Explore the vast range of titles available.

Visual inspection of histopathology slides is one of the main methods used by pathologists to assess the stage, type and subtype of lung tumors. Adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are the most prevalent subtypes of lung cancer, and their distinction requires visual inspection by an experienced pathologist. In this study, we trained a deep convolutional neural network (inception v3) on whole-slide images obtained from The Cancer Genome Atlas to accurately and automatically classify them into LUAD, LUSC or normal lung tissue. The performance of our method is comparable to that of pathologists, with an average area under the curve (AUC) of 0.97. Our model was validated on independent datasets of frozen tissues, formalin-fixed paraffin-embedded tissues and biopsies. Furthermore, we trained the network to predict the ten most commonly mutated genes in LUAD. We found that six of them—STK11, EGFR, FAT1, SETBP1, KRAS and TP53—can be predicted from pathology images, with AUCs from 0.733 to 0.856 as measured on a held-out population. These findings suggest that deep-learning models can assist pathologists in the detection of cancer subtype or gene mutations. Our approach can be applied to any cancer type, and the code is available at https://github.com/ncoudray/DeepPATH . A convolutional neural network model using feature extraction and machine-learning techniques provides a tool for classification of lung cancer histopathology images and predicting mutational status of driver oncogenes

Deregulation of the BCL-2 family interaction network ensures cancer resistance to apoptosis and is a major challenge to current treatments. Cancer cells commonly evade apoptosis through upregulation of the BCL-2 anti-apoptotic proteins; however, more resistant cancers also downregulate or inactivate pro-apoptotic proteins to suppress apoptosis. Here, we find that apoptosis resistance in a diverse panel of solid and hematological malignancies is mediated by both overexpression of BCL-XL and an unprimed apoptotic state, limiting direct and indirect activation mechanisms of pro-apoptotic BAX. Both survival mechanisms can be overcome by the combination of an orally bioavailable BAX activator, BTSA1.2 with Navitoclax. The combination demonstrates synergistic efficacy in apoptosis-resistant cancer cells, xenografts, and patient-derived tumors while sparing healthy tissues. Additionally, functional assays and genomic markers are identified to predict sensitive tumors to the combination treatment. These findings advance the understanding of apoptosis resistance mechanisms and demonstrate a novel therapeutic strategy for cancer treatment. Deregulation of the BCL-2 family interactions ensures cancer resistance to apoptosis and is a major challenge to current treatments. Here the authors describe a novel therapeutic strategy to overcome two anti-apoptotic mechanisms for cancer therapy.

The bone marrow microenvironment has a key role in regulating haematopoiesis, but its molecular complexity and response to stress are incompletely understood. Here we map the transcriptional landscape of mouse bone marrow vascular, perivascular and osteoblast cell populations at single-cell resolution, both at homeostasis and under conditions of stress-induced haematopoiesis. This analysis revealed previously unappreciated levels of cellular heterogeneity within the bone marrow niche and resolved cellular sources of pro-haematopoietic growth factors, chemokines and membrane-bound ligands. Our studies demonstrate a considerable transcriptional remodelling of niche elements under stress conditions, including an adipocytic skewing of perivascular cells. Among the stress-induced changes, we observed that vascular Notch delta-like ligands (encoded by Dll1 and Dll4 ) were downregulated. In the absence of vascular Dll4 , haematopoietic stem cells prematurely induced a myeloid transcriptional program. These findings refine our understanding of the cellular architecture of the bone marrow niche, reveal a dynamic and heterogeneous molecular landscape that is highly sensitive to stress and illustrate the utility of single-cell transcriptomic data in evaluating the regulation of haematopoiesis by discrete niche populations. The transcriptional landscape of cell populations of the mouse bone marrow microenvironment, mapped at single-cell resolution, reveals cellular heterogeneity in this niche as well as substantial transcriptional remodelling under stress conditions.

Cell fate transitions are accompanied by global transcriptional, epigenetic and topological changes driven by transcription factors, as is exemplified by reprogramming somatic cells to pluripotent stem cells through the expression of OCT4, KLF4, SOX2 and cMYC. How transcription factors orchestrate the complex molecular changes around their target gene loci remains incompletely understood. Here, using KLF4 as a paradigm, we provide a transcription-factor-centric view of chromatin reorganization and its association with three-dimensional enhancer rewiring and transcriptional changes during the reprogramming of mouse embryonic fibroblasts to pluripotent stem cells. Inducible depletion of KLF factors in PSCs caused a genome-wide decrease in enhancer connectivity, whereas disruption of individual KLF4 binding sites within pluripotent-stem-cell-specific enhancers was sufficient to impair enhancer–promoter contacts and reduce the expression of associated genes. Our study provides an integrative view of the complex activities of a lineage-specifying transcription factor and offers novel insights into the nature of the molecular events that follow transcription factor binding. Di Giammartino, Kloetgen, Polyzos, Liu et al. probe chromatin organization, enhancer status and transcriptional changes and show that KLF4 acts as a transcriptional regulator and chromatin organizer during induced pluripotent stem cell reprogramming and in pluripotent stem cells.

The metazoan genome is compartmentalized in areas of highly interacting chromatin known as topologically associating domains (TADs). TADs are demarcated by boundaries mostly conserved across cell types and even across species. However, a genome-wide characterization of TAD boundary strength in mammals is still lacking. In this study, we first use fused two-dimensional lasso as a machine learning method to improve Hi-C contact matrix reproducibility, and, subsequently, we categorize TAD boundaries based on their insulation score. We demonstrate that higher TAD boundary insulation scores are associated with elevated CTCF levels and that they may differ across cell types. Intriguingly, we observe that super-enhancers are preferentially insulated by strong boundaries. Furthermore, we demonstrate that strong TAD boundaries and super-enhancer elements are frequently co-duplicated in cancer patients. Taken together, our findings suggest that super-enhancers insulated by strong TAD boundaries may be exploited, as a functional unit, by cancer cells to promote oncogenesis. Topologically associating domains (TADs) detected by Hi-C technologies are megabase-scale areas of highly interacting chromatin. Here Gong, Lazaris et al. develop a computational approach to improve the reproducibility of Hi-C contact matrices and stratify TAD boundaries based on their insulating strength.

The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDAC) is a complex ecosystem that drives tumor progression; however, in-depth single cell characterization of the PDAC TME and its role in response to therapy is lacking. Here, we perform single-cell RNA sequencing on freshly collected human PDAC samples either before or after chemotherapy. Overall, we find a heterogeneous mixture of basal and classical cancer cell subtypes, along with distinct cancer-associated fibroblast and macrophage subpopulations. Strikingly, classical and basal-like cancer cells exhibit similar transcriptional responses to chemotherapy and do not demonstrate a shift towards a basal-like transcriptional program among treated samples. We observe decreased ligand-receptor interactions in treated samples, particularly between TIGIT on CD8  + T cells and its receptor on cancer cells, and identify TIGIT as the major inhibitory checkpoint molecule of CD8  + T cells. Our results suggest that chemotherapy profoundly impacts the PDAC TME and may promote resistance to immunotherapy. The role of therapy in shaping the tumor microenvironment in pancreatic ductal adenocarcinoma (PDAC) remains to be explored. Here, the authors perform single-cell RNA sequencing in PDAC samples before and after chemotherapy and suggest that chemotherapy may promote resistance to immunotherapy.

Using Hi-C, promoter-capture Hi-C (pCHi-C), and other genome-wide approaches in skeletal muscle progenitors that inducibly express a master transcription factor, Pax7, we systematically characterize at high-resolution the spatio-temporal re-organization of compartments and promoter-anchored interactions as a consequence of myogenic commitment and differentiation. We identify key promoter-enhancer interaction motifs, namely, cliques and networks, and interactions that are dependent on Pax7 binding. Remarkably, Pax7 binds to a majority of super-enhancers, and together with a cadre of interacting transcription factors, assembles feed-forward regulatory loops. During differentiation, epigenetic memory and persistent looping are maintained at a subset of Pax7 enhancers in the absence of Pax7. We also identify and functionally validate a previously uncharacterized Pax7-bound enhancer hub that regulates the essential myosin heavy chain cluster during skeletal muscle cell differentiation. Our studies lay the groundwork for understanding the role of Pax7 in orchestrating changes in the three-dimensional chromatin conformation in muscle progenitors. Chromatin structure and topology play important roles in the regulation of gene expression. Here the authors study the spatio-temporal re-organization of promoter-enhancer interactions in pluripotent ES and skeletal muscle stem cells and the corresponding impact on gene expression as a consequence of myogenic commitment and differentiation.

Background Chromatin conformation capture techniques have evolved rapidly over the last few years and have provided new insights into genome organization at an unprecedented resolution. Analysis of Hi-C data is complex and computationally intensive involving multiple tasks and requiring robust quality assessment. This has led to the development of several tools and methods for processing Hi-C data. However, most of the existing tools do not cover all aspects of the analysis and only offer few quality assessment options. Additionally, availability of a multitude of tools makes scientists wonder how these tools and associated parameters can be optimally used, and how potential discrepancies can be interpreted and resolved. Most importantly, investigators need to be ensured that slight changes in parameters and/or methods do not affect the conclusions of their studies. Results To address these issues (compare, explore and reproduce), we introduce HiC-bench, a configurable computational platform for comprehensive and reproducible analysis of Hi-C sequencing data. HiC-bench performs all common Hi-C analysis tasks, such as alignment, filtering, contact matrix generation and normalization, identification of topological domains, scoring and annotation of specific interactions using both published tools and our own. We have also embedded various tasks that perform quality assessment and visualization. HiC-bench is implemented as a data flow platform with an emphasis on analysis reproducibility. Additionally, the user can readily perform parameter exploration and comparison of different tools in a combinatorial manner that takes into account all desired parameter settings in each pipeline task. This unique feature facilitates the design and execution of complex benchmark studies that may involve combinations of multiple tool/parameter choices in each step of the analysis. To demonstrate the usefulness of our platform, we performed a comprehensive benchmark of existing and new TAD callers exploring different matrix correction methods, parameter settings and sequencing depths. Users can extend our pipeline by adding more tools as they become available. Conclusions HiC-bench consists an easy-to-use and extensible platform for comprehensive analysis of Hi-C datasets. We expect that it will facilitate current analyses and help scientists formulate and test new hypotheses in the field of three-dimensional genome organization.

Epigenetic plasticity is a pivotal factor that drives metastasis. Here, we show that the promoter of the gene that encodes the ubiquitin ligase subunit FBXL7 is hypermethylated in advanced prostate and pancreatic cancers, correlating with decreased FBXL7 mRNA and protein levels. Low FBXL7 mRNA levels are predictive of poor survival in patients with pancreatic and prostatic cancers. FBXL7 mediates the ubiquitylation and proteasomal degradation of active c-SRC after its phosphorylation at Ser 104. The DNA-demethylating agent decitabine recovers FBXL7 expression and limits epithelial-to-mesenchymal transition and cell invasion in a c-SRC-dependent manner. In vivo, FBXL7-depleted cancer cells form tumours with a high metastatic burden. Silencing of c-SRC or treatment with the c-SRC inhibitor dasatinib together with FBXL7 depletion prevents metastases. Furthermore, decitabine reduces metastases derived from prostate and pancreatic cancer cells in a FBXL7-dependent manner. Collectively, this research implicates FBXL7 as a metastasis-suppressor gene and suggests therapeutic strategies to counteract metastatic dissemination of pancreatic and prostatic cancer cells.Moro et al. show that hypermethylation-induced silencing of the ubiquitin ligase FBXL7 rescues c-SRC from ubiquitin-mediated degradation and enhances epithelial-to-mesenchymal transition and metastasis.

Regulatory T (T reg ) cells accumulate into tumors, hindering the success of cancer immunotherapy. Yet, therapeutic targeting of T reg cells shows limited efficacy or leads to autoimmunity. The molecular mechanisms that guide T reg cell stability in tumors remain elusive. In the present study, we identify a cell-intrinsic role of the alarmin interleukin (IL)-33 in the functional stability of T reg cells. Specifically, IL-33-deficient T reg cells demonstrated attenuated suppressive properties in vivo and facilitated tumor regression in a suppression of tumorigenicity 2 receptor (ST2) (IL-33 receptor)-independent fashion. On activation, Il33 −/− T reg cells exhibited epigenetic re-programming with increased chromatin accessibility of the Ifng locus, leading to elevated interferon (IFN)-γ production in a nuclear factor (NF)-κB–T-bet-dependent manner. IFN-γ was essential for T reg cell defective function because its ablation restored Il33 −/− T reg cell-suppressive properties. Importantly, genetic ablation of Il33 potentiated the therapeutic effect of immunotherapy. Our findings reveal a new and therapeutically important intrinsic role of IL-33 in T reg cell stability in cancer. IL-33, an IL-1 family member, plays dual roles as an intracellular transcription factor and as an extracellular alarmin of tissue damage. Verginis and colleagues identify a cell-intrinsic role for nuclear IL-33 stabilizing T reg cell suppressor function in tumor environments.