ImportanceThe recent successes of poly-ADP ribose polymerase (PARP) inhibitors and belzutifan support germline genetic data as an exciting, accessible source for biomarkers in cancer treatment. This study hypothesizes, however, that most oncology clinical trials using germline data largely prioritize BRCA1/2 as biomarkers and PARP inhibitors as therapy.ObjectiveTo characterize past and ongoing oncology trials that use germline data.Design, Setting, and ParticipantsThis retrospective cross-sectional study of oncology trials used the Informa Trialtrove database to evaluate trial attributes. Trials using germline information (including the terms germline, hereditary, or inherited in the title, treatment plan, interventions, end points, objectives, results, or notes) and conducted globally between December 1, 1990, and April 4, 2022 (data freeze date), were included.Main Outcomes and MeasuresTrials by cancer type, phase, participants, sponsor type, end points, outcomes, and locations were described. Associated biomarkers and mechanisms of action for studied therapeutic interventions were counted. How germline data in trial inclusion and exclusion criteria are associated with end points, outcomes, and enrollment were also examined.ResultsA total of 887 of 84 297 (1.1%) oncology clinical trials in the Trialtrove database that use germline data were identified. Most trials were conducted in cancer types where PARP inhibitors are already approved. A total of 74.8% (672) of trials were performed in the phase 2 setting or above. Trials were primarily sponsored by industry (523 trials [59.0%]), academia (382 trials [43.1%]), and the government (274 trials [30.9%]), where trials may have multiple sponsor types. Among 343 trials using germline data with outcomes in Trialtrove, 180 (52.5%) reported meeting primary end points. Although BRCA1/2 are the most frequent biomarkers seen (BRCA1, 224 trials [25.3%]; BRCA2, 228 trials [25.7%]), trials also examine pharmacogenomic variants and germline mediators of somatic biomarkers. PARP inhibitors or immunotherapy were tested in 69.9% of trials; PARP inhibition was the most frequently studied mechanism (367 trials [41.4%]). An overwhelming number of trials using germline data were conducted in the US, Canada, and Europe vs other countries, mirroring disparities in cancer genetics data. Germline data in inclusion and exclusion criteria are associated with altered end point, outcomes, and enrollment compared with oncology trials with no germline data use. Examples of inclusion and exclusion criteria regarding germline data that may unintentionally exclude patients were identified.Conclusions and RelevanceThese findings suggest that for germline biomarkers to gain clinical relevance, trials must expand biomarkers, therapies, and populations under study.

Background: Synthetic lethality (SL) denotes a genetic interaction between two genes whose co-inactivation is detrimental to cells. Since the seminal paper of Hartwell and colleagues has raised the possibility that SL can be used to devise highly selective cancer treatments, it has been one of the promising approaches for precision oncology and drug discovery. Many different avenues have so far been explored to bring this idea to the clinic. As 25 years have passed by now, we take stock and systematically and comprehensively chart the landscape of SL-based preclinical research and clinical trials. Approach and Key Findings: We systematically mined both public and commercial databases to curate the preclinical and clinical landscape of the SL-based oncology studies. Our analysis shows that the number of SL oncology studies is rapidly growing since the first identification of the well-known BRCA-PARP synthetic lethality axis. Importantly, we find that the success rate of SL oncology trials is significantly higher than non-SL-based trials. While more than 70% of SL-oncology trials involve genes in the most-studied DNA damage response (DDR) pathways, the fraction of SL trials involving non-DDR pathways keeps growing since 2009. We further charted the landscape of SL triplets, which is a promising future higher-order extension of the conventional pairwise SL interactions. We find that only about 8% of preclinically validated SL triplets were clinically tested in trials, providing new opportunities for more refined clinical trial design. Our analysis suggests that emerging opportunities in SL oncology may arise from metabolic and paralogous interactions, disease-agnostic biomarkers, context-specific combinations against treatment resistance, artificial intelligence and data science approaches, and multi-omics patient stratification signatures. Significance: Taken together, our findings testify that a considerable potential benefits of SL based approaches are yet untapped, reinforcing the belief that the synthetic lethality approach may serve as a key driver of precision oncology going forward. Citation Format: Joo Sang Lee, Youngmin Chung, Ashwin V. Kammula, Alejandro A. Schaffer, Eytan Ruppin. A silver jubilee for synthetic lethality in cancer treatment: where do we stand [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 946.

e18808 Background: NIH guidance advises clinical trials to analyze participants by sex to improve inclusivity. We performed a systematic analysis of reported differences in outcomes between males and females in a registry of oncology clinical trials to characterize treatment response differences more broadly by sex for future trials. Methods: We analyzed Trialtrove ( https://citeline.informa.com/trials/results ), a trial repository using over 58,000 sources, to search for oncology trials that compared outcomes in male and female participants. We implemented algorithms using Python3 programs to search for all trials that contained terms regarding sex in the context of terms suggesting comparison or outcome and considered these as candidate comparison trials. Candidate trials were manually curated to record comparisons by sex across cancer type, treatment, outcome measure, “similar” or “different” by sex and evidence. Outcomes were classified as either “survival / response / other outcome” (SRO) or side effects (E). Evidence for each comparison was labeled as statistically significant (multivariate or univariate), having non-significant numerical evidence, or having no numerical evidence. We counted only those trials in which all comparisons by sex were consistent. Results: 472 of 89,221 oncology trials in Trialtrove (data freeze 12/23/22) (0.5%) performed 532 post-treatment comparisons by sex. Among 288 trials that did statistical SRO comparisons, 47 (16%) trials reported that males showed better, statistically significant treatment responses, while 122 (42%) trials reported better results for females. We observed the strongest differences by sex for two disease-treatment pairs: EGFR inhibitors (EGFRi) in non-small cell lung cancer (NSCLC) and rituximab in non-Hodgkin’s lymphoma (NHL). In 82 trials with SRO comparisons in NSCLC, 35 (43%) showed better treatment responses in females, and 13 (16%) showed better treatment responses in males. Among the 36 NSCLC trials using EGFRi, 21 (58%) showed better treatment responses in females, versus only 1 (3%) in males. In contrast, among all 46 other NSCLC trials with SRO comparisons, 14 (30%) favored females and 12 (26%) favored males. These results suggest that EGFRi may have treatment-specific benefits in females with NSCLC. Among 33 trials with SRO comparisons in NHL, 20 (61%) showed better treatment response in females, versus only 4 (12%) in males. 13 of these trials used rituximab, among which 10 (77%) favor females and only 1 (8%) favors males. Better response in females to rituximab has been reported in single trials but not characterized in aggregate. Conclusions: Our search identified two clinically important disease-treatment pairs that showed markedly improved outcomes in females versus males. Better understanding of differences in treatment response by sex across clinical trials is needed, both to improve inclusivity and as a basis for potential future combination treatments.