Dataset Information

Quantitative Proteomics to identify nuclear RNA-binding proteins of Malat1

ABSTRACT: The long non-coding RNA Malat1 has been implicated in several human cancers, while the mechanism of action is not completely understood. As RNAs in cells function in the context of RBPs identification of their RNA-binding proteins can shed light on their functionality. We here performed quantitative interactomics of 14 non-overlapping fragments covering the full length of Malat1 to identify possible nuclear interacting proteins. Overall, we identified 35 candidates including 14 already known binders, which are able to interact with Malat1 in the nucleus. Furthermore, the use of fragments along the full-length RNA allowed us to reveal two hotspots for protein binding, one in the 5’-region and one in the 3’-region of Malat1. Our results provide confirmation on previous RNA-protein interaction studies and suggest new candidates for functional investigations.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Mus Musculus (mouse)

SUBMITTER: F Butter

LAB HEAD: Falk Butter

PROVIDER: PXD017309 | Pride | 2020-01-29

REPOSITORIES: Pride

ACCESS DATA

Publications

Quantitative Proteomics to Identify Nuclear RNA-Binding Proteins of Malat1.

Scherer Marian M Levin Michal M Butter Falk F Scheibe Marion M

International journal of molecular sciences 20200210 3

The long non-coding RNA Malat1 has been implicated in several human cancers, while the mechanism of action is not completely understood. As RNAs in cells function together with RNA-binding proteins (RBPs), the composition of their RBP complex can shed light on their functionality. We here performed quantitative interactomics of 14 non-overlapping fragments covering the full length of Malat1 to identify possible nuclear interacting proteins. Overall, we identified 35 candidates including 14 alrea ...[more]

PMID: 32050583

Similar Datasets

Project description:Non-small cell lung cancer is the leading cause of cancer death worldwide. Gefitinib, epidermal growth factor receptor tyrosine kinase inhibitor, is the first-line treatment of NSCLC, however, many patients eventually become resistant and experience progressive disease. Therefore, development of efficient therapeutic agents to overcome resistance is urgent. We previously found that citreoviridin, one of toxic mycotoxins derived from fungal species, can suppress lung cancer cell growth by inhibiting the activity of ectopic ATP synthase, but has limited effect on normal cells. Citreoviridin suppresses mitogen-activated protein kinase/extracellular signal-regulated kinase signaling by site-specific dephosphorylation of HSP90AB1 on Serine 255 in gefitinib non-resistant lung cancer CL1-0 cells and xenograft model. We are curious whether signaling pathways underlying citreoviridin-treated gefitinib-acquired resistant lung cancer cells are different. In this study, we showed that citreoviridin inhibited cell proliferation and anchorage-dependent growth of gefitinib-acquired resistance NCI-H1975 cells with EGFR T790M mutation. Furthermore, we explored the dynamic molecular response by temporal phosphoproteomic approach. We identified 1476 phosphopeptides corresponding to 738 phosphoproteins and quantified 1901 phosphorylation sites. There were 274 phosphosites corresponding to 174 phosphorylated proteins significantly differential expressed. Functional enrichment analysis demonstrated that citreoviridin treatment affected chromatin organization, cell cycle and apoptosis. Interestingly, we found that citreovirdin suppressed cell proliferation by site-specific phosphorylation of topoisomerase on serine 1106. Citreovirdin induced double strands breaks, and then leaded to DNA damage response. The DNA lesions triggered cells to cell cycle arrest at S phase for repairing or apoptosis for cell death. The results indicated that citreoviridin could potentially be a therapeutic agent against gefitinib-resistant NSCLC.

Dataset Information

Quantitative Proteomics to identify nuclear RNA-binding proteins of Malat1

Publications

Quantitative Proteomics to Identify Nuclear RNA-Binding Proteins of Malat1.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure