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Gene Expression and Comparative Genomic Hybridization of Ductal Carcinoma In Situ of the Breast

ABSTRACT: Background The dramatic increase in incidence of ductal carcinoma in situ (DCIS) associated with mammographic screening for breast cancer has given emphasis to the challenges of managing this important clinical entity. Unlike invasive breast cancer, there is no established histopathologic grading system for DCIS, nor are there biological markers of prognosis to guide clinical management. The aim of this study is to use molecular profiling to identify robust and clinically applicable indicators of DCIS malignant potential. Methods Areas of intraduct carcinoma, atypical ductal hyperplasia and benign epithelium were isolated from 46 well-characterised invasive breast cancers by laser capture microdissection. Microarray based gene expression profiling was used to identify genes differentially expressed between DCIS associated with grade 1 and grade 3 invasive carcinoma (‘grade associated genes’). The expression profile of these genes was then determined in all samples and used to define ‘molecular grade’ categories. The genomic basis of gene expression derived categories was examined by array-based comparative genomic hybridisation (CGH). Results DCIS samples could be divided into two subgroups, designated low and high molecular grade (MG) on the basis of expression at 173 grade associated oligonucleotide probes. The low MG subgroup included 21 DCIS samples of low (n=10) and intermediate (n=11) nuclear grade as well as all samples of ADH (n=4) and benign epithelium (n=7). The high MG subgroup included 27 DCIS samples of intermediate (n=7) and high (n=19) nuclear grade. Array CGH revealed distinct differences in the character and degree of genomic aberration associated with MG and the clinical significance of MG was verified by a strong correlation with survival in two independent invasive breast cancer gene expression datasets (n=295 and n=186). MG categories were strongly associated with histopathologic and biomarker features of DCIS. Using a classification tree model, DCIS MG could be accurately predicted in 44/46 (95.7%) of samples using a combination of nuclear grade and Ki67 score. Conclusions Molecular profiling indicates a binary grading scheme for DCIS that is both biologically relevant and clinically informative. The low and high MG DCIS classification could be recapitulated by a novel combination of routinely accessible features. This practical approach has potential to immediately improve clinical evaluation and management of DCIS. Keywords: Paired gene expression and CGH

ORGANISM(S): Homo sapiens

PROVIDER: GSE7882 | GEO | 2008/11/24

SECONDARY ACCESSION(S): PRJNA99915

REPOSITORIES: GEO

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Project description:Background The dramatic increase in incidence of ductal carcinoma in situ (DCIS) associated with mammographic screening for breast cancer has given emphasis to the challenges of managing this important clinical entity. Unlike invasive breast cancer, there is no established histopathologic grading system for DCIS, nor are there biological markers of prognosis to guide clinical management. The aim of this study is to use molecular profiling to identify robust and clinically applicable indicators of DCIS malignant potential. Methods Areas of intraduct carcinoma, atypical ductal hyperplasia and benign epithelium were isolated from 46 well-characterised invasive breast cancers by laser capture microdissection. Microarray based gene expression profiling was used to identify genes differentially expressed between DCIS associated with grade 1 and grade 3 invasive carcinoma (‘grade associated genes’). The expression profile of these genes was then determined in all samples and used to define ‘molecular grade’ categories. The genomic basis of gene expression derived categories was examined by array-based comparative genomic hybridisation (CGH). Results DCIS samples could be divided into two subgroups, designated low and high molecular grade (MG) on the basis of expression at 173 grade associated oligonucleotide probes. The low MG subgroup included 21 DCIS samples of low (n=10) and intermediate (n=11) nuclear grade as well as all samples of ADH (n=4) and benign epithelium (n=7). The high MG subgroup included 27 DCIS samples of intermediate (n=7) and high (n=19) nuclear grade. Array CGH revealed distinct differences in the character and degree of genomic aberration associated with MG and the clinical significance of MG was verified by a strong correlation with survival in two independent invasive breast cancer gene expression datasets (n=295 and n=186). MG categories were strongly associated with histopathologic and biomarker features of DCIS. Using a classification tree model, DCIS MG could be accurately predicted in 44/46 (95.7%) of samples using a combination of nuclear grade and Ki67 score. Conclusions Molecular profiling indicates a binary grading scheme for DCIS that is both biologically relevant and clinically informative. The low and high MG DCIS classification could be recapitulated by a novel combination of routinely accessible features. This practical approach has potential to immediately improve clinical evaluation and management of DCIS. Keywords: Paired gene expression and CGH Paired CGH and Gene Expression on DCIS of the breast

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.

Project description:DCIS is a non-invasive precursor lesion to invasive breast carcinoma. We still have no understanding on why only some DCIS lesions evolve to invasive cancer while others appear not to do so during the life span of the patient. Here, we performed full exome (tumor vs. matching normal), transcriptome and methylome analysis of 30 pure high-grade DCIS (HG-DCIS) and 10 normal breast epithelial samples. Sixty two percent of HG-DCIS cases displayed mutations affecting cancer driver genes or potential drivers. Mutations were observed affecting PIK3CA (21% of cases), TP53 (17%), GATA3 (7%), MLL3 (7%) and single cases of mutations affecting CDH1, MAP2K4, TBX3, NF1, ATM and ARID1A. Significantly, 83% of lesions displayed numerous large chromosomal copy number alterations, suggesting they might precede selection of cancer driver mutations. Integrated pathway-based modeling analysis of RNA-seq data allowed us to identify two DCIS subgroups (DCIS-C1 and DCIS-C2) based on their tumor intrinsic subtypes, proliferative, immune scores and in the activity of specific signaling pathways. The more aggressive DCIS-C1 (highly proliferative, basal-like or ERBB2+) displayed signatures characteristic of activated Treg cells (CD4+/CD25+/FOXP3+) and CTLA4+/CD86+ complexes indicative of a tumor-associated immune suppressive phenotype. Strikingly, all lesions showed evidence of TP53 pathway inactivation. Similarly ncRNA and methylation profiles reproduce changes observed post-invasion. Among the most significant findings we observed upregulation of lncRNA HOTAIR in DCIS-C1 lesions and hypermethylation of HOXA5 and specific SOX genes. We conclude that most HG-DCIS lesions, in spite of representing a pre-invasive stage of tumor progression, displayed molecular profiles indistinguishable from invasive breast cancer. DNA from 24 out of 30 (80%) HG-DCIS samples and 5 normal breast organoids (total 29 samples) were subjected to reduced representation bisulfite sequencing analysis (RRBS) by using Illumina HiSeq2000 platform. Please note that description of samples employed for the NGS analyses including age, race, ER/PR immunohistochemistry results, ITIL/STIL scores and PAM50 classification is provided the 'Supplementary Data1_Samples data.xlsx' (available on Superseries record)

Project description:DCIS is a non-invasive precursor lesion to invasive breast carcinoma. We still have no understanding on why only some DCIS lesions evolve to invasive cancer while others appear not to do so during the life span of the patient. Here, we performed full exome (tumor vs. matching normal), transcriptome and methylome analysis of 30 pure high-grade DCIS (HG-DCIS) and 10 normal breast epithelial samples. Sixty two percent of HG-DCIS cases displayed mutations affecting cancer driver genes or potential drivers. Mutations were observed affecting PIK3CA (21% of cases), TP53 (17%), GATA3 (7%), MLL3 (7%) and single cases of mutations affecting CDH1, MAP2K4, TBX3, NF1, ATM and ARID1A. Significantly, 83% of lesions displayed numerous large chromosomal copy number alterations, suggesting they might precede selection of cancer driver mutations. Integrated pathway-based modeling analysis of RNA-seq data allowed us to identify two DCIS subgroups (DCIS-C1 and DCIS-C2) based on their tumor intrinsic subtypes, proliferative, immune scores and in the activity of specific signaling pathways. The more aggressive DCIS-C1 (highly proliferative, basal-like or ERBB2+) displayed signatures characteristic of activated Treg cells (CD4+/CD25+/FOXP3+) and CTLA4+/CD86+ complexes indicative of a tumor-associated immune suppressive phenotype. Strikingly, all lesions showed evidence of TP53 pathway inactivation. Similarly ncRNA and methylation profiles reproduce changes observed post-invasion. Among the most significant findings we observed upregulation of lncRNA HOTAIR in DCIS-C1 lesions and hypermethylation of HOXA5 and specific SOX genes. We conclude that most HG-DCIS lesions, in spite of representing a pre-invasive stage of tumor progression, displayed molecular profiles indistinguishable from invasive breast cancer. RNAs from 25 out of 30 (83%) pure HG-DCIS and 10 normal breast organoids (total 35 samples) were subjected to RNA-Seq analysis by using Illumina HiSeq2000 platform Please note that description of samples employed for the NGS analyses including age, race, ER/PR immunohistochemistry results, ITIL/STIL scores and PAM50 classification is provided the 'Supplementary Data1_Samples data.xlsx' (available on Superseries record)

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Gene Expression and Comparative Genomic Hybridization of Ductal Carcinoma In Situ of the Breast

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