JUN 11, 2024 8:00 AM PDT

Exploring the value of oligonucleotide antibody-pair based proteomics in cancer cell lines

PLEASE NOTE: THE INFORMATION PRESENTED IS NOT PUBLISHED AND WILL NOT BE AVAILABLE FOR ON-DEMAND VIEWING AT THIS TIME.

Sponsored by: Olink Proteomics
Speakers

Event Date & Time
Date: June 11, 2024
Time: 8:00 AM (PDT), 11:00 AM (EDT), 5:00 PM (CEST)
 
THE INFORMATION PRESENTED TODAY IS NOT PUBLISHED AND WILL NOT BE AVAILABLE FOR ON-DEMAND VIEWING AT THIS TIME.  
 
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Abstract
Cancer genome alterations that cause cancer cells to grow also confer vulnerabilities, which normal cells lack. The challenge is that, for the majority of cancers, we do not understand the relationship between the genetic alterations and the dependencies they cause. To solve this problem, we are creating a Cancer Dependency Map (DepMap) by systematically identifying genetic dependencies and small molecule sensitivities as well as discovering the biomarkers that predict them. However, we are still in the early stages of having a complete map and there are many dependencies and drug vulnerabilities that are not explained by any of the omics features. Using the antibody-based barcoding Olink technology, we profiled 164 cancer cell lines and compared results to previous MS proteomics. Our initial quality control analysis indicated that Olink to mRNA correlation, in the cell lines, was higher than MS data sets. Using Olink technology, we were able to detect low abundance proteins that might have been missed with MS proteomics. Furthermore, in preliminary analysis we were able to show expected results of dependencies associated with protein expression, and additional investigation with genomic correlations is ongoing. This new proteomics platform will help make progress towards the identification of the landscape of cancer vulnerabilities and create a roadmap for cancer therapeutics.
 
Learning Objectives
  • Learn how DepMap reveals genetic dependencies critical for cancer cell survival.
  • Understand how Olink technology enhances proteomic profiling in cancer cell lines and is able to detect low-abundance proteins missed using mass spectrometry, showing better correlations with mRNA expression levels
  • Explore preliminary findings associating protein expression with cancer cell dependencies.
  • Hear how this proteomics platform will accelerate the identification of the landscape of cancer vulnerabilities and create a roadmap for cancer therapeutics
 
 
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