# Unraveling the MALAT1 lncRNA-protein interaction networks that drive lung cancer metastasis > **NIH NIH K22** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $162,000 ## Abstract PROJECT SUMMARY/ABSTRACT Long non-coding RNAs (lncRNAs), through interactions with RNA-binding proteins, play critical roles in development and cellular homeostasis. Many lncRNAs are associated with cancer and disease, representing a largely untouched pool of potential therapeutic targets. Metastasis Associated Lung Adenocarcinoma Transcript 1 (MALAT1) is a highly conserved lncRNA whose expression is associated with poor prognosis and drug- resistance and whose activity accelerates cell proliferation and increases metastatic potential in multiple cancer types. MALAT1 is ubiquitously expressed at high levels in many normal cell lines, and yet genetic deletion of the transcript has no negative effects on development or viability in mice. The mechanisms of MALAT1 in both normal and cancer cells are unclear, and a better understanding of these mechanisms would unlock the potential of MALAT1 as a therapeutic target in the treatment of cancer. My preliminary data show that while levels of MALAT1 transcript are lower in a lung adenocarcinoma cell line than in normal human lung airway epithelial cells, metastatic activity of the adenocarcinoma is dependent on MALAT1: therefore high expression of MALAT1 is not sufficient to promote metastasis. I observe no differences in MALAT1 RNA structure between cell lines, but levels of expression of many MALAT1-binding proteins increase significantly. These data strongly indicate that proteins present in lung cancer cells are imparting pro-metastatic activity onto MALAT1. My goal is to integrate cutting-edge sequencing and quantitative proteomics technologies with cell-based functional approaches to understand how RNA-protein interaction networks of MALAT1 promote metastatic activity in human lung cancers. In Aim 1, I will purify MALAT1 RNA-protein complexes (RNPs) from normal lung cells and lung cancer cells and mechanistically detail the RNA and protein components of metastases-specific RNA- protein interaction networks. I will express fragments of MALAT1 in lung cancer cell lines and identify sequences sufficient to assemble RNP complexes and reprogram metastatic behavior in cell culture. In Aim 2, I will employ RBPome-wide total and phospho-protemics, nucleic acid interactome capture, and fluorescent microscopy to understand the signaling pathways that assemble dysfunctional MALAT1 RNPs genome- and transcriptome- wide. Together, these experiments will identify the mechanisms by which MALAT1-protein interaction networks promote each step of metastasis in lung cancer. I expect that this work will improve our fundamental understanding of MALAT1, inform strategies to target MALAT1 therapeutically, and act as a framework for the characterization of pro-metastatic lncRNA-protein complexes throughout the transcriptome. Development of these proposed aims will lay the foundation for a successful career as a leader in a new field of cancer RBPomes. ## Key facts - **NIH application ID:** 10492765 - **Project number:** 5K22CA262349-02 - **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR - **Principal Investigator:** Chase A Weidmann - **Activity code:** K22 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $162,000 - **Award type:** 5 - **Project period:** 2021-09-22 → 2024-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10492765 ## Citation > US National Institutes of Health, RePORTER application 10492765, Unraveling the MALAT1 lncRNA-protein interaction networks that drive lung cancer metastasis (5K22CA262349-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10492765. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*