Clash of Titans: A MUSE dynamical study of the extreme cluster merger SPT-CL J0307-6225

We present MUSE spectroscopy, Megacam imaging, and Chandra X-ray emission for SPT-CL J0307-6225, a z = 0.58 major merging galaxy cluster with a large BCG-SZ centroid separation and a highly disturbed X-ray morphology. The galaxy density distribution shows two main overdensities with separations of 0.144 and 0.017 arcmin to their respective BCGs. We characterize the central regions of the two colliding structures, namely 0307-6225N and 0307-6225S, finding velocity derived masses of M200, N = 2.44 ± 1.41 × 1014M⊙ and M200, S = 3.16 ± 1.88 × 1014M⊙, with a line-of-sight velocity difference of |Δv| = 342 km s-1. The total dynamically derived mass is consistent with the SZ derived mass of 7.63 h70-1 ± 1.36 × 1014M⊙. We model the merger using the Monte Carlo Merger Analysis Code, estimating a merging angle of 36+14-12 ° with respect to the plane of the sky. Comparing with simulations of a merging system with a mass ratio of 1:3, we find that the best scenario is that of an ongoing merger that began 0.96+0.31-0.18 Gyr ago. We also characterize the galaxy population using Hδand [O ii] λ3727 Å lines. We find that most of the emission-line galaxies belong to 0307-6225S, close to the X-ray peak position with a third of them corresponding to red-cluster sequence galaxies, and the rest to blue galaxies with velocities consistent with recent periods of accretion. Moreover, we suggest that 0307-6225S suffered a previous merger, evidenced through the two equally bright BCGs at the centre with a velocity difference of ∼674 km s-1

Correlation of IDH1 Mutation with Clinicopathologic Factors and Prognosis in Primary Glioblastoma: A Report of 118 Patients from China

It has been reported that IDH1 (IDH1R132) mutation was a frequent genomic alteration in grade II and grade III glial tumors but rare in primary glioblastoma (pGBM). To elucidate the frequency of IDH1 mutation and its clinical significance in Chinese patients with pGBM, one hundred eighteen pGBMs were assessed by pyro-sequencing for IDH1 mutation status, and the results were correlated with clinical characteristics and molecular pathological factors. IDH1 mutations were detected in 19/118 pGBM cases (16.1%). Younger age, methylated MGMT promoter, high expression of mutant P53 protein, low expression of Ki-67 or EGFR protein were significantly correlated with IDH1 mutation status. Most notably, we identified pGBM cases with IDH1 mutation were mainly involved in the frontal lobe when compared with those with wild-type IDH1. In addition, Kaplan-Meier survival analysis revealed a highly significant association between IDH1 mutation and a better clinical outcome (p = 0.026 for progression-free survival; p = 0.029 for overall survival). However, in our further multivariable regression analysis, the independent prognostic effect of IDH1 mutation is limited when considering age, preoperative KPS score, extent of resection, TMZ chemotherapy, and Ki-67 protein expression levels, which might narrow its prognostic power in Chinese population in the future

Genomic deletion and promoter methylation status of Hypermethylated in Cancer 1 (HIC1) in mantle cell lymphoma

Mantle cell lymphomas (MCL), characterized by the t(11;14)(q13;q32), frequently carry secondary genetic alterations such as deletions in chromosome 17p involving the TP53 locus. Given that the association between TP53-deletions and concurrent mutations of the remaining allele is weak and based on our recent report that the Hypermethylated in Cancer 1 (HIC1) gene, that is located telomeric to the TP53 gene, may be targeted by deletions in 17p in diffuse large B-cell lymphoma (DLBCL), we investigated whether HIC1 inactivations might also occur in MCL. Monoallelic deletions of the TP53 locus were detected in 18 out of 59 MCL (31%), while overexpression of p53 protein occurred in only 8 out of 18 of these MCL (44%). In TP53-deleted MCL, the HIC1 gene locus was co-deleted in 11 out of 18 cases (61%). However, neither TP53 nor HIC1 deletions did affect survival of MCL patients. In most analyzed cases, no hypermethylation of the HIC1 exon 1A promoter was observed (17 out of 20, 85%). However, in MCL cell lines without HIC1-hypermethylation, the mRNA expression levels of HIC1 were nevertheless significantly reduced, when compared to reactive lymph node specimens, pointing to the occurrence of mechanisms other than epigenetic or genetic events for the inactivation of HIC1 in this entity

Explorative data analysis of MCL reveals gene expression networks implicated in survival and prognosis supported by explorative CGH analysis

<p>Abstract</p> <p>Background</p> <p>Mantle cell lymphoma (MCL) is an incurable B cell lymphoma and accounts for 6% of all non-Hodgkin's lymphomas. On the genetic level, MCL is characterized by the hallmark translocation t(11;14) that is present in most cases with few exceptions. Both gene expression and comparative genomic hybridization (CGH) data vary considerably between patients with implications for their prognosis.</p> <p>Methods</p> <p>We compare patients over and below the median of survival. Exploratory principal component analysis of gene expression data showed that the second principal component correlates well with patient survival. Explorative analysis of CGH data shows the same correlation.</p> <p>Results</p> <p>On chromosome 7 and 9 specific genes and bands are delineated which improve prognosis prediction independent of the previously described proliferation signature. We identify a compact survival predictor of seven genes for MCL patients. After extensive re-annotation using GEPAT, we established protein networks correlating with prognosis. Well known genes (CDC2, CCND1) and further proliferation markers (WEE1, CDC25, aurora kinases, BUB1, PCNA, E2F1) form a tight interaction network, but also non-proliferative genes (SOCS1, TUBA1B CEBPB) are shown to be associated with prognosis. Furthermore we show that aggressive MCL implicates a gene network shift to higher expressed genes in late cell cycle states and refine the set of non-proliferative genes implicated with bad prognosis in MCL.</p> <p>Conclusion</p> <p>The results from explorative data analysis of gene expression and CGH data are complementary to each other. Including further tests such as Wilcoxon rank test we point both to proliferative and non-proliferative gene networks implicated in inferior prognosis of MCL and identify suitable markers both in gene expression and CGH data.</p

Ki-67 as a prognostic marker in mantle cell lymphoma—consensus guidelines of the pathology panel of the European MCL Network

Mantle cell lymphoma (MCL) has a heterogeneous clinical course and is mainly an aggressive B cell non-Hodgkin lymphoma; however, there are some indolent cases The Ki-67 index, defined by the percentage of Ki-67-positive lymphoma cells on histopathological slides, has been shown to be a very powerful prognostic biomarker. The pathology panel of the European MCL Network evaluated methods to assess the Ki-67 index including stringent counting, digital image analysis, and estimation by eyeballing. Counting of 2 × 500 lymphoma cells is the gold standard to assess the Ki-67 index since this value has been shown to predict survival in prospective randomized trials of the European MCL Network. Estimation by eyeballing and digital image analysis showed a poor concordance with the gold standard (concordance correlation coefficients [CCC] between 0.29 and 0.61 for eyeballing and CCC of 0.24 and 0.37 for two methods of digital image analysis, respectively). Counting a reduced number of lymphoma cells (2 × 100 cells) showed high interobserver agreement (CCC = 0.74). Pitfalls of the Ki-67 index are discussed and guidelines and recommendations for assessing the Ki-67 index in MCL are given

A cytomorphological and immunohistochemical profile of aggressive B-cell lymphoma: high clinical impact of a cumulative immunohistochemical outcome predictor score

We analyzed morphological and immunohistochemical features in 174 aggressive B-cell lymphomas of nodal and extranodal origin. Morphological features included presence or absence of a follicular component and cytologic criteria according to the Kiel classification, whereas immunohistochemical studies included expression of CD10, BCL-2, BCL-6, IRF4/MUM1, HLA-DR, p53, Ki-67 and the assessment of plasmacytoid differentiation. Patients were treated with a CHOP-like regimen. While the presence or absence of either CD10, BCL-6 and IRF4/MUM1 reactivity or plasmacytoid differentiation did not identify particular cytomorphologic or site-specific subtypes, we found that expression of CD10 and BCL-6, and a low reactivity for IRF4/MUM1 were favourable prognostic indicators. In contrast, BCL-2 expression and presence of a monotypic cytoplasmic immunoglobulin expression was associated with an unfavourable prognosis in univariate analyses. Meta-analysis of these data resulted in the development of a cumulative immunohistochemical outcome predictor score (CIOPS) enabling the recognition of four distinct prognostic groups. Multivariate analysis proved this score to be independent of the international prognostic index. Such a cumulative immunohistochemical scoring approach might provide a valuable alternative in the recognition of defined risk types of aggressive B-cell lymphomas

Swimming with Predators and Pesticides: How Environmental Stressors Affect the Thermal Physiology of Tadpoles

To forecast biological responses to changing environments, we need to understand how a species’s physiology varies through space and time and assess how changes in physiological function due to environmental changes may interact with phenotypic changes caused by other types of environmental variation. Amphibian larvae are well known for expressing environmentally induced phenotypes, but relatively little is known about how these responses might interact with changing temperatures and their thermal physiology. To address this question, we studied the thermal physiology of grey treefrog tadpoles (Hyla versicolor) by determining whether exposures to predator cues and an herbicide (Roundup) can alter their critical maximum temperature (CTmax) and their swimming speed across a range of temperatures, which provides estimates of optimal temperature (Topt) for swimming speed and the shape of the thermal performance curve (TPC). We discovered that predator cues induced a 0.4uC higher CTmax value, whereas the herbicide had no effect. Tadpoles exposed to predator cues or the herbicide swam faster than control tadpoles and the increase in burst speed was higher near Topt. In regard to the shape of the TPC, exposure to predator cues increased Topt by 1.5uC, while exposure to the herbicide marginally lowered Topt by 0.4uC. Combining predator cues and the herbicide produced an intermediate Topt that was 0.5uC higher than the control. To our knowledge this is the first study to demonstrate a predator altering the thermal physiology of amphibian larvae (prey) by increasing CTmax, increasing the optimum temperature, and producing changes in the thermal performance curves. Furthermore, these plastic responses of CTmax and TPC to different inducing environments should be considered when forecasting biological responses to global warming.Peer reviewe

A joint SZ-X-ray-optical analysis of the dynamical state of 288 massive galaxy clusters

We use imaging from the first three years of the Dark Energy Survey to characterize the dynamical state of 288 galaxy clusters at $0.1 \lesssim z \lesssim 0.9$ detected in the South Pole Telescope (SPT) Sunyaev-Zeldovich (SZ) effect survey (SPT-SZ). We examine spatial offsets between the position of the brightest cluster galaxy (BCG) and the center of the gas distribution as traced by the SPT-SZ centroid and by the X-ray centroid/peak position from Chandra and XMM data. We show that the radial distribution of offsets provides no evidence that SPT SZ-selected cluster samples include a higher fraction of mergers than X-ray-selected cluster samples. We use the offsets to classify the dynamical state of the clusters, selecting the 43 most disturbed clusters, with half of those at $z \gtrsim 0.5$, a region seldom explored previously. We find that Schechter function fits to the galaxy population in disturbed clusters and relaxed clusters differ at $z>0.55$ but not at lower redshifts. Disturbed clusters at $z>0.55$ have steeper faint-end slopes and brighter characteristic magnitudes. Within the same redshift range, we find that the BCGs in relaxed clusters tend to be brighter than the BCGs in disturbed samples, while in agreement in the lower redshift bin. Possible explanations includes a higher merger rate, and a more efficient dynamical friction at high redshift. The red-sequence population is less affected by the cluster dynamical state than the general galaxy population.Comment: 21 pages, 12 Figures, 4 Tables. Accepted for publication in MNRA

Refinement of 1p36 Alterations Not Involving PRDM16 in Myeloid and Lymphoid Malignancies

Fluorescence in situ hybridization was performed to characterize 81 cases of myeloid and lymphoid malignancies with cytogenetic 1p36 alterations not affecting the PRDM16 locus. In total, three subgroups were identified: balanced translocations (N = 27) and telomeric rearrangements (N = 15), both mainly observed in myeloid disorders; and unbalanced non-telomeric rearrangements (N = 39), mainly observed in lymphoid proliferations and frequently associated with a highly complex karyotype. The 1p36 rearrangement was isolated in 12 cases, mainly myeloid disorders. The breakpoints on 1p36 were more widely distributed than previously reported, but with identifiable rare breakpoint cluster regions, such as the TP73 locus. We also found novel partner loci on 1p36 for the known multi-partner genes HMGA2 and RUNX1. We precised the common terminal 1p36 deletion, which has been suggested to have an adverse prognosis, in B-cell lymphomas [follicular lymphomas and diffuse large B-cell lymphomas with t(14;18)(q32;q21) as well as follicular lymphomas without t(14;18)]. Intrachromosomal telomeric repetitive sequences were detected in at least half the cases of telomeric rearrangements. It is unclear how the latter rearrangements occurred and whether they represent oncogenic events or result from chromosomal instability during oncogenesis