Large-scale analyses of genomic data from patients with newly diagnosed multiple myeloma (ndMM) have been undertaken, however, large-scale analysis of relapsed/refractory MM (rrMM) has not been performed. We hypothesize that somatic variants chronicle the therapeutic exposures and clonal structure of myeloma from ndMM to rrMM stages. We generated whole-genome sequencing (WGS) data from 418 tumors (386 patients) derived from 6 rrMM clinical trials and compared them with WGS from 198 unrelated patients with ndMM in a population-based case-control fashion. We identified significantly enriched events at the rrMM stage, including drivers (DUOX2, EZH2, TP53), biallelic inactivation (TP53), noncoding mutations in bona fide drivers (TP53BP1, BLM), copy number aberrations (CNAs; 1qGain, 17pLOH), and double-hit events (Amp1q-ISS3, 1qGain-17p loss-of-heterozygosity). Mutational signature analysis identified a subclonal defective mismatch repair signature enriched in rrMM and highly active in high mutation burden tumors, a likely feature of therapy-associated expanding subclones. Further analysis focused on the association of genomic aberrations enriched at different stages of resistance to immunomodulatory agent (IMiD)-based therapy. This analysis revealed that TP53, DUOX2, 1qGain, and 17p loss-of-heterozygosity increased in prevalence from ndMM to lenalidomide resistant (LENR) to pomalidomide resistant (POMR) stages, whereas enrichment of MAML3 along with immunoglobulin lambda (IGL) and MYC translocations distinguished POM from the LEN subgroup. Genomic drivers associated with rrMM are those that confer clonal selective advantage under therapeutic pressure. Their role in therapy evasion should be further evaluated in longitudinal patient samples, to confirm these associations with the evolution of clinical resistance and to identify molecular subsets of rrMM for the development of targeted therapies.
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http://dx.doi.org/10.1182/blood.2022017010 | DOI Listing |
Zhonghua Yi Xue Za Zhi
July 2024
Department of Pediatric Lymphoma, Beijing GoBroad Boren Hospital, Beijing 100070, China.
To analyze the mid-term efficacy of the China Net Childhood Lymphoma mature B-cell lymphoma 2017 (CNCL-B-NHL-2017) regimen in treating children with high-grade B-cell lymphoma (HGBL). Clinical and pathological data of HGBL children aged≤18 years admitted to 16 hospitals of the Chinese Children's Lymphoma Collaborative Group (CNCL) from May 2017 to April 2021 were collected retrospectively. They were divided in to high-grade B-cell lymphoma with double hit/triple hit (HGBL-DH/TH) group and high-grade B-cell lymphoma non-specified (HGBL-NOS) group, according to the 2016 version of the World Health Organization (WHO) Hematopoietic and Lymphoid Tissues Cancer Classification.
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September 2024
Division of Hematology, Mayo Clinic, Rochester, Minnesota, USA.
Blood
August 2024
Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
This meta-analysis evaluates the efficacy and safety of chimeric antigen receptor (CAR) T-cell therapy and bispecific antibodies for relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL). We searched MEDLINE, Embase, and Cochrane databases until July 2023 for trials assessing CAR T-cell therapies and CD20×CD3 bispecific antibodies as third or subsequent lines in R/R DLBCL. Random-effects models estimated the complete response (CR) rate and secondary outcomes, with meta-regressions adjusting for relevant covariates.
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April 2024
State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng East Road, Guangzhou, 510060, China.
Mutations in isocitrate dehydrogenases (IDH) are oncogenic events due to the generation of oncogenic metabolite 2-hydroxyglutarate. However, the role of wild-type IDH in cancer development remains elusive. Here we show that wild-type IDH2 is highly expressed in triple negative breast cancer (TNBC) cells and promotes their proliferation in vitro and tumor growth in vivo.
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October 2023
Hematology Division, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel.
Deep learning applications are emerging as promising new tools that can support the diagnosis and classification of different cancer types. While such solutions hold great potential for hematological malignancies, there have been limited studies describing the use of such applications in this field. The rapid diagnosis of double/triple-hit lymphomas (DHLs/THLs) involving , and/or rearrangements is obligatory for optimal patient care.
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