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Targeted Cancer Therapy Xiaole Shirley Liu STAT115, STAT215, BIO298, BIST520 Limited Number of Cancer Driver Genes and Pathways ~140 genes 2 Limited Number of Cancer Driver Genes Half Druggable ~479 genes 3 Cancer Profiles vs Treatment • “The Difficulty is going to be figuring out how to use the information to help people rather than to just catalogue lots and lots of mutations.” – Bert Voglestein, John Hopkins University • Chemotherapy vs targeted therapy – Chemotherapy: non-specific cytotoxic drugs, mostly affecting dividing cells, mostly intravenous – Targeted: inhibit a specific target, less toxic to normal cells, mostly oral • http://www.foundationone.com video 4 ALK Inhibitors • ALK normally functions in the brain • First rearrangement in lung cancer discovered 2007 in Japan • Upstream of multiple cancer pathways • 2010 starting clinical trials on ALK inhibitor • 2011 FDA approved crizotinib 5 6 Testing on Patients Takes Lots of Time and Money Can we do this faster? 7 Cell Line Drug Screens • CGP: 138 drugs on 727 cell lines • CCLE: 24 drugs on 1,036 cell lines 8 Targeting a Cancer Pathway • Why bother screening if we know the target of a drug? E.g. doesn’t ALK inhibitor inhibit ALK? 9 Cell Line Drug Screens • Cell lines: – Expression – Mutations – Drug sensitivity measure: IC50, half maximal inhibitory concentration (IC50) • How to find expression or mutation biomarkers for drug response? HW6 10 Drug Response BioMarkers • Mutations • Expression AHR expression high or low on MEK inhibitor (PD-0325901) 11 Instead of Drug-Focused, Can we Test Tumor-Specific Therapies? 12 Targeted Therapy • ENO1 and ENO2 parallel pathway • Glioblastoma tumors with ENO1 deletion (5%) is sensitive to ENO2 inhibition 13 Genome-wide Loss of Function Screens • Get rid of a gene (DNA or RNA) in a cell • See how it influences one specific cancer cell as compared to other cells (specificity) • Can we do this in high throughput? 14 Profile Cancer Cell Vulnerability 15 Genome-Wide CRISPR/Cas9 Knockout Screens • Each vector contains a guide sequence (sgRNA) knock out a gene (influence DNA) instead of knock down expression (influence RNA) • Detection through sequencing instead of barcoded arrays Shalem et al, Science 2014; Wang et al, Science 2014 16 Analyzing Ge-LoF Screen Data • How to normalize raw data? • What if one shRNA / sgRNA doesn’t work • How to identify key genes if we have multiple shRNAs / sgRNA per gene? 17 Summary • Use expression and mutations as biomarkers to predict drug response • Use high throughput screening to identify specific targets essential for cancer cells • Can do this in cell lines (or animals) to save time and $ • Lots of data, great for big data mining and machine learning!! 18 Acknolwedgement • • • • John Pack James Lechner Alex Chenchik Haiyun Wang 19