Abstract LBA013: Phosphoproteomics reveals active drug targets on pathways of resistance and predicts response to midostaurin plus chemotherapy in FLT3 mutant-positive acute myeloid leukemia
Notice bibliographique
Résumé
Abstract Background: Midostaurin (mido) is approved for treatment of FLT3 mutant-positive (FLT3+) acute myeloid leukemia (AML). However, FLT3 mutation is not the only determinant of mido sensitivity. Here we report phosphoprotein signatures which predict response to chemotherapy (chemo) plus mido, and identify active drug targets on potential resistance pathways. Methods: Samples collected at diagnosis, post-treatment and relapse from FLT3+ patients treated with chemo+mido were obtained from the Leukemia Tissue Bank at the Princess Margaret Cancer Centre. Peptides and enriched phosphopeptides from bone marrow (BM) and peripheral blood (PB) mononuclear cells were quantified using liquid chromatography-tandem mass spectrometry. Signatures for BM/PB diagnosis samples were analyzed independently and used to train a classification machine learning algorithm to group patients (n=54) based on response to treatment. Additional features (e.g. genetic mutations) were also analyzed. Kaplan-Meier and Log-Rank test methods were used to assess differential survival between patient groups. To investigate pathways potentially driving resistance to chemo+mido, differential protein phosphorylation indexes were identified through comparison of post-treatment or relapse samples to paired diagnosis samples. To account for population heterogeneity, a filter was applied based on frequency of observation. Activated pathways potentially driving resistance were identified with functional enrichment tools and kinase-substrate enrichment analysis. Statistical significance of enrichment were determined using parametric methods and p-values adjusted for multiple testing using the Benjamini-Hochberg method. Results: Patients positive for a signature consisting of 26 phosphorylation sites showed a markedly longer survival time than negative patients (PB: 269 vs 76 weeks, Log-Rank p=1.30e-05; BM: 241 vs 56, Log-Rank p=2.13e-09). This signature partially overlapped with an ex-vivo signature of response to mido, described previously by Casado et al (Leukemia, 2018). A proteomic signature was also identified, with positive patients showing a longer survival time than negative patients (PB: 330 vs 173 weeks, Log-Rank p=5.0e-04; BM: 460 vs 156, Log-Rank p=5.2e-06). Key, diverging phosphorylation site signatures were identified between patients with refractory disease/early relapse and patients with complete response and no relapse or death within 2 years post-treatment. Pathways with increased activity in post-treatment or relapse specimens were associated with molecular functions such as regulation of cell proliferation, migration, differentiation and anti-apoptosis. Conclusions: We identified phosphoproteomic and proteomic signatures that differentiate survival mediated by response to chemo+mido. While the former was more predictive, both may enable further stratification of FLT3+ AML receiving mido treatment. Drug targets on pathways demonstrating increased activity in relapse/refractory cases may play a role in resistance; this will be determined in follow-up inhibitor studies. Citation Format: Luis Veiga Nobre, Celia Colomina Basanta, Salvatore Federico Pedicona, Arran David Dokal, Andrea Arruda, Ryan Smith, Calum Greenhalgh, Francesca Patella, Pedro Maria Casado-Izquierdo, Bela Wrench, Jane Theaker, Andrew Thompson, Mark D. Minden, John G. Gribben, David James Britton, Pedro Rodriguez Cutillas. Phosphoproteomics reveals active drug targets on pathways of resistance and predicts response to midostaurin plus chemotherapy in FLT3 mutant-positive acute myeloid leukemia [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr LBA013.
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) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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) | 0,002 | 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 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 ».