Lentiviral shRNA screen to test the validity of a gene signature of breast cancer stem cells using high throughput mammosphere assays Bhuvanesh Dave PhD 1 , Trey Westbrook 2 , Michael T Lewis PhD 1 , Jessi Wu 1 , Jenny C Chang MD 1 Lester and Sue Smith Breast Center, and Dept of Biochemistry & Molecular Biology Baylor College of Medicine, Houston, TX 77030 Abstract Background Acknowledgements; This study was done with support from Grant# RO1 CA112305-01 and SPORE P50 CA50183 References • Creighton et al. Residual breast cancers after conventional therapy display mesenchymal as well as tumor-initiating features. Proc Natl Acad Sci U S A. 2009 Aug 18;106(33):13820-5. • Dave et al. Treatment Ressistance in Stem Cells and Breast Cancer. J Mammary Gland Biol Neoplasia. 2009 Mar;14(1):79-82. • Al-Hajj et al. Prospective identification of tumorigenic breast cancer cells. Proc Natl Acad Sci U S A. 2003 Apr 1;100(7):3983-8 Gene Expression Profiling of Chemoresistant , MS initiating population of cells by Affymetrix Gene Array Expression of Control GFP shRNA genes in SUM 159 Cell Line and Dose Dependent effect of GSI Inhibitor on MS formation Correlation of Gene Signature with Different Types of Tumor Types by Bioinformatics. Pathways important in MS formation as determined by Lentiviral shRNA screen Genes that Significantly Alter Primary MS Formation (p<0.05). One in 8 women in the US suffer from breast cancer and although current treatments have been successful in reducing the rate of cancer dependent deaths over the past few years, the major problem that faces this field is the high likelihood of relapse within 5-10 years of initial therapy. One possible reason for the relapse might be the presence of cancer stem cells in the tumor which are not inhibited by traditional therapies and thus may require therapies that target this subpopulation of cells. The cancer stem cell hypothesis postulates that the cancer functions in a hierarchical manner similar to the breast tissue and contains a population of tumor initiating cells/ cancer stem cells. We have identified a gene signature which is derived from an overlap between CD44 + /CD24 -/low vs. all other cell subpopulations, and cancer-derived Mammosphere (MS) vs. bulk tumor which we reasoned will best represent the tumor-initiating or “cancer stem cells. We found that 477 genes were differentially expressed in the combination group of which 185 of these were highly expressed in CD44 + /CD24 -/low cells and in MS, a highly significant overlap (p<1.0E-9, one-sided Fisher’s exact). The rest of the 292 genes demonstrated a reduction in expression in the CD44 + /CD24 -/low cells and cancer-derived MS vs. all other cells and bulk tumors, respectively (p<5.0E-5, one-sided Fisher’s exact). We then proceed to test our gene signature by screening this entire list of genes for its role in MS. We created a library comprises ~14 plates containing approximately ~1200unique shRNA constructs, with 3-4 shRNA constructs per gene, thereby targeting ~500 unique genes. The library is designed and constructed on a “one gene, one well” structure, such that each sequence validated lentiviral shRNA construct targeting an individual gene is located in a unique well of a 96-well plate. We have modeled our screen after a similar synthetic lethal screen published recently to identify shRNAs conferring sensitivity of non-small-cell lung cancer (NSCLC) cells. Using SUM159 cells that were transduced with individual lentiviruses representing our previously identified genes (efficiency ~80%), along with a positive control lentivirus targeting Bmi1, a polycomb group gene known to be required for self-renewal of many stem/progenitor cell types, a non-specific negative control lentivirus targeting firefly luciferase, as well as untreated cells. In each of the transduced population cells will be plated in a 96 well dish at a density of 2,000 cells/well in serum-free medium supplemented with B27 nutrients, bFGF, EGF. MSs were allowed to form for 4 days, and then counted using Gelcount (Oxford Optornix). The MSs were trypsinized and replated in the same plate to form secondary mammospheres and primary and secondary mammosphere formation efficiency will be calculated. The secondary mammospheres were counterstained with PKH26 (a red membrane staining dye) and the MSs were photographed by high throughput microscopy to determine the changes in morphology with respect to MS formation. The primary MSFE was determined for all the shRNAs and we identified 151 shRNAs that demonstrated significant change (p< 0.05) in MS formation with respect to control. This gives us a set of targets that need to be validated by testing them in another cell line, which in the long run will give us possible targets for pharmaceutical intervention to eliminate cancer stem cells. This screen will be repeated in another cell line and a common set of genes will give us targets to test in our tumor xenograft models which will get us closer to the clinical relevant therapies which target the cancer stem cells which would be used in conjunction with chemotherapy to target both the bulk of the tumor and the cancer stem cell population in order to reduce the possibility of relapse in breast cancer patients. 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 Control 1um GSI 5uM GSI 10uM GSI % MSFE A Model For “Cancer Stem Cells” In Treatment Resistance and Disease Recurrence Patient Samples Treated with Standard Chemotherapy showed an increase in Cancer Stem Cells as demonstrated by the CD44+/CD24- profile and MS formation Efficiency data Open Biosystems Lentiviral shRNA Library Screen to Confirm the Genes that Regulate the Cancer Stem Cell Pathway  Genes identified in the gene signature were confirmed using the shRNA mediated Lentiviral Screen Growth Factor Signaling, Notch, Hedgehog and β-Catenin play an important role in Chemoresistant Cancer Stem Cells This data will be used to determine a list of candidate genes that will be inhibited along with Standard Chemotherapy for complete response Conclusions We started with 493 genes and 1120 shRNA’s for this Lentiviral screen. 128 shRNA’s representing 108 unique genes showed significant alteration in the MS formation Efficiency 79 shRNA’s representing 62 unique genes showed significant alteration in the MS formation Efficiency Genes that Significantly Alter Secondary MS Formation (p<0.05). AA_Bmi1_pos2_3 AA_Bmi1_pos2_8 AA_GSI_pos1_1 AB_BLANK2_6 AB_BLANK2_8 AB_EV2_14 AC_EG5_neg2_13 RHPN2_172_0329_BDave7_C9_7 OAZ3_172_0327_BDave6_B4_6 CENPF_172_0042_BDave2_C5_2 ANLN_172_0611_BDave1_H1_1 LOC157381_172_0381_BDave11_C5_11 IFT81_172_0297_BDave4_C11_4 KIAA0194_172_0473_BDave11_C8_11 CENPF_172_0190_BDave2_B5_2 IGSF3_172_0370_BDave4_A12_4 CISH_172_0066_BDave2_H6_2 SSX2IP_172_0357_BDave8_A8_8 TACSTD1_172_0053_BDave8_D11_8 RAB25_172_0620_BDave7_H10_7 ERBB3_172_0527_BDave3_G4_3 KIAA1632_172_0659_BDave11_A8_11 F11R_172_0135_BDave3_C5_3 ANLN_172_0735_BDave1_G12_1 NTN4_172_0218_BDave6_F8_6 ROGDI_172_0024_BDave7_G9_7 BAIAP2L1_172_0223_BDave1_F9_1 VAV3_172_0024_BDave9_A2_9 CDCA2_172_0579_BDave2_D10_2 ADH1B_172_0330_BDave14_D10_14 DEFA1_172_0050_BDave2_B10_2 GSTO2_172_0118_BDave4_B11_4 TRPS1_172_0031_BDave9_H10_9 SORBS2_172_0288_BDave8_G5_8 RASSF7_172_0568_BDave7_G4_7 MAP4K4_172_0131_BDave11_E8_11 KPNA3_172_0252_BDave11_H9_11 TRPS1_172_0262_BDave9_F3_9 PPP3CA_172_0462_BDave12_E4_12 BIRC5_172_0486_BDave1_G1_1 CREB3L4_172_0550_BDave2_E9_2 NTN4_172_0205_BDave6_B10_6 ZNF93_172_0742_BDave9_B5_9 ZNF93_172_0317_BDave9_A12_9 ZNF93_172_0335_BDave9_D1_9 NPNT_172_0067_BDave6_B4_6 MAGI3_172_0143_BDave5_C4_5 ZNF93_172_0690_BDave9_B11_9 ZNF93_172_0111_BDave9_B4_9 NKX3-1_172_0353_BDave6_B9_6 MTAC2D1_172_0320_BDave6_D6_6 PDLIM5_172_0673_BDave7_G2_7 ENAH_172_0259_BDave3_A8_3 PKIB_172_0587_BDave7_C6_7 ERBB3_172_0303_BDave3_F8_3 FRK_172_0402_BDave4_E6_4 FRK_172_0598_BDave4_G6_4 PDE4DIP_172_0380_BDave12_B7_12 COX6C_172_0527_BDave2_E11_2 TMSL8_172_0140_BDave8_C6_8 IRX5_172_0278_BDave4_F3_4 PDE4DIP_172_0223_BDave12_A5_12 KIF9_172_0105_BDave5_H9_5 CTBP2_172_0393_BDave2_C11_2 C17orf28_172_0188_BDave1_H2_1 RBM35A_172_0473_BDave7_A4_7 GCNT1_172_0307_BDave4_A8_4 PGM2_172_0184_BDave7_A1_7 POU2F2_172_0191_BDave12_E3_12 LGR4_172_0309_BDave5_F7_5 NUP188_172_0229_BDave12_B1_12 DKFZP779L1068_172_0073_BDave2_E3_2 ENAH_172_0124_BDave3_B5_3 DKFZP779L1068_172_0110_BDave2_D2_2 Control Genes Genes that Promote MS formation Waterfall plot of all genes Waterfall plot of all genes Objective: Confirmation of the Cancer Stem Cell Signature derived from patients using high throughput Mammosphere Screen