Universität zu Köln

Zucker, Mark R., Abruzzo, Lynne, V, Herling, Carmen D., Barron, Lynn L., Keating, Michael J., Abrams, Zachary B., Heerema, Nyla and Coombes, Kevin R. (2019). Inferring clonal heterogeneity in cancer using SNP arrays and whole genome sequencing. Bioinformatics, 35 (17). S. 2924 - 2932. OXFORD: OXFORD UNIV PRESS. ISSN 1460-2059

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Abstract

Motivation: Clonal heterogeneity is common in many types of cancer, including chronic lymphocytic leukemia (CLL). Previous research suggests that the presence of multiple distinct cancer clones is associated with clinical outcome. Detection of clonal heterogeneity from high throughput data, such as sequencing or single nucleotide polymorphism (SNP) array data, is important for gaining a better understanding of cancer and may improve prediction of clinical outcome or response to treatment. Here, we present a new method, CloneSeeker, for inferring clinical heterogeneity from sequencing data, SNP array data, or both. Results: We generated simulated SNP array and sequencing data and applied CloneSeeker along with two other methods. We demonstrate that CloneSeeker is more accurate than existing algorithms at determining the number of clones, distribution of cancer cells among clones, and mutation and/or copy numbers belonging to each clone. Next, we applied CloneSeeker to SNP array data from samples of 258 previously untreated CLL patients to gain a better understanding of the characteristics of CLL tumors and to elucidate the relationship between clonal heterogeneity and clinical outcome. We found that a significant majority of CLL patients appear to have multiple clones distinguished by copy number alterations alone. We also found that the presence of multiple clones corresponded with significantly worse survival among CLL patients. These findings may prove useful for improving the accuracy of prognosis and design of treatment strategies.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Zucker, Mark R. UNSPECIFIED UNSPECIFIED UNSPECIFIED Abruzzo, Lynne, V UNSPECIFIED UNSPECIFIED UNSPECIFIED Herling, Carmen D. UNSPECIFIED UNSPECIFIED UNSPECIFIED Barron, Lynn L. UNSPECIFIED UNSPECIFIED UNSPECIFIED Keating, Michael J. UNSPECIFIED UNSPECIFIED UNSPECIFIED Abrams, Zachary B. UNSPECIFIED UNSPECIFIED UNSPECIFIED Heerema, Nyla UNSPECIFIED UNSPECIFIED UNSPECIFIED Coombes, Kevin R. UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-142220
DOI:	10.1093/bioinformatics/btz057
Journal or Publication Title:	Bioinformatics
Volume:	35
Number:	17
Page Range:	S. 2924 - 2932
Date:	2019
Publisher:	OXFORD UNIV PRESS
Place of Publication:	OXFORD
ISSN:	1460-2059
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language EVOLUTION; PROGRESSION; INFERENCE; CLL Multiple languages Biochemical Research Methods; Biotechnology & Applied Microbiology; Computer Science, Interdisciplinary Applications; Mathematical & Computational Biology; Statistics & Probability Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/14222