2020
Integrative analysis of the genomic and transcriptomic landscape of double-refractory multiple myeloma
Ziccheddu B, Biancon G, Bagnoli F, De Philippis C, Maura F, Rustad EH, Dugo M, Devecchi A, De Cecco L, Sensi M, Terragna C, Martello M, Bagratuni T, Kastritis E, Dimopoulos MA, Cavo M, Carniti C, Montefusco V, Corradini P, Bolli N. Integrative analysis of the genomic and transcriptomic landscape of double-refractory multiple myeloma. Blood Advances 2020, 4: 830-844. PMID: 32126144, PMCID: PMC7065476, DOI: 10.1182/bloodadvances.2019000779.Peer-Reviewed Original ResearchMeSH KeywordsGenomicsHumansMultiple MyelomaNeoplasm Recurrence, LocalProteasome InhibitorsTranscriptomeConceptsChemotherapy resistanceMultiple myelomaProteasome inhibitorsDouble-refractory multiple myelomaHigh-risk featuresBulk tumor populationOverexpression of MCL1Whole-exome sequencingRefractory patientsImmunomodulatory agentsDisease progressionSame patientNovel treatmentsPatientsKaryotypic eventsEvolution of subclonesMyeloma cellsDrug resistanceMyelomaNovel targetIMiDsTumor populationGene mutationsNext-generation sequencingTP53 pathway
2018
Analysis of the genomic landscape of multiple myeloma highlights novel prognostic markers and disease subgroups
Bolli N, Biancon G, Moarii M, Gimondi S, Li Y, de Philippis C, Maura F, Sathiaseelan V, Tai YT, Mudie L, O’Meara S, Raine K, Teague JW, Butler AP, Carniti C, Gerstung M, Bagratuni T, Kastritis E, Dimopoulos M, Corradini P, Anderson KC, Moreau P, Minvielle S, Campbell PJ, Papaemmanuil E, Avet-Loiseau H, Munshi NC. Analysis of the genomic landscape of multiple myeloma highlights novel prognostic markers and disease subgroups. Leukemia 2018, 32: 2604-2616. PMID: 29789651, PMCID: PMC6092251, DOI: 10.1038/s41375-018-0037-9.Peer-Reviewed Original Research