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Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes.
Background
Acute graft-versus-host disease (aGVHD) poses a major limitation for broader therapeutic application of allogeneic hematopoietic cell transplantation (allo-HCT). Early diagnosis of aGVHD remains difficult and is based on clinical symptoms and histopathological evaluation of tissue biopsies. Thus, current aGVHD diagnosis is limited to patients with established disease manifestation. Therefore, for improved disease prevention it is important to develop predictive assays to identify patients at risk of developing aGVHD. Here we address whether insights into the timing of the aGVHD initiation and effector phases could allow for the detection of migrating alloreactive T cells before clinical aGVHD onset to permit for efficient therapeutic intervention.
Methods
Murine major histocompatibility complex (MHC) mismatched and minor histocompatibility antigen (miHAg) mismatched allo-HCT models were employed to assess the spatiotemporal distribution of donor T cells with flow cytometry and in vivo bioluminescence imaging (BLI). Daily flow cytometry analysis of peripheral blood mononuclear cells allowed us to identify migrating alloreactive T cells based on homing receptor expression profiles.
Results
We identified a time period of 2 weeks of massive alloreactive donor T cell migration in the blood after miHAg mismatch allo-HCT before clinical aGVHD symptoms appeared. Alloreactive T cells upregulated α4β7 integrin and P-selectin ligand during this migration phase. Consequently, targeted preemptive treatment with rapamycin, starting at the earliest detection time of alloreactive donor T cells in the peripheral blood, prevented lethal aGVHD.
Conclusions
Based on this data we propose a critical time frame prior to the onset of aGVHD symptoms to identify alloreactive T cells in the peripheral blood for timely and effective therapeutic intervention.
Background: Multiple myeloma (MM) is a B-cell malignancy, where malignant plasma cells clonally expand in the bone marrow of older people, causing significant morbidity and mortality. Typical clinical symptoms include increased serum calcium levels, renal insufficiency, anemia, and bone lesions. With standard therapies, MM remains incurable; therefore, the development of new drugs or immune cell-based therapies is desirable. To advance the goal of finding a more effective treatment for MM, we aimed to develop a reliable preclinical MM mouse model applying sensitive and reproducible methods for monitoring of tumor growth and metastasis in response to therapy. Material and Methods: A mouse model was created by intravenously injecting bone marrow-homing mouse myeloma cells (MOPC-315.BM) that expressed luciferase into BALB/c wild type mice. The luciferase in the myeloma cells allowed in vivo tracking before and after melphalan treatment with bioluminescence imaging (BLI). Homing of MOPC-315.BM luciferase+ myeloma cells to specific tissues was examined by flow cytometry. Idiotype-specific myeloma protein serum levels were measured by ELISA. In vivo measurements were validated with histopathology. Results: Strong bone marrow tropism and subsequent dissemination of MOPC-315.BM luciferase+ cells in vivo closely mimicked the human disease. In vivo BLI and later histopathological analysis revealed that 12 days of melphalan treatment slowed tumor progression and reduced MM dissemination compared to untreated controls. MOPC-315.BM luciferase+ cells expressed CXCR4 and high levels of CD44 and a4b1 in vitro which could explain the strong bone marrow tropism. The results showed that MOPC-315.BM cells dynamically regulated homing receptor expression and depended on interactions with surrounding cells. Conclusions: This study described a novel MM mouse model that facilitated convenient, reliable, and sensitive tracking of myeloma cells with whole body BLI in living animals. This model is highly suitable for monitoring the effects of different treatment regimens.
Background
Deep brain stimulation (DBS) is an effective evidence‐based therapy for dystonia. However, no unequivocal predictors of therapy responses exist. We investigated whether patients optimally responding to DBS present distinct brain network organization and structural patterns.
Methods
From a German multicenter cohort of 82 dystonia patients with segmental and generalized dystonia who received DBS implantation in the globus pallidus internus, we classified patients based on the clinical response 3 years after DBS. Patients were assigned to the superior‐outcome group or moderate‐outcome group, depending on whether they had above or below 70% motor improvement, respectively. Fifty‐one patients met MRI‐quality and treatment response requirements (mean age, 51.3 ± 13.2 years; 25 female) and were included in further analysis. From preoperative MRI we assessed cortical thickness and structural covariance, which were then fed into network analysis using graph theory. We designed a support vector machine to classify subjects for the clinical response based on individual gray‐matter fingerprints.
Results
The moderate‐outcome group showed cortical atrophy mainly in the sensorimotor and visuomotor areas and disturbed network topology in these regions. The structural integrity of the cortical mantle explained about 45% of the DBS stimulation amplitude for optimal response in individual subjects. Classification analyses achieved up to 88% of accuracy using individual gray‐matter atrophy patterns to predict DBS outcomes.
Conclusions
The analysis of cortical integrity, informed by group‐level network properties, could be developed into independent predictors to identify dystonia patients who benefit from DBS.
Acute graft-versus-host disease (aGvHD) is a severe and often life-threatening complication of allogeneic hematopoietic cell transplantation (allo-HCT). AGvHD is mediated by alloreactive donor T-cells targeting predominantly the gastrointestinal tract, liver, and skin. Recent work in mice and patients undergoing allo-HCT showed that alloreactive T-cells can be identified by the expression of α4β7 integrin on T-cells even before manifestation of an aGvHD. Here, we investigated whether the detection of a combination of the expression of T-cell surface markers on peripheral blood (PB) CD8\(^+\) T-cells would improve the ability to predict aGvHD. To this end, we employed two independent preclinical models of minor histocompatibility antigen mismatched allo-HCT following myeloablative conditioning. Expression profiles of integrins, selectins, chemokine receptors, and activation markers of PB donor T-cells were measured with multiparameter flow cytometry at multiple time points before the onset of clinical aGvHD symptoms. In both allo-HCT models, we demonstrated a significant upregulation of α4β7 integrin, CD162E, CD162P, and conversely, a downregulation of CD62L on donor T-cells, which could be correlated with the development of aGvHD. Other surface markers, such as CD25, CD69, and CC-chemokine receptors were not found to be predictive markers. Based on these preclinical data from mouse models, we propose a surface marker panel on peripheral blood T-cells after allo-HCT combining α4β7 integrin with CD62L, CD162E, and CD162P (cutaneous lymphocyte antigens, CLA, in humans) to identify patients at risk for developing aGvHD early after allo-HCT.