Systematic Bias in Genomic Classification Due to Contaminating Normal Tissue in Breast Tumor Samples
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Elloumi F
PROVIDER: S-ECPF-GEOD-22384 | biostudies-other | 2011
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Results: Normal tissue contamination caused misclassification of tumors in all predictors, but different breast cancer predictors showed different susceptibility to normal tissue bias. Sensitivity and negative predictive value (NPV) of the PAM50 assay was improved by accounting for normal tissue. Conclusions: Normal tissue sampled concurrently with tumor tissue is an important source of bias in genomic predictors. Adjustments for normal tissue contamination could improve the application of breast cancer genomic predictors in both research and in clinical settings.
2011-07-19 | GSE22384 | GEO
Project description:Results: Normal tissue contamination caused misclassification of tumors in all predictors, but different breast cancer predictors showed different susceptibility to normal tissue bias. Sensitivity and negative predictive value (NPV) of the PAM50 assay was improved by accounting for normal tissue. Conclusions: Normal tissue sampled concurrently with tumor tissue is an important source of bias in genomic predictors. Adjustments for normal tissue contamination could improve the application of breast cancer genomic predictors in both research and in clinical settings. Reference x breast tumor samples.
2011-07-18 | E-GEOD-22384 | biostudies-arrayexpress
Project description:Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification.To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors.Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability.Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor.
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Project description:We investigate 71 single nucleotide polymorphisms (SNPs) identified in meta-analytic studies of genome-wide association studies (GWAS) of breast cancer, the majority of which are located in intergenic or intronic regions. To explore regulatory impacts of these variants we conducted expression quantitative loci (eQTL) analyses on tissue samples from 376 invasive postmenopausal breast cancer cases in the Nurses' Health Study (NHS) diagnosed from 1990-2004. Expression analysis was conducted on all formalin-fixed paraffin-embedded (FFPE) tissue samples (and on 264 adjacent normal samples) using the Affymetrix Human Transcriptome Array. Significance and ranking of associations between tumor receptor status and expression variation was preserved between NHS FFPE and TCGA fresh-frozen sample sets (Spearman r = 0.85, p<10^-10 for 17 of the 21 Oncotype DX recurrence signature genes). At an FDR threshold of 10%, we identified 27 trans-eQTLs associated with expression variation in 217 distinct genes. SNP-gene associations can be explored using an open-source interactive browser distributed in a Bioconductor package. Using a new a procedure for testing hypotheses relating SNP content to expression patterns in gene sets, defined as molecular function pathways, we find that loci on 6q14 and 6q25 affect various gene sets and molecular pathways (FDR < 10%). Although the ultimate biological interpretation of the GWAS-identified variants remains to be uncovered, this study validates the utility of expression analysis of this FFPE expression set for more detailed integrative analyses.
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Project description:Tumor associated miRNAs in hereditary breast cancer. In this study we investigated the role of miRNAs in hereditary breast tumors comparing with normal breast tissue. Global miRNA expression profiling was performed on 22 hereditary breast tumors and 15 non-tumoral breast tissues. We identified 19 miRNAs differentially expressed, most of them down-regulated in tumors. An important proportion of deregulated miRNAs in hereditary tumors were previously identified commonly deregulated in sporadic breast tumors. Our results identify miRNAs associated to hereditary breast cancer, as well as miRNAs commonly miss-expressed in hereditary and sporadic tumors, suggesting common underlying mechanisms of tumor progression. In addition, we provide evidence that KRAS is a target of miR-30c, and that this miRNA suppresses breast cancer cell growth potentially through inhibition of KRAS signaling. Single color experiments in a pairwise comparison design.
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Project description:RNA editing is phenomenon that occurs in both protein coding and non-coding RNAs. Increasing evidence have shown that adenosine-to-inosine RNA editing can potentially rendering substantial functional effects throughout the genome. Using RNA editing datasets from two large consortiums: The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) project, we quantitatively analyzed human genome-wide RNA editing events derived from tumor or normal tissues. Generally, a common RNA editing site tends to have a higher editing level in tumors as compared to normal samples. Of the 14 tumor-normal-paired cancer types examined, Eleven of the 14 cancers tested had overall increased RNA editing levels in the tumors. The editomes in cancer or normal tissues were dissected by genomic locations, and significant RNA editing locational difference was found between cancerous and healthy subjects. Additionally, our results indicated a significant correlation between the RNA editing rate and the gene density across chromosomes, highlighted hyper RNA editing clusters through visualization of running RNA editing rates along chromosomes, and identified hyper RNA edited genes (protein-coding genes, lincRNAs, and pseudogenes) that embody a large portion of cancer prognostic predictors. This study reinforces the potential functional effects of RNA editing in protein-coding genes, and also makes a strong foundation for further exploration of RNA editing's roles in non-coding regions.
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Project description:Field cancerization effects as well as isolated tumor cell foci extending well beyond the invasive tumor margin have been described previously to account for local recurrence rates following breast conserving surgery despite adequate surgical margins and breast radiotherapy. To look for evidence of possible tumor cell contamination or field cancerization by genetic effects, a pilot study (Study 1: 12 sample pairs) followed by a verification study (Study 2: 20 sample pairs) were performed on DNA extracted from HER2-positive breast tumors and matching normal adjacent mammary tissue samples excised 1-3 cm beyond the invasive tumor margin. High-resolution molecular inversion probe (MIP) arrays were used to compare genomic copy number variations, including increased HER2 gene copies, between the paired samples; as well, a detailed histologic and immunohistochemical (IHC) re-evaluation of all Study 2 samples was performed blinded to the genomic results to characterize the adjacent normal tissue composition bracketing the DNA-extracted samples. Overall, 14/32 (44 %) sample pairs from both studies produced genome-wide evidence of genetic aberrations including HER2 copy number gains within the adjacent normal tissue samples. The observed single-parental origin of monoallelic HER2 amplicon haplotypes shared by informative tumor-normal pairs, as well as commonly gained loci elsewhere on 17q, suggested the presence of contaminating tumor cells in the genomically aberrant normal samples. Histologic and IHC analyses identified occult 25-200 μm tumor cell clusters overexpressing HER2 scattered in more than half, but not all, of the genomically aberrant normal samples re-evaluated, but in none of the genomically normal samples. These genomic and microscopic findings support the conclusion that tumor cell contamination rather than genetic field cancerization represents the likeliest cause of local clinical recurrence rates following breast conserving surgery, and mandate caution in assuming the genomic normalcy of histologically benign appearing peritumor breast tissue.
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Project description:Breast carcinogenesis is a multistep process accompanied by widespread molecular and genomic alterations, both in tumor and in surrounding microenvironment. It is known that tumors have altered metabolism, but the metabolic changes in normal or cancer-adjacent, nonmalignant normal tissues and how these changes relate to alterations in gene expression and histological composition are not well understood. Normal or cancer-adjacent normal breast tissues from 99 women of the Normal Breast Study (NBS) were evaluated. Data of metabolomics, gene expression and histological composition was collected by mass spectrometry, whole genome microarray, and digital image, respectively. Unsupervised clustering analysis determined metabolomics-derived subtypes. Their association with genomic and histological features, as well as other breast cancer risk factors, genomic and histological features were evaluated using logistic regression. Unsupervised clustering of metabolites resulted in two main clusters. The metabolite differences between the two clusters suggested enrichment of pathways involved in lipid metabolism, cell growth and proliferation, and migration. Compared with Cluster 1, subjects in Cluster 2 were more likely to be obese (body mass index ≥30 kg/m2, p<0.05), have increased adipose proportion (p<0.01) and associated with a previously defined Active genomic subtype (p<0.01). By the integrated analyses of histological, metabolomics and transcriptional data, we characterized two distinct subtypes of non-malignant breast tissue. Further research is needed to validate our findings, and understand the potential role of these alternations in breast cancer initiation, progression and recurrence.
| S-EPMC5905995 | biostudies-literature
Project description:Sporadic breast cancer develops through the accumulation of molecular abnormalities in normal breast tissue, resulting from exposure to estrogens and other carcinogens beginning at adolescence and continuing throughout life. These molecular changes may take a variety of forms, including numerical and structural chromosomal abnormalities, epigenetic changes, and gene expression alterations. To characterize these abnormalities, a review of the literature has been conducted to define the molecular changes in each of the above major genomic categories in normal breast tissue considered to be either at normal risk or at high risk for sporadic breast cancer. This review indicates that normal risk breast tissues (such as reduction mammoplasty) contain evidence of early breast carcinogenesis including loss of heterozygosity, DNA methylation of tumor suppressor and other genes, and telomere shortening. In normal tissues at high risk for breast cancer (such as normal breast tissue adjacent to breast cancer or the contralateral breast), these changes persist, and are increased and accompanied by aneuploidy, increased genomic instability, a wide range of gene expression differences, development of large cancerized fields, and increased proliferation. These changes are consistent with early and long-standing exposure to carcinogens, especially estrogens. A model for the breast carcinogenic pathway in normal risk and high-risk breast tissues is proposed. These findings should clarify our understanding of breast carcinogenesis in normal breast tissue and promote development of improved methods for risk assessment and breast cancer prevention in women.
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Project description:BackgroundGene expression profiles of normal and tumor tissue reflect both differences in biological processes taking place in vivo and differences in response to stress during surgery and sample handling. The effect of cold (room temperature) ischemia in the time interval between surgical removal of the specimen and freezing is described in a few studies. However, not much is known about the effect of warm (body temperature) ischemia during surgery.MethodsThree women with primary operable breast cancer underwent in situ biopsies from normal breast and tumor tissue prior to radical mastectomy. Ex vivo biopsies from normal and tumor tissue were collected immediately after surgical excision. The putative effects on gene expression of malignancy (tumor versus normal), surgical manipulation (post- versus pre-surgical) and interaction between the two (differences in effect of surgical manipulation on tumor and normal samples) were investigated simultaneously by Generalized Estimating Equation (GEE) analysis in this self-matched study.ResultsGene set enrichment analysis (GSEA) demonstrates a marked difference in effect of surgical manipulation on tumor compared to normal tissue. Interestingly, a large proportion of pathways affected by ischemia especially in tumor tissue are pathways considered to be specifically up regulated in tumor tissue compared to normal.ConclusionThe results of this study suggest that a large contribution to this differential expression originates from altered response to stress in tumor cells rather than merely representing in vivo differences. It is important to bear this in mind when using gene-expression analysis to deduce biological function, and when collecting material for gene expression profiling.
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