Atypical ductal hyperplasia is a multipotent precursor of breast carcinoma

The current model for breast cancer progression proposes independent “low‐grade (LG) like” and “high‐grade (HG) like” pathways but lacks a known precursor to HG cancer. We applied low coverage whole genome sequencing to atypical ductal hyperplasia (ADH) with and without carcinoma to shed light on breast cancer progression. 14/20 isolated ADH cases harboured at least one copy number alteration (CNA), but had fewer aberrations than LG or HG ductal carcinoma in situ (DCIS). ADH carried more HG‐like CNA than LG DCIS (eg. 8q gain). Correspondingly, 64% (7/11) of ADH cases with synchronous HG carcinoma were clonally related, similar to LG carcinoma (67%, 6/9). This study represents a significant shift in our understanding of breast cancer progression, with ADH as a common precursor lesion to the independent “low‐grade like” and “high‐grade like” pathways. These data suggest that ADH can be a precursor of HG breast cancer and that LG and HG carcinomas can evolve from a similar ancestor lesion. We propose that although LG DCIS may be committed to a LG molecular pathway, ADH may remain multipotent, progressing to either LG or HG carcinoma. This multipotent nature suggests that some ADH could be more clinically significant than LG DCIS, requiring biomarkers for personalising management

A classification model for distinguishing copy number variants from cancer-related alterations

<p>Abstract</p> <p>Background</p> <p>Both somatic copy number alterations (CNAs) and germline copy number variants (CNVs) that are prevalent in healthy individuals can appear as recurrent changes in comparative genomic hybridization (CGH) analyses of tumors. In order to identify important cancer genes CNAs and CNVs must be distinguished. Although the Database of Genomic Variants (DGV) contains a list of all known CNVs, there is no standard methodology to use the database effectively.</p> <p>Results</p> <p>We develop a prediction model that distinguishes CNVs from CNAs based on the information contained in the DGV and several other variables, including segment's length, height, closeness to a telomere or centromere and occurrence in other patients. The models are fitted on data from glioblastoma and their corresponding normal samples that were collected as part of The Cancer Genome Atlas project and hybridized to Agilent 244 K arrays.</p> <p>Conclusions</p> <p>Using the DGV alone CNVs in the test set can be correctly identified with about 85% accuracy if the outliers are removed before segmentation and with 72% accuracy if the outliers are included, and additional variables improve the prediction by about 2-3% and 12%, respectively. Final models applied to data from ovarian tumors have about 90% accuracy with all the variables and 86% accuracy with the DGV alone.</p

Prevalence and Co-Occurrence of Actionable Genomic Alterations in High-Grade Bladder Cancer

We sought to define the prevalence and co-occurrence of actionable genomic alterations in patients with high-grade bladder cancer to serve as a platform for therapeutic drug discovery

Clonality: an R package for testing clonal relatedness of two tumors from the same patient based on their genomic profiles

Summary: If a cancer patient develops multiple tumors, it is sometimes impossible to determine whether these tumors are independent or clonal based solely on pathological characteristics. Investigators have studied how to improve this diagnostic challenge by comparing the presence of loss of heterozygosity (LOH) at selected genetic locations of tumor samples, or by comparing genomewide copy number array profiles. We have previously developed statistical methodology to compare such genomic profiles for an evidence of clonality. We assembled the software for these tests in a new R package called ‘Clonality’. For LOH profiles, the package contains significance tests. The analysis of copy number profiles includes a likelihood ratio statistic and reference distribution, as well as an option to produce various plots that summarize the results