Abstract PS4-48: Development of a multiplexed protein panel using a targeted proteomics approach for the study of CDK4/6 inhibitors resistance in hormone receptor positive breast cancer
Notice bibliographique
Résumé
Abstract Background Breast cancer is the most common malignancy in woman and hormone receptor positive breast cancer represents approximately 70% of all cases. These patients are treated with endocrine therapies aimed at disrupting hormone receptor signaling and estrogen production which improves survival and allows a cure in early stages. However, recurrent disease, metastatic dissemination and drug resistance limit the survival of patients. The limitations regarding endocrine therapy have prompted the search for new therapeutic targets, such as CDK4/6 Inhibitors. Despite the improved disease control that CDK4/6 Inhibitors offer to patients, not all patients respond to these drugs and some patients whose tumors respond to CDK4/6 Inhibitors eventually develop acquired resistance. No proven biomarkers of CDK4/6 Inhibitors efficacy exist to date, and there is a need for diagnostic tools that could stratify patients to save costs and the burden of unnecessary therapy. Our aim is to perform a quantitative evaluation of marker proteins with a developed multiplexed panel using targeted mass spectrometry (MS)-based proteomics for 25 proteins from the CDK/RB/E2F-pathway which have been shown in the literature to be central to CDK4/6I resistance. Material and Methods We developed Multiple Reaction Monitoring (MRM) MS methods for the 25 target proteins from the CDK/RB/E2F-pathway using synthetic heavy-isotope-labeled standards with the aim of creating MRM assays to enable specific, sensitive and precise quantitation of these proteins in small amounts of cell line and tissue samples. Moreover, we developed a high resolution peptide fractionation system using high-pH micro-flow liquid chromatography (LC) which is required to overcome the problem of small samples amounts while improving analytical assay sensitivity in the analysis of complex biological matrices such as breast cancer biopsies. The MCF-7 human breast cancer cell line was used as model during method development. Proteins from cell lysates were isolated, reduced, alkylated and digested with trypsin. The resulting tryptic peptides were micro-flow fractionated into 70 fractions and the developed nano-LC-MS MRM assays were used for peptide detection and quantification. Data were analyzed using Skyline. Results Our developed micro-flow fractionation method allowed us to work on limited amounts of samples (60ug), and increased the possibility to detecting low abundance proteins such as cell cycle components. Using the MCF-7 cell model, we are able to identify and quantify 17 proteins out of the 25 from our panel: CDK1, CDK2, CDK4, Cyclin B1, Cyclin D1, Cyclin D3, Cyclin E1, RB1, E2F-3, E2F-4, E2F-5, ESR1, TOP2A, TYMS, EZH2, MKI67, BIRC5. Conclusion We have developed a highly specific MS-based multiplexed assay with peptide standards targeting 25 proteins relevant to CDK4/6 Inhibitors breast cancer treatment. Our micro-flow fractionation method increased assay sensitivity and allows for the analysis of small sample amounts. In the future we will apply this workflow to samples such as Patient Derived Xenografts models, breast cancer tissues and FFPE samples in order to identify the predictive value of these potential biomarkers for responsiveness to CDK4/6 Inhibitors. Citation Format: Marta Zurawska, Adriana Aguilar-Mahecha, Mark Basik, Michal Dadlez, Dominik Domanski. Development of a multiplexed protein panel using a targeted proteomics approach for the study of CDK4/6 inhibitors resistance in hormone receptor positive breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS4-48.
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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) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,001 |
| 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 ».