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Researchers Aim to Characterize 1,000 Breast Cancer Tumors

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By Monica Heger

At last week's Biology of Genomes meeting at Cold Spring Harbor Laboratory, researchers from the Cambridge Research Institute presented initial unpublished results of an analysis of 1,000 breast cancer tumors as part of the UK-Canada project the Molecular Taxonomy of Breast Cancer International Consortium, or METABRIC, which aims to classify tumors based on their molecular properties.

The researchers are using a combination of technologies including exome sequencing, RNA sequencing, copy number profiling, gene expression analysis, and targeted resequencing in order to gain a better understanding of the different types of breast cancer tumors and eventually tailor treatment and improve diagnostics.

Christina Curtis, a post-doctoral fellow at the Cambridge Research Institute, said at the meeting that the group first performed a copy number analysis on 1,000 tumors from the METABRIC study in order to identify classes of tumors that they would study further.

Additionally, they performed exome sequencing and RNA sequencing on 60 triple-negative breast cancer tumors, as well as targeted sequencing on a subset of the 1,000 tumors. All sequencing was done using a paired-end sequencing strategy on the Illumina Genome Analyzer with 72 base pair reads.

The group chose tumors for targeted sequencing by identifying "key loci" in a subset of the 1,000 tumors and are "in the process of further expanding this list of actionable mutations based on the joint copy number and expression analyses," Curtis said.

Curtis said that their analyses are already identifying key differences between the cancer subtypes. For instance, the basal-like tumors are the most homogeneous, while the luminal subtypes show "extensive inter-tumor heterogeneity." Within the subtypes themselves she said there is heterogeneity that should enable further subtyping. The goal is to "uncover novel subtypes of disease that are indicative of prognosis," she said.

She said their approach — doing copy number and expression analyses before sequencing — allowed them to focus the sequencing on specific types of tumors. For example, "by having profiles, we can select cases that are very flat, where one rearrangement might be very important to that disease," she said. "We can pinpoint things that look recurrent and then do focused sequencing to look for mutations."

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