Genomic classification and individualized prognosis in multiple myeloma Journal Article
| Authors: | Maura, F.; Rajanna, A. R.; Ziccheddu, B.; Poos, A. M.; Derkach, A.; Maclachlan, K.; Durante, M.; Diamond, B.; Papadimitriou, M.; Davies, F.; Boyle, E. M.; Walker, B.; Hultcrantz, M.; Silva, A.; Hampton, O.; Teer, J. K.; Siegel, E. M.; Bolli, N.; Jackson, G. H.; Kaiser, M.; Pawlyn, C.; Cook, G.; Kazandjian, D.; Stein, C.; Chesi, M.; Bergsagel, L.; Mai, E. K.; Goldschmidt, H.; Weisel, K. C.; Fenk, R.; Raab, M. S.; Van Rhee, F.; Usmani, S.; Shain, K. H.; Weinhold, N.; Morgan, G.; Landgren, O. |
| Article Title: | Genomic classification and individualized prognosis in multiple myeloma |
| Abstract: | PURPOSEOutcomes for patients with newly diagnosed multiple myeloma (NDMM) are heterogenous, with overall survival (OS) ranging from months to over 10 years.METHODSTo decipher and predict the molecular and clinical heterogeneity of NDMM, we assembled a series of 1,933 patients with available clinical, genomic, and therapeutic data.RESULTSLeveraging a comprehensive catalog of genomic drivers, we identified 12 groups, expanding on previous gene expression-based molecular classifications. To build a model predicting individualized risk in NDMM (IRMMa), we integrated clinical, genomic, and treatment variables. To correct for time-dependent variables, including high-dose melphalan followed by autologous stem-cell transplantation (HDM-ASCT), and maintenance therapy, a multi-state model was designed. The IRMMa model accuracy was significantly higher than all comparator prognostic models, with a c-index for OS of 0.726, compared with International Staging System (ISS; 0.61), revised-ISS (0.572), and R2-ISS (0.625). Integral to model accuracy was 20 genomic features, including 1q21 gain/amp, del 1p, TP53 loss, NSD2 translocations, APOBEC mutational signatures, and copy-number signatures (reflecting the complex structural variant chromothripsis). IRMMa accuracy and superiority compared with other prognostic models were validated on 256 patients enrolled in the GMMG-HD6 (ClinicalTrials.gov identifier: NCT02495922) clinical trial. Individualized patient risks were significantly affected across the 12 genomic groups by different treatment strategies (ie, treatment variance), which was used to identify patients for whom HDM-ASCT is particularly effective versus patients for whom the impact is limited.CONCLUSIONIntegrating clinical, demographic, genomic, and therapeutic data, to our knowledge, we have developed the first individualized risk-prediction model enabling personally tailored therapeutic decisions for patients with NDMM. © American Society of Clinical Oncology. |
| Keywords: | adult; human tissue; aged; retrospective studies; human cell; major clinical study; overall survival; genetics; clinical trial; drug megadose; follow up; biological marker; multiple myeloma; gene expression; randomized controlled trial; maintenance therapy; melphalan; autologous stem cell transplantation; hematopoietic stem cell transplantation; retrospective study; genomics; transplantation, autologous; autotransplantation; cancer prognosis; chromothripsis; international staging system; humans; prognosis; human; male; female; article; patient risk; apolipoprotein b mrna editing enzyme catalytic polypeptide like |
| Journal Title: | Journal of Clinical Oncology |
| Volume: | 42 |
| Issue: | 11 |
| ISSN: | 0732-183X |
| Publisher: | American Society of Clinical Oncology |
| Date Published: | 2024-04-10 |
| Start Page: | 1229 |
| End Page: | 1240 |
| Language: | English |
| DOI: | 10.1200/jco.23.01277 |
| PUBMED: | 38194610 |
| PROVIDER: | scopus |
| PMCID: | PMC11095887 |
| DOI/URL: | |
| Notes: | Article -- MSK Cancer Center Support Grant (P30 CA008748) acknowledged in PDF -- Source: Scopus |
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
-
142Maclachlan -
148Derkach -
294Usmani
Related MSK Work