Dataset Information

Ductal Carcinoma Progression

ABSTRACT: To obtain insight into the molecular basis of ductal carcinoma in situ (DCIS) and its progression by infiltrating surrounding tissue, we have performed cellular-based gene expression analysis of pure DCIS and DCIS with co-existing invasive ductal carcinoma (IDC) and compared the histological and molecular aspects between these morphologically identical lesions seeking to find key genes involved in DCIS progression. For that, 30 samples were evaluated, 4 non-neoplastic (N), 5 pure DCIS, 11 DCIS with co-existing IDC (DCIS-IDC) and 10 IDC. All samples were laser capture microdissected and RNAs were amplified using T7-based methodology. Microarray technology was performed using a customized cDNA platform containing 4,608 human genes. To classify the 4 sample groups according to molecular similarity we performed comparisons of their general expression pattern using ANOVA test (pFDR<0,01) followed by Tukey´s test (fold>l2l). Among the 4 sample groups, as expected, non-neoplastic cells reported the most distinct gene expression pattern. However, among the 3 groups of neoplastic cells, in contrast to morphological aspects, pure DCIS had the most distinct expression profile when compared to the other lesions: DCIS-IDC and IDC. Additionally, by comparison among pure DCIS, DCIS-IDC and N, we identified 147 genes potentially involved in DCIS progression. Unsupervised hierarchical cluster based on expression profile of this gene-set could discriminate DCIS-IDC from 60% of pure DCIS samples. Keywords: disease state analysis

ORGANISM(S): Homo sapiens

PROVIDER: GSE11042 | GEO | 2008/04/05

SECONDARY ACCESSION(S): PRJNA107021

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:To obtain insight into the molecular basis of ductal carcinoma in situ (DCIS) and its progression by infiltrating surrounding tissue, we have performed cellular-based gene expression analysis of pure DCIS and DCIS with co-existing invasive ductal carcinoma (IDC) and compared the histological and molecular aspects between these morphologically identical lesions seeking to find key genes involved in DCIS progression. For that, 30 samples were evaluated, 4 non-neoplastic (N), 5 pure DCIS, 11 DCIS with co-existing IDC (DCIS-IDC) and 10 IDC. All samples were laser capture microdissected and RNAs were amplified using T7-based methodology. Microarray technology was performed using a customized cDNA platform containing 4,608 human genes. To classify the 4 sample groups according to molecular similarity we performed comparisons of their general expression pattern using ANOVA test (pFDR<0,01) followed by Tukey´s test (fold>l2l). Among the 4 sample groups, as expected, non-neoplastic cells reported the most distinct gene expression pattern. However, among the 3 groups of neoplastic cells, in contrast to morphological aspects, pure DCIS had the most distinct expression profile when compared to the other lesions: DCIS-IDC and IDC. Additionally, by comparison among pure DCIS, DCIS-IDC and N, we identified 147 genes potentially involved in DCIS progression. Unsupervised hierarchical cluster based on expression profile of this gene-set could discriminate DCIS-IDC from 60% of pure DCIS samples. Keywords: disease state analysis Fresh-frozen human breast samples were retrieved from the Tumor Tissue Biobank of the Medical and Research Center - Hospital A. C. Camargo, São Paulo. This research was approved by Ethic Committee of the Medical and Research Center - Hospital A. C. Camargo under number 587/04 and a written informed consent signed by all participants. All patients had presented at least 5 years of follow-up. Thirty samples were evaluated, 4 non-neoplastic breast samples (MN), 5 pure DCIS (stage 0; DCIS-0), 11 DCIS with co-existing IDC (DCIS) and 10 IDC. The non-neoplastic samples were obtained from perilesional mammary specimens from patients submitted to resection of benign lesions. All cells types were laser capture microdissected using PixCell II LCM system (Arcturus Engineering, Mountain View, CA). The total RNA was extracted by using the PicoPureä RNA Isolation kit (Arcturus Engineering # KT0204). A two-round linear amplification procedure based on T7-driven amplification was carried out. Amplified RNA was then used in a transcriptase reverse reaction into cDNA in the presence of Cy3- or Cy5-labeled dCTP. HB4a normal luminal epithelial mammary cell line (O’Hare et al 1991) was amplified following the same protocol and used as reference for microarray hybridizations. Dye swap was performed for each sample analyzed and used as replicate samples. For the raw_data (lowess_data), see Web Link below.

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.

Dataset Information

Ductal Carcinoma Progression

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets