Abstract B024: Phosphoinositide focused CRISPR screen reveals ITGAV as a critical gene in pancreatic cancer growth and invasion
Bibliographic record
Abstract
Abstract Background: Pancreatic Cancer (PC) is one of the most aggressive cancer types, with less than 10% of patients surviving at 5-years. One hallmark of PC is the frequent mutation of the oncogene KRAS resulting in the constitutive activation of the phosphoinositide-3-kinase (PI3K) signaling pathway. The PI3K pathway is an intracellular signaling pathway that regulates cell growth, metabolism, and survival in response to extracellular signals. Given the importance of deregulated phosphoinositide (PI) signaling in PC, we hypothesize that genes coding for PI-metabolizing enzymes and effectors may have significant and unappreciated roles in PC. Methods: We generated a CRISPR knockout (KO) library that targets 1,534 PI-associated genes to discover novel essential genes in PC. Results: In a PANC-1 screen, we identified 106 essential genes across all timepoints, including 28 novel candidate genes and 78 previously identified essential genes. Among six validated candidate genes, we demonstrate that Integrin Subunit Alpha V (ITGAV) is a protein with clinical importance in PC. Treatment of PC cell lines with an ITGAV integrin antagonist as well as KO of ITGAV resulted in reduced cancer associated phenotypes in vitro, including reduced proliferation rate and compromised migration and invasion capacity. Ongoing studies will investigate perturbations in signaling pathways associated with ITGAV, and aim to elucidate roles for ITGAV in metastatic progression and therapy response. Conclusions: Overall, these findings indicate that ITGAV inhibition represents a putative strategy for the treatment of PC. Citation Format: Daniel K.C. Lee, Ryan Loke, Lydia To, Keyue Chen, Jonathan T.S. Chow, Leonardo Salmena. Phosphoinositide focused CRISPR screen reveals ITGAV as a critical gene in pancreatic cancer growth and invasion [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B024.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".