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Dataset Information

A systematic comparison of copy number alterations in four types of female cancer.


ABSTRACT:

Background

Detection and localization of genomic alterations and breakpoints are crucial in cancer research. The purpose of this study was to investigate, in a methodological and biological perspective, different female, hormone-dependent cancers to identify common and diverse DNA aberrations, genes, and pathways.

Methods

In this work, we analyzed tissue samples from patients with breast (n = 112), ovarian (n = 74), endometrial (n = 84), or cervical (n = 76) cancer. To identify genomic aberrations, the Circular Binary Segmentation (CBS) and Piecewise Constant Fitting (PCF) algorithms were used and segmentation thresholds optimized. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was applied to the segmented data to identify significantly altere

SUBMITTER: Kaveh F 

PROVIDER: S-EPMC5120489 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature