Molecular features of subtype-specific progression from ductal carcinoma in situ to invasive breast cancer [gene expression data]
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Robert Lesurf
PROVIDER: E-GEOD-59246 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Breast cancer consists of at least five main molecular âintrinsicâ subtypes, which are reflected in both pre-invasive and invasive disease. Although previous studies have suggested that many of the molecular features of invasive breast cancer are established early, it is unclear what mechanisms drive progression, and whether the mechanisms of progression are dependent or independent of subtype. We have generated mRNA, miRNA and DNA copy number profiles from a total of 59 in situ lesions and 85 invasive tumors, in order to comprehensively identify those genes, signaling pathways, processes, and cell types that are involved in breast cancer progression. Our work provides evidence that there are molecular features associated with disease progression that are unique to the intrinsic subtypes. We additionally establish subtype-specific signatures that are able to identify a small proportion of pre-invasive tumors with expression profiles that resemble invasive carcinoma, indicating a higher likelihood of future disease progression. One-color design, totaling 48 arrays and 41 unique tissues. Arrays consist of 4 normal controls (1 unique), 28 DCIS lesions (26 unique), and 16 small invasive breast cancers (14 unique).
2016-07-07 | E-GEOD-59247 | biostudies-arrayexpress
Project description:Breast cancer consists of at least five main molecular “intrinsic” subtypes, which are reflected in both pre-invasive and invasive disease. Although previous studies have suggested that many of the molecular features of invasive breast cancer are established early, it is unclear what mechanisms drive progression, and whether the mechanisms of progression are dependent or independent of subtype. We have generated mRNA, miRNA and DNA copy number profiles from a total of 59 in situ lesions and 85 invasive tumors, in order to comprehensively identify those genes, signaling pathways, processes, and cell types that are involved in breast cancer progression. Our work provides evidence that there are molecular features associated with disease progression that are unique to the intrinsic subtypes. We additionally establish subtype-specific signatures that are able to identify a small proportion of pre-invasive tumors with expression profiles that resemble invasive carcinoma, indicating a higher likelihood of future disease progression.
2016-07-07 | GSE59246 | GEO
Project description:Breast cancer consists of at least five main molecular “intrinsic” subtypes, which are reflected in both pre-invasive and invasive disease. Although previous studies have suggested that many of the molecular features of invasive breast cancer are established early, it is unclear what mechanisms drive progression, and whether the mechanisms of progression are dependent or independent of subtype. We have generated mRNA, miRNA and DNA copy number profiles from a total of 59 in situ lesions and 85 invasive tumors, in order to comprehensively identify those genes, signaling pathways, processes, and cell types that are involved in breast cancer progression. Our work provides evidence that there are molecular features associated with disease progression that are unique to the intrinsic subtypes. We additionally establish subtype-specific signatures that are able to identify a small proportion of pre-invasive tumors with expression profiles that resemble invasive carcinoma, indicating a higher likelihood of future disease progression.
2016-07-07 | GSE59247 | GEO
Project description:The purpose of this study was to understand the genomic and metabolomic changes in the breast tissue microenvironment at various stages of cancer development and progression (i.e. normal breast, DCIS, benign disease and invasive cancer). To understand the way in which metabolic microenvironments evolve with breast cancer, this study analyzed normal breast tissue adjacent to benign and malignant lesions at various stages of cancer development and studied samples adjacent to invasive cancers of distinct breast cancer subtypes.
| ST000053 | MetabolomicsWorkbench
Project description:Ductal carcinoma in situ (DCIS) is a non-invasive form of breast cancer where cells restricted to the ducts exhibit an atypical phenotype. Some DCIS lesions are believed to rapidly transit to invasive ductal carcinomas (IDCs), while others remain unchanged. Existing classification systems for DCIS fail to identify those lesions that transit to IDC. We studied gene expression patterns of 31 pure DCIS, 36 pure invasive cancers and 42 cases of mixed diagnosis (invasive cancer with an in situ component) using Agilent Whole Human Genome Oligo Microarrays 44k. Six normal breast tissue samples were also included as controls. qRT-PCR was used for validation. All DCIS and invasive samples could be classified into the intrinsic molecular subtypes defined for invasive breast cancer. Hierarchical clustering establishes that samples group by intrinsic subtype, and not by diagnosis. We observed heterogeneity in the transcriptomes among DCIS of high histological grade and identified a distinct subgroup containing seven of the 31 DCIS samples with gene expression characteristics more similar to advanced tumours. A set of genes independent of grade, ER-status and HER2-status was identified by logistic regression that univariately classified a sample as belonging to this distinct DCIS subgroup. qRT-PCR of single markers clearly separated this DCIS subgroup from the other DCIS, and contains samples from several histopathological and intrinsic molecular subtypes. The genes that differentiate between these two types of DCIS suggest several processes related to the re-organisation of the microenvironment. This raises interesting possibilities for identification of DCIS lesions both with and without invasive characteristics, which potentially could be used in clinical assessment of a woman's risk of progression, and lead to improved management that would avoid the current over- and under-treatment of patients. Breast cancer samples, 31 pure DCIS patients, 36 IDC patients, 42 mixed and 6 normal.
2010-12-24 | E-GEOD-26304 | biostudies-arrayexpress
Project description:Breast cancer consists of at least five main molecular “intrinsic” subtypes, which are reflected in both pre-invasive and invasive disease. Although previous studies have suggested that many of the molecular features of invasive breast cancer are established early, it is unclear what mechanisms drive progression, and whether the mechanisms of progression are dependent or independent of subtype. We have generated mRNA, miRNA and DNA copy number profiles from a total of 59 in situ lesions and 85 invasive tumors, in order to comprehensively identify those genes, signaling pathways, processes, and cell types that are involved in breast cancer progression. Our work provides evidence that there are molecular features associated with disease progression that are unique to the intrinsic subtypes. We additionally establish subtype-specific signatures that are able to identify a small proportion of pre-invasive tumors with expression profiles that resemble invasive carcinoma, indicating a higher likelihood of future disease progression.
| EGAS00001001866 | 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: 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:Ductal carcinoma in situ (DCIS) is a non-invasive form of breast cancer where cells restricted to the ducts exhibit an atypical phenotype. Some DCIS lesions are believed to rapidly transit to invasive ductal carcinomas (IDCs), while others remain unchanged. Existing classification systems for DCIS fail to identify those lesions that transit to IDC. We studied gene expression patterns of 31 pure DCIS, 36 pure invasive cancers and 42 cases of mixed diagnosis (invasive cancer with an in situ component) using Agilent Whole Human Genome Oligo Microarrays 44k. Six normal breast tissue samples were also included as controls. qRT-PCR was used for validation. All DCIS and invasive samples could be classified into the intrinsic molecular subtypes defined for invasive breast cancer. Hierarchical clustering establishes that samples group by intrinsic subtype, and not by diagnosis. We observed heterogeneity in the transcriptomes among DCIS of high histological grade and identified a distinct subgroup containing seven of the 31 DCIS samples with gene expression characteristics more similar to advanced tumours. A set of genes independent of grade, ER-status and HER2-status was identified by logistic regression that univariately classified a sample as belonging to this distinct DCIS subgroup. qRT-PCR of single markers clearly separated this DCIS subgroup from the other DCIS, and contains samples from several histopathological and intrinsic molecular subtypes. The genes that differentiate between these two types of DCIS suggest several processes related to the re-organisation of the microenvironment. This raises interesting possibilities for identification of DCIS lesions both with and without invasive characteristics, which potentially could be used in clinical assessment of a woman's risk of progression, and lead to improved management that would avoid the current over- and under-treatment of patients.
2010-12-24 | GSE26304 | 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