Genomic and Functional Approaches to Understanding Cancer Aneuploidy

By Alison M. Taylor, J. Shih, G. Ha, G. Gao, Xiaoyang Zhang, Ashton C. Berger, S. Schumacher, Chen Wang, Hai Hu, Jianfang Liu and 4 more. Cancer Cell, 2018

923 citations recorded by the source corpus.

Summary Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas (TCGA), aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was anti-correlated with expression of immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss of chromosome arm 3p in squamous cancers. We applied genome engineering to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication. This study defines genomic and phenotypic correlates of cancer aneuploidy and provides an experimental approach to study chromosome arm aneuploidy.

Subfields: Cancer Research, Genetics, Oncology

View Paper: https://www.semanticscholar.org/paper/c1ea82052866cd20a561d2115f42225cb5ecd49f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cancer Research

1. Peter W. Laird
2. M. Lawrence
3. Timothy Triche
4. M. Wiznerowicz
5. Houtan Noushmehr

In Genetics

1. Hui Shen
2. M. Wiznerowicz
3. Peter W. Laird
4. Timothy Triche
5. Ronglai Shen
6. Wanding Zhou
7. Christoph Bock
8. M. Smulders

In Oncology

1. Peter W. Laird

Citations in the corpus

• SeSAMe: reducing artifactual detection of DNA methylation by Infinium BeadChips in genomic deletions (2018, methodology): “DNA copy number segmentation from the same 749 TCGA normal samples (18) using an Affymetrix Human SNP Array 6.”
• Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer (2018, methodology): “Chromosome arm-level copy-number calls were determined by clustering breakpoint locations and fraction of arm altered (further detailed in Taylor et al., 2018).”