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Abstract Background & Methods In this study, a novel restriction enzyme (RE) digestion-based droplet digital polymerase chain reaction (ddPCR) assay was designed for cg005575921 within the AHRR gene body and compared with matching results obtained by bisulfite conversion (BIS) ddPCR and Illumina DNA methylation array. Results The RE ddPCR cg05575921 assay appeared concordant with BIS ddPCR (r 2 = 0.94, P

BackgroundTriggering receptor expressed on myeloid cells (TREM)-1 is a key mediator of innate immunity previously associated with the severity of inflammatory disorders, and more recently, the inferior survival of lung and liver cancer patients. Here, we investigated the prognostic impact and immunological correlates of TREM1 expression in breast tumors.MethodsBreast tumor microarray and RNAseq expression profiles (n=4,364 tumors) were analyzed for associations between gene expression, tumor immune subtypes, distant metastasis-free survival (DMFS) and clinical response to neoadjuvant chemotherapy (NAC). Single-cell (sc)RNAseq was performed using the 10X Genomics platform. Statistical associations were assessed by logistic regression, Cox regression, Kaplan-Meier analysis, Spearman correlation, Student’s t-test and Chi-square test.ResultsIn pre-treatment biopsies, TREM1 and known TREM-1 inducible cytokines (IL1B, IL8) were discovered by a statistical ranking procedure as top genes for which high expression was associated with reduced response to NAC, but only in the context of immunologically “hot” tumors otherwise associated with a high NAC response rate. In surgical specimens, TREM1 expression varied among tumor molecular subtypes, with highest expression in the more aggressive subtypes (Basal-like, HER2-E). High TREM1 significantly and reproducibly associated with inferior distant metastasis-free survival (DMFS), independent of conventional prognostic markers. Notably, the association between high TREM1 and inferior DMFS was most prominent in the subset of immunogenic tumors that exhibited the immunologically hot phenotype and otherwise associated with superior DMFS. Further observations from bulk and single-cell RNAseq analyses indicated that TREM1 expression was significantly enriched in polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) and M2-like macrophages, and correlated with downstream transcriptional targets of TREM-1 (IL8, IL-1B, IL6, MCP-1, SPP1, IL1RN, INHBA) which have been previously associated with pro-tumorigenic and immunosuppressive functions.ConclusionsTogether, these findings indicate that increased TREM1 expression is prognostic of inferior breast cancer outcomes and may contribute to myeloid-mediated breast cancer progression and immune suppression.

Aberrant expression of the Δ133p53 isoform is linked to many cancers. Here, the authors utilise a model of the Δ133p53 isoform that is prone to tumours and inflammation, showing that Δ133p53 promotes tumour cell invasion by activation of the JAK-STAT and RhoA-ROCK pathways in an IL-6 dependent manner.

Mounting evidence supports a role for the immune system in breast cancer outcomes. The ability to distinguish highly immunogenic tumors susceptible to anti-tumor immunity from weakly immunogenic or inherently immune-resistant tumors would guide development of therapeutic strategies in breast cancer. Genomic, transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) breast cancer cohorts were used to examine statistical associations between tumor mutational burden (TMB) and the survival of patients whose tumors were assigned to previously-described prognostic immune subclasses reflecting favorable, weak or poor immune-infiltrate dispositions (FID, WID or PID, respectively). Tumor immune subclasses were associated with survival in patients with high TMB (TMB-Hi, P

Over the last 10 years there has been an explosion of information about the molecular biology of cancer. A challenge in oncology is to translate this information into advances in patient care. While there are well-formed routes for translating new molecular information into drug therapy, the routes for translating new information into sensitive and specific diagnostic, prognostic and predictive tests are still being developed. Similarly, the science of using tumor molecular profiles to select clinical trial participants or to optimize therapy for individual patients is still in its infancy. This review will summarize the current technologies for predicting treatment response and prognosis in cancer medicine, and outline what the future may hold. It will also highlight the potential importance of methods that can integrate molecular, histopathological and clinical information into a synergistic understanding of tumor progression. While these possibilities are without doubt exciting, significant challenges remain if we are to implement them with a strong evidence base in a widely available and cost-effective manner.

BACKGROUND: Angiogenesis and vascular remodeling play critical roles in the cyclical growth and regression of endometrium. They also appear to play roles in the pathogenesis of endometriosis. METHODS and RESULTS: Supernatants were collected from cultured endometrium isolated from women with and without endometriosis. These supernatants induced endothelial cell proliferation and angiogenesis in vitro. They contained vascular endothelial growth factor (VEGF)-A, and their proliferative effects on endothelial cells were partially abrogated by a blocking anti-VEGF-A antibody. Gene array analysis showed that culture supernatants from proliferative phase endometrium, and to a lesser extent secretory phase endometrium, induced significant changes in the transcriptome of endothelial cells. We could not detect any association between endometriosis and the ability of endometrial-derived soluble factors to promote angiogenesis or to regulate the endothelial transcriptome. In addition, we could not detect any association between endometriosis and the concentration of VEGF-A in supernatants from cultured endometrium or in menstrual effluent. CONCLUSIONS: We have shown that endometrium cultured in vitro produced soluble factors, including VEGF-A, that promoted angiogenesis. Proliferative phase endometrium promoted significant endothelial cell transcriptome changes that appear overall to be pro-angiogenic. These transcriptome changes provide insight into the dynamic control of vessel structure on which both eutopic endometrium and endometriotic lesions depend. [ABSTRACT FROM AUTHOR]

The sculpting of blood vessels to meet the changing requirements of the tissues they supply is essential for life. Many researchers believe that endothelial cell apoptosis plays an important role in this process. This belief is bolstered by the detection of endothelial apoptosis within remodeling vessels in vivo, the dramatic vascular phenotypes of mice in which regulators of endothelial apoptosis have been inactivated and the apparent dependence of angiogenesis on endothelial apoptosis in vitro. However, when examined carefully, the evidence for or against endothelial cell apoptosis playing an important role in vascular biology is largely indirect and is far from clear-cut. In this review, we will discuss the idiosyncratic process of endothelial cell apoptosis. We will then examine its complex regulation and weigh the in vitro and in vivo evidence that it plays a significant role in mammalian vascular biology. [ABSTRACT FROM AUTHOR]

Motivation: Statistical inference of gene networks by using time-course microarray gene expression profiles is an essential step towards understanding the temporal structure of gene regulatory mechanisms. Unfortunately, most of the current studies have been limited to analysing a small number of genes because the length of time-course gene expression profiles is fairly short. One promising approach to overcome such a limitation is to infer gene networks by exploring the potential transcriptional modules which are sets of genes sharing a common function or involved in the same pathway. Results: In this article, we present a novel approach based on the state space model to identify the transcriptional modules and module-based gene networks simultaneously. The state space model has the potential to infer large-scale gene networks, e.g. of order 103, from time-course gene expression profiles. Particularly, we succeeded in the identification of a cell cycle system by using the gene expression profiles of Saccharomyces cerevisiae in which the length of the time-course and number of genes were 24 and 4382, respectively. However, when analysing shorter time-course data, e.g. of length 10 or less, the parameter estimations of the state space model often fail due to overfitting. To extend the applicability of the state space model, we provide an approach to use the technical replicates of gene expression profiles, which are often measured in duplicate or triplicate. The use of technical replicates is important for achieving highly-efficient inferences of gene networks with short time-course data. The potential of the proposed method has been demonstrated through the time-course analysis of the gene expression profiles of human umbilical vein endothelial cells (HUVECs) undergoing growth factor deprivation-induced apoptosis. Availability: Supplementary Information and the software (TRANS-MNET) are available at http://daweb.ism.ac.jp/~yoshidar/software/ssm/ Contact: yoshidar@ism.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]