| 1. |
- Broderick, Peter, et al.
(författare)
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Common variation at 3p22.1 and 7p15.3 influences multiple myeloma risk
- 2012
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 44:1, s. 58-83
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Tidskriftsartikel (refereegranskat)abstract
- To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in ULK4; odds ratio (OR) = 1.32; P = 7.47 x 10(-9)) and 7p15.3 (rs4487645, OR = 1.38; P = 3.33 x 10(-15)). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29; P = 1.22 x 10(-7)). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights.
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| 2. |
- Chubb, Daniel, et al.
(författare)
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Common variation at 3q26.2, 6p21.33, 17p11.2 and 22q13.1 influences multiple myeloma risk
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 45:10, s. 366-1221
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Tidskriftsartikel (refereegranskat)abstract
- To identify variants for multiple myeloma risk, we conducted a genome-wide association study with validation in additional series totaling 4,692 individuals with multiple myeloma (cases) and 10,990 controls. We identified four risk loci at 3q26.2 (rs10936599, P = 8.70 x 10(-14)), 6p21.33 (rs2285803, PSORS1C2, P = 9.67 x 10(-11)), 17p11.2 (rs4273077, TNFRSF13B, P = 7.67 x 10(-9)) and 22q13.1 (rs877529, CBX7, P = 7.63 x 10(-16)). These data provide further evidence for genetic susceptibility to this B-cell hematological malignancy, as well as insight into the biological basis of predisposition.
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| 3. |
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| 4. |
- Sachpekidis, Christos, et al.
(författare)
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Artificial intelligence–based, volumetric assessment of the bone marrow metabolic activity in [ 18 F]FDG PET/CT predicts survival in multiple myeloma
- 2024
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Ingår i: European Journal of Nuclear Medicine and Molecular Imaging. - 1619-7070 .- 1619-7089. ; In Press
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Multiple myeloma (MM) is a highly heterogeneous disease with wide variations in patient outcome. [18F]FDG PET/CT can provide prognostic information in MM, but it is hampered by issues regarding standardization of scan interpretation. Our group has recently demonstrated the feasibility of automated, volumetric assessment of bone marrow (BM) metabolic activity on PET/CT using a novel artificial intelligence (AI)–based tool. Accordingly, the aim of the current study is to investigate the prognostic role of whole-body calculations of BM metabolism in patients with newly diagnosed MM using this AI tool. Materials and methods: Forty-four, previously untreated MM patients underwent whole-body [18F]FDG PET/CT. Automated PET/CT image segmentation and volumetric quantification of BM metabolism were based on an initial CT-based segmentation of the skeleton, its transfer to the standardized uptake value (SUV) PET images, subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, ten different uptake thresholds (AI approaches), based on reference organs or absolute SUV values, were applied for definition of pathological tracer uptake and subsequent calculation of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Correlation analysis was performed between the automated PET values and histopathological results of the BM as well as patients’ progression-free survival (PFS) and overall survival (OS). Receiver operating characteristic (ROC) curve analysis was used to investigate the discrimination performance of MTV and TLG for prediction of 2-year PFS. The prognostic performance of the new Italian Myeloma criteria for PET Use (IMPeTUs) was also investigated. Results: Median follow-up [95% CI] of the patient cohort was 110 months [105–123 months]. AI-based BM segmentation and calculation of MTV and TLG were feasible in all patients. A significant, positive, moderate correlation was observed between the automated quantitative whole-body PET/CT parameters, MTV and TLG, and BM plasma cell infiltration for all ten [18F]FDG uptake thresholds. With regard to PFS, univariable analysis for both MTV and TLG predicted patient outcome reasonably well for all AI approaches. Adjusting for cytogenetic abnormalities and BM plasma cell infiltration rate, multivariable analysis also showed prognostic significance for high MTV, which defined pathological [18F]FDG uptake in the BM via the liver. In terms of OS, univariable and multivariable analysis showed that whole-body MTV, again mainly using liver uptake as reference, was significantly associated with shorter survival. In line with these findings, ROC curve analysis showed that MTV and TLG, assessed using liver-based cut-offs, could predict 2-year PFS rates. The application of IMPeTUs showed that the number of focal hypermetabolic BM lesions and extramedullary disease had an adverse effect on PFS. Conclusions: The AI-based, whole-body calculations of BM metabolism via the parameters MTV and TLG not only correlate with the degree of BM plasma cell infiltration, but also predict patient survival in MM. In particular, the parameter MTV, using the liver uptake as reference for BM segmentation, provides solid prognostic information for disease progression. In addition to highlighting the prognostic significance of automated, global volumetric estimation of metabolic tumor burden, these data open up new perspectives towards solving the complex problem of interpreting PET scans in MM with a simple, fast, and robust method that is not affected by operator-dependent interventions.
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| 5. |
- Saeed, Borhan R., et al.
(författare)
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Analysis of nonleukemic cellular subcompartments reconstructs clonal evolution of acute myeloid leukemia and identifies therapy-resistant preleukemic clones
- 2021
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Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 148:11, s. 2825-2838
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Tidskriftsartikel (refereegranskat)abstract
- To acquire a better understanding of clonal evolution of acute myeloid leukemia (AML) and to identify the clone(s) responsible for disease recurrence, we have comparatively studied leukemia-specific mutations by whole-exome-sequencing (WES) of both the leukemia and the nonleukemia compartments derived from the bone marrow of AML patients. The T-lymphocytes, B-lymphocytes and the functionally normal hematopoietic stem cells (HSC), that is, CD34+/CD38−/ALDH+ cells for AML with rare-ALDH+ blasts (<1.9% ALDH+ cells) were defined as the nonleukemia compartments. WES identified 62 point-mutations in the leukemia compartment derived from 12 AML-patients at the time of diagnosis and 73 mutations in 3 matched relapse cases. Most patients (8/12) showed 4 to 6 point-mutations per sample at diagnosis. Other than the mutations in the recurrently mutated genes such as DNMT3A, NRAS and KIT, we were able to identify novel point-mutations that have not yet been described in AML. Some leukemia-specific mutations and cytogenetic abnormalities including DNMT3A(R882H), EZH2(I146T) and inversion(16) were also detectable in the respective T-lymphocytes, B-lymphocytes and HSC in 5/12 patients, suggesting that preleukemia HSC might represent the source of leukemogenesis for these cases. The leukemic evolution was reconstructed for five cases with detectable preleukemia clones, which were tracked in follow-up and relapse samples. Four of the five patients with detectable preleukemic mutations developed relapse. The presence of leukemia-specific mutations in these nonleukemia compartments, especially after chemotherapy or after allogeneic stem cell transplantation, is highly relevant, as these could be responsible for relapse. This discovery may facilitate the identification of novel targets for long-term cure.
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| 6. |
- Weinhold, Niels, et al.
(författare)
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The CCND1 c.870G > A polymorphism is a risk factor for t(11;14)(q13;q32) multiple myeloma
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 45:5, s. 522-525
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Tidskriftsartikel (refereegranskat)abstract
- A number of specific chromosomal abnormalities define the subgroups of multiple myeloma. In a meta-analysis of two genome-wide association studies of multiple myeloma including a total of 1,661 affected individuals, we investigated risk for developing a specific tumor karyotype. The t(11;14)(q13;q32) translocation in which CCND1 is placed under the control of the immunoglobulin heavy chain enhancer was strongly associated with the CCND1 c.870G>A polymorphism (P = 7.96 x 10(-11)). These results provide a model in which a constitutive genetic factor is associated with risk of a specific chromosomal translocation.
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| 7. |
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