Integrative modeling identifies genetic ancestry-associated molecular correlates in human cancer

A Gordon Robertson; Christina Yau; Jian Carrot-Zhang; Jeffrey S Damrauer; Theo A Knijnenburg; Nyasha Chambwe; Katherine A Hoadley; Anab Kemal; Jean C Zenklusen; Andrew D Cherniack; Rameen Beroukhim; Wanding Zhou

doi:10.1016/j.xpro.2021.100483

Integrative modeling identifies genetic ancestry-associated molecular correlates in human cancer

STAR Protoc. 2021 Apr 19;2(2):100483. doi: 10.1016/j.xpro.2021.100483. eCollection 2021 Jun 18.

Authors

A Gordon Robertson¹, Christina Yau^{2

3}, Jian Carrot-Zhang^{4

5

6}, Jeffrey S Damrauer⁷, Theo A Knijnenburg⁸, Nyasha Chambwe⁸, Katherine A Hoadley⁷, Anab Kemal⁹, Jean C Zenklusen⁹, Andrew D Cherniack^{4

5

6}, Rameen Beroukhim^{4

5

6

10

11}, Wanding Zhou^{12

13}

Affiliations

¹ Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada.
² Buck Institute for Research on Aging, Novato, CA 94945, USA.
³ Department of Surgery, University of California, San Francisco, San Francisco, CA 94115, USA.
⁴ The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
⁵ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
⁶ Harvard Medical School, Boston, MA 02115, USA.
⁷ Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
⁸ Institute for Systems Biology, Seattle, WA 98109, USA.
⁹ National Cancer Institute, Bethesda, MD 20892, USA.
¹⁰ Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA.
¹¹ Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
¹² Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
¹³ Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

Abstract

Cellular and molecular aberrations contribute to the disparity of human cancer incidence and etiology between ancestry groups. Multiomics profiling in The Cancer Genome Atlas (TCGA) allows for querying of the molecular underpinnings of ancestry-specific discrepancies in human cancer. Here, we provide a protocol for integrative associative analysis of ancestry with molecular correlates, including somatic mutations, DNA methylation, mRNA transcription, miRNA transcription, and pathway activity, using TCGA data. This protocol can be generalized to analyze other cancer cohorts and human diseases. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020).

Keywords: Bioinformatics; Cancer; Genomics.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

DNA Methylation / genetics
Databases, Genetic
Female
Genomics / methods*
Humans
Male
MicroRNAs / genetics
Models, Genetic*
Neoplasms / genetics*
Transcription, Genetic / genetics

Substances

MicroRNAs

Abstract

Publication types

MeSH terms

Substances

Grants and funding