Genomic comparison of early-passage conditionally reprogrammed breast cancer cells to their corresponding primary tumors.

Conditionally reprogrammed cells (CRCs) are epithelial cells that are directly isolated from patients' specimens and propagated in vitro with feeder cells and a Rho kinase inhibitor. A number of these cells have been generated from biopsies of breast cancer patients, including ductal carcinoma in situ and invasive carcinomas. The characterization of their genomic signatures is essential to determine their ability to reflect the natural biology of their tumors of origin. In this study, we performed the genomic characterization of six newly established invasive breast cancer CRC cultures in comparison to the original patients' primary breast tumors (PBT) from which they derived. The CRCs and corresponding PBTs were simultaneously profiled by genome-wide array-CGH, targeted next generation sequencing and global miRNA expression to determine their molecular similarities in the patterns of copy number alterations (CNAs), gene mutations and miRNA expression levels, respectively. The CRCs' epithelial cells content and ploidy levels were also evaluated by flow cytometry. A similar level of CNAs was observed in the pairs of CRCs/PBTs analyzed by array-CGH, with >95% of overlap for the most frequently affected cytobands. Consistently, targeted next generation sequencing analysis showed the retention of specific somatic variants in the CRCs as present in their original PBTs. Global miRNA profiling closely clustered the CRCs with their PBTs (Pearson Correlation, ANOVA paired test, P<0.05), indicating also similarity at the miRNA expression level; the retention of tumor-specific alterations in a subset of miRNAs in the CRCs was further confirmed by qRT-PCR. These data demonstrated that the human breast cancer CRCs of this study maintained at early passages the overall copy number, gene mutations and miRNA expression patterns of their original tumors. The further characterization of these cells by other molecular and cellular phenotypes at late cell passages, are required to further expand their use as a unique and representative ex-vivo tumor model for basic science and translational breast cancer studies

Germline Variation in Cancer-Susceptibility Genes in a Healthy, Ancestrally Diverse Cohort: Implications for Individual Genome Sequencing

<div><p>Technological advances coupled with decreasing costs are bringing whole genome and whole exome sequencing closer to routine clinical use. One of the hurdles to clinical implementation is the high number of variants of unknown significance. For cancer-susceptibility genes, the difficulty in interpreting the clinical relevance of the genomic variants is compounded by the fact that most of what is known about these variants comes from the study of highly selected populations, such as cancer patients or individuals with a family history of cancer. The genetic variation in known cancer-susceptibility genes in the general population has not been well characterized to date. To address this gap, we profiled the nonsynonymous genomic variation in 158 genes causally implicated in carcinogenesis using high-quality whole genome sequences from an ancestrally diverse cohort of 681 healthy individuals. We found that all individuals carry multiple variants that may impact cancer susceptibility, with an average of 68 variants per individual. Of the 2,688 allelic variants identified within the cohort, most are very rare, with 75% found in only 1 or 2 individuals in our population. Allele frequencies vary between ancestral groups, and there are 21 variants for which the minor allele in one population is the major allele in another. Detailed analysis of a selected subset of 5 clinically important cancer genes, <i>BRCA1</i>, <i>BRCA2</i>, <i>KRAS</i>, <i>TP53</i>, and <i>PTEN</i>, highlights differences between germline variants and reported somatic mutations. The dataset can serve a resource of genetic variation in cancer-susceptibility genes in 6 ancestry groups, an important foundation for the interpretation of cancer risk from personal genome sequences.</p></div

Profile of the variability per individual.

<p>(A) Boxplot of the total number of variants, the number of variants listed in HGMD, the number of likely deleterious variants, and the number of variants of unknown significance per individual for cancer-associated genes. (B) Distribution of the number of cancer genes with at least one nonsynonymous variant per individual.</p

Variation prevalence per gene.

<p>Distribution of the number of individuals with a variant per gene for (A) all variants (B) rare variants.</p

Number of cancer-gene variants per individual by ancestry.

<p>The distribution of the number of nonsynonymous genes per subject for each of the 6 ancestry-based subpopulations.</p

Average numbers of cancer-gene variants per individual by ancestry.

<p>Average numbers of cancer-gene variants per individual by ancestry.</p

Positions at which the major allele differs between ancestry groups.

a<p>Bold: Allele frequencies >0.5.</p

p53 DNA-binding domain variants.

<p>The DNA-binding domain of the p53 protein (black) bound to DNA (purple) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094554#pone.0094554-Cho1" target="_blank">[84]</a>. Common somatic mutations (yellow) contact the DNA or stabilize the structure. Variants in our cohort (red) occur at residues distal to the DNA binding site except for Arg 283 (green).</p

Admixture coefficients for the subpopulations.

<p>The admixture proportions of the 6 ancestral populations (colors) are displayed for all individuals in each of the 7 groups defined in the cohort (panels). (A) European (B) Central Asian (C) East Asian (D) African (E) African-European (F) Hispanic (G) Other. Red: European, Blue: Central Asian, Cyan: East Asian, Yellow: African, Green: Native American, Magenta: Oceania.</p