Abstract 549: Genome-wide CRISPR-Cas9 screen and RNAseq analysis identify new candidate synthetic lethality partners to PARP inhibitor in triple-negative breast cancer
Notice bibliographique
Résumé
Abstract As monotherapy, Poly (ADP-ribose) polymerase inhibitors (PARPi) have achieved remarkable success in treating tumors with germline BRCA1/2 mutation due to the synthetic lethality in DNA damage response. The efficacy of PARPi in combination with other therapeutic agents is still under investigation. However, BRCA mutant tumors constitute only 5-10% of total breast cancer diagnoses. Therefore, to extend the benefit of PARPi beyond BRCA mutant tumors, it is imperative to identify other genetic determinants that also contribute to PARPi sensitivity. Such knowledge also provides valuable insight into the development of combination therapies involving PARPi. To identify genes and pathways that are essential for cell survival under PARPi treatment, we performed genome-wide CRISPR-Cas9 knockout screens in a BRCA-functional, triple-negative breast cancer cell line MDA-MB-231 treated with talazoparib at a low dose (IC20, 20nM). Toronto CRISPR human knockout library TKOV3 was introduced into cells using lentivirus at MOI of 0.3~0.4. After puromycin selection, the surviving cells were treated with talazoparib or DMSO for 20 days before harvesting. The sgRNAs were sequenced at ~30 million reads per sample to achieve a 300x coverage over the TKOV3 library. To increase the accuracy of the CRISPR-Cas9 screen result, and to capture the transcriptomic changes during a relative long-term PARPi treatment as used in the screening process, we also did RNAseq profiling in MDA-MD-231 cells cultured in the conditions matched with the CRISPR-Cas9 screen. Using mRNA level as a filter to remove non-expressed genes, we were able to generate a list of candidate genes that have the potential to form synthetic lethal partnership with talazoparib. Our negative selection screen confirmed that loss of key components of DNA damage repair and DNA replication pathways such as ATM, RNASEH2C, ESCO2, EME1, and several components of Fanconi Anemia (FA) core complex sensitizes cells to talazoparib, as has been reported in similar screens using other PARP inhibitors. Meanwhile, our analysis also revealed several previously unrecognized partner genes involved in subcellular trafficking, RNA splicing, and microRNA biogenesis. In addition, the RNAseq profile depicted a transcriptomic response to long-term talazoparib treatment that has many distinctions from the essential pathways shown in the CRISPR-Cas9 screen, suggesting a complex, multi-layer regulation system in cell response to PARP inhibition. Our study identified a set of genes that have potential synthetic lethal interaction with PARPi. The status of these genes can be used to identify subset of triple-negative breast cancer patients who could potentially benefit from PARPi treatment. Strategies targeting these genes represent new opportunities for PARPi combination therapies. Citation Format: Xue Wu, Yue Zhao, Xiaoyu Xie, Xiaoling Xuei, Yunlong Liu, Lijun Cheng, Lang Li. Genome-wide CRISPR-Cas9 screen and RNAseq analysis identify new candidate synthetic lethality partners to PARP inhibitor in triple-negative breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 549.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| 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 | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».