Lentiviral shRNA screen to test the validity of a gene signature of breast cancer stem cells using high throughput mammosphere assays Jenny Chang Lab by Bhuvanesh Dave PhD

Tumorigenic Cells: Are we missing the target? Jones et al. JNCI 96:583, 2004

Tumorigenic Cells: Are we missing the target? Jones et al. JNCI 96:583, 2004

Tumorigenic Cells: Are we missing the target? Jones et al. JNCI 96:583, 2004

A Model For “Cancer Stem Cells” In Treatment Resistance and Disease Recurrence

CD44+/CD24- n=31 A Mammosphere Formation Efficiency n=31 B Chemotherapy Increases the Proportion of CD44 + /CD24 low/- Cells and Mammosphere-Initiating Cells Li et al (2008) JNCI 100:672-9

The Proportion of CD44+/CD24- Cells Correlates With Mammosphere Initiation Potential Mammospheres Are Enriched For Mammosphere-initiating Cells Compared To The Tumor of Origin

Gene Expression Signature of Chemoresistant Mammosphere-initiating Cells

The “Signature” Is Preferentially Manifest in Claudin-Low Tumors

Design of GIPZ shRNAmir Library

Choosing a Cell Line In order to confirm our patient derived gene signature we looked for Claudin Low like cell lines Based on Joe gray’s dataset we narrowed it down to MDA-MB231, SUM-159PT & HS578T We chose SUM159PT because it possessed the CD44/24 population, which had been shown to have increased tumorigenic potential.

Lentiviral Screen using open bioystems library and our gene signature We started with 493 genes and 1120 shRNA’s for this Lentiviral screen.

Screening for CSC drug targets using shRNA for gene signature Library Cherry Picking of clones Purification of DNA TransfectionInfection Day 1 transfect Day 3 collect Day 4 collect Mammosp heres Visualize and count Trypsinize mammospheres HBSS + serum Spin and Resuspend in MEGM+ Visualize and count PKH26 dye on Day4 Phase I Phase II

20x 10x 96 Well 24 Well 6 Well SUM159PT cells-Mammospheres plated and photographed

Testing Controls Testing of Controls to Determine the Set of Controls to be used in the Screen - Infectivity - Impact on Mammosphere formation.

Experiments Conduct the screen using SUM159PT cells with the aforementioned controls and genes derived from our signature Add some of the Hedgehog and Notch sigaling pathway regulators to that gene list in order to test for things that have been the usual suspects in the cancer stem field. We added 40 genes from the ALDH1 derived signature from Dr. Max Wicha’s Group. Confirm reduction of gene expression of the control genes by real time PCR which will be eventually followed by western blots.

Results We conducted this screen in 14x96 well plates each time (8 times) We collected information on MS formation information for primary and secondary MS using Gelcount from Oxford Optronix We have currently analyzed the primary MS data and we got 151 unique shRNAs where MS number changes significantly p=0.05

Results of Primary MS formation screen depicted as a Z-score of all the genes tested in the screen Z Score

Candidate Regulators p< shRNA’s representing 108 unique genes showed significant alteration in the MS formation Efficiency in SUM159

Increasing MSFE Decreasing MSFE

BT549 p<0.05

Candidate Regulators p<0.05 BT549

Increasing MSFE Decreasing MSFE BT549

Future Directions Do real time PCR of all the targets. Liposomal delivery of shRNA in cells/animals using nanoparticles Target two tumor lines based on five target gene identified from the combination of these two cell lines.