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Integrative Metabolic Pathway Analysis Reveals Novel Therapeutic Targets in Osteoarthritis.

ABSTRACT: In osteoarthritis (OA), impairment of cartilage regeneration can be related to a defective chondrogenic differentiation of mesenchymal stromal cells (MSCs). Therefore, understanding the proteomic- and metabolomic-associated molecular events during the chondrogenesis of MSCs could provide alternative targets for therapeutic intervention. Here, a SILAC-based proteomic analysis identified 43 proteins related with metabolic pathways whose abundance was significantly altered during the chondrogenesis of OA human bone marrow MSCs (hBMSCs). Then, the level and distribution of metabolites was analyzed in these cells and healthy controls by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), leading to the recognition of characteristic metabolomic profiles at the early stages of differentiation. Finally, integrative pathway analysis showed that UDP-glucuronic acid synthesis and amino sugar metabolism were downregulated in OA hBMSCs during chondrogenesis compared with healthy cells. Alterations in these metabolic pathways may disturb the production of hyaluronic acid (HA) and other relevant cartilage extracellular matrix (ECM) components. This work provides a novel integrative insight into the molecular alterations of osteoarthritic MSCs and potential therapeutic targets for OA drug development through the enhancement of chondrogenesis.

SUBMITTER: Rocha B

PROVIDER: S-EPMC7124476 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Integrative Metabolic Pathway Analysis Reveals Novel Therapeutic Targets in Osteoarthritis.

Rocha Beatriz B Cillero-Pastor Berta B Eijkel Gert G Calamia Valentina V Fernandez-Puente Patricia P Paine Martin R L MRL Ruiz-Romero Cristina C Heeren Ron M A RMA Blanco Francisco J FJ

Molecular & cellular proteomics : MCP 20200124 4

In osteoarthritis (OA), impairment of cartilage regeneration can be related to a defective chondrogenic differentiation of mesenchymal stromal cells (MSCs). Therefore, understanding the proteomic- and metabolomic-associated molecular events during the chondrogenesis of MSCs could provide alternative targets for therapeutic intervention. Here, a SILAC-based proteomic analysis identified 43 proteins related with metabolic pathways whose abundance was significantly altered during the chondrogenesis ...[more]

PMID: 31980557

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Project description:BackgroundOsteoarthritis (OA), characterized by progressive degeneration of cartilage and reactive proliferation of subchondral bone, stands as a prevalent condition in orthopedic clinics. However, the precise mechanisms underlying OA pathogenesis remain inadequately explored.MethodsIn this study, Random Forest (RF), Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) machine learning techniques were employed to identify hub genes. Based on these hub genes, an Artificial Neural Network (ANN) diagnostic model was constructed. The Drug Signatures Database (DSigDB) was utilized to screen small-molecule drugs targeting these hub genes, and molecular docking analyses and molecular dynamics simulations were employed to explore and validate the binding interactions between proteins and small-molecule drugs. Expression changes of the hub genes under inflammatory conditions were validated through in vitro experiments, including RT-qPCR and Western blotting, and the therapeutic effects of the identified small-molecule drug on chondrocytes under inflammatory conditions were further verified in vitro. Lastly, Mendelian randomization analysis was conducted to examine the causal association between progesterone levels and various OA phenotypes.ResultsIn this study, we identified three hub genes: interleukin 1 receptor-associated kinase 3 (IRAK3), integrin subunit beta-like 1 (ITGBL1), and Ras homolog family member U (RHOU). An Artificial Neural Network (ANN) diagnostic model constructed based on these hub genes demonstrated excellent performance in both training and validation phases. Screening with the Drug Signatures Database (DSigDB) identified progesterone as a small-molecule drug targeting these key proteins. Molecular docking analysis using AutoDock Vina revealed that progesterone exhibited binding energies of ≤ -7 kcal/mol with each of the key proteins, indicating strong binding affinity. Furthermore, molecular dynamics simulations validated the stability and strength of these interactions. RT-qPCR and Western blotting confirmed the downregulation of the hub genes in IL-1β-treated chondrocytes. Western blotting also demonstrated the potential therapeutic effects of progesterone on IL-1β-treated chondrocytes. Finally, Mendelian randomization analysis established a significant association between progesterone levels and multiple OA phenotypes.ConclusionIn our study, IRAK3, ITGBL1, and RHOU were identified as potential novel diagnostic and therapeutic targets for OA. Progesterone was preliminarily validated as a small-molecule drug with potential effects on OA. Further research is crucial to elucidate the pathogenesis of OA and the specific therapeutic mechanisms involved.

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.ConclusionOur 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.

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.

Dataset Information

Integrative Metabolic Pathway Analysis Reveals Novel Therapeutic Targets in Osteoarthritis.

Publications

Integrative Metabolic Pathway Analysis Reveals Novel Therapeutic Targets in Osteoarthritis.

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