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ABSTRACT:
OTHER RELATED OMICS DATASETS IN: E-GEOD-10780
PROVIDER: PRJNA107463 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Analysis of 143 completely histologically-normal breast tissues resulted in the identification of a “malignancy risk” gene signature that may serve as a marker of subsequent risk of breast cancer development. Keywords: Tissue from breast cancer and adjacent regions
2009-03-09 | GSE10780 | GEO
Project description:Analysis of 143 completely histologically-normal breast tissues resulted in the identification of a âÂÂmalignancy riskâ gene signature that may serve as a marker of subsequent risk of breast cancer development. Experiment Overall Design: RNA was extracted from microdissected frozen breast tissues for gene array analysis
2009-03-15 | E-GEOD-10780 | biostudies-arrayexpress
Project description:Gene expression in histologically normal epithelium from breast cancer patients and cancer-free prophylactic mastectomy patients share a similar profile Introduction: We hypothesized that gene expression in histologically normal epithelium (NlEpi) would differ in breast cancer patients (HN) compared to usual-risk controls undergoing reduction mammoplasty (RM), and that gene expression in NlEpi from cancer-free prophylactic mastectomies from high-risk women (PM), would resemble HN gene expression. Methods: We analyzed gene expression in 73 NlEpi samples microdissected from frozen tissue. In 42 cases, we used Affymetrix HU133A microarrays to compare gene expression in 18 RM vs 18 age-matched HN (9 ER+, 9 ER-) and 6 PM. Data were validated with qPCR in 31 independent NlEpi samples (8 RM, 17 HN, 6 PM). Results: 98 probesets (86 genes) were differentially expressed between RM and HN samples. Perfoming supervised hierarchical analysis with these 98 probesets, PM and HN samples clustered together, away from RM samples. qPCR validation of independent samples was high (84%) and uniform in RM vs HN, and lower (58%), but more heterogeneous, in RM vs PM. The 86 genes were implicated in many processes including transcription and the MAPK pathway. Conclusion: Gene expression differs between NlEpi of cancer cases and controls. The cancer cases' profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes. We determined that 98 probesets significantly differed between reduction mammoplasty and histologically normal epithelium from breast cancer patients. We also found that the histologically normal epithelium from prophylactic mastectomy patients' gene expression was more similar to histologically normal epithelium from breast cancer patients' than to reduction mammoplasty patients' gene expression. These results demonstrate that gene expression differs between NlEpi of cancer cases and controls. The cancer casesâ?? profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes. 42 total laser capture microdissected histologically normal breast tissue samples were analyzed with Affymetrix HU133A microarrays. 36 samples were age-matched between reduction mammoplasty (n=18) and histologically normal epithelial samples from breast cancer patients (n=18; 9ER+, 9ER-). 6 histologically normal epithelial samples from prophylactic mastectomy patients were then compared to data generated from the original 36 sample comparison. Sample numbers correspond to individual patient samples.
2010-06-08 | E-GEOD-20437 | biostudies-arrayexpress
Project description:Gene expression in histologically normal epithelium from breast cancer patients and cancer-free prophylactic mastectomy patients share a similar profile Introduction: We hypothesized that gene expression in histologically normal epithelium (NlEpi) would differ in breast cancer patients (HN) compared to usual-risk controls undergoing reduction mammoplasty (RM), and that gene expression in NlEpi from cancer-free prophylactic mastectomies from high-risk women (PM), would resemble HN gene expression. Methods: We analyzed gene expression in 73 NlEpi samples microdissected from frozen tissue. In 42 cases, we used Affymetrix HU133A microarrays to compare gene expression in 18 RM vs 18 age-matched HN (9 ER+, 9 ER-) and 6 PM. Data were validated with qPCR in 31 independent NlEpi samples (8 RM, 17 HN, 6 PM). Results: 98 probesets (86 genes) were differentially expressed between RM and HN samples. Perfoming supervised hierarchical analysis with these 98 probesets, PM and HN samples clustered together, away from RM samples. qPCR validation of independent samples was high (84%) and uniform in RM vs HN, and lower (58%), but more heterogeneous, in RM vs PM. The 86 genes were implicated in many processes including transcription and the MAPK pathway. Conclusion: Gene expression differs between NlEpi of cancer cases and controls. The cancer cases' profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes. We determined that 98 probesets significantly differed between reduction mammoplasty and histologically normal epithelium from breast cancer patients. We also found that the histologically normal epithelium from prophylactic mastectomy patients' gene expression was more similar to histologically normal epithelium from breast cancer patients' than to reduction mammoplasty patients' gene expression. These results demonstrate that gene expression differs between NlEpi of cancer cases and controls. The cancer cases’ profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes.
2010-06-01 | GSE20437 | GEO
Project description:Emerging work has demonstrated that histologically normal (non-tumor) tissue adjacent to breast tumor tissue shows evidence of molecular alterations related to tumorigenesis, referred to as field cancerization effects. Although changes in DNA methylation are known to occur early in breast carcinogenesis and the landscape of breast tumor DNA methylation is profoundly altered compared with normal tissue, there have been limited efforts to identify DNA methylation field cancerization effects in histologically normal breast tissue adjacent to tumor. Matched tumor, histologically normal tissue of the ipsilateral breast (ipsilateral-normal), and histologically normal tissue of the contralateral breast (contralateral-normal) were obtained from nine women undergoing bilateral mastectomy. Laser capture microdissection was used to select breast epithelial cells from normal tissues, and neoplastic cells from tumor specimens for genome-scale measures of DNA methylation with the Illumina HumanMethylationEPIC array. We identified substantially more CpG loci that were differentially methylated between contralateral-normal breast and tumor tissue (63,271 CpG loci q < 0.01), than between ipsilateral-normal tissue and tumor (38,346 CpG loci q < 0.01). In addition, we identified differential methylation in ipsilateral-normal relative to contralateral-normal tissue (9,562 CpG loci p < 0.01). Hypomethylated loci in ipsilateral normal relative to contralateral were significantly enriched for breast cancer-relevant transcription factor binding sites including those for ESR1, FoxA1, and GATA3. Hypermethylated loci in ipsilateral-normal relative to contralateral-normal tissue were significantly enriched for CpG island shore regions.
2020-07-10 | GSE133985 | GEO
Project description:Samples were prospectively collected from patients with histologically normal surgical resection margins. 96 tissue samples (histologically normal margins, oral carcinoma and adjacent normal tissues) from 24 patients comprised the training set. Our study design was guided by the hypothesis that the expression of genes present in oral squamous cell carcinoma (OSCC) but not in healthy oral tissues would be indicative of recurrence in advance of histological alteration. We used meta-analysis of five published microarray data sets (GEO accession GDS2520, Kuriakose et al. 2004; GDS1584, Toruner et al. 2004; GSE6791, Pyeon et al. 2007; GSE9844, Ye et al. 2008; and GSE10121, Sticht et al. 2008), in conjunction with the current training set, to identify genes reliably over-expressed in OSCC. This reduced gene set was used to train a risk model to predict recurrence based on over-expression of a subset of these genes in histologically normal surgical resection margins. Validation of the risk signature was performed using quantitative real-time reverse-transcription PCR in an independent set of 136 samples from an independent cohort of 30 patients.
2011-08-03 | GSE31056 | GEO
Project description:Background: We hypothesize that important genomic differences between breast cancer subtypes occur early in carcinogenesis. Therefore, gene expression might distinguish histologically normal breast epithelium (NlEpi) from breasts containing estrogen receptor positive (ER+) compared with estrogen receptor negative (ER-) cancers. Methods: We examined gene expression in 46 cases of microdissected NlEpi from previously untreated women undergoing breast cancer surgery. From 30 age-matched cases (15 ER+, 15 ER-) we used Affymetryix U133A arrays. From 16 independent cases (9ER+, 7 ER-), we validated seven selected genes using qPCR. We then compared gene expression between NlEpi and invasive breast cancer using 4 publicly available datasets. Results: 216 probes (corresponding to 198 unique genes) distinguished the NlEpi from breasts with ER+ (NlEpiER+) compared to ER- cancers (NlEpiER-). These include genes characteristic of ER+ and ER- cancers themselves, (e.g., ESR1, GATA3, and CX3CL1, FABP7, respectively). QPCR validated the microarray results in both a sampling of the 30 original cases (84%) and all of the 16 independent cases (77%). Gene expression in NlEpiER+ and NlEPIERNlEpiER- resembled gene expression in ER+ and ER- cancers, respectively: 36%-53% of the genes or probes examined in each the 4 external datasets overlapped between NlEpi and the corresponding cancer subtype. Conclusions: Gene expression differs in NlEpi of breasts containing ER+ compared to ER- breast cancers. These differences echo differences in ER+ and ER- invasive cancers. Thus, breast cancer subtypes may be detectable before histologic abnormalities. NlEpi gene expression may help define subtype-specific risk signatures, identify initial subtype specific genomic differences, and suggest new targets for subtype-specific prevention and therapy. We determined that 216 probesets significantly differed between histologically normal epithelium from ER+ breast cancer patients and from ER- breast cancer patients, and that gene expression in each type of histologically normal epithelium resembles expression of the corresponding subtype of invasive breast cancer (i.e., ER+ or ER-). These findings suggest that characteristic features of breast cancer subtypes are detectable prior to any histologic abnormality. This suggestion has implications for understanding breast cancer biology and devising new tools for assessing breast cancer risk. 30 total laser capture microdissected histologically normal breast tissue samples were analyzed with Affymetrix HU133A microarrays. All samples were age-matched between histologically normal epithelial samples from ER+ breast cancer patients (n=15) and histologically normal epithelial samples from ER- breast cancer patients (n=15). Sample numbers correspond to individual patient samples. Of the 4 publicly available datasets mentioned above, the only dataset with a GEO number was GSE3494, corresponding to the Miller dataset. The supplementary file below lists the 251 Samples used from the GSE3494 study. We did not reanalyze the data - there was no change made to the Miller dataset; we only used these data for confirmation of our own dataset.
2010-12-07 | E-GEOD-21947 | biostudies-arrayexpress
Project description:Samples were prospectively collected from patients with histologically normal surgical resection margins. 96 tissue samples (histologically normal margins, oral carcinoma and adjacent normal tissues) from 24 patients comprised the training set. Our study design was guided by the hypothesis that the expression of genes present in oral squamous cell carcinoma (OSCC) but not in healthy oral tissues would be indicative of recurrence in advance of histological alteration. We used meta-analysis of five published microarray data sets (GEO accession GDS2520, Kuriakose et al. 2004; GDS1584, Toruner et al. 2004; GSE6791, Pyeon et al. 2007; GSE9844, Ye et al. 2008; and GSE10121, Sticht et al. 2008), in conjunction with the current training set, to identify genes reliably over-expressed in OSCC. This reduced gene set was used to train a risk model to predict recurrence based on over-expression of a subset of these genes in histologically normal surgical resection margins. Validation of the risk signature was performed using quantitative real-time reverse-transcription PCR in an independent set of 136 samples from an independent cohort of 30 patients. This was a case-only design involving a training set of 23 tumors and 73 margins from 24 patients with squamous cell carcinoma of the tongue.
2011-08-02 | E-GEOD-31056 | biostudies-arrayexpress
Project description:Correlated metabolomic, genomic, and histologic phenotypes in histologically normal breast tissue
| PRJNA437646 | ENA
Project description:Genome wide DNA methylation profiling of fresh frozen, histologically normal-appearing breast tissue from the Normal Breast Study (NBS). The Illumina HumanMethylation450 BeadChip was used to obtain DNA methylation profiles for 90 samples, including “current”, “former” and never users of HRT.
2017-12-19 | GSE108213 | GEO