Subtype specific progression from DCIS to invasive breast cancer
Ontology highlight
ABSTRACT:
PROVIDER: EGAS00001001866 | EGA |
REPOSITORIES: EGA
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 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 105 arrays and 103 unique tissues. Arrays consist of 3 normal controls (1 unique), 46 DCIS lesions (46 unique), and 56 small invasive breast cancers (56 unique).
2016-07-07 | E-GEOD-59246 | 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 | GSE59247 | 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 | GSE59246 | GEO
Project description:Background: Ductal carcinoma in-situ (DCIS) is a pre-invasive form of invasive breast cancer (IBC). Due to improved breast cancer screening, it now accounts for ~25% of all breast cancers. While the treatment success rates are over 90%, this comes at the cost of considerable morbidity, considering that the majority of DCIS never become invasive and our understanding of the molecular changes occurring in DCIS that predispose to invasive disease is limited. The aim of this study is to characterize molecular changes that occur in DCIS, with the goal of improving DCIS risk stratification. Methods: We identified and obtained a total of 197 breast tissue samples from 5 institutions (93 DCIS progressors, 93 DCIS non-progressors, and 11 adjacent normal breast tissues) that had at least 10-year follow-up. We isolated DNA and RNA from archival tissue blocks and characterized genome-wide mRNA expression, DNA methylation, DNA copy number variation, and RNA splicing variation. Results: We obtained all four genomic data sets in 122 of the 197 samples. Our intrinsic expression subtype-stratified analyses identified multiple molecular differences both between DCIS subtypes and between DCIS and IBC. While there was heterogeneity in molecular signatures and outcomes within intrinsic subtypes, several gene sets that differed significantly between progressing and non-progressing DCIS were identified by Gene Set Enrichment Analysis. Conclusions: DCIS is a molecularly highly heterogenous disease with variable outcomes, and the molecular events determining DCIS disease progression remain poorly defined. Our genome-wide multi-omic survey documents DCIS-associated alterations and reveals molecular heterogeneity within the intrinsic DCIS subtypes. Further studies investigating intrinsic subtype-stratified characteristics and molecular signatures are needed to determine if these may be exploitable for risk assessment and mitigation of DCIS progression. The highly significant associations of specific gene sets with IBC progression revealed by our Gene Set Enrichment Analysis may lend themselves to the development of a prognostic molecular score, to be validated on independent DCIS cohorts.
2024-11-15 | GSE281307 | GEO
Project description:Background: Ductal carcinoma in-situ (DCIS) is a pre-invasive form of invasive breast cancer (IBC). Due to improved breast cancer screening, it now accounts for ~25% of all breast cancers. While the treatment success rates are over 90%, this comes at the cost of considerable morbidity, considering that the majority of DCIS never become invasive and our understanding of the molecular changes occurring in DCIS that predispose to invasive disease is limited. The aim of this study is to characterize molecular changes that occur in DCIS, with the goal of improving DCIS risk stratification. Methods: We identified and obtained a total of 197 breast tissue samples from 5 institutions (93 DCIS progressors, 93 DCIS non-progressors, and 11 adjacent normal breast tissues) that had at least 10-year follow-up. We isolated DNA and RNA from archival tissue blocks and characterized genome-wide mRNA expression, DNA methylation, DNA copy number variation, and RNA splicing variation. Results: We obtained all four genomic data sets in 122 of the 197 samples. Our intrinsic expression subtype-stratified analyses identified multiple molecular differences both between DCIS subtypes and between DCIS and IBC. While there was heterogeneity in molecular signatures and outcomes within intrinsic subtypes, several gene sets that differed significantly between progressing and non-progressing DCIS were identified by Gene Set Enrichment Analysis. Conclusions: DCIS is a molecularly highly heterogenous disease with variable outcomes, and the molecular events determining DCIS disease progression remain poorly defined. Our genome-wide multi-omic survey documents DCIS-associated alterations and reveals molecular heterogeneity within the intrinsic DCIS subtypes. Further studies investigating intrinsic subtype-stratified characteristics and molecular signatures are needed to determine if these may be exploitable for risk assessment and mitigation of DCIS progression. The highly significant associations of specific gene sets with IBC progression revealed by our Gene Set Enrichment Analysis may lend themselves to the development of a prognostic molecular score, to be validated on independent DCIS cohorts.
2024-11-15 | GSE281303 | GEO
Project description:Epithelial ovarian cancer is morphologically and clinically heterogeneous. Transcriptional profiling has revealed molecular subtypes (referred to as M-bM-^@M-^\C-signaturesM-bM-^@M-^]) that correlate to biological as well as clinical features. We aimed to determine gene expression differences between malignant, benign and borderline serous ovarian tumors, and to investigate similarities to the intrinsic molecular subtypes of breast cancer. Global gene expression profiling was performed using Illumina's HT12 Bead Arrays and applied to 59 fresh-frozen ovarian tumors. SAM analysis revealed enrichment of cell cycel processes among the malignant tumors, in line with malignant tumors being highly proliferative. The borderline tumors were split between the malignant and benign tumor clusters, indicating that borderline tumors have both malignant and benign features. Furthermore, nearest centroid classification was performed applying previously published gene profiles for the ovarian cancer C-signatures and the intrinsic breast cancer subtypes, respectively, and showed significant correlations between the malignant serous tumors and the highly aggressive C1, C2 and C4 ovarian cancer signatures, and the basal-like breast cancer subtype. The benign and borderline serous tumors together were significantly correlated to the normal-like breast cancer subtype and the ovarian cancer C3 signature. The borderline tumors, on the other hand, correlated significantly to the Luminal A breast cancer subtype. These findings remained when analyzed in a large, independent dataset. The data in this study link the transcriptional profiles of serous ovarian cancer to the intrinsic molecular subtypes of breast cancer, in line with the shared clinical and molecular features between high-grade serous ovarian cancer and basal-like breast cancer, including an aggressive phenotype, frequent TP53 mutations and a high degree of genomic instability, and suggest that biomarkers and targeted therapies may overlap between these subsets of ovarian and breast cancers. Finally, the link between benign and borderline ovarian cancer and luminal breast cancer may indicate endocrine responsiveness in a subset of ovarian cancers. Total RNA obtained from serous ovarian adenocarcinomas, adenomas and borderline tumors. Gene expression profiling using Illumina's HT12 v4 bead arrays. Application of ovarian cancer molecular subtypes and intrinsic breast cancer subtypes using nearest centroid classification. KRAS and BRAF mutation analyses in the malignant and borderline tumors.
2014-08-15 | E-GEOD-57477 | 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. 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:Cancer development and progression depend on tumor cell intrinsic factors, the tumor microenvironment and host characteristics. Despite the identification of the plasticity of adipocytes, the primary breast stromal cells, both in physiology and cancer, we lack a complete understanding of mechanisms that regulate adipocyte-tumor cell crosstalk. Here we dissected the breast cancer crosstalk with adipocytes and studied relevant molecules. We identified that the ability of breast cancer cells to dedifferentiate adipocytes is intrinsic subtype-dependent, with all breast cancer subtypes, except for HER2+ER+ subtype, capable of inducing this phenomenon. Crosstalk between breast cancer cells and adipocytes in vitro increased cancer stem-like features and recruitment of pro-tumorigenic immune cells, through chemokine production. Serum amyloid A1 (SAA1) was in vitro identified as a regulator of the adipocyte dedifferentiation program in triple-negative breast cancer (TNBC) through CD36 and P2XR7 signaling. In human TNBCs, SAA1 expression was associated with CAA infiltration, inflammation, stimulated lipolysis, stem-like properties and distinct tumor immune microenvironment. Our findings provide evidence that interaction between tumor cells and adipocytes through SAA1 release is relevant to the aggressiveness of TNBC, potentially supporting its targeting.
2024-01-15 | PXD041186 | Pride
Project description:Epithelial ovarian cancer is morphologically and clinically heterogeneous. Transcriptional profiling has revealed molecular subtypes (referred to as “C-signatures”) that correlate to biological as well as clinical features. We aimed to determine gene expression differences between malignant, benign and borderline serous ovarian tumors, and to investigate similarities to the intrinsic molecular subtypes of breast cancer. Global gene expression profiling was performed using Illumina's HT12 Bead Arrays and applied to 59 fresh-frozen ovarian tumors. SAM analysis revealed enrichment of cell cycel processes among the malignant tumors, in line with malignant tumors being highly proliferative. The borderline tumors were split between the malignant and benign tumor clusters, indicating that borderline tumors have both malignant and benign features. Furthermore, nearest centroid classification was performed applying previously published gene profiles for the ovarian cancer C-signatures and the intrinsic breast cancer subtypes, respectively, and showed significant correlations between the malignant serous tumors and the highly aggressive C1, C2 and C4 ovarian cancer signatures, and the basal-like breast cancer subtype. The benign and borderline serous tumors together were significantly correlated to the normal-like breast cancer subtype and the ovarian cancer C3 signature. The borderline tumors, on the other hand, correlated significantly to the Luminal A breast cancer subtype. These findings remained when analyzed in a large, independent dataset. The data in this study link the transcriptional profiles of serous ovarian cancer to the intrinsic molecular subtypes of breast cancer, in line with the shared clinical and molecular features between high-grade serous ovarian cancer and basal-like breast cancer, including an aggressive phenotype, frequent TP53 mutations and a high degree of genomic instability, and suggest that biomarkers and targeted therapies may overlap between these subsets of ovarian and breast cancers. Finally, the link between benign and borderline ovarian cancer and luminal breast cancer may indicate endocrine responsiveness in a subset of ovarian cancers.
2014-08-15 | GSE57477 | GEO