Abstract A018: STRIDE as a technology platform for accurate measurement of DNA breaks and breaks-associated repair proteins
Bibliographic record
Abstract
Abstract Investigating synthetic lethality in DNA repair pathways holds significant promise for advancing targeted cancer therapies, as already proven by the successful introduction of PARP inhibitors. Essential to this endeavor is the precise measurement of DNA damage in the form of DNA breaks, which serves as a crucial and most proximal indicator of treatment efficacy during drug development. Understanding the dynamics of induced DNA damage not only validates treatment mechanisms but also informs optimization of therapeutic regimens and aids in the identification of predictive biomarkers. Accurate assessment of DNA breaks is pivotal in maximizing the therapeutic potential of synthetic lethality approaches and advancing the development of effective anticancer drugs. However, the currently utilized IHC or IF methods detecting the presence or activation of DNA repair proteins often fail due to their low sensitivity, specificity and dependence upon the presence of properly functioning DNA repair pathways.Here we present STRIDE, a fluorescence-based technology for direct and sensitive detection of DNA breaks that can be applied in biological material of different complexity, from cultured cell lines to FFPE tissue sections. STRIDE is the only tool that allows for quantitative assessment of the level of double- or single-strand DNA breaks that is independent of DNA repair processes and is thus a perfect fit for studying DNA repair inhibitors, informing about their efficiency and potential mechanism of action. While sSTRIDE and dSTRIDE measure the total pool of SSBs or DSBs, respectively, other variants of the technology report on the involvement of specific DNA repair proteins at DNA breaks sites. We present here several STRIDE assay variants that have been recently introduced to assist the development of compounds targeting different repair pathways and proteins, including: RAD51, RPA, PSM2, MLH1, SMUG1 and WRN. All assays underwent optimization and validation in an in vitro cell model setting, including establishing baseline level of repair-protein associated DNA breaks and testing positive and negative controls. STRIDE methods, including classic variants measuring DNA breaks as well as novel customized assays focused on specific DNA repair proteins are complementary tools that can also be multiplexed with standard IF approaches. The flexibility of the STRIDE platform allows the design and introduction of new assays offering proximal readouts of a drug’s influence on DNA repair pathways that can help advancing drug candidates throughout the drug development process. Citation Format: Anna Uherek, Karolina Stępień, Olga Wójcikowska, Franek Sierpowski, Zsombor Prucsi, Monika Jarosz, Maja Białecka, Jakub Lechowski, Karolina Korpanty, Magdalena Kordon-Kiszala, Kamil Solarczyk. STRIDE as a technology platform for accurate measurement of DNA breaks and breaks-associated repair proteins [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr A018.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.009 |
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".