Intensive instruction in BSE did not reduce mortality from breast cancer. Programs to encourage BSE in the absence of mammography would be unlikely to reduce mortality from breast cancer. Women who choose to practice BSE should be informed that its efficacy is unproven and that it may increase their chances of having a benign breast biopsy.

The breast cancer data are provided by Andrea L. Richardson, Zhigang C. Wang and James D. Iglehart.

Genome-wide copy number changes were analyzed in 70 primary human lung carcinoma specimens and 31 cell lines derived from human lung carcinomas, with high-density arrays representing f115,000 single nucleotide polymorphism loci. In addition to previously characterized loci, two regions of homozygous deletion were found, one near the PTPRD locus on chromosome segment 9p23 in four samples representing both small cell lung carcinoma (SCLC) and non-small cell lung carcinoma (NSCLC) and the second on chromosome segment 3q25 in one sample each of NSCLC and SCLC. Highlevel amplifications were identified within chromosome segment 8q12-13 in two SCLC specimens, 12p11 in two NSCLC specimens and 22q11 in four NSCLC specimens. Systematic copy number analysis of tyrosine kinase genes identified highlevel amplification of EGFR in three NSCLC specimens, FGFR1 in two specimens and ERBB2 and MET in one specimen each. EGFR amplification was shown to be independent of kinase domain mutational status. (Cancer Res 2005; 65(13): 5561-70)

Our data from a large group of women in a defined population indicate that screening mammography may miss tumors of lobular or mucinous histology and some rapidly proliferating, high-grade tumors.

Major efforts are underway to systematically define the somatic and germline genetic variations causally associated with disease. Genome-wide genetic analysis of actual clinical samples is, however, limited by the paucity of genomic DNA available. Here we have tested the fidelity and genome representation of phi29 polymerase-based genome amplification (phi29MDA) using direct sequencing and high density oligonucleotide arrays probing >10,000 SNP alleles. Genome representation was comprehensive and estimated to be 99.82% complete, although six regions encompassing a maximum of 5.62 Mb failed to amplify. There was no degradation in the accuracy of SNP genotyping and, in direct sequencing experiments sampling 500,000 bp, the estimated error rate (9.5 x 10(-6)) was the same as in paired unamplified samples. The detection of cancer-associated loss of heterozygosity and copy number changes, including homozygous deletion and gene amplification, were similarly robust. These results suggest that phi29MDA yields high fidelity, near-complete genome representation suitable for high resolution genetic analysis.

Loss of heterozygosity (LOH) of chromosomal regions bearing tumor suppressors is a key event in the evolution of epithelial and mesenchymal tumors. Identification of these regions usually relies on genotyping tumor and counterpart normal DNA and noting regions where heterozygous alleles in the normal DNA become homozygous in the tumor. However, paired normal samples for tumors and cell lines are often not available. With the advent of oligonucleotide arrays that simultaneously assay thousands of single-nucleotide polymorphism (SNP) markers, genotyping can now be done at high enough resolution to allow identification of LOH events by the absence of heterozygous loci, without comparison to normal controls. Here we describe a hidden Markov model-based method to identify LOH from unpaired tumor samples, taking into account SNP intermarker distances, SNP-specific heterozygosity rates, and the haplotype structure of the human genome. When we applied the method to data genotyped on 100 K arrays, we correctly identified 99% of SNP markers as either retention or loss. We also correctly identified 81% of the regions of LOH, including 98% of regions greater than 3 megabases. By integrating copy number analysis into the method, we were able to distinguish LOH from allelic imbalance. Application of this method to data from a set of prostate samples without paired normals identified known regions of prevalent LOH. We have developed a method for analyzing high-density oligonucleotide SNP array data to accurately identify of regions of LOH and retention in tumors without the need for paired normal samples.

Gene expression array profiles identify subclasses of breast cancers with different clinical outcomes and different molecular features. The present study attempted to correlate genomic alterations (loss of heterozygosity; LOH) with subclasses of breast cancers having distinct gene expression signatures. Hierarchical clustering of expression array data from 89 invasive breast cancers identified four major expression subclasses. Thirty-four of these cases representative of the four subclasses were microdissected and allelotyped using genome-wide single nucleotide polymorphism detection arrays (Affymetrix, Inc.). LOH was determined by comparing tumor and normal single nucleotide polymorphism allelotypes. A newly developed statistical tool was used to determine the chromosomal regions of frequent LOH. We found that breast cancers were highly heterogeneous, with the proportion of LOH ranging widely from 0.3% to >60% of heterozygous markers. The most common sites of LOH were on 17p, 17q, 16q, 11q, and 14q, sites reported in previous LOH studies. Signature LOH events were discovered in certain expression subclasses. Unique regions of LOH on 5q and 4p marked a subclass of breast cancers with "basal-like" expression profiles, distinct from other subclasses. LOH on 1p and 16q occurred preferentially in a subclass of estrogen receptorpositive breast cancers. Finding unique LOH patterns in different groups of breast cancer, in part defined by expression signatures, adds confidence to newer schemes of molecular classification. Furthermore, exclusive association between biological subclasses and restricted LOH events provides rationale to search for targeted genes.

Although an important biomarker in breast cancer, Ki67 lacks scoring standardization, which has limited its clinical use. Our previous study found variability when laboratories used their own scoring methods on centrally stained tissue microarray slides. In this current study, 16 laboratories from eight countries calibrated to a specific Ki67 scoring method and then scored 50 centrally MIB-1 stained tissue microarray cases. Simple instructions prescribed scoring pattern and staining thresholds for determination of the percentage of stained tumor cells. To calibrate, laboratories scored 18 'training' and 'test' web-based images. Software tracked object selection and scoring. Success for the calibration was prespecified as Root Mean Square Error of scores compared with reference o0.6 and Maximum Absolute Deviation from reference o 1.0 (log2-transformed data). Prespecified success criteria for tissue microarray scoring required intraclass correlation significantly 40.70 but aiming for observed intraclass correlation ≥ 0.90. Laboratory performance showed non-significant but promising trends of