Novel markers of gene methylation and expression in breast cancer

An optimized methylation-sensitive restriction fingerprinting technique was used to search for differentially methylated CpG islands in the tumor genome and detected seven genes subject to abnormal epigenetic regulation in breast cancer: SEMA6B, BIN1, VCPIP1, LAMC3, KCNH2, CACNG4, and PSMF1. For each gene, the rate of promoter methylation and changes in expression were estimated in tumor and morphologically intact paired specimens of breast tissue (N = 100). Significant methylation rates of 38, 18, and 8% were found for SEMA6B, BIN1, and LAMC3, respectively. The genes were not methylated in morphologically intact breast tissue. The expression of SEMA6B, BIN1, VCPIP1, LAMC3, KCNH2, CACNG4, and PSMF1 was decreased in 44–94% of tumor specimens by the real-time RT-PCR assay. The most profound changes in SEMA6B and LAMC3 suggest that these genes can be included in biomarker panels for breast cancer diagnosis. Fine methylation mapping of the most frequently methylated CpG islands (SEMA6B, BIN1, and LAMC3) provides a fundamental basis for developing efficient methylation tests for these genes.     

Distinct gene expression profiles of human type 1 and type 2 T helper cells

Background

The development and activation of CD4⁺ helper T cell (Th) subsets with distinct patterns of unbalanced production of cytokines play an important part in infectious, allergic and autoimmune diseases. Human neonatal cord blood CD4⁺ Th cells can be polarized into type 1 or type 2-like effector cells in vitro by culturing them in the presence of interleukin (IL)-12 or IL-4, respectively. We have exploited this experimental system to identify marker genes that are differentially expressed by polarized Th1 and Th2 cells. An oligonucleotide microarray specifically designed to screen for inflammation-related candidate genes was used and the differential expression was further validated with a quantitative real-time RT-PCR method.

Results

In addition to the previously described marker genes of Th cells, we report subtle changes in the expression of several other genes that represent growth factors, receptors and other signaling molecules in polarized Th1 and Th2 cell subsets. Additionally, we describe a novel set of genes as Th1/Th2 differentiation markers for cells activated by anti-CD3 and anti-CD28 antibodies.

Conclusions

This study demonstrates the power of the targeted use of microarrays in combination with quantitative real-time RT-PCR in identifying and validating new marker genes for gene expression studies.     

Coat Color Variation and Pigmentation Gene Expression in Rhesus Macaques (Macaca mulatta)

Light-dark coat color variation is a common aspect of color diversity within and across mammalian taxa. This variation in pelage brightness is associated with aspects of evolutionary ecology, particularly for primates, but little is known about the genetic mechanisms underlying light-dark differences in pelage pigmentation. Previous work, focusing particularly on macaques (Genus Macaca), has found no clear relationship between color variation and coding sequences of key pigmentation genes. This suggests that other loci and/or gene regulatory differences underlie this variation and raises the question of how patterns of gene expression differ in light verses dark hair follicles. Here, we examine relative expression levels of pigmentation genes in hair follicles from free-ranging rhesus macaques (Macaca mulatta) showing stark light-dark coat color variation. We quantified the brightness (reflectance) of plucked hair tufts using a spectrophotometer. We extracted RNA from the follicles and used quantitative RT-PCR to measure the relative amounts of gene product (mRNA) for seven candidate pigmentation genes (MITF, MC1R, MGRN1, ATRN, SLC24A5, TYRP1, and DCT). Expression values were normalized with the house-keeping gene ACTB. All candidate genes were expressed at similar levels in dark, intermediate, and light hair, and thus, light-dark variation in macaque coat color is unlikely to be due to differences in the expression of these key pigmentation genes. This study represents the first examination of gene expression and natural color variation in a non-human primate population. Our results indicate that even in a system, like pigmentation, where a candidate-gene approach is promising, identifying important intra-specific gene regulatory differences remains challenging.     

Analysis of DNA Methylation of Multiple Genes in Microdissected Cells From Formalin-fixed and Paraffin-embedded Tissues

A procedure for simultaneous quantification of DNA methylation of several genes in minute amounts of sample material was developed and applied to microdissected formalin-fixed and paraffin-embedded breast tissues. The procedure is comprised of an optimized bisulfite treatment protocol suitable for samples containing only few cells, a multiplex preamplification and subsequent locus specific reamplification, and a novel quantitative bisulfite sequencing method based on the incorporation of a normalization domain into the PCR product. A real-time PCR assay amplifying repetitive elements was established to quantify low amounts of bisulfite-treated DNA. Ten prognostic and diagnostic epigenetic breast cancer biomarkers (PITX2, RASSF1A, PLAU, LHX3, PITX3, LIMK1, SLITRK1, SLIT2, HS3ST2, and TFF1) were analyzed in tissue samples obtained from two patients with invasive ductal carcinoma of the breast. The microdissected samples were obtained from several areas within the tumor tissue, including intraductal and invasive carcinoma, adenosis, and normal ductal epithelia of adjacent normal tissue, as well as stroma, tumor infiltrating lymphocytes, and adipose tissue. Overall, reliable quantification was possible for all genes. For most genes, increased DNA methylation in invasive and intraductal carcinoma cells compared with other tissue components was observed. For TFF1, decreased methylation levels were observed in tumor cells. (J Histochem Cytochem 57:477–489, 2009)     

With Reference to Reference Genes: A Systematic Review of Endogenous Controls in Gene Expression Studies

The choice of reference genes that are stably expressed amongst treatment groups is a crucial step in real-time quantitative PCR gene expression studies. Recent guidelines have specified that a minimum of two validated reference genes should be used for normalisation. However, a quantitative review of the literature showed that the average number of reference genes used across all studies was 1.2. Thus, the vast majority of studies continue to use a single gene, with β-actin (ACTB) and/or glyceraldehyde 3-phosphate dehydrogenase (GAPDH) being commonly selected in studies of vertebrate gene expression. Few studies (15%) tested a panel of potential reference genes for stability of expression before using them to normalise data. Amongst studies specifically testing reference gene stability, few found ACTB or GAPDH to be optimal, whereby these genes were significantly less likely to be chosen when larger panels of potential reference genes were screened. Fewer reference genes were tested for stability in non-model organisms, presumably owing to a dearth of available primers in less well characterised species. Furthermore, the experimental conditions under which real-time quantitative PCR analyses were conducted had a large influence on the choice of reference genes, whereby different studies of rat brain tissue showed different reference genes to be the most stable. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies.     

Assessment of Tumor Heterogeneity,as Evidenced by Gene Expression Profiles,Pathway Activation,and Gene Copy Number,in Patients with Multifocal Invasive Lobular Breast Tumors

BackgroundInvasive lobular carcinoma (ILC) comprises approximately ~10–20% of breast cancers. In general, multifocal/multicentric (MF/MC) breast cancer has been associated with an increased rate of regional lymph node metastases. Tumor heterogeneity between foci represents a largely unstudied source of genomic variation in those rare patients with MF/MC ILC.MethodsWe characterized gene expression and copy number in 2 or more foci from 11 patients with MF/MC ILC (all ER+, HER2-) and adjacent normal tissue. RNA and DNA were extracted from 3x1.5mm cores from all foci. Gene expression (730 genes) and copy number (80 genes) were measured using Nanostring PanCancer and Cancer CNV panels. Linear mixed models were employed to compare expression in tumor versus normal samples from the same patient, and to assess heterogeneity (variability) in expression among multiple ILC within an individual.Results35 and 34 genes were upregulated (FC>2) and down-regulated (FC<0.5) respectively in ILC tumor relative to adjacent normal tissue, q<0.05. 9/34 down-regulated genes (FIGF, RELN, PROM1, SFRP1, MMP7, NTRK2, LAMB3, SPRY2, KIT) had changes larger than CDH1, a hallmark of ILC. Copy number changes in these patients were relatively few but consistent across foci within each patient. Amplification of three genes (CCND1, FADD, ORAOV1) at 11q13.3 was present in 2/11 patients in both foci. We observed significant evidence of within-patient between-foci variability (heterogeneity) in gene expression for 466 genes (p<0.05 with FDR 8%), including CDH1, FIGF, RELN, SFRP1, MMP7, NTRK2, LAMB3, SPRY2 and KIT.ConclusionsThere was substantial variation in gene expression between ILC foci within patients, including known markers of ILC, suggesting an additional level of complexity that should be addressed.     

Evaluation and validation of candidate endogenous control genes for real-time quantitative PCR studies of breast cancer

Background  

Real-time quantitative PCR (RQ-PCR) forms the basis of many breast cancer biomarker studies and novel prognostic assays, paving the way towards personalised cancer treatments. Normalisation of relative RQ-PCR data is required to control for non-biological variation introduced during sample preparation. Endogenous control (EC) genes, used in this context, should ideally be expressed constitutively and uniformly across treatments in all test samples. Despite widespread recognition that the accuracy of the normalised data is largely dependent on the reliability of the EC, there are no reports of the systematic validation of genes commonly used for this purpose in the analysis of gene expression by RQ-PCR in primary breast cancer tissues. The aim of this study was to identify the most suitable endogenous control genes for RQ-PCR analysis of primary breast tissue from a panel of eleven candidates in current use. Oestrogen receptor alpha (ESR1) was used a target gene to compare the effect of choice of EC on the estimate of gene quantity.     

Validation of internal control genes for quantitative gene expression studies in chickpea (Cicer arietinum L.)

The real-time polymerase chain reaction (PCR) data requires normalization with an internal control gene expressed at constant levels under all the experimental conditions being analyzed for accurate and reliable gene expression results. In this study, the expression of 12 candidate internal control genes, including ACT1, EF1α, GAPDH, IF4a, TUB6, UBC, UBQ5, UBQ10, 18SrRNA, 25SrRNA, GRX and HSP90, in a diverse set of 18 tissue samples representing different organs/developmental stages and stress conditions in chickpea (Cicer arietinum L.) has been validated. Their expression levels vary considerably in various tissue samples analyzed. The expression levels of EF1α and HSP90 are most constant across various organs/developmental stages analyzed. Similarly, the expression levels of IF4a and GAPDH are most constant across various stress conditions. A set of two most stable genes is found sufficient for accurate and reliable normalization of real-time PCR data in the given set of tissue samples of chickpea. The genes with most constant expression identified in this study should be useful for normalization of gene expression data in a wide variety of tissue samples in chickpea.     

Exploring Valid Reference Genes for Quantitative Real-time PCR Analysis in Plutella xylostella (Lepidoptera: Plutellidae)

Abstract: Quantitative real-time PCR (qRT-PCR), a primary tool in gene expression analysis, requires an appropriate normalization strategy to control for variation among samples. The best option is to compare the mRNA level of a target gene with that of reference gene(s) whose expression level is stable across various experimental conditions. In this study, expression profiles of eight candidate reference genes from the diamondback moth, Plutella xylostella, were evaluated under diverse experimental conditions. RefFinder, a web-based analysis tool, integrates four major computational programs including geNorm, Normfinder, BestKeeper, and the comparative ΔCt method to comprehensively rank the tested candidate genes. Elongation factor 1 (EF1) was the most suited reference gene for the biotic factors (development stage, tissue, and strain). In contrast, although appropriate reference gene(s) do exist for several abiotic factors (temperature, photoperiod, insecticide, and mechanical injury), we were not able to identify a single universal reference gene. Nevertheless, a suite of candidate reference genes were specifically recommended for selected experimental conditions. Our finding is the first step toward establishing a standardized qRT-PCR analysis of this agriculturally important insect pest.     

Concurrent Gene Signatures for Han Chinese Breast Cancers

The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers.We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival.Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. Prognostic comparisons with published gene expression signatures showed a better discerning ability of concurrent genes, many of which were rarely identifiable if expression data were pre-selected by phenotype correlations or variability of individual genes.We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer.