STAR Protocols (Dec 2021)
Analytical protocol to identify local ancestry-associated molecular features in cancer
- Jian Carrot-Zhang,
- Seunghun Han,
- Wanding Zhou,
- Jeffrey S. Damrauer,
- Anab Kemal,
- Andrew D. Cherniack,
- Rameen Beroukhim,
- Ashton C. Berger,
- Matthew Meyerson,
- Katherine A. Hoadley,
- Ina Felau,
- Samantha Caesar-Johnson,
- John A. Demchok,
- Michael K.A. Mensah,
- Roy Tarnuzzer,
- Zhining Wang,
- Liming Yang,
- Jean C. Zenklusen,
- Nyasha Chambwe,
- Theo A. Knijnenburg,
- A. Gordon Robertson,
- Christina Yau,
- Christopher Benz,
- Kuan-lin Huang,
- Justin Newberg,
- Garret Frampton,
- R. Jay Mashl,
- Li Ding,
- Alessandro Romanel,
- Francesca Demichelis,
- Rosalyn W. Sayaman,
- Elad Ziv,
- Peter W. Laird,
- Hui Shen,
- Christopher K. Wong,
- Joshua M. Stuart,
- Alexander J. Lazar,
- Xiuning Le,
- Ninad Oak
Affiliations
- Jian Carrot-Zhang
- The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA; Corresponding author
- Seunghun Han
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA
- Wanding Zhou
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, PA, 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Jeffrey S. Damrauer
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Anab Kemal
- National Cancer Institute, Bethesda, MD 20892, USA
- Andrew D. Cherniack
- The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA; Corresponding author
- Rameen Beroukhim
- The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA; Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA; Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Corresponding author
- Ashton C. Berger
- Matthew Meyerson
- Katherine A. Hoadley
- Ina Felau
- Samantha Caesar-Johnson
- John A. Demchok
- Michael K.A. Mensah
- Roy Tarnuzzer
- Zhining Wang
- Liming Yang
- Jean C. Zenklusen
- Nyasha Chambwe
- Theo A. Knijnenburg
- A. Gordon Robertson
- Christina Yau
- Christopher Benz
- Kuan-lin Huang
- Justin Newberg
- Garret Frampton
- R. Jay Mashl
- Li Ding
- Alessandro Romanel
- Francesca Demichelis
- Rosalyn W. Sayaman
- Elad Ziv
- Peter W. Laird
- Hui Shen
- Christopher K. Wong
- Joshua M. Stuart
- Alexander J. Lazar
- Xiuning Le
- Ninad Oak
- Journal volume & issue
-
Vol. 2,
no. 4
p. 100766
Abstract
Summary: People of different ancestries vary in cancer risk and outcome, and their molecular differences may indicate sources of these variations. Determining the “local” ancestry composition at each genetic locus across ancestry-admixed populations can suggest causal associations. We present a protocol to identify local ancestry and detect the associated molecular changes, using data from the Cancer Genome Atlas. This workflow can be applied to cancer cohorts with matched tumor and normal data from admixed patients to examine germline contributions to cancer.For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020).
