High-Throughput Ectopic Expression Screen for Tamoxifen Resistance Identifies an Atypical Kinase That Blocks Autophagy
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High-throughput ectopic expression screen for tamoxifen resistance identifies an atypical kinase that blocks autophagy Laura Gonzalez-Malervaa,b, Jaehong Parkb, Lihua Zouc, Yanhui Hub, Zahra Moradpoura,b,d, Joseph Pearlbergb, Jacqueline Sawyerb, Hallam Stevensb, Ed Harlowb,1, and Joshua LaBaera,b aThe Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287; bHarvard Institute of Proteomics, Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115; cThe Dana Farber Cancer Institute, Boston, MA 02115; and dDepartment of Pharmaceutical Biotechnology, Faculty of Pharmacy, University of Medical Sciences, 71364 Shiraz, Iran Contributed by Ed Harlow, December 13, 2010 (sent for review October 13, 2010) Resistance to tamoxifen in breast cancer patients is a serious Kinases play an essential role in cellular physiology and several therapeutic problem and major efforts are underway to understand have been shown to cause tamoxifen resistance. It is likely that underlying mechanisms. Resistance can be either intrinsic or ac- other kinases contribute to hormone independence. quired. We derived a series of subcloned MCF7 cell lines that were either highly sensitive or naturally resistant to tamoxifen and studied Results the factors that lead to drug resistance. Gene-expression studies Ectopic Kinase Expression Screen for Tamoxifen Resistance. revealed a signature of 67 genes that differentially respond to ta- Tamoxifen-sensitive and -resistant MCF7 subclones. We selected the moxifen in sensitive vs. resistant subclones, which also predicts MCF7 line for a cell-based screen because it requires estrogen for disease-free survival in tamoxifen-treated patients. High-throughput proliferation and is growth-inhibited by antihormone therapy. We cell-based screens, in which >500 human kinases were indepen- noted, however, that MCF7 displayed a heterogeneous response dently ectopically expressed, identified 31 kinases that conferred to hormonal manipulation, revealing partial but not complete cell drug resistance on sensitive cells. One of these, HSPB8, was also in killing after tamoxifen. Thus, we used limiting dilution to separate seven well-behaved, subcloned cell lines of which three were the expression signature and, by itself, predicted poor clinical out- MEDICAL SCIENCES sensitive and four were resistant to tamoxifen based on the ratio of come in one cohort of patients. Further studies revealed that HSPB8 A protected MCF7 cells from tamoxifen and blocked autophagy. More- growth in tamoxifen/control (Fig. 1 ). We used resazurin uptake (Fig. 1B) and microscopic observation (Fig. 1C) to further char- over, silencing HSBP8 induced autophagy and caused cell death. > Tamoxifen itself induced autophagy in sensitive cells but not in re- acterize two each of these that were either sensitive ( 90% cell death), MCF7-B7TamS and MCF7-C11TamS, or tamoxifen-re- sistant ones, and tamoxifen-resistant cells were sensitive to the in- sistant [proliferate in presence of 4-OHT (4-hydroxy-tamoxifen)], duction of autophagy by other drugs. These results may point to an MCF7-G11TamR and MCF7-H9TamR. The inhibitory concentra- important role for autophagy in the sensitivity to tamoxifen. tion for 50% of the sensitive cells (IC50) was 5 μM for tamoxifen (TAM) or 1 μM for 4-OHT after 6 d, whereas the resistant cells functional screen | estrogen receptor continued to grow at these conditions. We confirmed that the subclones were all derived from the he two thirds of women with estrogen receptor- (ER) or parental line by demonstrating 100% concordance with the Tprogesterone receptor-positive breast cancers are excellent parent and other MCF7 cells for a panel of 24 SNPs and less candidates for antihormone therapy. Selective ER modulators than 5% concordance across other non-MCF7 cells (Table S1). (SERMs), like tamoxifen, block ER activation and have impacted High-throughput functional cell-based screens. We screened our col- both therapy and survival. However, the success of tamoxifen lection of >500 full-length and fully-sequenced cDNAs of human therapy is limited by intrinsic and acquired drug resistance. Sev- kinases (14) to find those that confer tamoxifen resistance in the eral pathways have been implicated in antiestrogen resistance, sensitive subclones. We introduced the ectopic kinases using including: the PI3K/AKT/mTOR (mammalian target of rapamy- retroviral transduction because it was more efficient and showed A cin) pathway, which is implicated in cell survival; the EGFR less variability than transfection (Fig. S1 ). Assay conditions were family; and the RAS/RAF/MEK1/2/ERK1/2 family, which regu- adjusted using ERBB2 as a positive control because its ectopic overexpression conferred resistance to MCF7 (1) (Fig. S1B). late cell proliferation (1, 2). Loss of ER expression or function TamS may also be an important mechanism of de novo resistance to We adapted the MCF7-C11 for transduction in high- throughput screen (15). Using a partial set of 250 human kinases tamoxifen, either through relatively rare ER mutations or changes in a pilot screen, we established reproducible conditions on dif- in coactivators and corepressors (3). ferent days at different drug concentrations with a calculated Several groups have used gene-expression analysis to identify correlation coefficient of 0.80 (Fig. 1D). We then executed three genes regulated through ER (4) that are affected by SERMs in independent screens with the complete pJP1520-Kinase set breast cancer cells (5, 6). Others have used tumor samples to de- (505). From these and the pilot screen, we identified 80 kinases velop gene signatures that can predict clinical responses to tamox- that conferred resistance to 4-OHT (z score > 1.5). The viral – ifen (7 10). Genetic strategies have also been used to identify genes supernatants for these 80 chosen candidate kinases were prepared that drive tamoxifen resistance. Receptor tyrosine kinases and MAPK signaling were detected using expression of pooled cDNA libraries in ZR-75-1, an approach often biased toward the most Author contributions: L.G.-M., J. Park, E.H., and J.L. designed research; L.G.-M., J. Park, abundantly expressed genes and which requires recovery of hits by L.Z., and Z.M. performed research; J. Pearlberg and J.S. contributed new reagents/analytic PCR (11). The analysis of antiestrogen-sensitive and -resistant tools; L.G.-M., L.Z., Y.H., H.S., and J.L. analyzed data; and L.G.-M. and J.L. wrote the paper. MCF7 cells by SNP and comparative genomic hybridization pointed The authors declare no conflict of interest. to changes in protein abundance rather than somatic genomic Freely available online through the PNAS open access option. changes (12). An RNA interference screen of kinases identified 1To whom correspondence should be addressed. E-mail: [email protected]. CDK10, CRK7, and MAP2K7, whose knockdown cause tamoxifen This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. resistance in MCF7 cells (13). 1073/pnas.1018157108/-/DCSupplemental. www.pnas.org/cgi/doi/10.1073/pnas.1018157108 PNAS Early Edition | 1of6 Downloaded by guest on October 2, 2021 and resistant subclones by performing gene-expression profile analysis after estrogen and tamoxifen challenge. As expected in sensitive cells, tamoxifen blocked the ability of estrogen to induce (or repress) genes. We focused specifically on identifying the genes that failed to show an effect of tamoxifen in resistant cells. These 227 estrogen-responsive genes responded to tamoxifen in sensitive cells but not resistant ones (Fig. 2A). The genes included CCND1, IGF1R, MYC, and RERG, which are known to contribute to the development of resistance, as well as ERBB2, BCAR3, PIK3C2B, PIK3R3, and some negative regulators of cell cycle progression, such as CDKN1A (p21) and CDKN2B (p15) (1) (Table S4). We found that p53, TGFβ, p21 regulation, ErbB, cell cycle, and Jak-STAT signaling were the pathways that demonstrated statistically significant association with tamoxifen deregulation in resistant cells (Table S5). Clinical outcome prediction. We wondered if these 227 genes might also be predictive for outcomes in breast cancer patients who received tamoxifen. Because tumor tissue cannot be challenged with drugs, we focused on the subset of genes with an expression difference between the sensitive and resistant cells at baseline (no treatment). Using the PAM algorithm (17), we found 72 probes for 67 unique genes (Table S4). The entire microarray dataset is available through the Gene Expression Omnibus (ac- cession no. GSE 26459). Using clinical studies with long-term outcomes in tamoxifen- treated women that examined gene expression in tumors (18), the expression profile for each patient’s tumor was sorted into “re- sistance-like” or “sensitive-like” groups. These genes, selected entirely for their differential tamoxifen responses in our sensitive and resistant subclones, predicted better disease-free survival of patients that matched the “sensitive” signature (Fig. 2B). Pre- sumably, these patients were more likely to respond to tamoxifen and, hence, had a lower probability of relapse compared with patients whose patterns were closer to the resistant cells. In con- trast, the “resistance pattern” patients had a one in two chance of relapse after 5 y of tamoxifen treatment. We further confirmed C Fig. 1. MCF7 subclones and kinome screen. (A) MCF7 cells were diluted and this result using a different