Abstract A37: Mapping KRAS signaling pathways using the Mammalian-Membrane Two-Hybrid (MaMTH) assay to elucidate novel therapeutic targets
Bibliographic record
Abstract
Abstract Background: KRAS is a well-established cancer driver. Clinically successful therapeutics have not yet been developed despite its disease burden, suggesting that KRAS-driven cancers are more complicated than previously thought. Aim: Our goal is to identify the global changes in KRAS interaction patterns that occur in disease states. This is accomplished by mapping the dynamic interactome of both WT and oncogenic KRAS isoforms using the Mammalian Membrane Two-Hybrid (MaMTH) assay, which is suitable for identification of protein interactors of virtually any integral membrane or membrane-associated protein. Methods: To probe the protein-protein interactions (PPIs) of KRAS, we used the Mammalian Membrane Two-Hybrid (MaMTH) assay, a split-ubiquitin-based two-hybrid system that can be applied to any cell line. This assay is suited for PPI detection using both low- to-medium throughput array and high-throughput large-scale PPI screening. We generated stably expressing “bait”-tagged KRAS constructs in HEK293T cells that contained the MaMTH reporter system. KRAS baits, namely KRAS-WT, -G12D, -G12V, and -Q61H, were characterized using signaling assays as well as within the MaMTH system using “prey”-tagged CRAF interaction control, Western blotting, and immunofluorescence techniques. Currently, we are performing unbiased screening for PPIs of KRAS using the human ORFeome (hORFeome) library consisting of approximately 13,000 fully sequenced human ORFs. Results: We first validated compatibility of KRAS in the MaMTH assay through several means. Oncogenic KRAS variants showed increased interaction signal with CRAF (a known KRAS binding partner) compared to KRAS-WT. This corresponded with upregulated MAPK pathway activation by oncogenic KRAS, as determined from increased pERK levels via Western blotting. KRAS bait expression levels were similar across all variants, suggesting that these findings were not due to differential expression of KRAS isotypes. Additionally, we confirmed that the KRAS bait correctly localizes to the plasma membrane, consistent with previous literature. After establishing KRAS compatibility with the MaMTH assay, we have begun unbiased screening of the hORFeome against KRAS baits in the WT, G12D, G12V, and Q61H isoforms. Conclusions: We have characterized KRAS compatibility with the MaMTH assay. Currently, we are performing large screening protocols for high-throughput detection of PPIs of KRAS using MaMTH. Citation Format: Ingrid Claudia Grozavu, Jamie Snider, Anna Lyakisheva, Igor Stagljar. Mapping KRAS signaling pathways using the Mammalian-Membrane Two-Hybrid (MaMTH) assay to elucidate novel therapeutic targets [abstract]. In: Proceedings of the AACR Special Conference on Targeting RAS-Driven Cancers; 2018 Dec 9-12; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(5_Suppl):Abstract nr A37.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".