Mass Spectrometry-based Quantitative Proteomic Analysis of MCF-10A and MDA-MB-231 Cells using SILAC

1. Mass spectrometry-based quantitative proteomic analysis of MCF-10A and MDA-MB-231 cells using SILAC Shannon Mumenthaler, Ph.D. University of Southern California PS-OC Center for Applied Molecular Medicine 2nd NCI Physical Sciences - Oncology Center Cell Line Exercise June 19, 2010

2. Breast Cancer Progression MCF-10A MDA-MB-231 J. Clin. Invest. 117:3155-3163 (2007)

3. Signaling Pathways Involved in Breast Cancer

4. Observations in System Studies Ideker et al. Integrated Genomic & Proteomic Analyses of a Systematically Perturbed Metabolic Network, Science 292:929-934 (2001)

5. Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) Nature Protocols1: 2650-2660, 2006

6. Proteomics Discovery Experimental Workflow Treatment Cells In Culture Heavy LYS Light LYS mix heavy and light CELL SURFACE SECRETOME Cell surface Protein biotinylation Cell culture media TOTAL EXTRACT concentration Lysis and affinity capture Glycopeptide Capture Protein Fractionation Cell Lysis Elution SHOTGUN LC-MS/MS 25 … 1 25 … 1 25 … 1

7. Standard Cell Line Conditions • SILAC media components MCF-10A:MDA-MB-231: Advanced DMEM-F12 Flex Media Advanced DMEM-F12 Flex Media 5% dialyzed FBS* 10% dialyzed FBS 1% Pen/Strep 1% Pen/Strep 1% Glutamine (200mM) 1% Glutamine (200mM) 2.25% Glucose (200g/L) 2.25% Glucose (200g/L) 1% Sodium Pyruvate 1% Sodium Pyruvate 2% Hepes 2% Hepes 0.5µg/ml Hydrocortisone 100mg/L L-Arginine 20ng/ml hEGF 100mg/L L-Lysine or *L-Lysine 10µg/ml Insulin 100ng/ml Cholera Toxin 100mg/L L-Arginine 100mg/L L-Lysine or *L-Lysine *Used dialyzed FBS instead of dialyzed horse serum • Passaged 6 times in SILAC prior to experimental set-up • Lysed cells in 1% octyl glucoside + protease inhibitors & needle treated • Processed samples for mass spectrometer

8. MCF-10A MDA-MB-231 200 150 100 Cell Viability (%) Normal SILAC 50 0 0 24 48 Time (hrs) 300 250 SILAC Normal 200 150 Cell Viability (%) 100 50 0 0 6 30 Time (hrs) SILAC vs. Normal Growth Conditions *Similar Growth Rate* *Similar Morphology* Normal-MCF-10A SILAC-MCF-10A

9. Heavy LYS Heavy LYS Light LYS Proteomics Workflow Experiment #1- Non-transformed vs. Transformed Experiment #2- Non-treated vs. Treated Light LYS MCF-10A 15nM Paclitaxel MCF-10A 0.1% DMSO MDA-MB-231 MCF-10A A280 RT RT m/z

10. Proteome Comparison of MCF-10Aversus MDA-MB-231 Identified 22,024 peptides - >98% confidence Quantitated 1135 proteins ≥2 fold ≤2 fold upregulated *In MCF-10A* downregulated *In MCF-10A* 357 662 116

11. Gene Ontology Data MCF-10A vs. MDA-MB-231 Upregulated Downregulated

12. “Proof of Principle” Proteins Up in MCF-10A Gene Description Ratio Function F11R Junction Adhesion Molecule A 10.12 Highly expressed in normal mammary epithelium, but down-regulated in invasive BCa ITGB4 Itegrin beta-4 3.21 Expressed in normal breast cells; downregulated or lost in BCa TAGLN Transgelin 5.43 Loss of transgelin is an early event in tumor progression TTLL12 Tubulin-tyrosine ligase-like 2.52 Suppression of tubulin tyrosine ligase during tumor growth protein 12 Up in MDA-MB-231 Gene Description Ratio Function B2M Beta-2-microglobulin 2.7 Overexpression promotes growth and migration of cancer cells HMGA1 High mobility group protein 2.0 Involved in metastatic progression of cancer cells S100A4 Protein S100-A4 7.7 A metastasis-associated protein in breast cancer ANP32E Acidic leucine-rich nuclear 2.6 Member of “six gene signature predicting breast cancer lung metastasis phosphoprotein 32 family member E

13. Paclitaxel Induction of Apoptosis MCF-10A *SILAC* Paclitaxel Treatment Heavy Light Paclitaxel (nM) 0 15 0 15 PARP -actin

14. Kinetics of Paclitaxel Treatment on MCF-10A Cells 120 100 0nM 0.9375nM 1.875nM 80 3.75nM 7.5nM 60 Cell Viability (%) 15nM 30nM 40 60nM 120nM 240nM 20 0 18 24 44 48 72 Time (hrs)

15. Heavy LYS Light LYS Heavy LYS Proteomics Workflow Experiment #1- Non-transformed vs. Transformed Experiment #2- Non-treated vs. Treated Light LYS MCF-10A 15nM Paclitaxel MCF-10A 0.1% DMSO MDA-MB-231 MCF-10A A280 RT RT m/z

16. Quantitative Proteomics Using SILACMCF-10ATreatment with Paclitaxel Identified 8,947 peptides - >98% confidence Quantitated 664 proteins ≥2 fold ≤2 fold upregulated downregulated 12 634 18

17. Gene Ontology DataMCF-10A Treated vs. Untreated Upregulated Downregulated

18. Notable Proteins Upregulated with paclitaxel treatment Gene Description Ratio Function HSPA4 Heat shock 70kDa protein 4 5.9 Tubulin aggregates act as inducers for Hsp70 synthesis; upregulated in response to stress VDAC2 Voltage-depdendent anion channel 2 2.5 Plays a role in apoptotic signaling PLS3 Plastin-3 4.55 Family of actin-binding proteins Downregulated with paclitaxel treatment Gene Description Ratio Function PSMA2 Proteasome subunit alpha type2 10 Decreased expression involved in delaying anaphase onset NOL1 Proliferating cell nucleolar antigen p120 100 Involved in cell cycle regulation MATR3 Matrin 3 2.7 Involved in chromatin organization

19. Milestones • Compare protein expression changes during cellular transformation • Measure protein level differences attributable to treatment

20. Challenges & Future Directions Challenges: • SILAC media differs from standard media conditions • Paclitaxel treatment resulted in fewer protein changes than expected Future Directions: • Perform quantitative mass spectrometry kinetics studies • Synchronize cells before treatment with paclitaxel (using serum starvation, nocodazole) • Treatment with other drugs and alter microenvironment • Perform reciprocal experiments and validate using western blots

21. Acknowledgements University of Southern California: Parag Mallick Jenny Wan Jonathan Katz Ahyoung Joo David Agus Damien Wood Mitchell Gross Robert Burke Kian Kani University of California, San Francisco: Thea Tlsty Steve Oh Philippe Gascard Chira Chen-Tanyolac PS-OC Collaborators Arizona State University: Joshua LaBaer Laura Gonzalez Memorial Sloan Kettering Cancer Center: Franziska Michor Jasmine Foo *Funding: NCI Physical Sciences in Oncology Centers