Engineered reversal of drug resistance in cancer cells--metastases suppressor factors as change agents

Abstract

Building molecular correlates of drug resistance in cancer and exploiting them for therapeutic intervention remains a pressing clinical need. To identify factors that impact drug resistance herein we built a model that couples inherent cell-based response toward drugs with transcriptomes of resistant/sensitive cells. To test this model, we focused on a group of genes called metastasis suppressor genes (MSGs) that influence aggressiveness and metastatic potential of cancers. Interestingly, modeling of 84 000 drug response transcriptome combinations predicted multiple MSGs to be associated with resistance of different cell types and drugs. As a case study, on inducing MSG levels in a drug resistant breast cancer line resistance to anticancer drugs caerulomycin, camptothecin and topotecan decreased by more than 50-60%, in both culture conditions and also in tumors generated in mice, in contrast to control un-induced cells. To our knowledge, this is the first demonstration of engineered reversal of drug resistance in cancer cells based on a model that exploits inherent cellular response profiles.

Figure 1.

Scheme of overall approach showing coupled analysis of transcriptome profiles obtained from resistant/sensitive cells and following induction of MSG in cancer cells.

Figure 2.

MSGs are associated with chemosensitivity. (A) Clustering of drug/cell line combination based on GI₅₀ values (upper panel) and MSG expression in different cell lines (lower panel)—MSG expression segregates with resistance/sensitivity for many drug–cell line pairs. Absence of GI₅₀ value in upper panel heatmap represented by white color. (B) Representation of the groups containing resistant and sensitive cell lines based on GI50 values. A cell line with at least 6-fold change above/below average GI50 was considered as resistant/sensitive, respectively. (C) Expression of MSG was distinct between resistant and sensitive groups of cells for many drug molecules (see Supplementary Figure S1 for all molecules). (D) Cell lines with high or low expression of MSG (NME2, PTPN11 or CRMP1) show distinct response to most drug molecules.

Figure 3.

Chemoresistance and ‘MSG-induction’ are anti-correlated in many cases. (A–C) Comparative analysis of the ‘MSG-induction’ signature versus drug-specific gene signatures (REM)-NME2 expression in cell lines grouped as resistant or sensitive is shown in left panels. Expression profiling of MDA-MB-231 cells before or after NME2-induction and the resultant change in transcriptome of MDA-MB-231 cells is compared with the sensitive/resistant gene signature derived for camptothecin (A), doxorubicin (B) and caerulomycin (C) in the right panels. Correlation of the resistant-minus-sensitive gene signature derived from multiple cell lines—response engineering module (REM_r–s)—with the ‘NME2-induction’ signature in MDA-MB-231cells (center panels) is shown.

Figure 4.

MSG-induction leads to reversal of drug resistance. Viability of cells in presence of anticancer molecules decreased after induction of NME2 in MDA-MB-231 cells, but not in un-induced control cells in both, under culture conditions and also when tumors were developed in vivo in mice (n = 5).

Figure 5.

NME2 promotes MET. NME2-induced MDA-MB-231 cells showed up-regulation of epithelial and down-regulation of mesenchymal markers in quantitative real-time mRNA analysis.