Abstract 233: Identification of cancer vulnerabilities to metabolic perturbation using genome wide CRISPR screens
Bibliographic record
Abstract
Abstract The CRISPR-Cas9 system provides an effective way to introduce targeted loss-of-function mutations in mammalian cells. The advance that the CRISPR-Cas9 technology brings to human genetics sets the stage for identifying cellular fitness genes that operate either globally (core fitness genes) or specifically within a particular genetic background or environmental context (context-specific fitness genes). In tumors, this is the foundation for the concept of synthetic lethality as genes required in tumor cells but not in adjacent normal tissues should make ideal therapeutic targets with high effectiveness and minimal side effects. Towards this goal, we have developed a second-generation CRISPR gRNA library of 176,500 guides targeting 17,661 human protein-coding genes. We used the library to screen five human cell lines, representing a cross-section of wild type and cancer tissues, to identify genes whose knockouts induce significant fitness defects. Our screens accurately recapitulate pathway-specific genetic vulnerabilities induced by known oncogenes and identify novel context-specific vulnerabilities. Interestingly, we identified a specific dependency on mitochondrial activity and we validated this using various complex I inhibitors. This strongly supports the idea that oxidative phosphorylation (OXPHOS) dependency - a clear exception to the Warburg effect - is a targetable weakness of some tumors. In order to further understand this metabolic vulnerability, we performed a synthetic lethal screen to identify sensitizers of OXPHOS inhibition. Our screen revealed that inhibition of mitochondrial OXPHOS sensitizes the cells to loss of other metabolic pathways such as glycolysis, pentose phosphate pathway and lipid biosynthesis. Furthermore, loss of the cytosolic aspartate aminotransferase GOT1 was found to be synthetic lethal with perturbation of OXPHOS. This is consistent with the essential role of the electron transport chain in cell proliferation, which is to enable aspartate synthesis. Additionally, we also find novel genes, whose loss of function might alleviate the affect of OXPHOS perturbation. Our findings demonstrate that CRISPR-Cas9 screens enable a high-resolution view of the genetic vulnerabilities of a cell that may represent therapeutic opportunities in cancer. Further, synthetic lethal chemical-genetic screens can reveal novel functional drug combinations, which will enhance the efficacy of targeted therapies. Citation Format: Megha Chandrashekhar, Michael Arreger, Ashwin Seetharaman, Traver Hart, Jason Moffat. Identification of cancer vulnerabilities to metabolic perturbation using genome wide CRISPR screens. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 233.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".