Systematic analysis of migration factors by MigExpress identifies essential cell migration control genes in non-small cell lung cancer

  • Jagriti Pal
  • , Andrea C. Becker
  • , Sonam Dhamija
  • , Jeanette Seiler
  • , Mahmoud Abdelkarim
  • , Yogita Sharma
  • , Jürgen Behr
  • , Chen Meng
  • , Christina Ludwig
  • , Bernhard Kuster
  • , Sven Diederichs*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Cell migration is an essential process in health and in disease, including cancer metastasis. A comprehensive inventory of migration factors is nonetheless lacking—in part due to the difficulty in assessing migration using high-throughput technologies. Hence, there are currently very few screens that systematically reveal factors controlling cell migration. Here, we introduce MigExpress as a platform for the ‘identification of Migration control genes by differential Expression’. MigExpress exploits the combination of in-depth molecular profiling and the robust quantitative analysis of migration capacity in a broad panel of samples and identifies migration-associated genes by their differential expression in slow- versus fast-migrating cells. We applied MigExpress to investigate non-small cell lung cancer (NSCLC), which is the most frequent cause of cancer mortality mainly due to metastasis. In 54 NSCLC cell lines, we comprehensively determined mRNA and protein expression. Correlating the transcriptome and proteome profiles with the quantified migration properties led to the discovery and validation of FLNC, DSE, CPA4, TUBB6, and BICC1 as migration control factors in NSCLC cells, which were also negatively correlated with patient survival. Notably, FLNC was the least expressed filamin in NSCLC, but the only one controlling cell migration and correlating with patient survival and metastatic disease stage. In our study, we present MigExpress as a new method for the systematic analysis of migration factors and provide a comprehensive resource of transcriptomic and proteomic data of NSCLC cell lines related to cell migration.

Original languageEnglish
Pages (from-to)1797-1817
Number of pages21
JournalMolecular Oncology
Volume15
Issue number7
DOIs
StatePublished - Jul 2021
Externally publishedYes

Keywords

  • cancer cell migration
  • gene expression profiling
  • metastasis
  • non-small cell lung cancer
  • proteomics
  • quantitative migration analysis
  • transcriptomics

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