Integrative Metabolic Pathway Analysis Reveals Novel Therapeutic Targets in Osteoarthritis.
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ABSTRACT:
SUBMITTER: Rocha B
PROVIDER: S-EPMC7124476 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundA deep understanding of potential molecular biomarkers and therapeutic targets related to the progression of colorectal cancer (CRC) from early stages to metastasis remain mostly undone. Moreover, the regulation and crosstalk among different cancer-driving molecules including messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs) and micro-RNAs (miRNAs) in the transition from stage I to stage IV remain to be clarified, which is the aim of this study.MethodsWe carried out two separate differential expression analyses for two different sets of samples (stage-specific samples and tumor/normal samples). Then, by the means of robust dataset analysis we identified distinct lists of differently expressed genes (DEGs) for Robust Rank Aggregation (RRA) and weighted gene co-expression network analysis (WGCNA). Then, comprehensive computational systems biology analyses including mRNA-miRNA-lncRNA regulatory network, survival analysis and machine learning algorithms were also employed to achieve the aim of this study. Finally, we used clinical samples to carry out validation of a potential and novel target in CRC.ResultsWe have identified the most significant stage-specific DEGs by combining distinct results from RRA and WGCNA. After finding stage-specific DEGs, a total number of 37 DEGs were identified to be conserved across all stages of CRC (conserved DEGs). We also found DE-miRNAs and DE-lncRNAs highly associated to these conserved DEGs. Our systems biology approach led to the identification of several potential therapeutic targets, predictive and prognostic biomarkers, of which lncRNA LINC00974 shown as an important and novel biomarker.ConclusionsFindings of the present study provide new insight into CRC pathogenesis across all stages, and suggests future assessment of the functional role of lncRNA LINC00974 in the development of CRC.
| S-EPMC9339198 | biostudies-literature
Project description:Autophagy is involved in different degenerative diseases and it may control epigenetic modifications, metabolic processes, stem cells differentiation as well as apoptosis. Autophagy plays a key role in maintaining the homeostasis of cartilage, the tissue produced by chondrocytes; its impairment has been associated to cartilage dysfunctions such as osteoarthritis (OA). Due to their location in a reduced oxygen context, both differentiating and mature chondrocytes are at risk of premature apoptosis, which can be prevented by autophagy. AutophagomiRNAs, which regulate the autophagic process, have been found differentially expressed in OA. AutophagomiRNAs, as well as other regulatory molecules, may also be useful as therapeutic targets. In this review, we describe and discuss the role of autophagy in OA, focusing mainly on the control of autophagomiRNAs in OA pathogenesis and their potential therapeutic applications.
| S-EPMC7962119 | biostudies-literature
Project description:There is an urgent need to develop more effective therapies for hepatocellular carcinoma (HCC) because of its aggressiveness. Guadecitabine (SGI-110) is a second-generation DNA methyltransferase inhibitor (DNMTi), which is currently in clinical trials for HCC and shows greater stability and performance over first-generation DNMTis. In order to identify potential therapeutic targets of SGI-110 for clinical trials, HCC cell lines (SNU398, HepG2, and SNU475) were used to evaluate the effects of transient SGI-110 treatment by an integrative analysis of DNA methylation, nucleosome accessibility, gene expression profiles, and its clinical relevance by comparison to The Cancer Genome Atlas (TCGA) HCC clinical data. Each HCC cell line represents a different DNA methylation subtype of primary HCC tumors based on TCGA data. After SGI-110 treatment, all cell lines were sensitive to SGI-110 with prolonged antiproliferation effects. Expression of up-regulated genes, including tumor suppressors, was positively correlated with nucleosome accessibility and negatively correlated with gene promoter DNA methylation. Alternatively, expression of down-regulated genes, such as oncogenes, was negatively correlated with nucleosome accessibility and positively correlated with gene body DNA methylation. SGI-110 can also act as a dual inhibitor to down-regulate polycomb repressive complex 2 (PRC2) genes by demethylating their gene bodies, resulting in reactivation of PRC2 repressed genes without involvement of DNA methylation. Furthermore, it can up-regulate endogenous retroviruses to reactivate immune pathways. Finally, about 48% of frequently altered genes in primary HCC tumors can be reversed by SGI-110 treatment. CONCLUSION:Our integrative analysis has successfully linked the antitumor effects of SGI-110 to detailed epigenetic alterations in HCC cells, identified potential therapeutic targets, and provided a rationale for combination treatments of SGI-110 with immune checkpoint therapies.
| S-EPMC6173644 | biostudies-literature
Project description:BackgroundGene alterations are crucial to the molecular pathogenesis of pancreatic cancer. The present study was designed to identify the potential candidate genes in the pancreatic carcinogenesis.MethodsGene Expression Omnibus database (GEO) datasets of pancreatic cancer tissue were retrieval and the differentially expressed genes (DEGs) from individual microarray data were merged. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, protein-protein interaction (PPI) networks, and gene coexpression analysis were performed.ResultsThree GEO datasets, including 74 pancreatic cancer samples and 55 controls samples were selected. A total of 2325 DEGs were identified, including 1383 upregulated and 942 downregulated genes. The GO terms for molecular functions, biological processes, and cellular component were protein binding, small molecule metabolic process, and integral to membrane, respectively. The most significant pathway in KEGG analysis was metabolic pathways. PPI network analysis indicated that the significant hub genes including cytochrome P450, family 2, subfamily E, polypeptide 1 (CYP2E1), mitogen-activated protein kinase 3 (MAPK3), and phospholipase C, gamma 1 (PLCG1). Gene coexpression network analysis identified 4 major modules, and the potassium channel tetramerization domain containing 10 (KCTD10), kin of IRRE like (KIRREL), dipeptidyl-peptidase 10 (DPP10), and unc-80 homolog (UNC80) were the hub gene of each modules, respectively.ConclusionOur integrative analysis provides a comprehensive view of gene expression patterns associated with the pancreatic carcinogenesis.
| S-EPMC5662383 | biostudies-literature
Project description:In spite of the increasing availability of genomic and transcriptomic data, there is still a gap between the detection of perturbations in gene expression and the understanding of their contribution to the molecular mechanisms that ultimately account for the phenotype studied. Alterations in the metabolism are behind the initiation and progression of many diseases, including cancer. The wealth of available knowledge on metabolic processes can therefore be used to derive mechanistic models that link gene expression perturbations to changes in metabolic activity that provide relevant clues on molecular mechanisms of disease and drug modes of action (MoA). In particular, pathway modules, which recapitulate the main aspects of metabolism, are especially suitable for this type of modeling. We present Metabolizer, a web-based application that offers an intuitive, easy-to-use interactive interface to analyze differences in pathway metabolic module activities that can also be used for class prediction and in silico prediction of knock-out (KO) effects. Moreover, Metabolizer can automatically predict the optimal KO intervention for restoring a diseased phenotype. We provide different types of validations of some of the predictions made by Metabolizer. Metabolizer is a web tool that allows understanding molecular mechanisms of disease or the MoA of drugs within the context of the metabolism by using gene expression measurements. In addition, this tool automatically suggests potential therapeutic targets for individualized therapeutic interventions.
| S-EPMC6397295 | biostudies-literature
Project description:Little is known about the complex signaling architecture of KRAS and the interconnected RAS-driven protein-protein interactions, especially as it occurs in human clinical specimens. This study explored the activated and interconnected signaling network of KRAS mutant lung adenocarcinomas (AD) to identify novel therapeutic targets.Thirty-four KRAS mutant (MT) and twenty-four KRAS wild-type (WT) frozen biospecimens were obtained from surgically treated lung ADs. Samples were subjected to Laser Capture Microdissection and Reverse Phase Protein Microarray analysis to explore the expression/activation levels of 150 signaling proteins along with co-activation concordance mapping. An independent set of 90 non-small cell lung cancers (NSCLC) was used to validate selected findings by immunohistochemistry (IHC).Compared to KRAS WT tumors, the signaling architecture of KRAS MT ADs revealed significant interactions between KRAS downstream substrates, the AKT/mTOR pathway, and a number of Receptor Tyrosine Kinases (RTK). Approximately one-third of the KRAS MT tumors had ERK activation greater than the WT counterpart (p<0.01). Notably 18% of the KRAS MT tumors had elevated activation of the Estrogen Receptor alpha (ER-?) (p=0.02).This finding was verified in an independent population by IHC (p=0.03).KRAS MT lung ADs appear to have a more intricate RAS linked signaling network than WT tumors with linkage to many RTKs and to the AKT-mTOR pathway. Combination therapy targeting different nodes of this network may be necessary to treat this group of patients. In addition, for patients with KRAS MT tumors and activation of the ER-?, anti-estrogen therapy may have important clinical implications.
| S-EPMC4741699 | biostudies-other
Project description:BackgroundAs a rare pathologic subtype, small cell carcinoma of the cervix (SCCC) is characterized by extensive aggressiveness and resistance to current therapies. To date, our knowledge of SCCC origin and progression is limited and sometimes even controversial. Herein, we explored the whole-protein expression profiles in a panel of SCCC cases, aiming to provide more evidence for the precise diagnosis and targeting therapy.MethodsEighteen SCCC samples and six matched normal cervix tissues were collected from January 2013 to December 2017. Data independent acquisition mass spectrometry (DIA) was performed to discriminate the different proteins (DEPs) associated with SCCC. The expression of CDN2A and SYP in corresponding SCCC tissues was verified using immunohistochemistry. GO and KEGG enrichment analyses were used to identify the key DEPs related to SCCC development and tumor recurrence.ResultsAs a result, 1311 DEPs were identified in SCCC tissues (780 up-regulated and 531 down-regulated). In up-regulated DEPs, both GO analysis and KEGG analysis showed the most enriched were related to DNA replication (including nuclear DNA replication, DNA-dependent DNA replication, and cell cycle DNA replication), indicating the prosperous proliferation in SCCC. As for the down-regulated DEPs, GO analysis showed that the most enriched functions were associated with extracellular matrix collagen-containing extracellular matrix. KEGG analysis revealed that the DEPs were enriched in Complement and coagulation cascades, proteoglycans in cancer, and focal adhesion-related pathways. Down-regulation of these proteins could enhance the mobility of cancer cells and establish a favorable microenvironment for tumor metastasis, which might be accounted for the frequent local and distant metastasis in SCCC. Surprisingly, the blood vessels and circulatory system exhibit a down-regulation in SCCC, which might be partly responsible for its resistance to anti-angiogenic regimens. In the stratification analysis of early-stage tumors, a group of enzymes involved in the cancer metabolism was discriminated in these recurrence cases.ConclusionsUsing quantitative proteomics analysis, we first reported the whole-protein expression profiles in SCCC. Significant alterations were found in proteins associated with the enhancement of DNA replication and cellular motility. Besides the association with mitosis, a unique metabolic feature was detected in cases with tumor recurrence. These findings provided novel targets for disease surveillance and treatments, which warranted further validation in the future.
| S-EPMC10082492 | biostudies-literature
Project description:Identifying novel therapeutic targets for the treatment of disease is challenging. To this end, we developed a genome-wide approach of candidate gene prioritization. We independently collocated sets of genes that were implicated in rheumatoid arthritis (RA) pathogenicity through three genome-wide assays: (i) genome-wide association studies (GWAS), (ii) differentially expression in RA fibroblast-like synoviocytes (FLS), and (iii) differentially methylation in RA FLS. Integrated analysis of these complementary data sets identified a significant enrichment of multi-evidence genes (MEGs) within pathways relating to RA pathogenicity. One MEG is Engulfment and Cell Motility Protein-1 (ELMO1), a gene not previously considered as a therapeutic target in RA FLS. We demonstrated in RA FLS that ELMO1 is: (i) expressed, (ii) promotes cell migration and invasion, and (iii) regulates Rac1 activity. Thus, we created links between ELMO1 and RA pathogenicity, which in turn validates ELMO1 as a potential RA therapeutic target. This study illustrated the power of MEG-based approaches for therapeutic target identification.
| S-EPMC4406750 | biostudies-literature
Project description:IntroductionHepatocellular carcinoma (HCC) is an aggressive malignancy with steadily increasing incidence rates worldwide and poor therapeutic outcomes. Studies show that metabolic reprogramming plays a key role in tumor genesis and progression. In this study, we analyzed the metabolic heterogeneity of epithelial cells in the HCC and screened for potential biomarkers.MethodsThe hepatic single-cell RNA sequencing (scRNA-seq) datasets of HCC patients and healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Based on data intergration and measurement of differences among groups, the metabolic epithelial cell subpopulations were identified. The single-cell metabolic pathway was analyzed and the myeloid subpopulations were identified. Cell-cell interaction analysis and single-cell proliferation analysis were performed. The gene expression profiles of HCC patients were obtained from the GSE14520 dataset of GEO and TCGA-LIHC cohort of the UCSC Xena website. Immune analysis was performed. The differentially expressed genes (DEGs) were identified and functionally annotated. Tumor tissues from HCC patients were probed with anti-ALDOA, anti-CD68, anti-CD163, anti-CD4 and anti-FOXP3 antibodies. Results We analyzed the scRNA-seq data from 48 HCC patients and 14 healthy controls. The epithelial cells were significantly enriched in HCC patients compared to the controls (p = 0.011). The epithelial cells from HCC patients were classified into two metabolism-related subpopulations (MRSs) - pertaining to amino acid metabolism (MRS1) and glycolysis (MRS2). Depending on the abundance of these metabolic subpopulations, the HCC patients were also classified into the MRS1 and MRS2 subtype distinct prognoses and immune infiltration. The MRS2 group had significantly worse clinical outcomes and more inflamed tumor microenvironment (TME), as well as a stronger crosstalk between MRS2 cells and immune subpopulations that resulted in an immunosuppressive TME. We also detected high expression levels of ALDOA in the MRS2 cells and HCC tissues. In the clinical cohort, HCC patients with higher ALDOA expression showed greater enrichment of immunosuppressive cells including M2 macrophages and T regulatory cells.DiscussionThe glycolytic subtype of HCC cells with high ALDOA expression is associated with an immunosuppressive TME and predicts worse clinical outcomes, providing new insights into the metabolism and prognosis of HCC.
| S-EPMC10017446 | biostudies-literature
Project description:Lennert lymphoma (LL) is a lymphoepithelioid morphological variant of peripheral T-cell lymphoma-not otherwise specified (PTCL/NOS), clinically characterized by better prognosis if compared with other PTCL/NOS. Although well characterized as far as morphology and phenotype are concerned, very little is known regarding its molecular features. In this study, we investigated the transcriptional profile of this tumor aiming 1) to identify its cellular counterparts; 2) to better define its relation with other PTCLs-and, therefore, its possible position in lymphoma classification; and 3) to define pathogenetic mechanisms, possibly unveiling novel therapeutic targets. To address these issues, we performed gene and microRNA expression profiling on LL and other PTCL/NOS cases; we identified different genes and microRNAs that discriminated LL from other PTCL/NOS. Particularly, LL revealed a molecular signature significantly enriched in helper function and clearly distinguishable from other PTCL/NOS. Furthermore, PI3K/Akt/mTOR pathway emerged as novel potential therapeutic target. In conclusion, based on the already known particular morphological and clinical features, the new molecular findings support the hypothesis that LL might be classified as a separate entity. Preclinical and clinical studies testing the efficacy of PI3K/MTOR inhibitors in this setting are warranted.
| S-EPMC6748072 | biostudies-literature