NSD2 maintains lineage plasticity and castration-resistance in neuroendocrine prostate cancer.

The clinical use of potent androgen receptor (AR) inhibitors has promoted the emergence of novel subtypes of metastatic castration-resistant prostate cancer (mCRPC), including neuroendocrine prostate cancer (CRPC-NE), which is highly aggressive and lethal 1 . These mCRPC subtypes display increased lineage plasticity and often lack AR expression 2-5 . Here we show that neuroendocrine differentiation and castration-resistance in CRPC-NE are maintained by the activity of Nuclear Receptor Binding SET Domain Protein 2 (NSD2) 6 , which catalyzes histone H3 lysine 36 dimethylation (H3K36me2). We find that organoid lines established from genetically-engineered mice 7 recapitulate key features of human CRPC-NE, and can display transdifferentiation to neuroendocrine states in culture. CRPC-NE organoids express elevated levels of NSD2 and H3K36me2 marks, but relatively low levels of H3K27me3, consistent with antagonism of EZH2 activity by H3K36me2. Human CRPC-NE but not primary NEPC tumors expresses high levels of NSD2, consistent with a key role for NSD2 in lineage plasticity, and high NSD2 expression in mCRPC correlates with poor survival outcomes. Notably, CRISPR/Cas9 targeting of NSD2 or expression of a dominant-negative oncohistone H3.3K36M mutant results in loss of neuroendocrine phenotypes and restores responsiveness to the AR inhibitor enzalutamide in mouse and human CRPC-NE organoids and grafts. Our findings indicate that NSD2 inhibition can reverse lineage plasticity and castration-resistance, and provide a potential new therapeutic target for CRPC-NE.

Automated 3D scoring of fluorescence in situ hybridization (FISH) using a confocal whole slide imaging scanner.

Fluorescence in situ hybridization (FISH) is a technique to visualize specific DNA/RNA sequences within the cell nuclei and provide the presence, location and structural integrity of genes on chromosomes. A confocal Whole Slide Imaging (WSI) scanner technology has superior depth resolution compared to wide-field fluorescence imaging. Confocal WSI has the ability to perform serial optical sections with specimen imaging, which is critical for 3D tissue reconstruction for volumetric spatial analysis. The standard clinical manual scoring for FISH is labor-intensive, time-consuming and subjective. Application of multi-gene FISH analysis alongside 3D imaging, significantly increase the level of complexity required for an accurate 3D analysis. Therefore, the purpose of this study is to establish automated 3D FISH scoring for z-stack images from confocal WSI scanner. The algorithm and the application we developed, SHIMARIS PAFQ, successfully employs 3D calculations for clear individual cell nuclei segmentation, gene signals detection and distribution of break-apart probes signal patterns, including standard break-apart, and variant patterns due to truncation, and deletion, etc. The analysis was accurate and precise when compared with ground truth clinical manual counting and scoring reported in ten lymphoma and solid tumors cases. The algorithm and the application we developed, SHIMARIS PAFQ, is objective and more efficient than the conventional procedure. It enables the automated counting of more nuclei, precisely detecting additional abnormal signal variations in nuclei patterns and analyzes gigabyte multi-layer stacking imaging data of tissue samples from patients. Currently, we are developing a deep learning algorithm for automated tumor area detection to be integrated with SHIMARIS PAFQ.

Stromal reactivity differentially drives tumour cell evolution and prostate cancer progression.

Prostate cancer (PCa) progression is a complex eco-evolutionary process driven by the feedback between evolving tumour cell phenotypes and microenvironmentally driven selection. To better understand this relationship, we used a multiscale mathematical model that integrates data from biology and pathology on the microenvironmental regulation of PCa cell behaviour. Our data indicate that the interactions between tumour cells and their environment shape the evolutionary dynamics of PCa cells and explain overall tumour aggressiveness. A key environmental determinant of this aggressiveness is the stromal ecology, which can be either inhibitory, highly reactive (supportive) or non-reactive (neutral). Our results show that stromal ecology correlates directly with tumour growth but inversely modulates tumour evolution. This suggests that aggressive, environmentally independent PCa may be a result of poor stromal ecology, supporting the concept that purely tumour epithelium-centric metrics of aggressiveness may be incomplete and that incorporating markers of stromal ecology would improve prognosis.

Variable internal flexibility characterizes the helical capsid formed by agrobacterium VirE2 protein on single-stranded DNA.

Agrobacterium is known for gene transfer to plants. In addition to a linear ssDNA oligonucleotide, Agrobacterium tumefaciens secretes an abundant ssDNA-binding effector, VirE2. In many ways VirE2 adapts the conjugation mechanism to transform the eukaryotic host. The crystal structure of VirE2 shows two compact domains joined by a flexible linker. Bound to ssDNA, VirE2 forms an ordered solenoidal shell, or capsid known as the T-complex. Here, we present a three-dimensional reconstruction of the VirE2-ssDNA complex using cryo-electron microscopy and iterative helical real-space reconstruction. High-resolution refinement was not possible due to inherent heterogeneity in the protein structure. By a combination of computational modeling, chemical modifications, mass spectroscopy, and electron paramagnetic resonance, we found that the N-terminal domain is tightly constrained by both tangential and longitudinal links, while the C terminus is weakly constrained. The quaternary structure is thus rigidly assembled while remaining locally flexible. This flexibility may be important in accommodating substrates without sequence specificity.

A unique spatial arrangement of the snRNPs within the native spliceosome emerges from in silico studies.

The spliceosome is a mega-Dalton ribonucleoprotein (RNP) assembly that processes primary RNA transcripts, producing functional mRNA. The electron microscopy structures of the native spliceosome and of several spliceosomal subcomplexes are available; however, the spatial arrangement of the latter within the native spliceosome is not known. We designed a computational procedure to efficiently fit thousands of conformers into the spliceosome envelope. Despite the low resolution limitations, we obtained only one model that complies with the available biochemical data. Our model localizes the five small nuclear RNPs (snRNPs) mostly within the large subunit of the native spliceosome, requiring only minor conformation changes. The remaining free volume presumably accommodates additional spliceosomal components. The constituents of the active core of the spliceosome are juxtaposed, forming a continuous surface deep within the large spliceosomal cavity, which provides a sheltered environment for the splicing reaction.

CAPRI targets T29-T42: proving ground for new docking procedures.

The critical assessment of protein interactions (CAPRI) experiment provides a unique opportunity for unbiased assessment of docking procedures. The recent CAPRI targets T29-T42 entailed docking of bound, unbound, and modeled structures, presenting a wide range of prediction difficulty. We submitted accurate predictions for targets T40, T41, and T42, a good prediction for T32 and acceptable predictions for T29 and T34. The accuracy of our docking results generally matched the prediction difficulty; hence, docking of modeled proteins produced less accurate results. However, there were interesting exceptions: an accurate prediction was submitted for the dimer of modeled tetratricopeptide repeat (T42) and only an acceptable prediction for the bound/unbound case T29. The ensembles of docking models produced in the scans included an acceptable or better prediction for every target. We show here that our recently developed postscan reevaluation procedure, which tests propensity and solvation measures of the whole interface and the interface core, successfully distinguished these predictions from false docking models. For enzyme-inhibitor targets, we show that the distance of the interface from the enzyme's centroid ranked high native like docking models. Also, for one case we demonstrate that docking of an ensemble of conformers produced by normal modes analysis can improve the accuracy of the prediction.

FitEM2EM--tools for low resolution study of macromolecular assembly and dynamics.

Studies of the structure and dynamics of macromolecular assemblies often involve comparison of low resolution models obtained using different techniques such as electron microscopy or atomic force microscopy. We present new computational tools for comparing (matching) and docking of low resolution structures, based on shape complementarity. The matched or docked objects are represented by three dimensional grids where the value of each grid point depends on its position with regard to the interior, surface or exterior of the object. The grids are correlated using fast Fourier transformations producing either matches of related objects or docking models depending on the details of the grid representations. The procedures incorporate thickening and smoothing of the surfaces of the objects which effectively compensates for differences in the resolution of the matched/docked objects, circumventing the need for resolution modification. The presented matching tool FitEM2EMin successfully fitted electron microscopy structures obtained at different resolutions, different conformers of the same structure and partial structures, ranking correct matches at the top in every case. The differences between the grid representations of the matched objects can be used to study conformation differences or to characterize the size and shape of substructures. The presented low-to-low docking tool FitEM2EMout ranked the expected models at the top.

The immune-body cytokine network defines a social architecture of cell interactions.

BACKGROUND: Three networks of intercellular communication can be associated with cytokine secretion; one limited to cells of the immune system (immune cells), one limited to parenchymal cells of organs and tissues (body cells), and one involving interactions between immune and body cells (immune-body interface). These cytokine connections determine the inflammatory response to injury and subsequent healing as well as the biologic consequences of the adaptive immune response to antigens. We informatically probed the cytokine database to uncover the underlying network architecture of the three networks. RESULTS: We now report that the three cytokine networks are among the densest of complex networks yet studied, and each features a characteristic profile of specific three-cell motifs. Some legitimate cytokine connections are shunned (anti-motifs). Certain immune cells can be paired by their input-output positions in a cytokine architecture tree of five tiers: macrophages (MPhi) and B cells (BC) comprise the first tier; the second tier is formed by T helper 1 (Th1) and T helper 2 (Th2) cells; the third tier includes dendritic cells (DC), mast cells (MAST), Natural Killer T cells (NK-T) and others; the fourth tier is formed by neutrophils (NEUT) and Natural Killer cells (NK); and the Cytotoxic T cell (CTL) stand alone as a fifth tier. The three-cell cytokine motif architecture of immune system cells places the immune system in a super-family that includes social networks and the World Wide Web. Body cells are less clearly stratified, although cells involved in wound healing and angiogenesis are most highly interconnected with immune cells. CONCLUSION: Cytokine network architecture creates an innate cell-communication platform that organizes the biologic outcome of antigen recognition and inflammation. Informatics sheds new light on immune-body systems organization. REVIEWERS: This article was reviewed by Neil Greenspan, Matthias von Herrath and Anne Cooke.