Abstract A021: Hunting for synthetic lethal partners in DNA damage response-altered endometrial cancer
Notice bibliographique
Résumé
Abstract DNA damage response (DDR) genes are frequently altered in cancer, which may lead to protein loss-of-function (LoF) and result in particular DDR defects that can be therapeutically targeted via the concept of synthetic lethality (SL). There is a high prevalence of DDR alterations in endometrial cancer, a gynecologic malignancy with increased incidence and mortality in recent decades, and an unmet clinical need for a wider range of treatment options to reduce adverse effects and combat therapy resistance. In this study, a large-scale, agnostic bioinformatic screening approach was employed to discover novel potential SL targets specific to DDR LoF biomarkers in endometrial cancer for subsequent experimental validation in vitro. SL analysis was performed with the in-house Target / Biomarker / Lineage (TBL) bioinformatic pipeline (Division of Cancer Therapeutics, The Institute of Cancer Research) using datasets obtained from the Cancer Dependency Map (DepMap). The TBL pipeline statistically analyzed cancer cell line target gene dependency probabilities, inferred from Project Achilles and Project Score genome-wide CRISPR-Cas9 dropout screens, and integrated this with mutation and copy number variation genomic datasets. Potential interactions were filtered for target-biomarker mutual exclusivity using patient data from The Cancer Genome Atlas (TCGA). The ability of the TBL pipeline to identify known SL interactions was demonstrated through in silico identification of ARID1B/ARID1A in ovarian cancer and SMARCA2/SMARCA4 in lung cancer as significant hits. In addition, the identification of WRN/ARID1A as a significant hit in uterine cancer, given that ARID1A loss has been significantly associated with microsatellite instability (MSI) in endometrial cancer, is consistent with previous findings of WRN helicase as a SL partner with MSI in endometrial cancer. Analysis and downstream refinement of endometrial cancer significant hits led to the identification of seven final candidate target-biomarker gene pairs. These putative SL partners comprise novel potential endometrial cancer targets, with various functions ranging from nucleotide biosynthesis to epigenetic remodeling, and include novel potential and established LoF biomarkers relevant to endometrial cancer biology, namely DNA mismatch repair. In vitro validation of the final candidates by genetic or pharmacologic approaches to assess target gene dependency in endometrial cancer cell lines with altered or wildtype biomarker status will be discussed. These experiments will provide key experimental data to validate our bioinformatic approach to SL target-biomarker discovery, and may identify novel SL partners involving DDR LoF alterations in endometrial cancer that could lead to the development of new molecular targeted therapies and improved treatment options for this patient subpopulation. Citation Format: Julie Zhou, Konstantinos Mitsopoulos, Olivia Rossanese. Hunting for synthetic lethal partners in DNA damage response-altered endometrial cancer [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 A021.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».