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LIM-Domain-Binding Protein 1 Mediates Cell Proliferation and Drug Resistance in Colorectal Cancer.

ABSTRACT: Objective: It has been shown that LIM-domain-binding protein 1 (LDB1) is involved in the tumorigenesis of several cancers, but its function in colorectal cancer (CRC) has not been fully explained. This study is aimed to investigate whether LDB1 is involved in regulating the cell growth and drug sensitivity of CRC. Methods: To analyze the protein expression of LDB1 in CRC tissues, western blot was used. KM plotter and UALCAN databases were used to predict the prognosis of CRC patients with low or high LDB1 expression. To do the correlation analysis in CRC tissues, GEPIA database was used. CCK-8 assay and xenograft models were used to evaluate the effects of LDB1 in CRC cell growth. An oxaliplatin-resistant cell line was constructed to evaluate the effect of LDB1 in drug sensitivity of CRC cells. Results: Our current research confirmed that LDB1 was upregulated in CRC tumor tissues, and its elevation predicted a poor prognosis for CRC patients. LDB1 was also found positively correlated with CCNA1, BCL2 and BCLW, but negatively correlated with the pro-apoptotic signals (BID, BAX and BAK). Silence of LDB1 significantly inhibited CRC cell growth in vitro, and CRC cells with low expression of LDB1 had a lower tumorigenesis rate in tumor-bearing nude mice. Our experiments also showed that LDB1 silence enhanced the anti-tumor activity of oxaliplatin in CRC cells. The expression of LDB1 was also found increased in oxaliplatin-resistant CRC cell lines, and silence of LDB1 partly restored the antitumor effect of oxaliplatin in an oxaliplatin-resistant CRC cell line. Conclusion: Our current results revealed the roles of LDB1 in the growth and drug resistance of CRC cells, and may provide the new theoretical support for LDB1 as a potential target for the treatment of CRC in the future.

SUBMITTER: Zhu M

PROVIDER: S-EPMC8770319 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo investigate the role and expression pattern of LIM-domain binding protein 2 (LDB2) in lung adenocarcinoma.ObjectiveWe studied the expression pattern of LDB2 in lung adenocarcinoma based on data from the online databases TCGA, GEO and CPTAC, and the results were verified in lung adenocarcinoma tissues and cells using immunohistochemistry, qRT-PCR and Western blotting. The relationship between LDB2 and the prognosis of patients with lung adenocarcinoma was analyzed using GEPIA and GEO databases. We further analyzed the role of LDB2 in regulating cell behaviors in a H1299 cell model over-expressing LDB2 using cell counting, soft agar colony forming assay and flow cytometry. The m6A binding sites on LDB2 were confirmed by bioinformatics analysis and MeRIP-qPCR assays. The effect of YTHDC2 on LDB2 was examined using qRT-PCR and Western blotting, and the binding of YTHDC2 to the transcript of LDB2 was verified with RIP-qPCR assays. Dual luciferase reporter assay was performed to verify YTHDC2 functioning via m6A sites.ObjectiveLDB2 expression was significantly decreased in lung adenocarcinoma in comparison with normal tissues based on data from TCGA, GEPIA and CPTAC, and the same results were obtained from 80 lung adenocarcinoma tissues and 17 adjacent normal tissues. Similarly, LDB2 expression was decreased in lung adenocarcinoma cells as compared with 16HBE cells. The data from Prognoscan and GEPIA suggested that a high LDB2 expression was positively correlated with a more favorable outcome of lung adenocarcinoma patients. LDB2-overexpressing H1299 cells showed a significant inhibition of proliferative activity with cell cycle arrest in S phage. Bioinformatics analysis and MeRIP-qPCR assay confirmed the presence of m6A sites on LDB2. The m6A reader YTHDC2 was positively related with LDB2 in lung adenocarcinoma based on data from GEPIA (r=0.22). Overexpression YTHDC2 significantly enhanced LDB2 expression in H1299 cells by about 19.35 folds. Dual luciferase reporter assay showed that YTHDC2 enhanced the promoter activity in the wild-type group but not in deletion group.ObjectiveLDB2 expression can be up-regulated by m6A reader YTHDC2 in lung adenocarcinoma to inhibit the proliferation of the tumor cells in vitro.

Project description:Predictive approaches such as virtual screening have been used in drug discovery with the objective of reducing developmental time and costs. Current machine learning and network-based approaches have issues related to generalization, usability, or model interpretability, especially due to the complexity of target proteins' structure/function, and bias in system training datasets. Here, we propose a new method "DRUIDom" (DRUg Interacting Domain prediction) to identify bio-interactions between drug candidate compounds and targets by utilizing the domain modularity of proteins, to overcome problems associated with current approaches. DRUIDom is composed of two methodological steps. First, ligands/compounds are statistically mapped to structural domains of their target proteins, with the aim of identifying their interactions. As such, other proteins containing the same mapped domain or domain pair become new candidate targets for the corresponding compounds. Next, a million-scale dataset of small molecule compounds, including those mapped to domains in the previous step, are clustered based on their molecular similarities, and their domain associations are propagated to other compounds within the same clusters. Experimentally verified bioactivity data points, obtained from public databases, are meticulously filtered to construct datasets of active/interacting and inactive/non-interacting drug/compound-target pairs (~2.9M data points), and used as training data for calculating parameters of compound-domain mappings, which led to 27,032 high-confidence associations between 250 domains and 8,165 compounds, and a finalized output of ~5 million new compound-protein interactions. DRUIDom is experimentally validated by syntheses and bioactivity analyses of compounds predicted to target LIM-kinase proteins, which play critical roles in the regulation of cell motility, cell cycle progression, and differentiation through actin filament dynamics. We showed that LIMK-inhibitor-2 and its derivatives significantly block the cancer cell migration through inhibition of LIMK phosphorylation and the downstream protein cofilin. One of the derivative compounds (LIMKi-2d) was identified as a promising candidate due to its action on resistant Mahlavu liver cancer cells. The results demonstrated that DRUIDom can be exploited to identify drug candidate compounds for intended targets and to predict new target proteins based on the defined compound-domain relationships. Datasets, results, and the source code of DRUIDom are fully-available at: https://github.com/cansyl/DRUIDom.

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LIM-Domain-Binding Protein 1 Mediates Cell Proliferation and Drug Resistance in Colorectal Cancer.

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