Gene-specific methylation alterations in breast cancer have been suggested to occur early in tumorigenesis and have the potential to be used for early detection and prevention. The continuous increase in worldwide breast cancer incidences emphasizes the urgent need for identification of methylation biomarkers for early cancer detection and patient stratification. Using microfluidic PCR-based target enrichment and next-generation bisulfite sequencing technology, we analyzed methylation status of 48 candidate genes in paired tumor and normal tissues from 180 Chinese breast cancer patients. Analysis of the sequencing results showed 37 genes differentially methylated between tumor and matched normal tissues. Breast cancer samples with different clinicopathologic characteristics demonstrated distinct profiles of gene methylation. The methylation levels were significantly different between breast cancer subtypes, with basal-like and luminal B tumors having the lowest and the highest methylation levels, respectively. Six genes (ACADL, ADAMTSL1, CAV1, NPY, PTGS2, and RUNX3) showed significant differential methylation among the 4 breast cancer subtypes and also between the ER +/ER- tumors. Using unsupervised hierarchical clustering analysis, we identified a panel of 13 hypermethylated genes as candidate biomarkers that performed a high level of efficiency for cancer prediction. These 13 genes included CST6, DBC1, EGFR, GREM1, GSTP1, IGFBP3, PDGFRB, PPM1E, SFRP1, SFRP2, SOX17, TNFRSF10D, and WRN. Our results provide evidence that well-defined DNA methylation profiles enable breast cancer prediction and patient stratification. The novel gene panel might be a valuable biomarker for early detection of breast cancer.
Our results demonstrated the complex correlation and the possible regulatory mechanisms between DNA methylation and gene expression. Integration analysis of methylation and expression of candidate genes could improve performance in breast cancer prediction. These findings would contribute to molecular characterization and identification of biomarkers for potential clinical applications.
Acquired immune responses mediated by CD4 + T cells contribute to the initiation and progression of acute coronary syndrome (ACS). ACS patients show acquired immune system abnormalities that resemble the characteristics of autoimmune dysfunction described in the elderly. This study aimed to investigate the role of premature CD4 + T cells senescence in ACS and the underlying mechanism. We compared the immunological status of 25 ACS patients, 15 young healthy individuals (C1), and 20 elderly individuals with absence of ACS (C2). The percentages of CD4 + T lymphocyte subsets (including naï ve, regulatory, memory and effector T cells) in peripheral blood were analyzed. In ACS patients, a significant expansion of CD4 + CD28 null effector T cells and a decline of CD4 + CD25 + CD62L + Treg cells were observed. In addition, patients with ACS showed an accelerated loss of CD4 + CD45RA + CD62L + naï ve T cells and a compensatory increase in the number of CD4 + CD45RO + memory T cells. ACS patients demonstrated no significant difference in frequency of T cell receptor excision circles (TRECs) compared to age-matched healthy volunteers. The expression of p16 Ink4a was increased while CD62L was decreased in CD4 + CD28 null T cells of ACS patients. Compared to healthy donors, ACS patients demonstrated the lowest telomerase activity in both CD4 + CD28 + and CD4 + CD28 null T cells. The serum levels of C-reactive protein, Cytomegalovirus IgG, Helicobactor pylori IgG and Chlamydia pneumonia IgG were significantly higher in ACS patients. The results suggested that the percentage of CD4 + T cell subpopulations correlated with chronic infection, which contributes to immunosenescence. In conclusion, chronic infection induced senescence of premature CD4 + T cells, which may be responsible for the development of ACS.
#2024 Background and Rational: Ethnic-specific disparities in breast cancer (BC) stage of presentation and survival rates are well documented. To further investigate possible ethnic-specific genetic contributions to these disparities, we are completing gene expression profiling studies in a multi-ethnic cohort consisting of thirty “Triple Negative” BC patients [10 each African-American (AA), Hispanic (His) and non-Hispanic white (Cauc) women] matched for age of diagnosis and hormone receptor status. The overall study aim is an increased understanding of the biological basis of ethnic-specific BC disparities, leading ultimately to individualized, ethnic-specific diagnostic and therapeutic approaches. Two immediate study goals are to demonstrate the utility of FFPE samples in obtaining consistent, reproducible data from gene expression arrays, and secondly, to identify differentially expressed genes between tumor and normal tissue that are common or unique among the three ethnic groups. Methods: Pathology specimens were freshly cut from FFPE blocks and marked by a pathologist as to normal vs. tumor tissue. RNA isolation, labeled cDNA preparation, and hybridization of tumor and normal cDNAs to a breast cancer focused gene expression microarray (Breast Cancer DSA Research Tool) was performed by Almac Diagnostics. Each patient was self-matched (tumor vs. normal tissue) for gene expression studies. Results: Using 36 matched tumor and normal FFPE samples from 18 patients, approximately 17516 transcripts were detected on the Breast Cancer DSA with intensity significantly greater than background. For normal and tumor tissue samples, 9399 and 10,296 transcripts respectively, were detected in all three ethnic groups. Importantly, a subset of transcripts (hundreds to one thousand) was detected in only one or two ethnic groups. Using two-way ANOVA (disease state and ethnicity), a subset of 6479 transcripts was identified with p-value less than 0.01 in the statistical test and was selected and further used in data quality control. Data QC indicated that patient samples clustered well with respect to both ethnicity and normal versus tumor tissue. Additional analytical methods included K-means 2-Dimensional clustering and Principal Component Analysis. From these analyses, we identified ethnic-specific expression patterns in the matched normal and tumor tissue samples. We are completing these studies by increasing sample size and matching for stage of diagnosis, mapping clusters of differentially-expressed genes in pathway analysis, and validation by real-time PCR. In the longer term, DNA copy number variation (CNV) and chromosomal alterations will be investigated by high density arrays. Summary: These preliminary analyses shows that high quality gene expression data can be generated from FFPE samples, and that ethnic specific gene expression differences can be detected in tumor and matched normal breast tissue samples across ethnic groups. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2024.
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