Large-scale pharmacogenomics based drug discovery for ITGB3 dependent chemoresistance in mesenchymal lung cancer

Abstract

Even when targets responsible for chemoresistance are identified, drug development is often hampered due to the poor druggability of these proteins. We systematically analyzed therapy-resistance with a large-scale cancer cell transcriptome and drug-response datasets and predicted the candidate drugs based on the gene expression profile. Our results implicated the epithelial-mesenchymal transition as a common mechanism underlying resistance to chemotherapeutic drugs. Notably, we identified ITGB3, whose expression was abundant in both drug resistance and mesenchymal status, as a promising target to overcome chemoresistance. We also confirmed that depletion of ITGB3 sensitized cancer cells to conventional chemotherapeutic drugs by modulating the NF-κB signaling pathway. Considering the poor druggability of ITGB3 and the lack of feasible drugs to directly inhibit this protein, we took an in silico screening for drugs mimicking the transcriptome-level changes caused by knockdown of ITGB3. This approach successfully identified atorvastatin as a novel candidate for drug repurposing, paving an alternative path to drug screening that is applicable to undruggable targets.

Keywords: Atorvastatin; Biomarker; Chemoresistance; Drug repurposing; ITGB3; Mesenchymal cancer; NF-κB; Pharmacogenomics; Systems pharmacology.

Fig. 1

Epithelial mesenchymal transition as a common mechanism underlying anticancer drug resistance a Top 10 most up-regulated pathways in the resistance group across chemotherapeutic (left panel) and targeted drugs (right panel) are summarized as the number of drugs by which the corresponding pathway is significantly regulated. Significantly enriched pathways per a drug were selected through hypergeometric tests (FDR < 0.05) using the hallmark gene sets from MsigDB. b Clustering of A549 and TD cells together with other lung cancer cell lines from the resistant (red) and sensitive (green) groups for doxorubicin by Partial Least Square Discriminant Analysis (PLS-DA) based on known EMT-genes c Programed cell death was examined by Annexin V/7AAD staining after DMSO, etoposide (ETO: 80 μM) and Camptothecin (CPT: 1 μM) 48 h treatment. d Sub G1 population was measure by FACS at 48 h after IR. The quantified sub G1 population was presented as bar graph (right) e and f Immunoblotting for apoptosis marker such as cleaved caspase 3 and 9 (C.Caspase3 and 9) after doxorubicin (Doxo) treatment at indicative days (e) or concentration (f), β-actin and E-cadherin used for an equal loading control and epithelial marker

Fig. 2

ITGB3-NFkB signaling contributes to acquisition of chemoresistance in mesenchymal lung cancer cell a The genes strongly associated with chemoresistance and increased expression in TD compared to A549 cell. Known EMT-genes are marked in red. b Distribution of the number of ITGB3 vulnerable cells (dependency score < − 1) belonging to the sensitive (S) and resistant (R) group for 32 chemotherapeutic and 20 targeted drugs. (P-value by t-test). c Immunoblotting analysis for cleaved PARP (C.PARP), cleaved caspase 3 and 9 (C.Caspase3 and 9) of TD shCont, shβ #3 and shβ #4 after doxorubicin (Doxo) treatment at indicative days d Immunoblotting analysis for cleaved caspase 3 and 9 (C.Caspase3 and 9) after Etoposide (ETO, 80 μM) treatment with or without transient transfection of ITGB3 in A549 e Enriched pathways (hypergeometric test, q-value < 0.1) and the median hazard ratio of the member genes in each pathway among the down-regulated genes by ITGB3 depletion. Hazard ratio is calculated using TCGA LUAD patient dataset, and cancer signaling pathways are marked in red. f Expression change of NF-κB signaling genes (z-score, normalized log2 fold change) g Fluorescent microscopic images for p65 (Green) in A549 and TD cells. DAPI (Blue) for nuclear counterstaining, (The scale bars: 50 μm) h Immunoblotting analysis for IκB and acetylated p64 at lysine 221 (K221) in TD (shCont) and ITGB3 KD cells, β-actin for equal loading control i Luciferase reporter activity for NF-κB activity in TD (shCont) and ITGB3 KD cells (shβ#3 or shβ#4) j Immunoblotting analysis for p65, cleaved PARP, caspase 3 and 9 (C.PARP, C.Caspase3 and 9) after p65 knockdown with siRNAs (#2 or #3)

Fig. 3

Atrovastatin sensitizes chemotherapy through modulating NF-κB a CMap approach to identify chemosensitizer drugs using two different signatures: i) down-regulated genes by ITGB3 depletion, and ii) the intersection of i) and NF-κB pathway genes b the candidate drug list predicted by the two signatures. Atorvastatin was commonly predicted by both signatures. c and d Immunoblotting analysis for cleaved caspase 3 or (C.Caspase3 or C.Caspase9) at indicative dose c of atorvastatin (ATV) or Days (d, with 0.1 μM of ATV) with doxorubicin (Doxo). α-tubulin or β-actin for equal loading control e Light microscopic images of TD cells with or without atorvastatin (ATV, 1 μM) after doxorubicin treatment (Doxo) (top), Graphical presentation of cell viability (bottom) f Flow cytometry for Annexin V staining at 24 h after indicative dose of Doxorubicin (Doxo) with 0.1 μM of ATV pretreatment (top), Graphical presentation of apoptotic cells (bottom) g Luciferase reporter activity for NF-κB activity in TD after indicative dose of atorvastatin (ATV) h Immunoblotting analysis for ITGB3, BCL-xL and IκB after indicative dose of atorvastatin (ATV) treatment in TD cells, β-actin for equal loading control