Multi-Platform Whole-Genome Microarray Analyses Refine the Epigenetic Signature of Breast Cancer Metastasis with Gene Expression and Copy Number

Background

We have previously identified genome-wide DNA methylation changes in a cell line model of breast cancer metastasis. These complex epigenetic changes that we observed, along with concurrent karyotype analyses, have led us to hypothesize that complex genomic alterations in cancer cells (deletions, translocations and ploidy) are superimposed over promoter-specific methylation events that are responsible for gene-specific expression changes observed in breast cancer metastasis.

Methodology/Principal Findings

We undertook simultaneous high-resolution, whole-genome analyses of MDA-MB-468GFP and MDA-MB-468GFP-LN human breast cancer cell lines (an isogenic, paired lymphatic metastasis cell line model) using Affymetrix gene expression (U133), promoter (1.0R), and SNP/CNV (SNP 6.0) microarray platforms to correlate data from gene expression, epigenetic (DNA methylation), and combination copy number variant/single nucleotide polymorphism microarrays. Using Partek Software and Ingenuity Pathway Analysis we integrated datasets from these three platforms and detected multiple hypomethylation and hypermethylation events. Many of these epigenetic alterations correlated with gene expression changes. In addition, gene dosage events correlated with the karyotypic differences observed between the cell lines and were reflected in specific promoter methylation patterns. Gene subsets were identified that correlated hyper (and hypo) methylation with the loss (or gain) of gene expression and in parallel, with gene dosage losses and gains, respectively. Individual gene targets from these subsets were also validated for their methylation, expression and copy number status, and susceptible gene pathways were identified that may indicate how selective advantage drives the processes of tumourigenesis and metastasis.

Conclusions/Significance

Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer progression and metastasis.     

Yin Yang Gene Expression Ratio Signature for Lung Cancer Prognosis

Many studies have established gene expression-based prognostic signatures for lung cancer. All of these signatures were built from training data sets by learning the correlation of gene expression with the patients'' survival time. They require all new sample data to be normalized to the training data, ultimately resulting in common problems of low reproducibility and impracticality. To overcome these problems, we propose a new signature model which does not involve data training. We hypothesize that the imbalance of two opposing effects in lung cancer cells, represented by Yin and Yang genes, determines a patient’s prognosis. We selected the Yin and Yang genes by comparing expression data from normal lung and lung cancer tissue samples using both unsupervised clustering and pathways analyses. We calculated the Yin and Yang gene expression mean ratio (YMR) as patient risk scores. Thirty-one Yin and thirty-two Yang genes were identified and selected for the signature development. In normal lung tissues, the YMR is less than 1.0; in lung cancer cases, the YMR is greater than 1.0. The YMR was tested for lung cancer prognosis prediction in four independent data sets and it significantly stratified patients into high- and low-risk survival groups (p = 0.02, HR = 2.72; p = 0.01, HR = 2.70; p = 0.007, HR = 2.73; p = 0.005, HR = 2.63). It also showed prediction of the chemotherapy outcomes for stage II & III. In multivariate analysis, the YMR risk factor was more successful at predicting clinical outcomes than other commonly used clinical factors, with the exception of tumor stage. The YMR can be measured in an individual patient in the clinic independent of gene expression platform. This study provided a novel insight into the biology of lung cancer and shed light on the clinical applicability.     

大肠癌转移相关基因表达调控的生物信息学分析

大肠癌是常见的消化道恶性肿瘤,在中国呈逐年上升的趋势。对大肠癌发生发展转移的研究能够指导临床治疗,对研发新药也有着重要意义。本文通过对表达谱数据进行分析,通过表达谱差异数据进行功能富集,研究了大肠癌转移前的早期原发肿瘤的转录调控特点以及远隔器官转移后的大肠癌的转录调控特点,筛选出了部分能够受到多重调控并在转移后肿瘤组织中高表达的关键基因,通过对这些基因相互作用关系研究,构建出转移后关键基因相互作用调控网络,为大肠癌的治疗提供更多潜在靶点。     

miR-146a抑制酪氨酸酶基因家族在小鼠黑色素细胞中表达

miRNA是在许多生物过程中都起着至关重要作用的一类内源性非编码的小RNA,与癌症、肿瘤的发生有关。现发现很多miRNA在黑色素生成中都有重要的调控作用,但miR-146a是否对黑色素的生成具有影响未见报道。本研究发现miR-146a通过靶向抑制酪氨酸酶相关蛋白1(tyrosinase related protein 1,TYRP1)的表达而使黑色素生成降低。在小鼠黑色素细胞中分别转染miR-146a mimic和miR-146a 抑制剂,通过qRT-PCR与Western印迹分析比较各实验组中TYRP1基因与酪氨酸家族相关基因酪氨酸酶(tyrosinase, TYR)、酪氨酸酶相关蛋白2(tyrosinase related protein 2, TYRP2)的表达差异。双荧光报告实验验证TYRP1与miR-146a的靶向关系,双荧光酶活性结果显示,实验组相比对照组,荧光素酶活性明显降低,说明TYRP1是miR-146a的靶基因之一;qRT-PCR和Western印迹结果显示实验组TYR、TYRP1及TYRP2 在mRNA水平和蛋白质水平表达均显著降低;紫外分光光度法检测黑色素含量,结果显示miR-146a mimic转染组黑色素含量明显下降,而抑制组的黑色素含量呈上升趋势。综上所述,miR-146a通过靶向抑制TYRP1基因的表达,而影响TYR家族成员的表达,调控黑色素的生物合成。     

A Plasma Long Noncoding RNA Signature for Early Detection of Lung Cancer

The early detection of lung cancer is a major clinical challenge. Long noncoding RNAs (lncRNAs) have important functions in tumorigenesis. Plasma lncRNAs directly released from primary tumors or the circulating cancer cells might provide cell-free cancer biomarkers. The objective of this study was to investigate whether the lncRNAs could be used as plasma biomarkers for early-stage lung cancer. By using droplet digital polymerase chain reaction, we determined the diagnostic performance of 26 lung cancer–associated lncRNAs in plasma of a development cohort of 63 lung cancer patients and 33 cancer-free individuals, and a validation cohort of 39 lung cancer patients and 28 controls. In the development cohort, 7 of the 26 lncRNAs were reliably measured in plasma. Two (SNHG1 and RMRP) displayed a considerably high plasma level in lung cancer patients vs. cancer-free controls (all P?<?.001). Combined use of the plasma lncRNAs as a biomarker signature produced 84.13% sensitivity and 87.88% specificity for diagnosis of lung cancer, independent of stage and histological type of lung tumor, and patients' age and sex (all P?>?.05). The diagnostic value of the plasma lncRNA signature for lung cancer early detection was confirmed in the validation cohort. The plasma lncRNA signature may provide a potential blood-based assay for diagnosing lung cancer at the early stage. Nevertheless, a prospective study is warranted to validate its clinical value.     

Gene Expression Signature of Normal Cell-of-Origin Predicts Ovarian Tumor Outcomes

The potential role of the cell-of-origin in determining the tumor phenotype has been raised, but not adequately examined. We hypothesized that distinct cells-of-origin may play a role in determining ovarian tumor phenotype and outcome. Here we describe a new cell culture medium for in vitro culture of paired normal human ovarian (OV) and fallopian tube (FT) epithelial cells from donors without cancer. While these cells have been cultured individually for short periods of time, to our knowledge this is the first long-term culture of both cell types from the same donors. Through analysis of the gene expression profiles of the cultured OV/FT cells we identified a normal cell-of-origin gene signature that classified primary ovarian cancers into OV-like and FT-like subgroups; this classification correlated with significant differences in clinical outcomes. The identification of a prognostically significant gene expression signature derived solely from normal untransformed cells is consistent with the hypothesis that the normal cell-of-origin may be a source of ovarian tumor heterogeneity and the associated differences in tumor outcome.     

Mining Disease Risk Patterns from Nationwide Clinical Databases for the Assessment of Early Rheumatoid Arthritis Risk

Rheumatoid arthritis (RA) is a chronic autoimmune rheumatic disease that can cause painful swelling in the joint lining, morning stiffness, and joint deformation/destruction. These symptoms decrease both quality of life and life expectancy. However, if RA can be diagnosed in the early stages, it can be controlled with pharmacotherapy. Although many studies have examined the possibility of early assessment and diagnosis, few have considered the relationship between significant risk factors and the early assessment of RA. In this paper, we present a novel framework for early RA assessment that utilizes data preprocessing, risk pattern mining, validation, and analysis. Under our proposed framework, two risk patterns can be discovered. Type I refers to well-known risk patterns that have been identified by existing studies, whereas Type II denotes unknown relationship risk patterns that have rarely or never been reported in the literature. These Type II patterns are very valuable in supporting novel hypotheses in clinical trials of RA, and constitute the main contribution of this work. To ensure the robustness of our experimental evaluation, we use a nationwide clinical database containing information on 1,314 RA-diagnosed patients over a 12-year follow-up period (1997–2008) and 965,279 non-RA patients. Our proposed framework is employed on this large-scale population-based dataset, and is shown to effectively discover rich RA risk patterns. These patterns may assist physicians in patient assessment, and enhance opportunities for early detection of RA. The proposed framework is broadly applicable to the mining of risk patterns for major disease assessments. This enables the identification of early risk patterns that are significantly associated with a target disease.     

新型R-扁桃酸脱氢酶的基因挖掘及表达鉴定

R-扁桃酸脱氢酶在苯乙酮酸的生物合成中起着关键的作用,挖掘具有高催化活性及稳定性的新型R-扁桃酸脱氢酶具有重要的意义。为了获得理想的R-扁桃酸脱氢酶,采用了基因组挖矿技术从Lactobacillus harbinensis菌株中获得了一个新型的R-扁桃酸脱氢酶LhDMDH,重组LhDMDH的比酶活高达1264.3 U/mg,约为探针的4倍,在已报道的R-扁桃酸脱氢酶中处于领先水平。同时,考察了4个重组酶主要的酶学特性,它们的最适反应温度在25~30℃,最适反应pH在9.0~9.5。动力学参数的结果表明,LhDMDH对底物的K_(cat)值为30.28 S~(-1),明显高于其它重组酶。此外,底物谱分析的结果也表明LhDMDH在外消旋扁桃酸的手性拆分及苯乙酮酸的生物合成中更具优势。在R-扁桃酸脱氢酶基因挖掘方面取得了较为理想的结果,为进一步的改造及应用奠定了坚实的基础,也为其它酶的挖掘提供了可资借鉴的经验。     

Epigenetic Drugs Can Stimulate Metastasis through Enhanced Expression of the Pro-Metastatic Ezrin Gene

Ezrin has been reported to be upregulated in many tumors and to participate in metastatic progression. No study has addressed epigenetic modification in the regulation of Ezrin gene expression, the importance of which is unknown. Here, we report that highly metastatic rhabdomyosarcoma (RMS) cells with high levels of Ezrin have elevated acetyl-H3-K9 and tri-methyl-H3-K4 as well as reduced DNA methylation at the Ezrin gene promoter. Conversely, poorly metastatic RMS cells with low levels of Ezrin have reduced acetyl-H3-K9 and elevated methylation. Thus epigenetic covalent modifications to histones within nucleosomes of the Ezrin gene promoter are linked to Ezrin expression, which in fact can be regulated by epigenetic mechanisms. Notably, treatment with histone deacetylase (HDAC) inhibitors or DNA demethylating agents could restore Ezrin expression and stimulate the metastatic potential of poorly metastatic RMS cells characterized by low Ezrin levels. However, the ability of epigenetic drugs to stimulate metastasis in RMS cells was inhibited by expression of an Ezrin-specific shRNA. Our data demonstrate the potential risk associated with clinical application of broadly acting covalent epigenetic modifiers, and highlight the value of combination therapies that include agents specifically targeting potent pro-metastatic genes.     

恶性卵巢肿瘤淋巴转移与相关基因表达

恶性卵巢肿瘤严重威胁着妇女健康和生命,其重要原因之一是易发生淋巴转移,给临床诊断和治疗带来困难。近年来国内外对恶性卵巢肿瘤淋巴转移的机制及其与相关基因表达进行了一系列的研究,现就这方面的进展作一综述。