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. 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)

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: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.

Dataset Information

Elevated NRAS expression during DCIS is a potential driver for progression to basal-like properties and local invasiveness

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets