EGAS00001000403-sc-20130904 - samples
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ABSTRACT:
PROVIDER: EGAD00001000661 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Bespoke validation experiments will be performed on ER+ Breast Cancer cases to confirm the presence of mutations found in whole genome sequencing.
| EGAS00001000403 | EGA
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.
2010-12-07 | GSE21947 | GEO
Project description:Background: Unlike estrogen receptor (ER) negative breast cancer, ER-positive breast cancer outcomes are less influenced by lymphocyte content, indicating a need for investigation of checkpoint targets and immune tolerance mechanisms that may be specific to this disease subset. Methods: A supervised analysis of microarray data from the Alliance/ACOSOG Z1031 trial was conducted to identify upregulated genes in Luminal B breast cancers that exhibited persistent tumor proliferation despite aromatase inhibitor therapy (33 cases Ki67 >10%) versus Luminal B breast cancers that were more sensitive (33 cases Ki67 <10%). Results: This study identified thirty genes (Pearson’s r>0.4 with Ki67 as a continuous variable). These genes were enriched for immune tolerance processes (p<0.005) and three targetable immune checkpoint components were upregulated in resistant cases: IDO1, LAG3, and PD1. High IDO1 mRNA associated with poor prognosis in ER+ disease across two independent cohorts (METABRIC and TCGA). Furthermore, analysis indicated IDO1 was tightly associated with IFN-γ/STAT1 signaling. As a composite immune tolerance signature, expression of these pathway components associated with higher baseline Ki67 and lower ER, PgR levels and poor disease specific survival. In tissue microarray analysis, IDO1 was observed in stromal cells and tumor-associated macrophages, with a higher incidence in Luminal B cases. Further mRNA and tissue microarray analyses associated IDO1 expression with the presence of macrophages (M1 by CIBERSORT) and regulatory T cells. Conclusion: Targetable immune-checkpoint components are upregulated in majority of neoadjuvant endocrine therapy resistant Luminal B cases. Our findings suggests potential for immune checkpoint inhibitors in poor outcome ER+ breast cancer.
2020-04-13 | GSE136644 | GEO
Project description:The contralateral unaffected breast of women with unilateral breast cancer (cases) is a good model for defining subtype-specific risk since women with ER-negative index primaries are at high risk for subsequent ER-negative primary cancers. We performed random fine needle aspiration (rFNA) of the unaffected breasts of cases; samples from 30 subjects (15 ER-positive and 15 ER-negative cases matched for age, race and menopausal status), were used for Illumina expression array analysis. In this study, we have examined gene expression profiles in random fine needle aspirate (rFNA) samples from the contralateral breasts of women with new unilateral breast cancer (cases) to seek candidate panels of ER-specific risk biomarkers. On a discovery set of 30 women, we have identified gene expression differences in the contralateral breast that associate with ER+ or ER- index primary tumors.
2013-03-26 | E-GEOD-41400 | biostudies-arrayexpress
Project description:The contralateral unaffected breast of women with unilateral breast cancer (cases) is a good model for defining subtype-specific risk since women with ER-negative index primaries are at high risk for subsequent ER-negative primary cancers. We performed random fine needle aspiration (rFNA) of the unaffected breasts of cases; samples from 30 subjects (15 ER-positive and 15 ER-negative cases matched for age, race and menopausal status), were used for Illumina expression array analysis.
2013-03-26 | GSE41400 | GEO
Project description:Expression profiling of papillary carcinoma of the breast and grade- and ER-matched cases of invasive ductal breast cancer To identify differential expression between papillary carcinomas of the breast and grade- and ER-matched invasive ductal breast cancers, we performed expression profiling of 16 cases of papillary carcinomas of the breast and 16 cases of grade- and ER-matched invasive ducatal carcinoma of no special subtype. We further reviewed the papillary carcinomas of the breast and classified them into 3 subtypes, namely, invasive papillary carcinoma, encapsulated papillary carcinoma and solid papillary carcinoma. We also performed a hypothesis-generating comparison of differential expression between the 3 subtypes of papillary carcinoma of the breast.
2014-06-20 | GSE55639 | GEO
Project description:Expression profiling of papillary carcinoma of the breast and grade- and ER-matched cases of invasive ductal breast cancer To identify differential expression between papillary carcinomas of the breast and grade- and ER-matched invasive ductal breast cancers, we performed expression profiling of 16 cases of papillary carcinomas of the breast and 16 cases of grade- and ER-matched invasive ducatal carcinoma of no special subtype. We further reviewed the papillary carcinomas of the breast and classified them into 3 subtypes, namely, invasive papillary carcinoma, encapsulated papillary carcinoma and solid papillary carcinoma. We also performed a hypothesis-generating comparison of differential expression between the 3 subtypes of papillary carcinoma of the breast. Expression profiling of 16 cases of papillary carcinioma of the brest and 16 cases of invasive ducal carcinomas using the Illumina HT-12 v4 arrays
2014-06-20 | E-GEOD-55639 | biostudies-arrayexpress
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:We have analyzed, using DNA microarrays, putative differences in gene-expression level between hereditary BRCA1 mutation-linked and sporadic breast cancer. Our results show that a previously reported marked difference between BRCA1-mutation linked and sporadic breast cancer was probably due to uneven stratification of samples with different ER status and basal-like versus luminal-like subtype. We observed that apparent difference between BRCA1-linked and other types of breast cancer found in univariate analysis was diminished when data were corrected for ER status and molecular subtype in multivariate analyses. In fact, the difference in gene expression pattern of BRCA1-mutated and sporadic cancer is very discrete. These conclusions were supported by the results of Q-PCR validation. We also found that BRCA1 gene inactivation due to promoter hypermethylation had similar effect on general gene expression profile as mutation-induced protein truncation. This suggests that in the molecular studies of hereditary breast cancer, BRCA1 gene methylation should be recognized and considered together with gene mutation. We analyzed 35 breast cancer specimens. Surgical samples obtained during mastectomy were flash-frozen in liquid nitrogen and stored at -80°C. Only samples from patients without neoadjuvant chemotherapy were used in this study as chemotherapy may seriously affect gene expression profile. All tissue samples were collected at the Pomeranian Medical University in Szczecin. Seventeen tumor samples were collected from patients with hereditary breast cancer: 12 were derived from tumors affecting women with hereditary BRCA1 mutation, the only one from a woman with BRCA2 mutation, while another eight cases had familial history of breast/ovarian cancer, but were negative for the BRCA1/2 mutations (so called BRCAx cases). Proportion of BRCA1 and BRCA2 mutated tumors was typical for the Polish population. Ten samples were derived from patients with apparently sporadic disease (no familial history of cancer) while 4 patients had a history of familial cancer aggregation (FCA) but without prevalence of breast/ovarian cancers. Thus, these samples were merged with sporadic samples in most of the analyses. All BRCA1 mutation-linked tumors in our study were negative for estrogen receptor (by immunohistochemistry, standard procedures for ER, PGR and HER2 staining were applied), while the only BRCA2-mutated tumor was ER-positive. There were 26 ductal and 5 medullary carcinomas within the study group, which is consistent with the distribution of histopathological types in BRCA1 mutation carriers. Patients were diagnosed at stage T1-2, N0-1 and M0. Caution: this submission contains the data from 6 microarrays done on the normal/pathologically unchanged breast tissue from breast cancer patiets. The data from normal tissues was not analyzed in the paper BRCA1-related gene signature in breast cancer is strongly influenced by ER status and molecular type by Lisowska et al., 2011, Front Biosci (Elite Ed). 2011 Jan 1;3:125-36
2013-09-05 | E-GEOD-50567 | biostudies-arrayexpress
Project description:The ESR1 ligand binding domain activating mutations are the most prevalent genetic mechanism of acquired endocrine resistance in metastatic hormone receptor-positive breast cancer. These mutations confer endocrine resistance that remains estrogen receptor (ER) dependent. We hypothesized that in the presence of the ER mutations, continued ER blockade with endocrine therapies that target mutant ER is essential for tumor suppression even with chemotherapy treatment. Here, we conducted comprehensive pre-clinical in vitro and in vivo experiments testing the efficacy of adding fulvestrant to fluorouracil (5FU) and the 5FU pro-drug, capecitabine, in models of wild-type (WT) and mutant ER. Our findings revealed that while this combination had an additive effect in the presence of WT-ER, in the presence of the Y537S ER mutation there was synergy. Notably, these effects were not seen with the combination of 5FU and selective estrogen receptor modulators, such as tamoxifen, or in the absence of intact P53. Likewise, in a patient derived xenograft (PDX) harboring a Y537S ER mutation the addition of fulvestrant to capecitabine potentiated tumor suppression. Moreover, multiplex immunofluorescence revealed that this effect was due to decreased cell proliferation in all cells expressing ER and was not dependent on the degree of ER expression. Taken together, these results support the clinical investigation of the combination of ER antagonists with capecitabine in patients with metastatic hormone receptor-positive breast cancer who have experienced progression on endocrine therapy and targeted therapies, particularly in the presence of an ESR1 activating mutation.
2024-06-01 | GSE266932 | GEO