Citations 2
Enhanced Risk Stratification of Smoldering Multiple Myeloma with Dynamic Biomarkers: A Multinational, Multicenter Study including 2,270 Participants (PANGEA 2.0)
Chabrun, Floris , Schwartz, Daniel L. , Gentile, Susanna, Elias, K. , Gupta, Tulika , Perry, Jacqueline , Santos, David M. Cordas dos , Hielscher, Thomas , Werly, Annika, Schmidt, Sophia, Liacos, Christine‐Ivy , Kanellias, Nikolaos , Gisbert, Noelia Collado, Chavda, Selina J , Ainley, Louise , Magistris, Claudio De, Pettine, Loredana , Timonian, Michael , Tobia, Catherine, Phan, Sally, Lamb, Jennifer, Silverio, Maria-Theresa, O’Donnell, Elizabeth , Mateos, María‐Victoria , Kumar, Shaji , Kastritis, Efstathis, Trippa, Lorenzo , Mai, Elias K , Santos, David Cordas Dos , Timonian, Michael , Alberge, Jean-Baptiste , Bolli, Niccolo' , Yong, Kwee , Kortüm, Martin , Einsele, Hermann , Mateos, María-Victoria , Kumar, Shaji K , San-Miguel, Jesus , Paiva, Bruno , Dimopoulos, Meletios A , Raab, Marc S , Ghobrial, Irene M , Schwartz, Daniel S. , Gentile, Susanna , Gupta, Tulika R. , Perry, Jacqueline, Schmidt, Sophia K., Theodorakakou, Foteini , Fotiou, Despina , Liacos, Christine Ivy, Martín‐Sánchez, Esperanza , Termini, Rosalinda , Waldschmidt, Johannes M , Ainley, Louise, Vià, Matteo Da , Alberge, Jean-Baptiste , Patel, Vidhi, Costello, Patrick , Tobia, Catherine, Phan, Sally, Lamb, Jennifer, Silverio, Maria-Theresa, Davis, Maya, Marinac, Catherine R. , Nadeem, Omar , Bolli, Niccolò , Yong, Kwee , Kortüm, K. Martin , Miguel, Jesús F. San , Paiva, Bruno , Kastritis, Efstathios , Dimopoulos, Meletios Α. , Raab, Marc S. , Ghobrial, Irene M.
No container title available | June 3, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available
Abstract Accurate prediction of risk of progression from smoldering (SMM) to active multiple myeloma (MM) is paramount to individualized early therapeutic strategies with minimum risk of overtreatment. Current risk stratification models do not account for evolving biomarker trajectories. We assembled the largest cohort to date of 2,270 SMM patients from six international centers with longitudinal clinical and biological data to train and validate the PANGEA 2.0 risk models. Four evolving biomarkers were significantly associated with shorter time-to-progression: M-protein increase ≥0.2g/dL, involved:uninvolved serum free light chain ratio increase ≥20, creatinine increase >25%, and hemoglobin decrease ≥1.5g/dL. PANGEA 2.0 outperforms established models including the 20/2/20 and IMWG models by more accurately predicting progression (C-statistics=0.69–0.84), even without biomarker history (C-statistics=0.69–0.83) or recent bone marrow biopsy. PANGEA 2.0 is an easy-to-use, open-access tool (https://ghobrial.shinyapps.io/pangea_2_calculator) to improve and individualize SMM risk stratification. Validation tools are available to compare PANGEA 2.0 to established models (https://ghobrial.shinyapps.io/pangea_validation).
Genomic Profiling of Smoldering Multiple Myeloma Identifies Patients at a High Risk of Disease Progression
Bustoros, Mark , Sklavenitis‐Pistofidis, Romanos , Park, Jihye , Zhitomirsky, Benny , Salem, Karma Z. , Chavda, Selina J , Boehner, Cody J. , Elagina, Liudmila, Neuse, Carl Jannes , Cha, Justin , Rahmat, Mahshid , Kumar, Shaji , Kastritis, Efstathis, Laubach, Jacob P. , Casneuf, Tineke, Richardson, Paul G. , Munshi, Nikhil C. , Trippa, Lorenzo , Bergsagel, P. Leif , Manier, Salomon , Ghobrial, Irene M. , Bergsagel, P. Leif , Ghobrial, Irene M , Sklavenitis-Pistofidis, Romanos , Redd, Robert , Dunford, Andrew , Tai, Yu‐Tzu , Anand, Shankara K. , Mouhieddine, Tarek H. , Taylor-Weiner, Amaro N , Van Allen, Eliezer M , Leshchiner, Ignaty , Morgan, Elizabeth A. , Richardson, Paul Gerard Guy , Anderson, Kenneth C. , Aguet, François , Stewart, Chip , Dimopoulos, Meletios Α. , Yong, Kwee , Getz, Gad
Journal of Clinical Oncology | May 22, 2020 | Volume: 38 | Issue: 21 | Pages: 2380-2389
PURPOSE Smoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with a 10% annual risk of progression. Various prognostic models exist for risk stratification; however, those are based on solely clinical metrics. The discovery of genomic alterations that underlie disease progression to MM could improve current risk models. METHODS We used next-generation sequencing to study 214 patients with SMM. We performed whole-exome sequencing on 166 tumors, including 5 with serial samples, and deep targeted sequencing on 48 tumors. RESULTS We observed that most of the genetic alterations necessary for progression have already been acquired by the diagnosis of SMM. Particularly, we found that alterations of the mitogen-activated protein kinase pathway ( KRAS and NRAS single nucleotide variants [SNVs]), the DNA repair pathway (deletion 17p, TP53, and ATM SNVs), and MYC (translocations or copy number variations) were all independent risk factors of progression after accounting for clinical risk staging. We validated these findings in an external SMM cohort by showing that patients who have any of these three features have a higher risk of progressing to MM. Moreover, APOBEC associated mutations were enriched in patients who progressed and were associated with a shorter time to progression in our cohort. CONCLUSION SMM is a genetically mature entity whereby most driver genetic alterations have already occurred, which suggests the existence of a right-skewed model of genetic evolution from monoclonal gammopathy of undetermined significance to MM. We identified and externally validated genomic predictors of progression that could distinguish patients at high risk of progression to MM and, thus, improve on the precision of current clinical models.