Camonsertib in DNA damage response-deficient advanced solid tumors: phase 1 trial results
Bibliographic record
Abstract
Abstract Predictive biomarkers of response are essential to effectively guide targeted cancer treatment. Ataxia telangiectasia and Rad3-related kinase inhibitors (ATRi) have been shown to be synthetic lethal with loss of function (LOF) of ataxia telangiectasia-mutated (ATM) kinase, and preclinical studies have identified ATRi-sensitizing alterations in other DNA damage response (DDR) genes. Here we report the results from module 1 of an ongoing phase 1 trial of the ATRi camonsertib (RP-3500) in 120 patients with advanced solid tumors harboring LOF alterations in DDR genes, predicted by chemogenomic CRISPR screens to sensitize tumors to ATRi. Primary objectives were to determine safety and propose a recommended phase 2 dose (RP2D). Secondary objectives were to assess preliminary anti-tumor activity, to characterize camonsertib pharmacokinetics and relationship with pharmacodynamic biomarkers and to evaluate methods for detecting ATRi-sensitizing biomarkers. Camonsertib was well tolerated; anemia was the most common drug-related toxicity (32% grade 3). Preliminary RP2D was 160 mg weekly on days 1–3. Overall clinical response, clinical benefit and molecular response rates across tumor and molecular subtypes in patients who received biologically effective doses of camonsertib (>100 mg d −1 ) were 13% (13/99), 43% (43/99) and 43% (27/63), respectively. Clinical benefit was highest in ovarian cancer, in tumors with biallelic LOF alterations and in patients with molecular responses. ClinicalTrials.gov registration: NCT04497116 .
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".