differential Gene

Differential gene analyses on gastric cancer usually focus on expression change of single genes between tumor and adjacent normal tissues. However, besides changes on single genes, there are also coexpression and expression network module changes during the development of gastric cancer. In this study, we proposed a pipeline to investigate various levels of changes between gastric cancer and adjacent normal tissues, which were used to repurpose potential drugs for treating gastric cancer. Specifically, we performed a series of analyses on 242 gastric cancer samples (33-normal, 209-cancer) downloaded from the cancer genome atlas (TCGA), including data quality control, differential gene analysis, gene coexpression network analysis, module function enrichment analysis, differential coexpression analysis, differential pathway analysis, and screening of potential therapeutic drugs. In the end, we discovered some genes and pathways that are significantly different between cancer and adjacent normal tissues (such as the interleukin-4 and interleukin-13 signaling pathway) and screened perturbed genes by 2703 drugs that have a high overlap with the identified differentially expressed genes. Our pipeline might be useful for understanding cancer pathogenesis as well as gastric cancer treatment.

scholarly journals Sonic Hedgehog Medulloblastoma Cancer Stem Cells Mirnome and Transcriptome Highlight Novel Functional Networks

2018 ◽  
Vol 19 (8) ◽  
pp. 2326 ◽  
Author(s):  
Agnese Po ◽  
Luana Abballe ◽  
Claudia Sabato ◽  
Francesca Gianno ◽  
Martina Chiacchiarini ◽  
...  
Keyword(s):  
Stem Cells ◽  
Cancer Stem Cells ◽  
Sonic Hedgehog ◽  
In Silico Analysis ◽  
Enrichment Analysis ◽  
Molecular Classification ◽  
Pathway Enrichment Analysis ◽  
Malignant Brain Tumour ◽  
Mirna Sequencing ◽  
Patched 1

Molecular classification has improved the knowledge of medulloblastoma (MB), the most common malignant brain tumour in children, however current treatments cause severe side effects in patients. Cancer stem cells (CSCs) have been described in MB and represent a sub population characterised by self-renewal and the ability to generate tumour cells, thus representing the reservoir of the tumour. To investigate molecular pathways that characterise this sub population, we isolated CSCs from Sonic Hedgehog Medulloblastoma (SHH MB) arisen in Patched 1 (Ptch1) heterozygous mice, and performed miRNA- and mRNA-sequencing. Comparison of the miRNA-sequencing of SHH MB CSCs with that obtained from cerebellar Neural Stem Cells (NSCs), allowed us to obtain a SHH MB CSC miRNA differential signature. Pathway enrichment analysis in SHH MB CSCs mirnome and transcriptome was performed and revealed a series of enriched pathways. We focused on the putative targets of the SHH MB CSC miRNAs that were involved in the enriched pathways of interest, namely pathways in cancer, PI3k-Akt pathway and protein processing in endoplasmic reticulum pathway. In silico analysis was performed in SHH MB patients and identified several genes, whose expression was associated with worse overall survival of SHH MB patients. This study provides novel candidates whose functional role should be further investigated in SHH MB.

scholarly journals Role of acidic tumor microenvironment in tumor pathogenesis and targeting

2020 ◽  
pp. 34-40
Author(s):  
Vishal Sharma ◽  
Chhaya Bawa ◽  
Kuldeep Chand Vatsyan
Keyword(s):  
Cell Growth ◽  
Tumor Microenvironment ◽  
Cancer Cells ◽  
Molecular Mechanisms ◽  
Physiological State ◽  
Therapeutic Interventions ◽  
Cancer Cell Growth ◽  
Molecular Alterations ◽  
Cancer Pathogenesis

Extensive efforts are going on to understand the molecular mechanisms behind tumor initiation, progression, and invasion and find novel targets for cancer treatment. The physiological state of the tumor microenvironment (TME) is crucial to every step of tumor cell growth and angiogenesis. Cancer cells are rarely in contact with each other. The intervening medium between the cancer cells, immune cells, and other cells become acidic, which significantly affects cancer pathogenesis. It could be a novel targeting marker and may help treat tumors. Even after extensive research in this area, the nature of molecular alterations and the basic mechanisms in the tumor microenvironment remains unclear. Based on recent studies of TME, this mini-review bids a more inclusive overview of the role of TME in cancer cell growth. Also, it helps to understand the potential of TME for therapeutic interventions.

scholarly journals Bioinformatic Analysis of Gene Expression Profile in Plasma of Hypertensive Patients

2020 ◽  
Vol 33 (6) ◽  
pp. 581-581
Author(s):  
Yan-zhen Li ◽  
Hao-jie Xu ◽  
Jia-min Hu ◽  
Shi-zhu Lin ◽  
Na Zhang ◽  
...  
Keyword(s):  
Messenger Rna ◽  
Noncoding Rna ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Therapeutic Interventions ◽  
Total Rna ◽  
Hormone Synthesis ◽  
Public Data

Abstract Background To analyze expression profiles of long noncoding RNA (lncRNA) and messenger RNA (mRNA) in patients with essential hypertension (EH) and normotensive adults. Methods The gene chip dataset GSE76845, which was generated from 5 plasma samples from patients with EH and 5 normotensives, was downloaded from the National Biotechnology Information Center Public Data Platform. Each sample (total RNA) was pooled from the total RNA of 3 age- and gender-matched subjects (EH patients or healthy controls). A ClusterProfiler package including gene set enrichment analysis (GSEA) was used to identify differentially expressed genes. The target microRNA and mRNA were predicted by microcode, microDB, microTarBase, and TargetScan databases. Finally, a competing endogenous RNAs (ceRNA) regulatory network was constructed. Results Compared with the healthy control adults, 191 differential lncRNAs (90 upregulated and 101 downregulated) and 1,187 differential mRNAs (533 upregulated and 654 downregulated) were identified in EH patients. GSEA analysis showed that 17 pathways, including ubiquinone and terpenoid-quinone biosynthesis, parathyroid hormone synthesis secretion and action, fatty acid metabolism, and steroid hormone biosynthesis are involved in hypertension. A ceRNA network consisting of 150 nodes and 488 interactive pairs was constructed. Conclusions lncRNA and mRNA profile analysis provides new insight into molecular mechanisms of EH pathogenesis and potential targets for therapeutic interventions.

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