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Luca Lanino
Yale University, IRCCS Humanitas Research Hospital, Humanitas University, University of Genoa
Research areas: Medicine · Hematology · Acute Myeloid Leukemia Research · Retinoids in leukemia and cellular processes · Hematopoietic Stem Cell Transplantation
0000-0003-2404-8829
Employment
- 2024 - Present
- 2021 - 2025
- 2021 - 2025
Education
-
Humanitas University Hematology Fellow2021 - 2025
- ? - 2020
Projects & Funding
Projects & funding information is unavailable.
Publications (30)
- Impact of Response to Hypomethylating Agent‐Based Therapy on Survival Outcomes in the Context of Baseline Clinical‐Molecular Risk and Transplant Status in Patients With Higher‐Risk Myelodysplastic Syndromes/Neoplasms: An analysis From the International C… Save
- Outcomes of patients with higher-risk myelodysplastic syndromes/neoplasms treated with hypomethylating agents + venetoclax—an analysis from the International Consortium for MDS (icMDS) VALIDATE database Save
- Molecular-Based Ecosystem to Improve Personalized Medicine in Chronic Myelomonocytic Leukemia Save
- CMML2AML: machine-learning discovery of co-mutations and specific single mutations predictive of blast transformation in chronic myelomonocytic leukemia Save
- Performance of molecular scoring systems in hypomethylating agent-treated myelodysplastic neoplasms Save
- Assessment of the IPSS-M in chronic myelomonocytic leukemia Save
- Comprehensive analysis of prognostic factors in myelodysplastic syndromes with isolated deletion of chromosome 5q Save
- HYPOMETHYLATING AGENTS PLUS VENETOCLAX VS INTENSIVE CHEMOTHERAPY PRIOR TO TRANSPLANT IN HIGH-RISK ACUTE MYELOID LEUKEMIA Save
- Hypomethylating Agents Plus Venetoclax Versus Intensive Chemotherapy Prior to Transplant in High-Risk Acute Myeloid Leukemia Save
- Prognostic Score for Myelodysplastic Syndromes Based on Molecular Evolution Save
- Real-world, multi-omics validation of the clinical relevance of molecular taxonomy for myelodysplastic syndromes (MDS) Save
- Artificial intelligence in myeloid malignancies: Clinical applications of machine learning in myelodysplastic syndromes and acute myeloid Leukemia. Save
- Characterization and Clinical Implications of p53 Dysfunction in Patients With Myelodysplastic Syndromes Save
- VAE-Surv: A novel approach for genetic-based clustering and prognosis prediction in myelodysplastic syndromes Save
- Longitudinal Synthetic Data Generation by Artificial Intelligence to Accelerate Clinical and Translational Research in Breast Cancer Save
- Response to luspatercept can be predicted and improves overall survival in the real-life treatment of LR-MDS Save
- Validation of BLAST and BLAST-Mol Risk Models in Chronic Myelomonocytic Leukemia: Mayo–Humanitas Collaborative Project Involving 1101 Patients Save
- Data-driven, harmonised classification system for myelodysplastic syndromes: a consensus paper from the International Consortium for Myelodysplastic Syndromes. Save
- Chronic myelomonocytic leukemia with ring sideroblasts/SF3B1 mutation presents with low monocyte count and resembles myelodysplastic syndromes with-RS/SF3B1 mutation in terms of phenotype and prognosis. Save
- Clinical and Genomic-Based Decision Support System to Define the Optimal Timing of Allogeneic Hematopoietic Stem-Cell Transplantation in Patients With Myelodysplastic Syndromes Save