2024
Predictors of response to venetoclax and therapeutic potential of CDK7 inhibition in multiple myeloma
Dutta R, Thibaud S, Leshchenko V, Ram M, Melnekoff D, Bhalla S, Restrepo P, Gupta V, Barwick B, Newman S, McCafferty J, Hantash F, Nooka A, Cho H, Richard S, Rodriguez C, Rossi A, Sanchez L, Chari A, Boise L, Jagannath S, Richter J, Parekh S, Laganà A. Predictors of response to venetoclax and therapeutic potential of CDK7 inhibition in multiple myeloma. Blood Neoplasia 2024, 1: 100049. DOI: 10.1016/j.bneo.2024.100049.Peer-Reviewed Original ResearchCyclin-dependent kinase 7Progression-free survivalMultiple myelomaAnalysis of RNA-seq dataMM cellsTherapeutic strategiesPatients treated with venetoclaxCDK7 inhibitor THZ1Overcome venetoclax resistanceRNA-seq dataSix-gene signaturePredictors of responseChromosome 1q gainPersonalized therapeutic strategiesDevelopment of personalized therapeutic strategiesInduce cell deathMarkers of sensitivityBCL2 inhibitorsCDK7 inhibitionMCL1 genePrognostic importanceStratify patientsCyclin-dependentMCL1 levelsPatient populationP-342 Impact of Achieving <VGPR With Dara-RVD Induction Therapy in Newly Diagnosed Multiple Myeloma (NDMM) Patients
Joseph N, Pruitt R, Gupta V, Hofmeister C, Dhodapkar M, Nooka A, Lonial S, Kaufman J. P-342 Impact of AchievingDOI: 10.1016/s2152-2650(24)02244-4. Peer-Reviewed Original ResearchP-234 Autocrine IL6 Signaling in Stromal Cells in Multiple Myeloma Influences the Bone Marrow Microenvironment
Matulis S, Barwick B, Bombin S, Ackley J, Gupta V, Hill G, Green D, Riddell S, Lonial S, Dhodapkar M, Boise L. P-234 Autocrine IL6 Signaling in Stromal Cells in Multiple Myeloma Influences the Bone Marrow Microenvironment. Clinical Lymphoma Myeloma & Leukemia 2024, 24: s173. DOI: 10.1016/s2152-2650(24)02137-2.Peer-Reviewed Original Research
2023
Machine Learning Models Predict Molecular Genetic Subtypes of Multiple Myeloma from Whole-Slide Bone Marrow Aspirate Smears
Lewis J, Shebelut C, Attieh M, Horwath M, Khanna A, Al-Rusan O, Ponnatt T, Smith G, Gutman D, Gupta V, Aljudi A, Cooper L, Jaye D. Machine Learning Models Predict Molecular Genetic Subtypes of Multiple Myeloma from Whole-Slide Bone Marrow Aspirate Smears. Blood 2023, 142: 7158. DOI: 10.1182/blood-2023-190686.Peer-Reviewed Original ResearchPlasma cell neoplasmsMolecular genetic subtypesBone marrow aspirate smearsMarrow aspirate smearsCell neoplasmsPlasma cellsAspirate smearsMultiple myelomaGenetic subtypesRisk stratificationBone marrow biopsy samplesCurrent prognostic systemsRisk stratification toolCommon hematologic malignancyPlasma cell morphologyMultiple myeloma casesSpecific morphologic featuresSubset of casesRecurrent genetic abnormalitiesLow-resource settingsBiologic subtypeStratification toolAggressive diseaseScanned whole slide imagesHematologic malignancies