Characterization of adjacent breast tumors using oligonucleotide microarrays.

BACKGROUND: Current methodology often cannot distinguish second primary breast cancers from multifocal disease, a potentially important distinction for clinical management. In the present study we evaluated the use of oligonucleotide-based microarray analysis in determining the clonality of tumors by comparing gene expression profiles. METHOD: Total RNA was extracted from two tumors with no apparent physical connection that were located in the right breast of an 87-year-old woman diagnosed with invasive ductal carcinoma (IDC). The RNA was hybridized to the Affymetrix Human Genome U95A Gene Chip (12,500 known human genes) and analyzed using the Gene Chip Analysis Suite 3.3 (Affymetrix, Inc, Santa Clara, CA, USA) and JMPIN 3.2.6 (SAS Institute, Inc, Cary, NC, USA). Gene expression profiles of tumors from five additional patients were compared in order to evaluate the heterogeneity in gene expression between tumors with similar clinical characteristics. RESULTS: The adjacent breast tumors had a pairwise correlation coefficient of 0.987, and were essentially indistinguishable by microarray analysis. Analysis of gene expression profiles from different individuals, however, generated a pairwise correlation coefficient of 0.710. CONCLUSION: Transcriptional profiling may be a useful diagnostic tool for determining tumor clonality and heterogeneity, and may ultimately impact on therapeutic decision making.

Recent advances in breast cancer biology.

Approximately 1 in 10 US women will be diagnosed with breast cancer in her lifetime. With such a high incidence, breast cancer is a serious health concern for all American women. Within the past year, clues about the function of genes associated with breast cancer have been garnered, and novel genes that may contribute to breast tumorigenesis have been discovered. In addition, unique animal models and improvements in gene expression profiling technology have given researchers new tools to address previously unanswerable questions about this disease.

Screening for genomic rearrangements in families with breast and ovarian cancer identifies BRCA1 mutations previously missed by conformation-sensitive gel electrophoresis or sequencing.

The frequency of genomic rearrangements in BRCA1 was assessed in 42 American families with breast and ovarian cancer who were seeking genetic testing and who were subsequently found to be negative for BRCA1 and BRCA2 coding-region mutations. An affected individual from each family was tested by PCR for the exon 13 duplication (Puget et al. 1999a) and by Southern blot analysis for novel genomic rearrangements. The exon 13 duplication was detected in one family, and four families had other genomic rearrangements. A total of 5 (11. 9%) of the 42 families with breast/ovarian cancer who did not have BRCA1 and BRCA2 coding-region mutations had mutations in BRCA1 that were missed by conformation-sensitive gel electrophoresis or sequencing. Four of five families with BRCA1 genomic rearrangements included at least one individual with both breast and ovarian cancer; therefore, 4 (30.8%) of 13 families with a case of multiple primary breast and ovarian cancer had a genomic rearrangement in BRCA1. Families with genomic rearrangements had prior probabilities of having a BRCA1 mutation, ranging from 33% to 97% (mean 70%) (Couch et al. 1997). In contrast, in families without rearrangements, prior probabilities of having a BRCA1 mutation ranged from 7% to 92% (mean 37%). Thus, the prior probability of detecting a BRCA1 mutation may be a useful predictor when considering the use of Southern blot analysis for families with breast/ovarian cancer who do not have detectable coding-region mutations.