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105 Enhancing Personalized Prognostic Assessment of Myelodysplastic Syndromes through a Multimodal and Explainable Deep Data Fusion Approach (MAGAERA)

Program: Oral and Poster Abstracts
Type: Oral
Session: 803. Emerging Tools, Techniques, and Artificial Intelligence in Hematology: New Approaches to Predicting Patient Outcomes in Hematologic Malignancies
Hematology Disease Topics & Pathways:
Artificial intelligence (AI), MDS, Research, Adult, Elderly, Translational Research, Clinical Research, Bioinformatics, Genomics, Chronic Myeloid Malignancies, Diseases, Real-world evidence, Myeloid Malignancies, Biological Processes, Emerging technologies, Technology and Procedures, Human, Study Population, Multi-systemic interactions, Imaging, Omics technologies
Saturday, December 7, 2024: 10:00 AM

Elisabetta Sauta, PhD1*, Flavio Sartori, MSc2*, Luca Lanino, MD3, Gianluca Asti, MSc1*, Saverio D'Amico, MSc1,4*, Mattia Delleani1*, Elena Riva, PhD3*, Matteo Zampini, PhD3*, Elena Zazzetti, MSc1*, Marilena Bicchieri, PhD1*, Giulia Maggioni, MD1*, Alessia Campagna, MD1*, Gabriele Todisco, MD5,6*, Cristina Astrid Tentori, MD1*, Marta Ubezio, MD1*, Antonio Russo, MD1*, Alessandro Buizza, MD1*, Francesca Ficara, PhD1,7*, Laura Crisafulli, PhD3,7*, Matteo Brindisi3,7*, Denise Ventura, MSc3*, Nicole Pinocchio, MSc3*, Daoud Rahal, MD1*, Cesare Lancellotti, MD8*, Arturo Bonometti, MD1,6*, Luca Di Tommaso, MD1,6*, Victor Savevski, MEng1*, Armando Santoro, MD9*, Nicolas Riccardo Derus, PhD10*, Daniele Dall'Olio, PhD11*, Valeria Santini, MD12, Francesc Sole, PhD13, Uwe Platzbecker, MD14, Pierre Fenaux, MD15, Maria Diez-Campelo, MD, PhD16*, Rami S. Komrokji, MD17, Guillermo Garcia-Manero, MD18, Torsten Haferlach, MD19, Shahram Kordasti, MD, PhD20,21, Amer M. Zeidan, MD22, Gastone Castellani, PhD23*, Tiziana Sanavia, PhD2*, Piero Fariselli, PhD2* and Matteo Giovanni Della Porta, MD1,6*

1IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
2Computational Biomedicine Unit, Department of Medical Sciences, University of Torino, Turin, Italy
3IRCCS Humanitas Research Hospital, Rozzano, Milano, Italy
4Train s.r.l., Milan, Italy
5IRCCS Humanitas Research Hospital, Houston, TX
6Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy
7Institute for Genetic and Biomedical Research, Milan Unit, CNR, Milan, Italy
8Struttura Complessa di Anatomia Patologica, Policlinico di Modena, Modena, Italy
9IRCCS Humanitas Research Hospital, Rozzano, Italy
10Department of Physics and Astronomy (DIFA), University of Bologna, Bologna, Italy
11IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
12AOU Careggi, University of Florence, Firenze, Italy
13Myelodysplastic Syndromes Research Group, Institut De Recerca Josep Carreras, Badalona, Barcelona, Spain
14Department for Hematology, Cell Therapy, Hemostaseology and Infectious Diseases, University of Leipzig Medical Center, Leipzig, Germany
15Hôpital Saint-Louis, Université de Paris 7, Paris, France
16Hospital Clínico Universitario de Salamanca, Salamanca, Spain
17Department of Malignant Hematology, Moffitt Cancer Center, Tampa, FL
18MD Anderson Cancer Center, Houston, TX
19MLL Munich Leukemia Laboratory, Munich, Germany
20Department of Clinical Haematology, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom
21Hematology Unit, Azienda Ospedaliero Universitaria delle Marche, Ancona, Italy
22Yale School of Medicine, Smilow Cancer Hospital at Yale New Haven, New Haven, CT
23Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy

Background. Recent advancements in genome characterization have transformed the study of myelodysplastic syndromes (MDS). Accordingly, there has been a shift from traditional classification and prognostication methods, which relied mainly on morphological and clinical data, to next-generation systems that incorporate genomic features. However, genetic abnormalities account for only part of the overall risk related to survival, disease progression, and individual response to hypomethylating agents (HMA), indicating that a significant portion of these risks is still tied to clinical and non-mutational factors. Increasing evidence suggests that transcriptomics, immune dysfunctions, and high-dimensional tumor morphology data extracted by Artificial Intelligence (AI) may play a crucial role in predicting clinical outcomes in human cancers, thereby improving the implementation of personalized medicine programs.

Aim. In this scenario, we developed MEGAERA, an innovative, deep learning-based framework for multimodal analysis of hematological malignancies. MEGAERA integrates clinical, multi-omics, and histopathological data, using specific strategies to ensure full clinical explainability and interpretability of predictions. This study was conducted by the GenoMed4All and Synthema EU consortia, with MDS included as use case, to improve personalized predictions of patient outcomes.

Methods. The study population consisted of 605 MDS patients from Humanitas Research Hospital. For these patients, multi-modal data were available, including clinical characteristics, cytogenetics, somatic mutation screening on 31 genes, bulk RNA-seq of CD34+ bone marrow (BM) cells, and deep flow cytometry evaluation of T lymphocytes, natural killer and myeloid cells. Whole slide images (WSI) of BM biopsies stained with Hematoxylin and Eosin (H&E) and May-Grunwald Giemsa (MGG) were also retrieved. Comprehensive information on treatments and clinical outcomes was collected.

MEGAERA deep-learning workflow involves two processing layers. The first one exploits a custom fine-tuned implementation of Prov-GigaPath for WSI segmentation and features extraction. The second layer uses Self-Normalizing Networks with two hidden layers for handling clinical and molecular profiles. All the processed variables are combined and fed into a fusion model that correlates them to clinical outcomes. Explainability was implemented using attention-based maps for WSI and Shapley Additive Explanations Approach for feature importance rankings. The predictive ability of the approach was assessed using Harrell’s concordance index (CI).

Results. We used Prov-GigaPath on BM WSI for extracting morphological features. Prov-GigaPath outperformed current state-of-the-art methods including ResNet50 and DinoBloom, achieving 10% improvement of CI.

We evaluated MAGAERA’s predictive performance on MDS population, analyzing the multimodal integration alongside unimodal contributions, with Overall Survival (OS) as primary endpoint. Sequential integration of data modalities into the model showed an increasing CI for OS: starting with 0.56 CI considering clinical information alone, then rising to 0.81 CI by including cytogenetic, genomic, transcriptomic and immunologic signatures, and finally reaching 0.85 CI with morphological features integration. Our fusion model significantly enhanced the performance of conventional IPSS-R (0.68) and IPSS-M (0.76) scores. Similar improvements were observed in predicting leukemic evolution risk (0.83) and the individual probability of response to HMA treatment (0.84).

An extensive validation of the model’s performance was performed using multimodal synthetic data (PMID: 37390377), reaching comparable CI. To facilitate the clinical implementation of this framework, we are exploring innovative AI-based dimensionality reduction and inference approaches, to enable model’s knowledge transfer to patients lacking information collected outside diagnostic routine tests.

Conclusion. The MEGAERA multimodal fusion model demonstrated improved clinical outcome prediction in MDS patients. Our approach leverages full interpretability to elucidate features contribution to risk prediction. This framework is expected to significantly enhance clinical decision-making in MDS by supporting the implementation of personalized medicine programs.

Disclosures: Santoro: Sanofi: Consultancy; Incyte: Consultancy; BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Servier: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; EISAI: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bayer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; MSD: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Speakers Bureau; Roche: Speakers Bureau; Abb-vie: Speakers Bureau; Amgen: Speakers Bureau; Celgene: Speakers Bureau; Astrazeneca: Speakers Bureau; Arqule: Speakers Bureau; Lilly: Speakers Bureau; Sandoz: Speakers Bureau; Novartis: Speakers Bureau; Beigene: Speakers Bureau. Santini: Ascentage, AbbVie, Bristol Myers Squibb, CTI BioPharma, Geron, Gilead, Novartis, Servier, Syros Pharmaceuticals: Other: Advisory Board. Platzbecker: Amgen: Consultancy, Research Funding; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Research Funding; MDS Foundation: Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Research Funding; Curis: Consultancy, Honoraria, Research Funding; Geron: Consultancy; Janssen: Consultancy, Honoraria, Research Funding; Merck: Research Funding; Novartis: Consultancy, Research Funding. Fenaux: Novartis: Research Funding; Janssen: Research Funding; Jazz Pharmaceuticals: Honoraria, Research Funding; Agios: Research Funding; Servier: Research Funding; Astex: Research Funding; AbbVie: Honoraria, Research Funding; BMS: Honoraria, Research Funding. Diez-Campelo: Gilead: Other: Travel reimbursement; BLUEPRINT MEDICINES: Consultancy, Membership on an entity's Board of Directors or advisory committees; KEROS: Honoraria, Membership on an entity's Board of Directors or advisory committees; SYROS: Membership on an entity's Board of Directors or advisory committees; HEMAVAN: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees; ASTEX/OTSUKA: Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL TO MEETINGS; CURIS: Membership on an entity's Board of Directors or advisory committees; AGIOS: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS/Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory board fees. Komrokji: Genentech: Consultancy; PharmaEssentia: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Taiho: Membership on an entity's Board of Directors or advisory committees; Keros: Membership on an entity's Board of Directors or advisory committees; DSI: Consultancy, Membership on an entity's Board of Directors or advisory committees; CTI biopharma: Membership on an entity's Board of Directors or advisory committees; Geron: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Servier: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Servio: Honoraria; DSI: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sumitomo Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sobi: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Rigel: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; Servio: Membership on an entity's Board of Directors or advisory committees. Garcia-Manero: Helsinn: Other: Personal fees; H3 Biomedicine: Research Funding; Merck: Research Funding; Novartis: Research Funding; Onconova: Research Funding; Genentech: Other: Personal fees; Curis: Research Funding; Janssen: Research Funding; Forty Seven: Research Funding; Astex: Other: Personal fees; Genentech: Research Funding; Astex: Research Funding; Aprea: Research Funding; Bristol Myers Squibb: Other: Personal fees, Research Funding; AbbVie: Research Funding; Helsinn: Research Funding; Amphivena: Research Funding. Della Porta: Bristol Myers Squibb: Consultancy.

*signifies non-member of ASH