Dataset Information

Breast field cancerization: isolation and comparison of telomerase-expressing cells in tumor and tumor adjacent, histologically normal breast tissue.

ABSTRACT: Telomerase stabilizes chromosomes by maintaining telomere length, immortalizes mammalian cells, and is expressed in more than 90% of human tumors. However, the expression of human telomerase reverse transcriptase (hTERT) is not restricted to tumor cells. We have previously shown that a subpopulation of human mammary epithelial cells (HMEC) in tumor-adjacent, histologically normal (TAHN) breast tissues expresses hTERT mRNA at levels comparable with levels in breast tumors. In the current study, we first validated a reporter for measuring levels of hTERT promoter activity in early-passage HMECs and then used this reporter to compare hTERT promoter activity in HMECs derived from tumor and paired TAHN tissues 1, 3, and 5 cm from the tumor (TAHN-1, TAHN-3, and TAHN-5, respectively). Cell sorting, quantitative real-time PCR, and microarray analyses showed that the 10% of HMECs with the highest hTERT promoter activity in both tumor and TAHN-1 tissues contain more than 95% of hTERT mRNA and overexpress many genes involved in cell cycle and mitosis. The percentage of HMECs within this subpopulation showing high hTERT promoter activity was significantly reduced or absent in TAHN-3 and TAHN-5 tissues. We conclude that the field of "normal tissue" proximal to the breast tumors contains a population of HMECs similar in hTERT expression levels and in gene expression to the HMECs within the tumor mass and that this population is significantly reduced in tissues more distal to the tumor.

SUBMITTER: Trujillo KA

PROVIDER: S-EPMC3249616 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Breast field cancerization: isolation and comparison of telomerase-expressing cells in tumor and tumor adjacent, histologically normal breast tissue.

Trujillo Kristina A KA Hines William C WC Vargas Keith M KM Jones Anna C AC Joste Nancy E NE Bisoffi Marco M Griffith Jeffrey K JK

Molecular cancer research : MCR 20110720 9

Telomerase stabilizes chromosomes by maintaining telomere length, immortalizes mammalian cells, and is expressed in more than 90% of human tumors. However, the expression of human telomerase reverse transcriptase (hTERT) is not restricted to tumor cells. We have previously shown that a subpopulation of human mammary epithelial cells (HMEC) in tumor-adjacent, histologically normal (TAHN) breast tissues expresses hTERT mRNA at levels comparable with levels in breast tumors. In the current study, w ...[more]

PMID: 21775421

Similar Datasets

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.

Project description:BackgroundAdenocarcinoma (ADC) and squamous cell carcinoma (SCC) are the most prevalent histological types among lung cancers. Distinguishing between these subtypes is critically important because they have different implications for prognosis and treatment. Normally, histopathological analyses are used to distinguish between the two, where the tissue samples are collected based on small endoscopic samples or needle aspirations. However, the lack of cell architecture in these small tissue samples hampers the process of distinguishing between the two subtypes. Molecular profiling can also be used to discriminate between the two lung cancer subtypes, on condition that the biopsy is composed of at least 50 % of tumor cells. However, for some cases, the tissue composition of a biopsy might be a mix of tumor and tumor-adjacent histologically normal tissue (TAHN). When this happens, a new biopsy is required, with associated cost, risks and discomfort to the patient. To avoid this problem, we hypothesize that a computational method can distinguish between lung cancer subtypes given tumor and TAHN tissue.MethodsUsing publicly available datasets for gene expression and DNA methylation, we applied four classification tasks, depending on the possible combinations of tumor and TAHN tissue. First, we used a feature selector (ReliefF/Limma) to select relevant variables, which were then used to build a simple naïve Bayes classification model. Then, we evaluated the classification performance of our models by measuring the area under the receiver operating characteristic curve (AUC). Finally, we analyzed the relevance of the selected genes using hierarchical clustering and IPA® software for gene functional analysis.ResultsAll Bayesian models achieved high classification performance (AUC > 0.94), which were confirmed by hierarchical cluster analysis. From the genes selected, 25 (93 %) were found to be related to cancer (19 were associated with ADC or SCC), confirming the biological relevance of our method.ConclusionsThe results from this study confirm that computational methods using tumor and TAHN tissue can serve as a prognostic tool for lung cancer subtype classification. Our study complements results from other studies where TAHN tissue has been used as prognostic tool for prostate cancer. The clinical implications of this finding could greatly benefit lung cancer patients.

Project description:BackgroundEarlier work identified specific tumor-promoting abnormalities that are shared between lung cancers and adjacent normal bronchial epithelia. We sought to characterize the yet unknown global molecular and adjacent airway field cancerization (FC) in early-stage non-small cell lung cancer (NSCLC).MethodsWhole-transcriptome expression profiling of resected early-stage (I-IIIA) NSCLC specimens (n = 20) with matched tumors, multiple cytologically controlled normal airways with varying distances from tumors, and uninvolved normal lung tissues (n = 194 samples) was performed using the Affymetrix Human Gene 1.0 ST platform. Mixed-effects models were used to identify differentially expressed genes among groups. Ordinal regression analysis was performed to characterize site-dependent airway expression profiles. All statistical tests were two-sided, except where noted.ResultsWe identified differentially expressed gene features (n = 1661) between NSCLCs and airways compared with normal lung tissues, a subset of which (n = 299), after gene set enrichment analysis, statistically significantly (P < .001) distinguished large airways in lung cancer patients from airways in cancer-free smokers. In addition, we identified genes (n = 422) statistically significantly and progressively differentially expressed in airways by distance from tumors that were found to be congruently modulated between NSCLCs and normal lung tissues. Furthermore, LAPTM4B, with statistically significantly increased expression (P < .05) in airways with shorter distance from tumors, was upregulated in human immortalized cells compared with normal bronchial epithelial cells (P < .001) and promoted anchorage-dependent and -independent lung cancer cell growth.ConclusionsThe adjacent airway FC comprises both site-independent profiles as well as gradient and localized airway expression patterns. Profiling of the airway FC may provide new insights into NSCLC oncogenesis and molecular tools for detection of the disease.

Dataset Information

Breast field cancerization: isolation and comparison of telomerase-expressing cells in tumor and tumor adjacent, histologically normal breast tissue.

Publications

Breast field cancerization: isolation and comparison of telomerase-expressing cells in tumor and tumor adjacent, histologically normal breast tissue.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets