Mapping lung tumor cell drug responses as a function of matrix context and genotype using cell microarrays

Abstract

Carcinoma progression is influenced by interactions between epithelial tumor cells and components of their microenvironment. In particular, cell-extracellular matrix (ECM) interactions are known to drive tumor growth, metastatic potential, and sensitivity or resistance to therapy. Yet the intrinsic complexity of ECM composition within the tumor microenvironment remains a barrier to comprehensive investigation of these interactions. We present here a high-throughput cell microarray-based approach to study the impact of defined combinations of ECM proteins on tumor cell drug responses. Using this approach, we quantitatively evaluated the effects of 55 different ECM environments representing all single and two-factor combinations of 10 ECM proteins on the responses of lung adenocarcinoma cells to a selection of cancer-relevant small molecule drugs. This drug panel consisted of an alkylating agent and five receptor tyrosine kinase inhibitors. We further determined that expression of the neuroendocrine transcription factor ASCL1, which has been previously associated with poor patient outcome when co-expressed with the RET oncogene, altered cell responses to drugs and modulated cleavage of the pro-apoptotic protein caspase-3 depending on ECM context. Our results suggest that co-expression of specific ECM proteins with known genetic drivers in lung adenocarcinoma may impact therapeutic efficacy. Furthermore, this approach could be utilized to define the molecular mechanisms by which cell-matrix interactions drive drug resistance through integration with clinical cell samples and genomics data.

A novel ex vivo tumor system identifies Src-mediated invasion and metastasis in mesenchymal tumor cells in non-small cell lung cancer

“…Multiple groups have attempted to capture the complexity of the microenvironment and test therapeutic sensitivity to drug treatments. For example, tumor cells have been cultured in different matrices to identify ECM combinations driving lung cancer 49,52 . Work done by such groups has given great insights into individual heterotypic interactions, however, these studies have been conducted using cell lines in an artificially created environment.…”

High-throughput RNAi screen identifies ILK as a target to overcome intrinsic EGFR-TKI resistance of lung squamous carcinoma

“…Then cell cycle, mitosis, ECM-receptor interaction and kinase activity, DNA binding were found closely correlated with the effect of ILK in EGFR-TKIs resistance. As they have been known, the cell cycle [25,26], ECM-receptor interaction [27,28], mitosis [29], were identified typically activated in cancer drug resistance, suggesting that ILK played a crucial role in EGFR-TKIs resistance of lung SqCC via these pathways. GO analysis also found that cell cycle and mitosis were the important signaling pathways involved in ILK knockout in EGFR-TKIs resistance.…”

Mechanism of intrinsic resistance of lung squamous cell carcinoma to epithelial growth factor receptor‑tyrosine kinase inhibitors revealed by high‑throughput RNA interference screening

“…The ‘cell cycle’, ‘oocyte meiosis, ‘ECM-receptor interaction’, ‘protein kinase activity’ and ‘DNA binding’ were identified to be closely associated with the effects of ILK on EGFR-TKI resistance. As the cell cycle ( 32 , 33 ), ECM-receptor interaction ( 34 , 35 ) and mitosis ( 36 ) have been identified to be activated in cancer drug resistance, ILK may serve a crucial role in the EGFR-TKI resistance of lung SqCC via these pathways. GO analysis results also demonstrated that ‘mitotic cell cycle’ and ‘mitosis’ were important signaling pathways involved in EGFR-TKI resistance in ILK-knockout cells.…”