8 research outputs found
HRAS-mutated Spitz tumors: A subtype of Spitz tumors with distinct features.
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88443.pdf (Publisher’s version ) (Open Access)It is often very difficult to confidently distinguish benign and malignant Spitz lesions, and a diagnosis of Spitz tumor of unknown malignant potential (STUMP) is rendered. To address this problem, we performed molecular genetic analysis in a large group of Spitz tumors (93 Spitz nevi and 77 STUMPs) and identified a subgroup of 24 lesions harboring a HRAS mutation. This subgroup lay predominantly in the dermis, had a relatively low cellularity, showed desmoplasia (with single cells interspersed between the collagen bundles), and had an infiltrating base. In 7 of these 24 cases (29%) melanoma had been the initial diagnosis, or an important differential diagnostic consideration, mainly based on the presence of multiple or deeply located mitotic figures, especially in adult patients. In our series none of the patients with the HRAS-mutated lesions developed recurrences or metastases (mean and median follow-up: 10.5 y). This was in accordance with the literature: review showed that no HRAS mutations had so far been reported in Spitzoid melanomas. We therefore conclude that HRAS mutation analysis may be a useful diagnostic tool to help differentiate between Spitz nevus and Spitzoid melanoma, thereby reducing the frequency of overdiagnosis of melanoma, and to help predict the biological behavior of a STUMP. Moreover, this might be a first step toward a more reproducible classification of Spitz tumors combining histological and genetic data.01 oktober 201
Uromodulin in Renal Transplant Recipients: Elevated Urinary Levels and Bimodal Association with Graft Failure
No full textBackground: Urinary uromodulin (UMOD) predicts renal prognosis in native kidneys, but data are conflicting. We investigated its prognostic impact for graft failure (GF) in renal transplant recipients (RTR; n = 600). Methods: UMOD concentration was measured cross-sectionally in RTR at 6.0 years [2.6-11.4] post-transplant, in matched patients with native chronic kidney disease (CKD) and healthy subjects. In 59 cases, RTR allograft biopsies were reviewed. Results: During a follow-up of 5.3 years [4.5-5.7], GF had occurred in 7% of RTR. Median UMOD excretion (mg/24 h) was 20.4 in RTR, 11.6 in CKD and 5.7 in controls (p <0.001). There was a curvilinear association between UMOD excretion and baseline renal function (p <0.003) and death-censored GF, with 5.5, 11.5 and 4.0% of the cases in subsequent UMOD excretion tertiles, respectively (p = 0.002). On multivariate Cox regression analysis, hazard ratios for GF for the 1st and 3rd tertiles were 0.37 (p = 0.01) and 0.21 (p = 0.001), respectively. Interstitial fibrosis and tubular atrophy were more severe in the middle tertile (p = 0.007). Conclusions: Urinary UMOD is elevated in RTR and associated with graft function, morphology and doutcome in a bimodal fashion. Dissection of the disparate mechanisms of GF prediction by urinary UMOD might provide new clues for its alleged pathogenetic significance in progressive renal function loss. Copyright (C) 2011 S. Karger AG, Base
Type I collagen expression contributes to angiogenesis and the development of deeply invasive cutaneous melanoma
No full textCorrection: Circulating alpha-klotho levels are not disturbed in patients with type 2 diabetes with and without macrovascular disease in the absence of nephropathy
No full textNovel insights in localization and expression levels of C5aR and C5L2 under native and post-transplant conditions in the kidney
No full text<p>Aims: The complement system, and especially C5a, plays an important role in the pathophysiology of renal diseases and post-transplant renal injury. The two receptors for C5a are C5a receptor (C5aR) and C5a-like-receptor-2 (C5L2). Only renal C5aR expression has been reported, although exact localization and alterations in expression after transplantation are unknown.</p><p>Materials and results: Renal C5aR and C5L2 expression and localization were analyzed immunohistochemically. C5aR and C5L2 expression was analyzed in human kidney biopsies obtained from living donors and patients suffering from acute tubular necrosis, acute cellular and vascular rejection or IF/TA.</p><p>C5aR was expressed in the thick ascending limb of Henle's loop and first part of the distal convoluted tubule (DCT). Under inflammatory conditions. C5aR was de novo expressed in proximal tubuli. C5L2 was expressed in the kidney and localized to DCT1, DCT2 and connecting tubule. Persistent distal tubular expression of both receptors was demonstrated after renal transplantation.</p><p>Conclusions: This study shows distinct renal expression patterns for C5aR and C5L2. Our findings suggest a functional role for renal C5L2 rather than being a C5a decoy receptor. Future studies focusing on renal C5a-C5aR interaction should take differential C5aR and C5L2 expression into account, alongside abundant C5aR expression on infiltrating cells. (c) 2012 Elsevier Ltd. All rights reserved.</p>
Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer
No full textIMPORTANCE: Application of deep learning algorithms to whole-slide pathology imagescan potentially improve diagnostic accuracy and efficiency. OBJECTIVE: Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin-stained tissue sections of lymph nodes of women with breast cancer and compare it with pathologists' diagnoses in a diagnostic setting. DESIGN, SETTING, AND PARTICIPANTS: Researcher challenge competition (CAMELYON16) to develop automated solutions for detecting lymph node metastases (November 2015-November 2016). A training data set of whole-slide images from 2 centers in the Netherlands with (n = 110) and without (n = 160) nodal metastases verified by immunohistochemical staining were provided to challenge participants to build algorithms. Algorithm performance was evaluated in an independent test set of 129 whole-slide images (49 with and 80 without metastases). The same test set of corresponding glass slides was also evaluated by a panel of 11 pathologists with time constraint (WTC) from the Netherlands to ascertain likelihood of nodal metastases for each slide in a flexible 2-hour session, simulating routine pathology workflow, and by 1 pathologist without time constraint (WOTC). EXPOSURES: Deep learning algorithms submitted as part of a challenge competition or pathologist interpretation. MAIN OUTCOMES AND MEASURES: The presence of specific metastatic foci and the absence vs presence of lymph node metastasis in a slide or image using receiver operating characteristic curve analysis. The 11 pathologists participating in the simulation exercise rated their diagnostic confidence as definitely normal, probably normal, equivocal, probably tumor, or definitely tumor. RESULTS: The area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.556 to 0.994. The top-performing algorithm achieved a lesion-level, true-positive fraction comparable with that of the pathologist WOTC (72.4% [95% CI, 64.3%-80.4%]) at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task, the best algorithm (AUC, 0.994 [95% CI, 0.983-0.999]) performed significantly better than the pathologists WTC in a diagnostic simulation (mean AUC, 0.810 [range, 0.738-0.884]; P <.001). The top 5 algorithms had a mean AUC that was comparable with the pathologist interpreting the slides in the absence of time constraints (mean AUC, 0.960 [range, 0.923-0.994] for the top 5 algorithms vs 0.966 [95% CI, 0.927-0.998] for the pathologist WOTC). CONCLUSIONS AND RELEVANCE: In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting
Tubular epithelial syndecan-1 maintains renal function in murine ischemia/reperfusion and human transplantation
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110067.pdf (Publisher’s version ) (Closed access)Syndecan-1, a heparan sulfate proteoglycan, has an important role in wound healing by binding several growth factors and cytokines. As these processes are also crucial in damage and repair after renal transplantation, we examined syndecan-1 expression in human control kidney tissue, renal allograft protocol biopsies, renal allograft biopsies taken at indication, and non-transplant interstitial fibrosis. Syndecan-1 expression was increased in tubular epithelial cells in renal allograft biopsies compared with control. Increased epithelial syndecan-1 in allografts correlated with low proteinuria and serum creatinine, less interstitial inflammation, less tubular atrophy, and prolonged allograft survival. Knockdown of syndecan-1 in human tubular epithelial cells in vitro reduced cell proliferation. Selective binding of growth factors suggests that syndecan-1 may promote epithelial restoration. Bilateral renal ischemia/reperfusion in syndecan-1-deficient mice resulted in increased initial renal failure and tubular injury compared with wild-type mice. Macrophage and myofibroblast numbers, tubular damage, and plasma urea levels were increased, and tubular proliferation reduced in the kidneys of syndecan-1 deficient compared with wild-type mice 14 days following injury. Hence syndecan-1 promotes tubular survival and repair in murine ischemia/reperfusion injury and correlates with functional improvement in human renal allograft transplantation.01 april 201
Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer
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181251.pdf (Publisher’s version ) (Open Access
