Dickkopf-related protein 1 (Dkk1) regulates the accumulation and function of myeloid derived suppressor cells in cancer

Tumor–stroma interactions contribute to tumorigenesis. Tumor cells can educate the stroma at primary and distant sites to facilitate the recruitment of heterogeneous populations of immature myeloid cells, known as myeloid-derived suppressor cells (MDSCs). MDSCs suppress T cell responses and promote tumor proliferation. One outstanding question is how the local and distant stroma modulate MDSCs during tumor progression. Down-regulation of β-catenin is critical for MDSC accumulation and immune suppressive functions in mice and humans. Here, we demonstrate that stroma-derived Dickkopf-1 (Dkk1) targets β-catenin in MDSCs, thus exerting immune suppressive effects during tumor progression. Mice bearing extraskeletal tumors show significantly elevated levels of Dkk1 in bone microenvironment relative to tumor site. Strikingly, Dkk1 neutralization decreases tumor growth and MDSC numbers by rescuing β-catenin in these cells and restores T cell recruitment at the tumor site. Recombinant Dkk1 suppresses β-catenin target genes in MDSCs from mice and humans and anti-Dkk1 loses its antitumor effects in mice lacking β-catenin in myeloid cells or after depletion of MDSCs, demonstrating that Dkk1 directly targets MDSCs. Furthermore, we find a correlation between CD15(+) myeloid cells and Dkk1 in pancreatic cancer patients. We establish a novel immunomodulatory role for Dkk1 in regulating tumor-induced immune suppression via targeting β-catenin in MDSCs

WordCloud: a Cytoscape plugin to create a visual semantic summary of networks

<p>Abstract</p> <p>Background</p> <p>When biological networks are studied, it is common to look for clusters, i.e. sets of nodes that are highly inter-connected. To understand the biological meaning of a cluster, the user usually has to sift through many textual annotations that are associated with biological entities.</p> <p>Findings</p> <p>The WordCloud Cytoscape plugin generates a visual summary of these annotations by displaying them as a tag cloud, where more frequent words are displayed using a larger font size. Word co-occurrence in a phrase can be visualized by arranging words in clusters or as a network.</p> <p>Conclusions</p> <p>WordCloud provides a concise visual summary of annotations which is helpful for network analysis and interpretation. WordCloud is freely available at <url>http://baderlab.org/Software/WordCloudPlugin</url></p

Tumour invasiveness, the local and systemic environment and the basis of staging systems in colorectal cancer

background: The present study aimed to examine the relationship between tumour invasiveness (T stage), the local and systemic environment and cancer-specific survival (CSS) of patients with primary operable colorectal cancer. methods: The tumour microenvironment was examined using measures of the inflammatory infiltrate (Klintrup-Makinen (KM) grade and Immunoscore), tumour stroma percentage (TSP) and tumour budding. The systemic inflammatory environment was examined using modified Glasgow Prognostic Score (mGPS) and neutrophil:lymphocyte ratio (NLR). A 5-year CSS was examined. results: A total of 331 patients were included. Increasing T stage was associated with colonic primary, N stage, poor differentiation, margin involvement and venous invasion (P&lt;0.05). T stage was significantly associated with KM grade (P=0.001), Immunoscore (P=0.016), TSP (P=0.006), tumour budding (P&lt;0.001), and elevated mGPS and NLR (both P&lt;0.05). In patients with T3 cancer, N stage stratified survival from 88 to 64%, whereas Immunoscore and budding stratified survival from 100 to 70% and from 91 to 56%, respectively. The Glasgow Microenvironment Score, a score based on KM grade and TSP, stratified survival from 93 to 58%. conclusions: Although associated with increasing T stage, local and systemic tumour environment characteristics, and in particular Immunoscore, budding, TSP and mGPS, are stage-independent determinants of survival and may be utilised in the staging of patients with primary operable colorectal cancer

Lactate signalling regulates fungal β-glucan masking and immune evasion

AJPB: This work was supported by the European Research Council (STRIFE, ERC- 2009-AdG-249793), The UK Medical Research Council (MR/M026663/1), the UK Biotechnology and Biological Research Council (BB/K017365/1), the Wellcome Trust (080088; 097377). ERB: This work was supported by the UK Biotechnology and Biological Research Council (BB/M014525/1). GMA: Supported by the CNPq-Brazil (Science without Borders fellowship 202976/2014-9). GDB: Wellcome Trust (102705). CAM: This work was supported by the UK Medical Research Council (G0400284). DMM: This work was supported by UK National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC/K000306/1). NARG/JW: Wellcome Trust (086827, 075470,101873) and Wellcome Trust Strategic Award in Medical Mycology and Fungal Immunology (097377). ALL: This work was supported by the MRC Centre for Medical Mycology and the University of Aberdeen (MR/N006364/1).Peer reviewedPostprin

Tumor innate immunity primed by specific interferon-stimulated endogenous retroviruses.

Mesenchymal tumor subpopulations secrete pro-tumorigenic cytokines and promote treatment resistance1-4. This phenomenon has been implicated in chemorefractory small cell lung cancer and resistance to targeted therapies5-8, but remains incompletely defined. Here, we identify a subclass of endogenous retroviruses (ERVs) that engages innate immune signaling in these cells. Stimulated 3 prime antisense retroviral coding sequences (SPARCS) are oriented inversely in 3' untranslated regions of specific genes enriched for regulation by STAT1 and EZH2. Derepression of these loci results in double-stranded RNA generation following IFN-γ exposure due to bi-directional transcription from the STAT1-activated gene promoter and the 5' long terminal repeat of the antisense ERV. Engagement of MAVS and STING activates downstream TBK1, IRF3, and STAT1 signaling, sustaining a positive feedback loop. SPARCS induction in human tumors is tightly associated with major histocompatibility complex class 1 expression, mesenchymal markers, and downregulation of chromatin modifying enzymes, including EZH2. Analysis of cell lines with high inducible SPARCS expression reveals strong association with an AXL/MET-positive mesenchymal cell state. While SPARCS-high tumors are immune infiltrated, they also exhibit multiple features of an immune-suppressed microenviroment. Together, these data unveil a subclass of ERVs whose derepression triggers pathologic innate immune signaling in cancer, with important implications for cancer immunotherapy

Tumor immunosurveillance in human cancers

Until now, the anatomic extent of tumor (TNM classification) has been by far the most important factor to predict the prognosis of colorectal cancer patients. However, in recent years, data collected from large cohorts of human cancers demonstrated that the immune contexture of the primary tumors is an essential prognostic factor for patients’ disease-free and overall survival. Tumoral and immunological markers predicted by systems biology methods are involved in the shaping of an efficient immune reaction and can serve as targets for novel therapeutic approaches. Global analysis of tumor microenvironment showed that the nature, the functional orientation, the density, and the location of adaptive immune cells within distinct tumor regions influence the risk of relapse events. The density and the immune cell location within the tumor have a prognostic value that is superior to the TNM classification, and tumor invasion is statistically dependent on the host-immune reaction. Thus, the strength of the immune reaction could advance our understanding of cancer evolution and have important consequences in clinical practice

The prognostic impact of anti-cancer immune response: a novel classification of cancer patients

Until now, the anatomic extent of tumor (TNM classification) has been, by far, the most important factor to predict the prognosis of colorectal cancer patients. However, in recent years, data collected from large cohorts of human cancers demonstrated that the immune contexture of the primary tumors is an essential prognostic factor for patients' disease-free and overall survival. Global analysis of tumor microenvironment showed that the nature, the functional orientation, the density, and the location of adaptive immune cells within distinct tumor regions influence the risk of relapse events. An immune classification of the patients was proposed based on the density and the immune cell location within the tumor. The immune classification has a prognostic value that is superior to the TNM classification, and tumor invasion is statistically dependent on the host immune reaction. Tumor and immunological markers predicted by systems biology methods are involved in the shaping of an efficient immune reaction and can serve as targets for novel therapeutic approaches. Thus, the strength of the immune reaction could advance our understanding of cancer evolution and have important consequences in clinical practice

SIDEKICK: Genomic data driven analysis and decision-making framework

<p>Abstract</p> <p>Background</p> <p>Scientists striving to unlock mysteries within complex biological systems face myriad barriers in effectively integrating available information to enhance their understanding. While experimental techniques and available data sources are rapidly evolving, useful information is dispersed across a variety of sources, and sources of the same information often do not use the same format or nomenclature. To harness these expanding resources, scientists need tools that bridge nomenclature differences and allow them to integrate, organize, and evaluate the quality of information without extensive computation.</p> <p>Results</p> <p>Sidekick, a genomic data driven analysis and decision making framework, is a web-based tool that provides a user-friendly intuitive solution to the problem of information inaccessibility. Sidekick enables scientists without training in computation and data management to pursue answers to research questions like "What are the mechanisms for disease X" or "Does the set of genes associated with disease X also influence other diseases." Sidekick enables the process of combining heterogeneous data, finding and maintaining the most up-to-date data, evaluating data sources, quantifying confidence in results based on evidence, and managing the multi-step research tasks needed to answer these questions. We demonstrate Sidekick's effectiveness by showing how to accomplish a complex published analysis in a fraction of the original time with no computational effort using Sidekick.</p> <p>Conclusions</p> <p>Sidekick is an easy-to-use web-based tool that organizes and facilitates complex genomic research, allowing scientists to explore genomic relationships and formulate hypotheses without computational effort. Possible analysis steps include gene list discovery, gene-pair list discovery, various enrichments for both types of lists, and convenient list manipulation. Further, Sidekick's ability to characterize pairs of genes offers new ways to approach genomic analysis that traditional single gene lists do not, particularly in areas such as interaction discovery.</p