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- In ’t Veld, Sjors G.J.G., et al.
(författare)
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Detection and localization of early- and late-stage cancers using platelet RNA
- 2022
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Ingår i: Cancer Cell. - : Elsevier. - 1535-6108 .- 1878-3686. ; 40:9, s. 999-1009.e6
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Tidskriftsartikel (refereegranskat)abstract
- Cancer patients benefit from early tumor detection since treatment outcomes are more favorable for less advanced cancers. Platelets are involved in cancer progression and are considered a promising biosource for cancer detection, as they alter their RNA content upon local and systemic cues. We show that tumor-educated platelet (TEP) RNA-based blood tests enable the detection of 18 cancer types. With 99% specificity in asymptomatic controls, thromboSeq correctly detected the presence of cancer in two-thirds of 1,096 blood samples from stage I–IV cancer patients and in half of 352 stage I–III tumors. Symptomatic controls, including inflammatory and cardiovascular diseases, and benign tumors had increased false-positive test results with an average specificity of 78%. Moreover, thromboSeq determined the tumor site of origin in five different tumor types correctly in over 80% of the cancer patients. These results highlight the potential properties of TEP-derived RNA panels to supplement current approaches for blood-based cancer screening.
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- Ge, R, et al.
(författare)
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Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization
- 2023
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Ingår i: bioRxiv : the preprint server for biology. - : Cold Spring Harbor Laboratory.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background: Normative modeling is a statistical approach to quantify the degree to which a particular individual-level measure deviates from the pattern observed in a normative reference population. When applied to human brain morphometric measures it has the potential to inform about the significance of normative deviations for health and disease. Normative models can be implemented using a variety of algorithms that have not been systematically appraised. Methods: To address this gap, eight algorithms were compared in terms of performance and computational efficiency using brain regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) collated from 87 international MRI datasets. Performance was assessed with the mean absolute error (MAE) and computational efficiency was inferred from central processing unit (CPU) time. The algorithms evaluated were Ordinary Least Squares Regression (OLSR), Bayesian Linear Regression (BLR), Generalized Additive Models for Location, Scale, and Shape (GAMLSS), Parametric Lambda, Mu, Sigma (LMS), Gaussian Process Regression (GPR), Warped Bayesian Linear Regression (WBLG), Hierarchical Bayesian Regression (HBR), and Multivariable Fractional Polynomial Regression (MFPR). Model optimization involved testing nine covariate combinations pertaining to acquisition features, parcellation software versions, and global neuroimaging measures (i.e., total intracranial volume, mean cortical thickness, and mean cortical surface area). Findings: Statistical comparisons across models at PFDR<0.05 indicated that the MFPR-derived sex- and region-specific models with nonlinear polynomials for age and linear effects of global measures had superior predictive accuracy; the range of the MAE of the models of regional subcortical volumes was 70-520 mm3 and the corresponding ranges for regional cortical thickness and regional cortical surface area were 0.09-0.26 mm and 24-560 mm2, respectively. The MFPR-derived models were also computationally more efficient with a CPU time below one second compared to a range of 2 seconds to 60 minutes for the other algorithms. The performance of all sex- and region-specific MFPR models plateaued at sample sizes exceeding 3,000 and showed comparable MAEs across distinct 10-year age-bins covering the human lifespan. Interpretation: These results provide an empirically benchmarked framework for normative modeling of brain morphometry that is useful for interpreting prior literature and supporting future study designs. The model and tools described here are freely available through CentileBrain (https://centilebrain.org/), a user-friendly web platform.
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- Kurth, F, et al.
(författare)
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Large-scale analysis of structural brain asymmetries during neurodevelopment : Associations with age and sex in 4265 children and adolescents.
- 2024
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Ingår i: Human Brain Mapping. - 1065-9471 .- 1097-0193. ; 45:11, s. e26754-
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Tidskriftsartikel (refereegranskat)abstract
- Only a small number of studies have assessed structural differences between the two hemispheres during childhood and adolescence. However, the existing findings lack consistency or are restricted to a particular brain region, a specific brain feature, or a relatively narrow age range. Here, we investigated associations between brain asymmetry and age as well as sex in one of the largest pediatric samples to date (n = 4265), aged 1-18 years, scanned at 69 sites participating in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our study revealed that significant brain asymmetries already exist in childhood, but their magnitude and direction depend on the brain region examined and the morphometric measurement used (cortical volume or thickness, regional surface area, or subcortical volume). With respect to effects of age, some asymmetries became weaker over time while others became stronger; sometimes they even reversed direction. With respect to sex differences, the total number of regions exhibiting significant asymmetries was larger in females than in males, while the total number of measurements indicating significant asymmetries was larger in males (as we obtained more than one measurement per cortical region). The magnitude of the significant asymmetries was also greater in males. However, effect sizes for both age effects and sex differences were small. Taken together, these findings suggest that cerebral asymmetries are an inherent organizational pattern of the brain that manifests early in life. Overall, brain asymmetry appears to be relatively stable throughout childhood and adolescence, with some differential effects in males and females.
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- Balgobind, Brian V, et al.
(författare)
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Novel prognostic subgroups in childhood 11q23/MLL-rearranged acute myeloid leukemia : results of an international retrospective study.
- 2009
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Ingår i: Blood. - : American Society of Hematology. - 0006-4971 .- 1528-0020. ; 114:12, s. 2489-2496
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Tidskriftsartikel (refereegranskat)abstract
- Translocations involving chromosome 11q23 frequently occur in pediatric acute myeloid leukemia (AML) and are associated with poor prognosis. In most cases, the MLL gene is involved, and more than 50 translocation partners have been described. Clinical outcome data of the 11q23-rearranged subgroups are scarce because most 11q23 series are too small for meaningful analysis of subgroups, although some studies suggest that patients with t(9;11)(p22;q23) have a more favorable prognosis. We retrospectively collected outcome data of 756 children with 11q23- or MLL-rearranged AML from 11 collaborative groups to identify differences in outcome based on translocation partners. All karyotypes were centrally reviewed before assigning patients to subgroups. The event-free survival of 11q23/MLL-rearranged pediatric AML at 5 years from diagnosis was 44% (+/- 5%), with large differences across subgroups (11% +/- 5% to 92% +/- 5%). Multivariate analysis identified the following subgroups as independent prognostic predictors: t(1;11)(q21;q23) (hazard ratio [HR] = 0.1, P = .004); t(6;11)(q27;q23) (HR = 2.2, P < .001); t(10;11)(p12;q23) (HR = 1.5, P = .005); and t(10;11)(p11.2;q23) (HR = 2.5, P = .005). We could not confirm the favorable prognosis of the t(9;11)(p22;q23) subgroup. We identified large differences in outcome within 11q23/MLL-rearranged pediatric AML and novel subgroups based on translocation partners that independently predict clinical outcome. Screening for these translocation partners is needed for accurate treatment stratification at diagnosis.
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