1 / 19

Targeted Cancer Therapy

Targeted Cancer Therapy. Xiaole Shirley Liu STAT115, STAT215, BIO298, BIST520. Limited Number of Cancer Driver Genes and Pathways. ~140 genes. Limited Number of Cancer Driver Genes Half Druggable. ~479 genes. Cancer Profiles vs Treatment.

louvain
Download Presentation

Targeted Cancer Therapy

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Targeted Cancer Therapy Xiaole Shirley Liu STAT115, STAT215, BIO298, BIST520

  2. Limited Number of Cancer Driver Genes and Pathways ~140 genes

  3. Limited Number of Cancer Driver Genes Half Druggable ~479 genes

  4. 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

  5. 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

  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 bar-coded 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

More Related