Patient-specific signaling signatures predict optimal therapeutic combinations for triple negative breast cancer
Rattachement africain : il, us. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Triple negative breast cancer (TNBC) is a heterogeneous group of tumors which lack estrogen receptor, progesterone receptor, and HER2 expression. Targeted therapies have limited success in treating TNBC, thus a strategy enabling effective targeted combinations is an unmet need. To tackle these challenges and discover individualized targeted combination therapies for TNBC, we integrated phosphoproteomic analysis of altered signaling networks with patient-specific signaling signature (PaSSS) analysis using an information-theoretic, thermodynamic-based approach. Using this method on a large number of TNBC patient-derived tumors (PDX), we were able to thoroughly characterize each PDX by computing a patient-specific set of unbalanced signaling processes and assigning a personalized therapy based on them. We discovered that each tumor has an average of two separate processes, and that, consistent with prior research, EGFR is a major core target in at least one of them in half of the tumors analyzed. However, anti-EGFR monotherapies were predicted to be ineffective, thus we developed personalized combination treatments based on PaSSS. These were predicted to induce anti-EGFR responses or to be used to develop an alternative therapy if EGFR was not present.In-vivo experimental validation of the predicted therapy showed that PaSSS predictions were more accurate than other therapies. Thus, we suggest that a detailed identification of molecular imbalances is necessary to tailor therapy for each TNBC. In summary, we propose a new strategy to design personalized therapy for TNBC using pY proteomics and PaSSS analysis. This method can be applied to different cancer types to improve response to the biomarker-based treatment.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Patient-specific signaling signatures predict optimal therapeutic combinations for triple negative breast cancer
- Date Crossref
- 16/01/2024
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Hebrew University of Jerusalem The Institute of Biomedical and Oral Research pays non établi dans la noticeUniversité ou école supérieure
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Massachusetts Institute of Technology Department of Biological Engineering pays non établi dans la noticeUniversité ou école supérieure
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Tel Aviv University pays non établi dans la noticeUniversité ou école supérieure
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Tel Aviv Sourasky Medical Center pays non établi dans la noticeÉtablissement de santé
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Hadassah Medical Center Sharett Institute of Oncology pays non établi dans la noticeÉtablissement de santé
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Mayo Clinic in Arizona Department of Surgery pays non établi dans la noticeÉtablissement de santé
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Mayo Clinic pays non établi dans la noticeÉtablissement de santé
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Koch Institute for Integrative Cancer Research pays non établi dans la noticeStructure de recherche
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Sackler Faculty of Medicine pays non établi dans la noticeUniversité ou école supérieure
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Samson Assuta Ashdod University Hospital Department of Surgery pays non établi dans la noticeUniversité ou école supérieure
The Institute of Biomedical and Oral Research — Hebrew University of Jerusalem, Department of Biological Engineering — Massachusetts Institute of Technology et Tel Aviv University, avec 7 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.