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Ghobrial IM, Gormley N, Kumar SK, Mateos MV, Bergsagel PL, Chesi M, Dhodapkar MV, Dispenzieri A, Fonseca R, Getz G, Kastritis E, Kristinsson SY, Martinez-Climent JA, Manier S, Marinac CR, Maura F, Morgan GJ, Davies FE, Nadeem O, Nuvolone M, Paiva B, O'Donnell E, Prosper F, Shah UA, Sklavenitis-Pistofidis R, Sperling AS, Vassiliou GS, Munshi NC, Castle PE, Anderson KC, San Miguel JF. Round Table Discussion on Optimal Clinical Trial Design in Precursor Multiple Myeloma. Blood Cancer Discov 2024; 5:146-152. [PMID: 38441243 PMCID: PMC11061588 DOI: 10.1158/2643-3230.bcd-24-0022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2024] Open
Abstract
SUMMARY While the current approach to precursor hematologic conditions is to "watch and wait," this may change with the development of therapies that are safe and extend survival or delay the onset of symptomatic disease. The goal of future therapies in precursor hematologic conditions is to improve survival and prevent or delay the development of symptomatic disease while maximizing safety. Clinical trial considerations in this field include identifying an appropriate at-risk population, safety assessments, dose selection, primary and secondary trial endpoints including surrogate endpoints, control arms, and quality-of-life metrics, all of which may enable more precise benefit-risk assessment.
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Affiliation(s)
| | - Nicole Gormley
- Division of Hematology, Food and Drug Administration, Silver Spring, Maryland
| | - Shaji K. Kumar
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Maria-Victoria Mateos
- Hospital Universitario de Salamanca, Instituto de Investigacion Biomedica de Salamanca (IBSAL), Centro de Investigación del Cancer (IBMCC-USAL, CSIC), CIBER-ONC number CB16/12/00233, Salamanca, Spain
| | | | - Marta Chesi
- Division of Hematology/Oncology, Mayo Clinic, Scottsdale, Arizona
| | | | - Angela Dispenzieri
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Rafael Fonseca
- Division of Hematology/Oncology, Mayo Clinic, Scottsdale, Arizona
| | - Gad Getz
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Efstathios Kastritis
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, Athens, Greece
| | | | - Jose Angel Martinez-Climent
- Cancer Center Clinica Universidad de Navarra (CCUN), Centro de Investigacion Medica Aplicada (CIMA), Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | - Salomon Manier
- Hematology Department, CHU Lille, Lille University, INSERM UMR-S1277, Lille, France
| | | | - Francesco Maura
- Myeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, Florida
| | - Gareth J. Morgan
- Myeloma Research Program, NYU Langone, Perlmutter Cancer Center, New York, New York
| | - Faith E. Davies
- Myeloma Research Program, NYU Langone, Perlmutter Cancer Center, New York, New York
| | - Omar Nadeem
- Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Mario Nuvolone
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
- Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Bruno Paiva
- Cancer Center Clinica Universidad de Navarra (CCUN), Centro de Investigacion Medica Aplicada (CIMA), Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | | | - Felipe Prosper
- Hematology Service and Cell Therapy Unit and Program of Hematology-Oncology CIMA, Clinica Universidad de Navarra, Cancer Center Clínica Universidad de Navarra (CCUN) and Instituto de Investigación Sanitaria de Navarra (IdISNA), Pamplona, Spain
- Centro de Investigación Biomedica en Red Cancer (CIBERONC) and RICORS TERAV, Madrid, Spain
| | - Urvi A. Shah
- Department of Medicine, Myeloma Service, Memorial Sloan Kettering Cancer Center, New York, New York
| | | | | | - George S. Vassiliou
- Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom
- Department of Haematology, University of Cambridge, Cambridge, United Kingdom
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | | | - Philip E. Castle
- Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland
| | | | - Jesus F. San Miguel
- Cancer Center Clinica Universidad de Navarra (CCUN), Centro de Investigacion Medica Aplicada (CIMA), Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
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Nadeem O, Aranha MP, Redd R, Timonian M, Magidson S, Lightbody ED, Alberge JB, Bertamini L, Dutta AK, El-Khoury H, Bustoros M, Laubach JP, Bianchi G, O'Donnell E, Wu T, Tsuji J, Anderson K, Getz G, Trippa L, Richardson PG, Sklavenitis-Pistofidis R, Ghobrial IM. Long-Term Follow-Up Defines the Population That Benefits from Early Interception in a High-Risk Smoldering Multiple Myeloma Clinical Trial Using the Combination of Ixazomib, Lenalidomide, and Dexamethasone. medRxiv 2024:2024.04.19.24306082. [PMID: 38699307 PMCID: PMC11064995 DOI: 10.1101/2024.04.19.24306082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Background Early therapeutic intervention in high-risk SMM (HR-SMM) has demonstrated benefit in previous studies of lenalidomide with or without dexamethasone. Triplets and quadruplet studies have been examined in this same population. However, to date, none of these studies examined the impact of depth of response on long-term outcomes of participants treated with lenalidomide-based therapy, and whether the use of the 20/2/20 model or the addition of genomic alterations can further define the population that would benefit the most from early therapeutic intervention. Here, we present the results of the phase II study of the combination of ixazomib, lenalidomide, and dexamethasone in patients with HR-SMM with long-term follow-up and baseline single-cell tumor and immune sequencing that help refine the population to be treated for early intervention studies. Methods This is a phase II trial of ixazomib, lenalidomide, and dexamethasone (IRD) in HR-SMM. Patients received 9 cycles of induction therapy with ixazomib 4mg on days 1, 8, and 15; lenalidomide 25mg on days 1-21; and dexamethasone 40mg on days 1, 8, 15, and 22. The induction phase was followed by maintenance with ixazomib 4mg on days 1, 8, and 15; and lenalidomide 15mg d1-21 for 15 cycles for 24 months of treatment. The primary endpoint was progression-free survival after 2 years of therapy. Secondary endpoints included depth of response, biochemical progression, and correlative studies included single-cell RNA sequencing and/or whole-genome sequencing of the tumor and single-cell sequencing of immune cells at baseline. Results Fifty-five patients, with a median age of 64, were enrolled in the study. The overall response rate was 93%, with 31% of patients achieving a complete response and 45% achieving a very good partial response or better. The most common grade 3 or greater treatment-related hematologic toxicities were neutropenia (16 patients; 29%), leukopenia (10 patients; 18%), lymphocytopenia (8 patients; 15%), and thrombocytopenia (4 patients; 7%). Non-hematologic grade 3 or greater toxicities included hypophosphatemia (7 patients; 13%), rash (5 patients; 9%), and hypokalemia (4 patients; 7%). After a median follow-up of 50 months, the median progression-free survival (PFS) was 48.6 months (95% CI: 39.9 - not reached; NR) and median overall survival has not been reached. Patients achieving VGPR or better had a significantly better progression-free survival (p<0.001) compared to those who did not achieve VGPR (median PFS 58.2 months vs. 31.3 months). Biochemical progression preceded or was concurrent with the development of SLiM-CRAB criteria in eight patients during follow-up, indicating that biochemical progression is a meaningful endpoint that correlates with the development of end-organ damage. High-risk 20/2/20 participants had the worst PFS compared to low- and intermediate-risk participants. The use of whole genome or single-cell sequencing of tumor cells identified high-risk aberrations that were not identified by FISH alone and aided in the identification of participants at risk of progression. scRNA-seq analysis revealed a positive correlation between MHC class I expression and response to proteasome inhibition and at the same time a decreased proportion of GZMB+ T cells within the clonally expanded CD8+ T cell population correlated with suboptimal response. Conclusions Ixazomib, lenalidomide and dexamethasone in HR-SMM demonstrates significant clinical activity with an overall favorable safety profile. Achievement of VGPR or greater led to significant improvement in time to progression, suggesting that achieving deep response is beneficial in HR-SMM. Biochemical progression correlates with end-organ damage. Patients with high-risk FISH and lack of deep response had poor outcomes. ClinicalTrials.gov identifier: ( NCT02916771 ).
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Rees MJ, Kumar S. High-risk multiple myeloma: Redefining genetic, clinical, and functional high-risk disease in the era of molecular medicine and immunotherapy. Am J Hematol 2024. [PMID: 38613829 DOI: 10.1002/ajh.27327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 03/22/2024] [Accepted: 04/02/2024] [Indexed: 04/15/2024]
Abstract
Multiple myeloma (MM) exhibits significant heterogeneity in its presentation, genetics, and treatment response. Despite therapeutic advances, some patients continue to relapse early (ER, <18-months) and rapidly cycle through therapies. Myriad prognostic factors have been identified and incorporated into risk stratification models; however, these produce discordant, often three-tiered outputs that fail to identify many patients destined for ER. Treatment strategies are increasingly focused on disease biology and trials enriched for high-risk (HR)MM, but consensus on the minimum required testing and a succinct, specific, and clinically meaningful definition for HRMM remains elusive. We review the risk-factors, definitions, and future directions for HRMM.
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Affiliation(s)
- Matthew J Rees
- Division of Hematology, Mayo Clinic, Rochester, Minnesota, USA
| | - Shaji Kumar
- Division of Hematology, Mayo Clinic, Rochester, Minnesota, USA
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Dhodapkar MV. Immune-Pathogenesis of Myeloma. Hematol Oncol Clin North Am 2024; 38:281-291. [PMID: 38195307 DOI: 10.1016/j.hoc.2023.12.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
This research indicates that monoclonal gammopathy of undetermined significance (MGUS) and myeloma may stem from chronic immune activation and inflammation, causing immune dysfunction and spatial immune exclusion. As the conditions progress, a shift toward myeloma involves ongoing immune impairment, affecting both innate and adaptive immunity. Intriguingly, even in advanced myeloma stages, susceptibility to immune effector cells persists. This insight highlights the intricate interplay between immune responses and the development of these conditions, paving the way for potential therapeutic interventions targeting immune modulation in the management of MGUS and myeloma.
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Affiliation(s)
- Madhav V Dhodapkar
- Department of Hematology/Medical Oncology, Emory University, Winship Cancer Institute, 1365 Clifton Road, Atlanta, GA 30332, USA.
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5
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Stanton SE, Castle PE, Finn OJ, Sei S, Emens LA. Advances and challenges in cancer immunoprevention and immune interception. J Immunother Cancer 2024; 12:e007815. [PMID: 38519057 PMCID: PMC10961508 DOI: 10.1136/jitc-2023-007815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/29/2024] [Indexed: 03/24/2024] Open
Abstract
Invasive cancers typically evade immune surveillance through profound local and systemic immunosuppression, preventing their elimination or control. Targeting immune interventions to prevent or intercept premalignant lesions, before significant immune dysregulation has occurred, may be a more successful strategy. The field of cancer immune interception and prevention is nascent, and the scientific community has been slow to embrace this potentially most rational approach to reducing the global burden of cancer. This may change due to recent promising advances in cancer immunoprevention including the use of vaccines for the prevention of viral cancers, the use of cancer-associated antigen vaccines in the setting of precancers, and the development of cancer-preventative vaccines for high-risk individuals who are healthy but carry cancer-associated heritable genetic mutations. Furthermore, there is increasing recognition of the importance of cancer prevention and interception by national cancer organizations. The National Cancer Institute (NCI) recently released the National Cancer Plan, which includes cancer prevention among the top priorities of the institute. The NCI's Division of Cancer Prevention has been introducing new funding opportunities for scientists with an interest in the field of cancer prevention: The Cancer Prevention-Interception Targeted Agent Discovery Program and The Cancer Immunoprevention Network. Moreover, the Human Tumor Atlas Network is spearheading the development of a precancer atlas to better understand the biology of pre-invasive changes, including the tissue microenvironment and the underlying genetics that drive carcinogenesis. These data will inform the development of novel immunoprevention/immuno-interception strategies. International cancer foundations have also started recognizing immunoprevention and immune interception with the American Association for Cancer Research, Cancer Research UK and the Society for Immunotherapy of Cancer each implementing programming focused on this area. This review will present recent advances, opportunities, and challenges in the emerging field of cancer immune prevention and immune interception.
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Affiliation(s)
- Sasha E Stanton
- Cancer Immunoprevention Laboratory, Earle A Chiles Research Institute, Providence Cancer Institute, Portland, Oregon, USA
| | - Philip E Castle
- Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA
| | - Olivera J Finn
- Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Shizuko Sei
- Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA
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Suzuki K, Matsumoto M, Hiramatsu Y, Takezako N, Tamai Y, Suzuki K. NK and T-lymphocyte Kinetics Predict Outcome in Myeloma Patients Treated With Elotuzumab, Lenalidomide Plus Dexamethasone. Cancer Diagn Progn 2024; 4:97-104. [PMID: 38434915 PMCID: PMC10905294 DOI: 10.21873/cdp.10293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 01/22/2024] [Indexed: 03/05/2024]
Abstract
Background/Aim Elotuzumab, an anti-SLAMF7 monoclonal antibody, can enhance immune activity via elevated antibody-dependent cellular cytotoxicity and reduced SLAMF7+CD8+CD57+ regulatory T-cells (Tregs). This multicenter observational study investigated the kinetics of lymphocytes in myeloma patients treated with elotuzumab, lenalidomide, and dexamethasone (ERd) by two-color flow cytometry using peripheral blood samples. Patients and Methods Twenty-one patients were included in this study. The median duration of ERd was 22.6 months, and the cutoff time for long-duration ERd was two years. Results The CD2+CD16+ and CD16+CD57- NK cells were significantly increased over time in the long-duration ERd group compared to those in the short-duration ERd group (p=0.035 and p<0.001). The CD8+ and CD16-CD57+ lymphocytes, identified as low-activity NK cells or SLAMF7+ Tregs, were significantly increased in the patients whose ERd outcome was progressive disease (PD) compared to those in the non-PD group (p=0.023 and p<0.001). The mean CD4/CD8 ratio and CD19+ lymphocyte counts in the long-duration ERd group were significantly lower than those in the short-duration ERd group, although the kinetics of them did not change over time (p=0.016 and p=0.011). When the cutoff value of CD4/CD8 ratio was 0.792 according to ROC curves, the two-year time to next treatment (TTNT) in the low CD4/CD8 group was significantly longer than that in the high CD4/CD8 group (80.0% vs. 15.0%, p=0.024). Conclusion The change in NK cells and CD8+ Tregs predicted long-duration ERd and PD, and maintaining low CD4/8 ratio predicted long TTNT, suggesting that these lymphocyte fractions might be biomarkers for a durable therapeutic effect of ERd in myeloma patients.
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Affiliation(s)
- Kazuhito Suzuki
- Division of Clinical Oncology/Hematology, Department of Internal Medicine, The Jikei University School of Medicine, Tokyo, Japan
| | - Morio Matsumoto
- Department of Hematology, Shibukawa Medical Center, Gunma, Japan
| | - Yasushi Hiramatsu
- Department of Hematology/Oncology, Japanese Red Cross Society Himeji Hospital, Hyogo, Japan
| | - Naoki Takezako
- Department of Hematology, National Hospital Organization Disaster Medical Center, Tokyo, Japan
| | - Yotaro Tamai
- Department of Hematology, Shonan Kamakura General Hospital, Kanagawa, Japan
| | - Kenshi Suzuki
- Department of Hematology, Japanese Red Cross Medical Center, Tokyo, Japan
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7
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Poos AM, Prokoph N, Przybilla MJ, Mallm JP, Steiger S, Seufert I, John L, Tirier SM, Bauer K, Baumann A, Rohleder J, Munawar U, Rasche L, Kortüm KM, Giesen N, Reichert P, Huhn S, Müller-Tidow C, Goldschmidt H, Stegle O, Raab MS, Rippe K, Weinhold N. Resolving therapy resistance mechanisms in multiple myeloma by multiomics subclone analysis. Blood 2023; 142:1633-1646. [PMID: 37390336 PMCID: PMC10733835 DOI: 10.1182/blood.2023019758] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/17/2023] [Accepted: 06/12/2023] [Indexed: 07/02/2023] Open
Abstract
Intratumor heterogeneity as a clinical challenge becomes most evident after several treatment lines, when multidrug-resistant subclones accumulate. To address this challenge, the characterization of resistance mechanisms at the subclonal level is key to identify common vulnerabilities. In this study, we integrate whole-genome sequencing, single-cell (sc) transcriptomics (scRNA sequencing), and chromatin accessibility (scATAC sequencing) together with mitochondrial DNA mutations to define subclonal architecture and evolution for longitudinal samples from 15 patients with relapsed or refractory multiple myeloma. We assess transcriptomic and epigenomic changes to resolve the multifactorial nature of therapy resistance and relate it to the parallel occurrence of different mechanisms: (1) preexisting epigenetic profiles of subclones associated with survival advantages, (2) converging phenotypic adaptation of genetically distinct subclones, and (3) subclone-specific interactions of myeloma and bone marrow microenvironment cells. Our study showcases how an integrative multiomics analysis can be applied to track and characterize distinct multidrug-resistant subclones over time for the identification of molecular targets against them.
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Affiliation(s)
- Alexandra M. Poos
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Nina Prokoph
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Moritz J. Przybilla
- Division Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Cambridge, United Kingdom
| | - Jan-Philipp Mallm
- Single Cell Open Lab, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Simon Steiger
- Division of Chromatin Networks, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Isabelle Seufert
- Division of Chromatin Networks, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Lukas John
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Stephan M. Tirier
- Division of Chromatin Networks, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Katharina Bauer
- Single Cell Open Lab, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Anja Baumann
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Jennifer Rohleder
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Umair Munawar
- Department of Internal Medicine 2, University Hospital of Würzburg, Würzburg, Germany
| | - Leo Rasche
- Department of Internal Medicine 2, University Hospital of Würzburg, Würzburg, Germany
- Mildred Scheel Early Career Center, University Hospital of Würzburg, Würzburg, Germany
| | - K. Martin Kortüm
- Department of Internal Medicine 2, University Hospital of Würzburg, Würzburg, Germany
| | - Nicola Giesen
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Philipp Reichert
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
| | - Stefanie Huhn
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
| | - Carsten Müller-Tidow
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- National Center for Tumor Diseases, Heidelberg, Germany
| | - Hartmut Goldschmidt
- Department of Internal Medicine V, GMMG-Study Group at University Hospital Heidelberg, Heidelberg, Germany
| | - Oliver Stegle
- Division Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Marc S. Raab
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Karsten Rippe
- Division of Chromatin Networks, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Niels Weinhold
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
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8
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Parry EM, Lemvigh CK, Deng S, Dangle N, Ruthen N, Knisbacher BA, Broséus J, Hergalant S, Guièze R, Li S, Zhang W, Johnson C, Long JM, Yin S, Werner L, Anandappa A, Purroy N, Gohil S, Oliveira G, Bachireddy P, Shukla SA, Huang T, Khoury JD, Thakral B, Dickinson M, Tam C, Livak KJ, Getz G, Neuberg D, Feugier P, Kharchenko P, Wierda W, Olsen LR, Jain N, Wu CJ. ZNF683 marks a CD8 + T cell population associated with anti-tumor immunity following anti-PD-1 therapy for Richter syndrome. Cancer Cell 2023; 41:1803-1816.e8. [PMID: 37738974 PMCID: PMC10618915 DOI: 10.1016/j.ccell.2023.08.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 05/30/2023] [Accepted: 08/30/2023] [Indexed: 09/24/2023]
Abstract
Unlike many other hematologic malignancies, Richter syndrome (RS), an aggressive B cell lymphoma originating from indolent chronic lymphocytic leukemia, is responsive to PD-1 blockade. To discover the determinants of response, we analyze single-cell transcriptome data generated from 17 bone marrow samples longitudinally collected from 6 patients with RS. Response is associated with intermediate exhausted CD8 effector/effector memory T cells marked by high expression of the transcription factor ZNF683, determined to be evolving from stem-like memory cells and divergent from terminally exhausted cells. This signature overlaps with that of tumor-infiltrating populations from anti-PD-1 responsive solid tumors. ZNF683 is found to directly target key T cell genes (TCF7, LMO2, CD69) and impact pathways of T cell cytotoxicity and activation. Analysis of pre-treatment peripheral blood from 10 independent patients with RS treated with anti-PD-1, as well as patients with solid tumors treated with anti-PD-1, supports an association of ZNF683high T cells with response.
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Affiliation(s)
- Erin M Parry
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Camilla K Lemvigh
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Health Technology, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Stephanie Deng
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Nathan Dangle
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Neil Ruthen
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | | | - Julien Broséus
- Inserm UMRS1256 Nutrition-Génétique et Exposition Aux Risques Environnementaux (N-GERE), Université de Lorraine, 54000 Nancy, France; Université de Lorraine, CHRU-Nancy, Service d'hématologie Biologique, Pôle Laboratoires, 54000 Nancy, France
| | - Sébastien Hergalant
- Inserm UMRS1256 Nutrition-Génétique et Exposition Aux Risques Environnementaux (N-GERE), Université de Lorraine, 54000 Nancy, France
| | - Romain Guièze
- CHU Clermont-Ferrand, 63000 Clermont-Ferrand, France; EA 7453 (CHELTER), Université Clermont Auvergne, 63001 Clermont-Ferrand, France
| | - Shuqiang Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Wandi Zhang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Connor Johnson
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jaclyn M Long
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA; Evergrande Center for Immunologic Diseases, Harvard Medical School and Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Gastroenterology, Hepatology, and Nutrition, Boston Children's Hospital, Boston, MA 02115, USA
| | - Shanye Yin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Lillian Werner
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Annabelle Anandappa
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Noelia Purroy
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Satyen Gohil
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Giacomo Oliveira
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Pavan Bachireddy
- Department of Hematopoietic Biology and Malignancy, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sachet A Shukla
- Department of Hematopoietic Biology and Malignancy, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Teddy Huang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Joseph D Khoury
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA
| | - Beenu Thakral
- Department of Hematopathology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Michael Dickinson
- Peter MacCallum Cancer Centre, Royal Melbourne Hospital, Melbourne, VIC, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Constantine Tam
- Alfred Health, Melbourne, VIC, Australia; Monash University, Melbourne, VIC, Australia
| | - Kenneth J Livak
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Gad Getz
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Donna Neuberg
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Pierre Feugier
- Inserm UMRS1256 Nutrition-Génétique et Exposition Aux Risques Environnementaux (N-GERE), Université de Lorraine, 54000 Nancy, France; Université de Lorraine, CHRU Nancy, service d'hématologie clinique, Nancy, France
| | - Peter Kharchenko
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02215, USA
| | - William Wierda
- Department of Leukemia, University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA
| | - Lars Rønn Olsen
- Department of Health Technology, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Nitin Jain
- Department of Leukemia, University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA
| | - Catherine J Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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9
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Zhang M, Huang Y, Pan J, Sang C, Lin Y, Dong L, Shen X, Wu Y, Song G, Ji S, Liu F, Wang M, Zheng Y, Zhang S, Wang Z, Ren J, Gao D, Zhou J, Fan J, Wei W, Lin J, Gao Q. An Inflammatory Checkpoint Generated by IL1RN Splicing Offers Therapeutic Opportunity for KRAS-Mutant Intrahepatic Cholangiocarcinoma. Cancer Discov 2023; 13:2248-2269. [PMID: 37486241 DOI: 10.1158/2159-8290.cd-23-0282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 06/30/2023] [Accepted: 07/20/2023] [Indexed: 07/25/2023]
Abstract
KRAS mutations are causally linked to protumor inflammation and are identified as driving factors in tumorigenesis. Here, using multiomics data gathered from a large set of patients, we showed that KRAS mutation was associated with a specific landscape of alternative mRNA splicing that connected to myeloid inflammation in intrahepatic cholangiocarcinoma (iCCA). Then, we identified a negative feedback mechanism in which the upregulation of interleukin 1 receptor antagonist (IL1RN)-201/203 due to alternative splicing confers vital anti-inflammatory effects in KRAS-mutant iCCA. In KRAS-mutant iCCA mice, both IL1RN-201/203 upregulation and anakinra treatment ignited a significant antitumor immune response by altering neutrophil recruitment and phenotypes. Furthermore, anakinra treatment synergistically enhanced anti-PD-1 therapy to activate intratumoral GZMB+ CD8+ T cells in KRAS-mutant iCCA mice. Clinically, we found that high IL1RN-201/203 levels in patients with KRAS-mutant iCCA were significantly associated with superior response to anti-PD-1 immunotherapy. SIGNIFICANCE This work describes a novel inflammatory checkpoint mediated by IL1RN alternative splicing variants that may serve as a promising basis to develop therapeutic options for KRAS-mutant iCCA and other cancers. This article is featured in Selected Articles from This Issue, p. 2109.
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Affiliation(s)
- Mao Zhang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Yingying Huang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jiaomeng Pan
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Chen Sang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Youpei Lin
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Liangqing Dong
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Xia Shen
- Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, China
| | - Yingcheng Wu
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Guohe Song
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Shuyi Ji
- Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, China
| | - Fen Liu
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China
| | - Mengcheng Wang
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China
| | - Yuyan Zheng
- Department of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Sirui Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Zefeng Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jianke Ren
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Daming Gao
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China
| | - Jian Zhou
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
- Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Jia Fan
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
- Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Wu Wei
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Lingang Laboratory, Shanghai, China
- Translational Medicine Institute of Jiangxi, The First Affiliated Hospital of Nanchang University, Jiangxi, China
| | - Jian Lin
- Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, China
| | - Qiang Gao
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
- Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
- State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China
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10
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Botta C, Perez C, Larrayoz M, Puig N, Cedena MT, Termini R, Goicoechea I, Rodriguez S, Zabaleta A, Lopez A, Sarvide S, Blanco L, Papetti DM, Nobile MS, Besozzi D, Gentile M, Correale P, Siragusa S, Oriol A, González-Garcia ME, Sureda A, de Arriba F, Rios Tamayo R, Moraleda JM, Gironella M, Hernandez MT, Bargay J, Palomera L, Pérez-Montaña A, Goldschmidt H, Avet-Loiseau H, Roccaro A, Orfao A, Martinez-Lopez J, Rosiñol L, Lahuerta JJ, Blade J, Mateos MV, San-Miguel JF, Martinez Climent JA, Paiva B. Large T cell clones expressing immune checkpoints increase during multiple myeloma evolution and predict treatment resistance. Nat Commun 2023; 14:5825. [PMID: 37730678 PMCID: PMC10511411 DOI: 10.1038/s41467-023-41562-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 09/07/2023] [Indexed: 09/22/2023] Open
Abstract
Tumor recognition by T cells is essential for antitumor immunity. A comprehensive characterization of T cell diversity may be key to understanding the success of immunomodulatory drugs and failure of PD-1 blockade in tumors such as multiple myeloma (MM). Here, we use single-cell RNA and T cell receptor sequencing to characterize bone marrow T cells from healthy adults (n = 4) and patients with precursor (n = 8) and full-blown MM (n = 10). Large T cell clones from patients with MM expressed multiple immune checkpoints, suggesting a potentially dysfunctional phenotype. Dual targeting of PD-1 + LAG3 or PD-1 + TIGIT partially restored their function in mice with MM. We identify phenotypic hallmarks of large intratumoral T cell clones, and demonstrate that the CD27- and CD27+ T cell ratio, measured by flow cytometry, may serve as a surrogate of clonal T cell expansions and an independent prognostic factor in 543 patients with MM treated with lenalidomide-based treatment combinations.
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Grants
- This work was supported by grants from the Instituto de Salud Carlos III/Subdireccion General de Investigacion Sanitaria and co-financed by FEDER funds (CB16/12/00233, CB16/12/00369, PI17/01243, PI19/00818 and PI20/00048), and together with Fundación Científica de la Asociación Española Contra el Cáncer (FCAECC) for iMMunocell Transcan-2 (AC17/00101), FCAECC Predoctoral Grant Junta Provincial Navarra, the Cancer Research UK (C355/A26819), FCAECC and Italian Association for Cancer Research (AIRC) under the Accelerator Award Program (EDITOR), 2017 Multiple Myeloma Research Foundation Immunotherapy Networks of Excellence, Black Swan Research Initiative of the International Myeloma Foundation, European Hematology Association nonclinical advanced research grant (3680644), European Research Council 2015 Starting Grant (MYELOMANEXT grant 680200), the Cancer Research Innovation in Science Cancer Foundation (PR_EX_2020-02), the Leukemia Lymphoma Society, unrestricted grants from Bristol-Myers Squibb/Celgene and Takeda, Roche imCORE program (NAV-4 and NAV-15), Fondazione Regionale per la Ricerca Biomedica (Regione Lombardia) (Project ID 065 JTC 2016), ERA-NET TRANSCAN-2, and by My First AIRC Grant 2020 (n. 24534, 2021/2026), and by the Riney Family Multiple Myeloma Research Program Fund.
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Affiliation(s)
- Cirino Botta
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, University of Palermo, Palermo, Italy.
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain.
| | - Cristina Perez
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | - Marta Larrayoz
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | - Noemi Puig
- Hospital Universitario de Salamanca, Instituto de Investigacion Biomedica de Salamanca (IBSAL), Centro de Investigación del Cancer (IBMCC-USAL, CSIC), CIBER-ONC number CB16/12/00233, Salamanca, Spain
| | - Maria-Teresa Cedena
- Hospital Universitario 12 de Octubre, CIBER-ONC number CB16/12/00369, Madrid, Spain
| | - Rosalinda Termini
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | - Ibai Goicoechea
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | - Sara Rodriguez
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | - Aintzane Zabaleta
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | - Aitziber Lopez
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | - Sarai Sarvide
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | - Laura Blanco
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | - Daniele M Papetti
- Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy
| | - Marco S Nobile
- Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Venice, Italy
- Bicocca Bioinformatics, Biostatistics and Bioimaging Centre-B4, Milan, Italy
| | - Daniela Besozzi
- Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy
- Bicocca Bioinformatics, Biostatistics and Bioimaging Centre-B4, Milan, Italy
| | - Massimo Gentile
- Department of Oncohematology, "Annunziata" Hospital, Cosenza, Italy
| | - Pierpaolo Correale
- Medical Oncology Unit, Great Metropolitan Hospital "Riuniti" of Reggio Calabria, Reggio Calabria, Italy
| | - Sergio Siragusa
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, University of Palermo, Palermo, Italy
| | - Albert Oriol
- Institut Català d'Oncologia i Institut Josep Carreras, Badalona, Spain
| | | | - Anna Sureda
- Institut Català d'Oncologia-Hospitalet, Instituto de Investigación Biomédica de Bellvitge (IDIBELL), Barcelona, Spain
| | - Felipe de Arriba
- Hospital Morales Meseguer, IMIB-Arrixaca, Universidad de Murcia, Murcia, Spain
| | | | - Jose-Maria Moraleda
- Hospital Morales Meseguer, IMIB-Arrixaca, Universidad de Murcia, Murcia, Spain
| | | | | | - Joan Bargay
- Hospital Son Llatzer, Palma de Mallorca, Spain
| | | | | | - Hartmut Goldschmidt
- Department of Internal Medicine V, University of Heidelberg, Heidelberg, Germany
| | | | - Aldo Roccaro
- Department of Hematology, ASST Spedali Civili di Brescia, Brescia, BS, Italy
| | - Alberto Orfao
- Cancer Research Center (IBMCC-CSIC/USAL-IBSAL), CIBER-ONC number CB16/12/00400, Salamanca, Spain
- Cytometry Service (NUCLEUS) and Department of Medicine, University of Salamanca, Salamanca, Spain
| | | | | | - Juan-José Lahuerta
- Hospital Universitario 12 de Octubre, CIBER-ONC number CB16/12/00369, Madrid, Spain
| | - Joan Blade
- Hospital Clínic IDIBAPS, Barcelona, Spain
| | - Maria-Victoria Mateos
- Hospital Universitario de Salamanca, Instituto de Investigacion Biomedica de Salamanca (IBSAL), Centro de Investigación del Cancer (IBMCC-USAL, CSIC), CIBER-ONC number CB16/12/00233, Salamanca, Spain
| | - Jesús F San-Miguel
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | - Jose-Angel Martinez Climent
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain
| | - Bruno Paiva
- Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), CCUN, Instituto de Investigacion Sanitaria de Navarra (IDISNA), CIBER-ONC numbers CB16/12/00369, CB16/12/00489, Pamplona, Spain.
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11
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Samur MK, Szalat R, Munshi NC. Single-cell profiling in multiple myeloma: insights, problems, and promises. Blood 2023; 142:313-324. [PMID: 37196627 PMCID: PMC10485379 DOI: 10.1182/blood.2022017145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 04/05/2023] [Accepted: 05/11/2023] [Indexed: 05/19/2023] Open
Abstract
In a short time, single-cell platforms have become the norm in many fields of research, including multiple myeloma (MM). In fact, the large amount of cellular heterogeneity in MM makes single-cell platforms particularly attractive because bulk assessments can miss valuable information about cellular subpopulations and cell-to-cell interactions. The decreasing cost and increasing accessibility of single-cell platform, combined with breakthroughs in obtaining multiomics data for the same cell and innovative computational programs for analyzing data, have allowed single-cell studies to make important insights into MM pathogenesis; yet, there is still much to be done. In this review, we will first focus on the types of single-cell profiling and the considerations for designing a single-cell profiling experiment. Then, we will discuss what have learned from single-cell profiling about myeloma clonal evolution, transcriptional reprogramming, and drug resistance, and about the MM microenvironment during precursor and advanced disease.
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Affiliation(s)
- Mehmet Kemal Samur
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Raphael Szalat
- Department of Hematology and Medical Oncology, Boston University Medical Center, Boston, MA
| | - Nikhil C. Munshi
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
- VA Boston Healthcare System, Boston, MA
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12
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Shimazu Y, Kanda J, Kosugi S, Ito T, Kaneko H, Imada K, Shimura Y, Fuchida SI, Fukushima K, Tanaka H, Yoshihara S, Ohta K, Uoshima N, Yagi H, Shibayama H, Yamamura R, Tanaka Y, Uchiyama H, Onda Y, Adachi Y, Hanamoto H, Takahashi R, Matsuda M, Miyoshi T, Takakuwa T, Hino M, Hosen N, Nomura S, Shimazaki C, Matsumura I, Takaori-Kondo A, Kuroda J. Efficacy of elotuzumab for multiple myeloma in reference to lymphocyte counts and kappa/lambda ratio or B2 microglobulin. Sci Rep 2023; 13:5159. [PMID: 36991096 PMCID: PMC10060246 DOI: 10.1038/s41598-023-32426-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 03/27/2023] [Indexed: 03/30/2023] Open
Abstract
AbstractNovel therapeutic drugs have dramatically improved the overall survival of patients with multiple myeloma. We sought to identify the characteristics of patients likely to exhibit a durable response to one such drug, elotuzumab, by analyzing a real-world database in Japan. We analyzed 179 patients who underwent 201 elotuzumab treatments. The median time to next treatment (TTNT) with the 95% confidence interval was 6.29 months (5.18–9.20) in this cohort. Univariate analysis showed that patients with any of the following had longer TTNT: no high risk cytogenic abnormalities, more white blood cells, more lymphocytes, non-deviated κ/λ ratio, lower β2 microglobulin levels (B2MG), fewer prior drug regimens, no prior daratumumab use and better response after elotuzumab treatment. A multivariate analysis showed that TTNT was longer in patients with more lymphocytes (≥ 1400/μL), non-deviated κ/λ ratio (0.1–10), lower B2MG (< 5.5 mg/L) and no prior daratumumab use. We proposed a simple scoring system to predict the durability of the elotuzumab treatment effect by classifying the patients into three categories based on their lymphocyte counts (0 points for ≥ 1400/μL and 1 point for < 1400/μL) and κ/λ ratio (0 points for 0.1–10 and 1 point for < 0.1 or ≥ 10) or B2MG (0 points for < 5.5 mg/L and 1 point for ≥ 5.5 mg/L). The patients with a score of 0 showed significantly longer TTNT (p < 0.001) and better survival (p < 0.001) compared to those with a score of 1 or 2. Prospective cohort studies of elotuzumab treatment may be needed to validate the usefulness of our new scoring system.
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13
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Zhao J, Wang X, Zhu H, Wei S, Zhang H, Ma L, He P. Integrative Analysis of Bulk RNA-Seq and Single-Cell RNA-Seq Unveils Novel Prognostic Biomarkers in Multiple Myeloma. Biomolecules 2022; 12:biom12121855. [PMID: 36551283 PMCID: PMC9776050 DOI: 10.3390/biom12121855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 12/06/2022] [Accepted: 12/09/2022] [Indexed: 12/14/2022] Open
Abstract
Molecular heterogeneity has great significance in the disease biology of multiple myeloma (MM). Thus, the analysis combined single-cell RNA-seq (scRNA-seq) and bulk RNA-seq data were performed to investigate the clonal evolution characteristics and to find novel prognostic targets in MM. The scRNA-seq data were analyzed by the Seurat pipeline and Monocle 2 to identify MM cell branches with different differentiation states. Marker genes in each branch were uploaded to the STRING database to construct the Protein-Protein Interaction (PPI) network, followed by the detection of hub genes by Cytoscape software. Using bulk RNA-seq data, Kaplan-Meier (K-M) survival analysis was then carried out to determine prognostic biomarkers in MM. A total of 342 marker genes in two branches with different differentiation states were identified, and the top 20 marker genes with the highest scores in the network calculated by the MCC algorithm were selected as hub genes in MM. Furthermore, K-M survival analysis revealed that higher NDUFB8, COX6C, NDUFA6, USMG5, and COX5B expression correlated closely with a worse prognosis in MM patients. Moreover, ssGSEA and Pearson analyses showed that their expression had a significant negative correlation with the proportion of Tcm (central memory cell) immune cells. Our findings identified NDUFB8, COX6C, NDUFA6, USMG5, and COX5B as novel prognostic biomarkers in MM, and also revealed the significance of genetic heterogeneity during cell differentiation in MM prognosis.
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14
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Maclachlan KH, Lesokhin AM. Are we ready to look beyond plasma cells in assessing high-risk smoldering myeloma? Cancer Cell 2022; 40:1270-1272. [PMID: 36379204 DOI: 10.1016/j.ccell.2022.10.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Sklavenitis-Pistofidis et al. report clinical and correlative results of a single-arm phase II trial of elotuzumab, lenalidomide, and dexamethasone in patients with high-risk smoldering myeloma. The authors explore the interactions between the genetics of the plasma cell clone and the immune microenvironment as potential biomarkers of treatment susceptibility and efficacy.
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Affiliation(s)
- Kylee H Maclachlan
- Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Weill-Cornell Medical College, New York, NY, USA
| | - Alexander M Lesokhin
- Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Weill-Cornell Medical College, New York, NY, USA.
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