Gene expression analysis of pre-defined sets of neoplastic tissues
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE9662 | GEO | 2008/11/19
SECONDARY ACCESSION(S): PRJNA103537
REPOSITORIES: GEO
Similar Datasets
Project description:To identify a group of genes, characteristic of a single neoplasia and determinant for the risk to relapse, we have performed gene expression analysis of ductal breast carcinoma samples using Affymetrix oligonucletide microarray (HU133A). Biopses from 60 patients, 30 good prognosis (desease free from six to ten years after surgical treatment) and 30 poor prognosis, have been analyzed. From each group we have created six homogeneous pools to show, during the analysis, only genes expressed in a greatly different way. A reduced number of cases has been used to avoid dilution of genes expressed only in few samples. Analysis have identified 77 candidate genes with a specific ontological distribution that contained some genes that were linked to breast cancer by previous studies. Microarray results validation has been performed by real-time PCR analysis on 127 single cases of breast cancer. Gene function study and literature data allow to define our candidate genes as potential markers of prognosis. Keywords: Breast cancer gene expression analysis From a group of 130 frozen tumor samples, 30 cases of ductal invasive carcinoma with recurrence within 72 months from surgery (high-risk) and 30 without recurrence (low-risk) were selected for microarray analysis. From each group, 6 RNA pools of 5 samples each were prepared and analyzed on GeneChip Human Genome U133A oligonucleotide microarrays. Hybridizations were performed in technical duplicates, in two experimental sessions.
2008-11-19 | E-GEOD-9662 | biostudies-arrayexpress
Project description:In the study presented here, a consecutively operated, well-defined cohort of 30 triple-negative breast cancer cases with neoadjuvant chemotherapy, followed up more than five years, was used to acquire TP53 signature composed of a total of 33 genes. Combining the response to NAC and the TP53signature score in triple-negative breast cancer was able to predict an unfavorable prognosis.
2021-12-10 | GSE190275 | 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: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:Genome-wide location analysis of trimethyl-K4 histone H3 and RNA polymerase II binding in interferon gamma-induced for 30 minutes HeLa cells and uninduced HeLa cells was done using 50mer oligonucletide probes at 38bp intervals tiling over non-repetitive ENCODE regions (HG17, NCBI build 35). Keywords: ChIP-chip
2005-06-15 | GSE2813 | GEO
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:T-cell prolymphocytic leukemina (T-PLL) is an agressive lymphoma derived from mature T-cells, which is in most cases characterized by the presence of an inv(14)(q11q32) and a characteristic pattern of secondary chromosomal abberations. We used microarrays to compare the transcriptomes of eight immunomagnetically purified CD3+ normal donor derived peripheral blood cells with five highly purified inv(14)-positive T-PLL blood samples. Keywords: desease state analysis
2007-08-27 | GSE5788 | 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.
2013-03-26 | GSE41400 | GEO
Project description:Alternative promoters (APs) occur in >30% protein-coding genes and contribute to proteome diversity. However, large-scale analyses of AP regulation are lacking, and little is known about their potential physiopathologic significance. To better understand the transcriptomic impact of estrogens, which play a major role in breast cancer, we analyzed gene and AP regulation by estradiol in MCF7 cells using pan-genomic exon arrays. We thereby identified novel estrogen-regulated genes, and determined the regulation of AP-encoded transcripts in 150 regulated genes. In <30% cases, APs were regulated in a similar manner by estradiol, while in >70% cases, they were regulated differentially. The patterns of AP regulation correlated with the patterns of estrogen receptor (ERα) and CCCTC-binding factor (CTCF) binding sites at regulated gene loci. Interestingly, among genes with differentially regulated APs, we identified cases where estradiol regulated APs in an opposite manner, sometimes without affecting global gene expression levels. This promoter switch was mediated by the DDX5/DDX17 family of ERα coregulators. Finally, genes with differentially regulated promoters were preferentially involved in specific processes (e.g., cell structure and motility, and cell cycle). We show in particular that isoforms encoded by the NET1 gene APs, which are inversely regulated by estradiol, play distinct roles in cell adhesion and cell cycle regulation, and that their expression is differentially associated with prognosis in ER+ breast cancer. Altogether, this study identifies the patterns of AP regulation in estrogen-regulated genes, demonstrates the contribution of AP-encoded isoforms to the estradiol-regulated transcriptome, as well as their physiopathologic significance in breast cancer.
2010-02-17 | GSE20342 | GEO
Project description:Genome-wide location analysis of trimethyl-K4 histone H3 and RNA polymerase II binding in interferon gamma-induced for 30 minutes HeLa cells and uninduced HeLa cells was done using 50mer oligonucletide probes at 38bp intervals tiling over non-repetitive ENCODE regions (HG17, NCBI build 35). There are three replicates for each marker at each state.
2005-06-15 | E-GEOD-2813 | biostudies-arrayexpress