Targeting synthetic lethality between the SRC kinase and the EPHB6 receptor may benefit cancer treatment
Bibliographic record
Abstract
// James M. Paul 1, * , Behzad Toosi 2, * , Frederick S. Vizeacoumar 2, * , Kalpana Kalyanasundaram Bhanumathy 2 , Yue Li 3, 4, 5 , Courtney Gerger 2 , Amr El Zawily 2, 6 , Tanya Freywald 7 , Deborah H. Anderson 7 , Darrell Mousseau 8 , Rani Kanthan 2 , Zhaolei Zhang 3, 4 , Franco J. Vizeacoumar 2, 7 , Andrew Freywald 2 1 Department of Biochemistry, University of Saskatchewan, Saskatoon, SK, S7N 5E5, Canada 2 Department of Pathology and Laboratory Medicine, College of Medicine, University of Saskatchewan, Royal University Hospital, Saskatoon, SK, S7N 0W8, Canada 3 Department of Computer Science, University of Toronto, Toronto, ON, M5S 3G4, Canada 4 The Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada 5 Present address: Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA 6 Faculty of Science, Damanhour University, Damanhour, 22516, Egypt 7 Cancer Research, Saskatchewan Cancer Agency, Saskatoon, SK, S7N 5E5, Canada 8 Cell Signaling Laboratory, Neuroscience Cluster, University of Saskatchewan, Saskatoon, SK, S7N 5E5, Canada * These authors contributed equally to this work Correspondence to: Franco J. Vizeacoumar, email: franco.vizeacoumar@usask.ca Andrew Freywald, email: andrew.freywald@usask.ca Keywords: breast cancer, genetic interaction, synthetic lethality, EPHB6, SRC kinase Received: April 22, 2016 Accepted: June 17, 2016 Published: July 13, 2016 ABSTRACT Application of tumor genome sequencing has identified numerous loss-of-function alterations in cancer cells. While these alterations are difficult to target using direct interventions, they may be attacked with the help of the synthetic lethality (SL) approach. In this approach, inhibition of one gene causes lethality only when another gene is also completely or partially inactivated. The EPHB6 receptor tyrosine kinase has been shown to have anti-malignant properties and to be downregulated in multiple cancers, which makes it a very attractive target for SL applications. In our work, we used a genome-wide SL screen combined with expression and interaction network analyses, and identified the SRC kinase as a SL partner of EPHB6 in triple-negative breast cancer (TNBC) cells. Our experiments also reveal that this SL interaction can be targeted by small molecule SRC inhibitors, SU6656 and KX2-391, and can be used to improve elimination of human TNBC tumors in a xenograft model. Our observations are of potential practical importance, since TNBC is an aggressive heterogeneous malignancy with a very high rate of patient mortality due to the lack of targeted therapies, and our work indicates that FDA-approved SRC inhibitors may potentially be used in a personalized manner for treating patients with EPHB6-deficient TNBC. Our findings are also of a general interest, as EPHB6 is downregulated in multiple malignancies and our data serve as a proof of principle that EPHB6 deficiency may be targeted by small molecule inhibitors in the SL approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".