Cytogenetic analysis of 130 renal oncocytomas identify three distinct and mutually exclusive diagnostic classes of chromosome aberrations

The cytogenetic alterations in renal oncocytoma (RO) are poorly understood. We analyzed 130 consecutive RO for karyotypic alterations. Clonal chromosome abnormalities were identified in 63 (49%) cases, which could be categorized into three classes of mutually exclusive cytogenetic categories. Class 1 (N = 20) RO had diploid karyotypes with characteristic 11q13 rearrangement in balanced translocations with 10 or more different chromosome partners in all cases. We identified recurrent translocation partners at 5q35, 6p21, 9p24, 11p13-14, and 11q23, and confirmed that CCND1 gene rearrangement at 11q13 utilizing fluorescence in situ hybridization (FISH). Class 2 RO (N = 25) exhibited hypodiploid karyotypes with loss of chromosome 1 and/or losses of Y in males and X in females in all cases. The class 3 tumors comprising of 18 cases showed diverse types of abnormalities with the involvement of two or more chromosomes exclusive of abnormalities seen in classes 1 and 2 tumors. Furthermore, karyotypically uninformative cases were subjected to FISH analysis to identify classes 1 and 2 abnormalities. In this group, we found similar frequencies of CCND1 rearrangement, loss of chromosome 1 or Y as with karyotypically abnormal cases. We validated our results against 91 tumors from the Mitelman database. Correlation of clinical data with all the three classes of ROs showed no clear evidence of overall patient survival. Our findings support the hypothesis that RO exhibit three principal cytogenetic categories, which may have different roles in initiation and/or progression. These cytogenetic markers provide a key tool in the diagnostic evaluation of RO

Chromatin mapping and single-cell immune profiling define the temporal dynamics of ibrutinib response in CLL

The Bruton tyrosine kinase (BTK) inhibitor ibrutinib provides effective treatment for patients with chronic lymphocytic leukemia (CLL), despite extensive heterogeneity in this disease. To define the underlining regulatory dynamics, we analyze high-resolution time courses of ibrutinib treatment in patients with CLL, combining immune-phenotyping, single-cell transcriptome profiling, and chromatin mapping. We identify a consistent regulatory program starting with a sharp decrease of NF-kappa B binding in CLL cells, which is followed by reduced activity of lineage-defining transcription factors, erosion of CLL cell identity, and acquisition of a quiescence-like gene signature. We observe patient-to-patient variation in the speed of execution of this program, which we exploit to predict patient-specific dynamics in the response to ibrutinib based on the pre-treatment patient samples. In aggregate, our study describes time-dependent cellular, molecular, and regulatory effects for therapeutic inhibition of B cell receptor signaling in CLL, and it establishes a broadly applicable method for epigenome/transcriptome-based treatment monitoring

Nonlinear optical microscopy is a novel tool for the analysis of cutaneous alterations in pseudoxanthoma elasticum

Pseudoxanthoma elasticum (PXE, OMIM 264800) is a rare autosomal recessive disorder with ectopic mineralization and fragmentation of elastin fibers. It is caused by mutations of the ABCC6 gene that leads to decreased serum levels of inorganic pyrophosphate (PPi) anti-mineralization factor. The occurrence of severe complications among PXE patients highlights the importance of early diagnosis so that prompt multidisciplinary care can be provided to patients. We aimed to examine dermal connective tissue with nonlinear optical (NLO) techniques, as collagen emits second-harmonic generation (SHG) signal, while elastin can be excited by two-photon excitation fluorescence (TPF). We performed molecular genetic analysis, ophthalmological and cardiovascular assessment, plasma PPi measurement, conventional histopathological examination, and ex vivo SHG and TPF imaging in five patients with PXE and five age- and gender-matched healthy controls. Pathological mutations including one new variant were found in the ABCC6 gene in all PXE patients and their plasma PPi level was significantly lower compared with controls. Degradation and mineralization of elastin fibers and extensive calcium deposition in the mid-dermis was visualized and quantified together with the alterations of the collagen structure in PXE. Our data suggests that NLO provides high-resolution imaging of the specific histopathological features of PXE-affected skin. In vivo NLO may be a promising tool in the assessment of PXE, promoting early diagnosis and follow-up

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Recurrent gross mutations of the PTEN tumor suppressor gene in breast cancers with deficient DSB repair

Basal-like breast cancer (BBC) is a subtype of breast cancer with poor prognosis. Inherited mutations of BRCA1, a cancer susceptibility gene involved in double-strand DNA break (DSB) repair, lead to breast cancers that are nearly always of the BBC subtype; however, the precise molecular lesions and oncogenic consequences of BRCA1 dysfunction are poorly understood. Here we show that heterozygous inactivation of the tumor suppressor gene Pten leads to the formation of basal-like mammary tumors in mice, and that loss of PTEN expression is significantly associated with the BBC subtype in human sporadic and BRCA1-associated hereditary breast cancers. In addition, we identify frequent gross PTEN mutations, involving intragenic chromosome breaks, inversions, deletions and micro copy number aberrations, specifically in BRCA1-deficient tumors. These data provide an example of a specific and recurrent oncogenic consequence of BRCA1-dependent dysfunction in DNA repair and provide insight into the pathogenesis of BBC with therapeutic implications. These findings also argue that obtaining an accurate census of genes mutated in cancer will require a systematic examination for gross gene rearrangements, particularly in tumors with deficient DSB repair

Hub-Centered Gene Network Reconstruction Using Automatic Relevance Determination

Network inference deals with the reconstruction of biological networks from experimental data. A variety of different reverse engineering techniques are available; they differ in the underlying assumptions and mathematical models used. One common problem for all approaches stems from the complexity of the task, due to the combinatorial explosion of different network topologies for increasing network size. To handle this problem, constraints are frequently used, for example on the node degree, number of edges, or constraints on regulation functions between network components. We propose to exploit topological considerations in the inference of gene regulatory networks. Such systems are often controlled by a small number of hub genes, while most other genes have only limited influence on the network's dynamic. We model gene regulation using a Bayesian network with discrete, Boolean nodes. A hierarchical prior is employed to identify hub genes. The first layer of the prior is used to regularize weights on edges emanating from one specific node. A second prior on hyperparameters controls the magnitude of the former regularization for different nodes. The net effect is that central nodes tend to form in reconstructed networks. Network reconstruction is then performed by maximization of or sampling from the posterior distribution. We evaluate our approach on simulated and real experimental data, indicating that we can reconstruct main regulatory interactions from the data. We furthermore compare our approach to other state-of-the art methods, showing superior performance in identifying hubs. Using a large publicly available dataset of over 800 cell cycle regulated genes, we are able to identify several main hub genes. Our method may thus provide a valuable tool to identify interesting candidate genes for further study. Furthermore, the approach presented may stimulate further developments in regularization methods for network reconstruction from data