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Submission of Evidence on Online Violence Against Women to the UN Special Rapporteur on Violence Against Women, its Causes and Consequences, Dr Dubravka Šimonović
Figure S1. B3GALNT2 levels determined by W.B. and ROC curve. aâc Relative mRNA expression of B3GALNT2 in HCC tumor tissues and normal liver tissues obtained from GSE76427, GSE36376, and TCGA-LIHC datasets. d Western blot analysis of B3GALNT2 levels in 24 pairs of HCC tissues. T HCC tumor tissue, N adjacent non-tumor tissue. e ROC curve analysis of the sensitivity and specificity for the predictive value of TNM model, B3GALNT2 expression, and the combination model. (TIFF 546Â kb
Comprehensive analysis of normal adjacent to tumor transcriptomes.
Histologically normal tissue adjacent to the tumor (NAT) is commonly used as a control in cancer studies. However, little is known about the transcriptomic profile of NAT, how it is influenced by the tumor, and how the profile compares with non-tumor-bearing tissues. Here, we integrate data from the Genotype-Tissue Expression project and The Cancer Genome Atlas to comprehensively analyze the transcriptomes of healthy, NAT, and tumor tissues in 6506 samples across eight tissues and corresponding tumor types. Our analysis shows that NAT presents a unique intermediate state between healthy and tumor. Differential gene expression and protein-protein interaction analyses reveal altered pathways shared among NATs across tissue types. We characterize a set of 18 genes that are specifically activated in NATs. By applying pathway and tissue composition analyses, we suggest a pan-cancer mechanism of pro-inflammatory signals from the tumor stimulates an inflammatory response in the adjacent endothelium
Absence of an embryonic stem cell DNA methylation signature in human cancer.
BackgroundDifferentiated cells that arise from stem cells in early development contain DNA methylation features that provide a memory trace of their fetal cell origin (FCO). The FCO signature was developed to estimate the proportion of cells in a mixture of cell types that are of fetal origin and are reminiscent of embryonic stem cell lineage. Here we implemented the FCO signature estimation method to compare the fraction of cells with the FCO signature in tumor tissues and their corresponding nontumor normal tissues.MethodsWe applied our FCO algorithm to discovery data sets obtained from The Cancer Genome Atlas (TCGA) and replication data sets obtained from the Gene Expression Omnibus (GEO) data repository. Wilcoxon rank sum tests, linear regression models with adjustments for potential confounders and non-parametric randomization-based tests were used to test the association of FCO proportion between tumor tissues and nontumor normal tissues. P-values of < 0.05 were considered statistically significant.ResultsAcross 20 different tumor types we observed a consistently lower FCO signature in tumor tissues compared with nontumor normal tissues, with 18 observed to have significantly lower FCO fractions in tumor tissue (total n = 6,795 tumor, n = 922 nontumor, P < 0.05). We replicated our findings in 15 tumor types using data from independent subjects in 15 publicly available data sets (total n = 740 tumor, n = 424 nontumor, P < 0.05).ConclusionsThe results suggest that cancer development itself is substantially devoid of recapitulation of normal embryologic processes. Our results emphasize the distinction between DNA methylation in normal tightly regulated stem cell driven differentiation and cancer stem cell reprogramming that involves altered methylation in the service of great cell heterogeneity and plasticity
Investigation of NQO1 genetic polymorphism, NQO1 gene expression and PAH-DNA adducts in ESCC. A case-control study from Iran
We evaluated the effect of NQO1 genetic variation on PAH-DNA adducts in esophageal squamous cell carcinoma (ESCC) in northeast Iran. Golestan Province in northeast of Iran has one of the highest esophageal cancer incidences in the world. The study included 93 ESCC cases and 50 control individuals who were seen at the clinical cancer center in Golestan province. NQO1 C609T genotypes were determined by PCR-RFLP analysis. NQO1 gene expression in tissue samples was determined by quantitative real-time PCR. Immunohistochemical techniques were used to detect PAH-DNA adducts in ESCC and normal esophageal tissues. The distributions of NQO1 genetic polymorphism between cases and the control group were not significantly different. NQO1 gene expression was not higher in tumor tissues than in normal esophageal tissues adjacent to the ESCC; expression was higher in tumor tissues that had the NQO1 T allele. NQO1 gene expression was high in normal esophageal tissues. The level of PAH-DNA adducts was significantly higher in ESCC tissues of cases than in normal tissues adjacent to tumor tissues and in normal esophageal tissues of healthy controls. There were no significant differences between the adduct levels of normal esophageal tissues of patients and controls. There was also no significant relationship between cigarette smoking and PAH-DNA adducts. We concluded that PAHs are a risk factor for ESCC and that PAH-DNA adducts have potential as a biomarker for risk of ESCC
α-Smooth muscle actin expression in cancerassociated fibroblasts in canine epithelial tumors
Tumor tissues contain not only cancer cells but also other cell types including, fibroblasts, immune cells, and endothelial cells, which interact with cancer cells. In human medicine, cancer-associated fibroblasts (CAFs) have been reported to promote tumor growth. CAFs are known to express α-smooth muscle actin (α-SMA), and this expression is correlated with poor prognosis in humans with cancer. However, the role of CAFs in canines and α-SMA expression in canine CAFs remains unknown. This study evaluated whether CAFs are present within the stroma of various types of canine epithelial tumors, for example, mammary gland tumors, squamous cell carcinoma, and anal sac adenocarcinoma, and assessed α-SMA expression in CAFs isolated from canine epithelial tumors. α-SMA analysis of tumor tissues revealed a cytoplasmic localization with variable levels of expression. α-SMA was detected in 60.9% (14/23) of epithelial tumor tissues and in 80% (8/10) of anal sac adenocarcinoma tissues. CAFs and normal fibroblasts (NFs) were isolated from tumor and skin tissues. The size of CAFs was variable, and most CAFs had large cell volume, in contrast to NFs. Most CAFs expressed α-SMA stress fibers and had higher α-SMA protein levels than NFs. Taken together, our findings provide evidence that canine CAFs express α-SMA in various canine epithelial tumors. Further studies are required to investigate the correlation between canine CAFs and clinical parameters and to elucidate the mechanisms underlying the effects of CAFs on cancer progression
ISOWN: accurate somatic mutation identification in the absence of normal tissue controls.
BackgroundA key step in cancer genome analysis is the identification of somatic mutations in the tumor. This is typically done by comparing the genome of the tumor to the reference genome sequence derived from a normal tissue taken from the same donor. However, there are a variety of common scenarios in which matched normal tissue is not available for comparison.ResultsIn this work, we describe an algorithm to distinguish somatic single nucleotide variants (SNVs) in next-generation sequencing data from germline polymorphisms in the absence of normal samples using a machine learning approach. Our algorithm was evaluated using a family of supervised learning classifications across six different cancer types and ~1600 samples, including cell lines, fresh frozen tissues, and formalin-fixed paraffin-embedded tissues; we tested our algorithm with both deep targeted and whole-exome sequencing data. Our algorithm correctly classified between 95 and 98% of somatic mutations with F1-measure ranges from 75.9 to 98.6% depending on the tumor type. We have released the algorithm as a software package called ISOWN (Identification of SOmatic mutations Without matching Normal tissues).ConclusionsIn this work, we describe the development, implementation, and validation of ISOWN, an accurate algorithm for predicting somatic mutations in cancer tissues in the absence of matching normal tissues. ISOWN is available as Open Source under Apache License 2.0 from https://github.com/ikalatskaya/ISOWN
Transcriptomic profiling disclosed the role of DNA methylation and histone modifications in tumor-infiltrating myeloid-derived suppressor cell subsets in colorectal cancer
Increased numbers of myeloid-derived suppressor cells (MDSCs) are positively correlated with poor prognosis and reduced survivals of cancer patients. They play central roles in tumor immune evasion and tumor metastasis. However, limited data are available on phenotypic/transcriptomic characteristics of the different MDSCs subsets in cancer. These cells include immature (I-MDSCs), monocytic (M-MDSCs), and polymorphonuclear/granulocytic (PMN-MDSCs). Phenotypic characterization of myeloid subsets from 27 colorectal cancer (CRC) patients was assessed by flow cytometric analyses. RNA-sequencing of sorted I-MDSCs, PMN-MDSCs, and antigen-presenting cells (APCs) was also performed. We found that the levels of I-MDSCs and PMN-MDSCs were increased in tumor tissues (TT), compared with normal tissues (NT) in colorectal cancer. Our functional annotation analyses showed that genes associated with histone deacetylase (HDAC) activation- and DNA methylation-mediated transcriptional silencing were upregulated, and histone acetyl transferase (HAT)-related genes were downregulated in tumor-infiltrating I-MDSCs. Moreover, pathways implicated in cell trafficking and immune suppression, including Wnt, interleukin-6 (IL-6), and mitogen-activated protein kinase (MAPK) signaling, were upregulated in I-MDSCs. Notably, PMN-MDSCs showed downregulation in genes related to DNA methylation and HDAC binding. Using an ex vivo model, we found that inhibition of HDAC activation or neutralization of IL-6 in CRC tumor tissues downregulates the expression of genes associated with immunosuppression and myeloid cell chemotaxis, confirming the importance of HDAC activation and IL-6 signaling pathway in MDSC function and chemotaxis. This study provides novel insights into the epigenetic regulations and other molecular pathways in different myeloid cell subsets within the CRC tumor microenvironment (TME), giving opportunities to potential targets for therapeutic benefits
Determination of Rottlerin, a Natural Protein Kinases C Inhibitor, in Pancreatic Cancer Cells and Mouse Xenografts by RP-HPLC Method.
Rottlerin is a natural polyphenolic ketone isolated from the pericarps of Mallotus phillippinensis. In previous studies we showed that parenteral administration of rottlerin reduced tumor growth in murine xenograft models of pancreatic cancer. The aim of this study was to develop a simple and validated method for the quantitative determination of rottlerin in plasma and tumor tissues of mice fed a rottlerin diet. A xenograft model of pancreatic cancer was prepared by injection of 2×106 HPAF-II cells subcutaneously into nude mice. One week before tumor implantation, mice were randomly allocated to standard diet (AIN76A) and standard diet supplement with 0.012% rottlerin (n=6 per group). Mice were sacrificed after 6 weeks on diets. Rottlerin was extracted from the plasma and tissues using protein precipitation-extraction and analyzed by reverse-phase HPLC-DAD method. The same HPLC method was also applied to determine rottlerin levels in conditioned culture media and in cell lysates from HPAF-II cells exposed to 25 µM concentration of rottlerin. A substantial amount of rottlerin was detected in tumor (2.11 ± 0.25 nmol/g tissue) and plasma (2.88 ± 0.41 µM) in mice fed rottlerin diet. In addition, significant levels of rottlerin (57.4 ± 5.4 nmol/mg protein) were detected in cell lysates from rottlerin-treated HPAF-II cells. These data indicate that rottlerin is efficiently absorbed in cells and tissues both in vivo and in vitro and suggest a strong potential for rottlerin as a preventive or adjuvant supplement for pancreatic cancer
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