Dataset Information

A genomic and transcriptomic approach for a differential diagnosis between primary and secondary ovarian carcinomas in patients with a previous history of breast cancer.

ABSTRACT: BACKGROUND: The distinction between primary and secondary ovarian tumors may be challenging for pathologists. The purpose of the present work was to develop genomic and transcriptomic tools to further refine the pathological diagnosis of ovarian tumors after a previous history of breast cancer. METHODS: Sixteen paired breast-ovary tumors from patients with a former diagnosis of breast cancer were collected. The genomic profiles of paired tumors were analyzed using the Affymetrix GeneChip Mapping 50 K Xba Array or Genome-Wide Human SNP Array 6.0 (for one pair), and the data were normalized with ITALICS (ITerative and Alternative normaLIzation and Copy number calling for affymetrix Snp arrays) algorithm or Partek Genomic Suite, respectively. The transcriptome of paired samples was analyzed using Affymetrix GeneChip Human Genome U133 Plus 2.0 Arrays, and the data were normalized with gc-Robust Multi-array Average (gcRMA) algorithm. A hierarchical clustering of these samples was performed, combined with a dataset of well-identified primary and secondary ovarian tumors. RESULTS: In 12 of the 16 paired tumors analyzed, the comparison of genomic profiles confirmed the pathological diagnosis of primary ovarian tumor (n = 5) or metastasis of breast cancer (n = 7). Among four cases with uncertain pathological diagnosis, genomic profiles were clearly distinct between the ovarian and breast tumors in two pairs, thus indicating primary ovarian carcinomas, and showed common patterns in the two others, indicating metastases from breast cancer. In all pairs, the result of the transcriptomic analysis was concordant with that of the genomic analysis. CONCLUSIONS: In patients with ovarian carcinoma and a previous history of breast cancer, SNP array analysis can be used to distinguish primary and secondary ovarian tumors. Transcriptomic analysis may be used when primary breast tissue specimen is not available.

SUBMITTER: Meyniel JP

PROVIDER: S-EPMC2891634 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A genomic and transcriptomic approach for a differential diagnosis between primary and secondary ovarian carcinomas in patients with a previous history of breast cancer.

Meyniel Jean-Philippe JP Cottu Paul H PH Decraene Charles C Stern Marc-Henri MH Couturier Jérôme J Lebigot Ingrid I Nicolas André A Weber Nina N Fourchotte Virginie V Alran Séverine S Rapinat Audrey A Gentien David D Roman-Roman Sergio S Mignot Laurent L Sastre-Garau Xavier X

BMC cancer 20100521

<h4>Background</h4>The distinction between primary and secondary ovarian tumors may be challenging for pathologists. The purpose of the present work was to develop genomic and transcriptomic tools to further refine the pathological diagnosis of ovarian tumors after a previous history of breast cancer.<h4>Methods</h4>Sixteen paired breast-ovary tumors from patients with a former diagnosis of breast cancer were collected. The genomic profiles of paired tumors were analyzed using the Affymetrix Gen ...[more]

PMID: 20492709

Similar Datasets

Project description:BACKGROUND: It is known that all tumors studied in sufficient number to draw conclusions show characteristic/specific chromosomal rearrangements, and the identification of these chromosomes and the genes rearranged behind the aberrations may ultimately lead to a tailor-made therapy for each cancer patient. Knowledge about the acquired genomic aberrations of ovarian carcinomas is still unsatisfactory. METHODS: We cytogenetically analyzed 110 new cases of ovarian carcinoma of different histological subtypes using karyotyping of G-banded chromosomes and high-resolution comparative genomic hybridization. We first compared the aberration patterns identified by the two genomic screening techniques using the so-called "classical" pathological classification in which the carcinomas are grouped as tumors of types I and II. We also broke down our findings according to the more "modern" classification which groups the carcinomas in five different categories. RESULTS: The chromosomal breakpoints identified by karyotyping tended to cluster to 19p/q and to 11q, but no unquestionably recurrent rearrangement could be seen. Common imbalances were scored as gains from 1q, 3q, 7q, and 8q and losses from 17p, 19q, and 22q. Gain of material from 8q23 and losses from 19q and 22q have previously been described at high frequencies in bilateral and borderline ovarian carcinomas. The fact that they were present both in "precursor" lesions, i.e., borderline tumors, as well as in tumors of more advanced stages, i.e., carcinomas, highlights the possibility of an adenoma-carcinoma sequence in ovarian carcinogenesis. CONCLUSION: Based on the relatively simple genomic changes we identified in the low-grade serous carcinomas examined (n = 7) and which largely corresponded to the aberration pattern formerly identified in borderline tumors, one can interpret the cytogenetic data as supporting the view that the low-grade carcinomas represent a phenotypically more advanced stage of borderline tumors. Whether transition from low-grade to high-grade carcinoma also occurs, is a question about which the genomic data is still inconclusive.

Project description:Metaplastic breast carcinoma is a rare and aggressive histologic type of breast cancer, preferentially displaying a triple-negative phenotype. We sought to define the transcriptomic heterogeneity of metaplastic breast cancers on the basis of current gene expression microarray-based classifiers, and to determine whether these tumors display gene copy number profiles consistent with those of BRCA1-associated breast cancers. Twenty-eight consecutive triple-negative metaplastic breast carcinomas were reviewed, and the metaplastic component present in each frozen specimen was defined (ie, spindle cell, squamous, chondroid metaplasia). RNA and DNA extracted from frozen sections with tumor cell content >60% were subjected to gene expression (Illumina HumanHT-12 v4) and copy number profiling (Affymetrix SNP 6.0), respectively. Using the best practice PAM50/claudin-low microarray-based classifier, all metaplastic breast carcinomas with spindle cell metaplasia were of claudin-low subtype, whereas those with squamous or chondroid metaplasia were preferentially of basal-like subtype. Triple-negative breast cancer subtyping using a dedicated website (http://cbc.mc.vanderbilt.edu/tnbc/) revealed that all metaplastic breast carcinomas with chondroid metaplasia were of mesenchymal-like subtype, spindle cell carcinomas preferentially of unstable or mesenchymal stem-like subtype, and those with squamous metaplasia were of multiple subtypes. None of the cases was classified as immunomodulatory or luminal androgen receptor subtype. Integrative clustering, combining gene expression and gene copy number data, revealed that metaplastic breast carcinomas with spindle cell and chondroid metaplasia were preferentially classified as of integrative clusters 4 and 9, respectively, whereas those with squamous metaplasia were classified into six different clusters. Eight of the 26 metaplastic breast cancers subjected to SNP6 analysis were classified as BRCA1-like. The diversity of histologic features of metaplastic breast carcinomas is reflected at the transcriptomic level, and an association between molecular subtypes and histology was observed. BRCA1-like genomic profiles were found only in a subset (31%) of metaplastic breast cancers, and were not associated with a specific molecular or histologic subtype.

Dataset Information

A genomic and transcriptomic approach for a differential diagnosis between primary and secondary ovarian carcinomas in patients with a previous history of breast cancer.

Publications

A genomic and transcriptomic approach for a differential diagnosis between primary and secondary ovarian carcinomas in patients with a previous history of breast cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets