Quantification of within-sample genetic heterogeneity from SNP-array data. 2017

Pierre Martinez, and Christopher Kimberley, and Nicolai J BirkBak, and Andrea Marquard, and Zoltan Szallasi, and Trevor A Graham
Université de Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, Centre Léon Bérard, Cancer Research Center of Lyon, Lyon, France. pierre.martinez@lyon.unicancer.fr.

Intra-tumour genetic heterogeneity (ITH) fosters drug resistance and is a critical hurdle to clinical treatment. ITH can be well-measured using multi-region sampling but this is costly and challenging to implement. There is therefore a need for tools to estimate ITH in individual samples, using standard genomic data such as SNP-arrays, that could be implemented routinely. We designed two novel scores S and R, respectively based on the Shannon diversity index and Ripley's L statistic of spatial homogeneity, to quantify ITH in single SNP-array samples. We created in-silico and in-vitro mixtures of tumour clones, in which diversity was known for benchmarking purposes. We found significant but highly-variable associations of our scores with diversity in-silico (p < 0.001) and moderate associations in-vitro (p = 0.015 and p = 0.085). Our scores were also correlated to previous ITH estimates from sequencing data but heterogeneity in the fraction of tumour cells present across samples hampered accurate quantification. The prognostic potential of both scores was moderate but significantly predictive of survival in several tumour types (corrected p = 0.03). Our work thus shows how individual SNP-arrays reveal intra-sample clonal diversity with moderate accuracy.

UI MeSH Term Description Entries
D009369 Neoplasms New abnormal growth of tissue. Malignant neoplasms show a greater degree of anaplasia and have the properties of invasion and metastasis, compared to benign neoplasms. Benign Neoplasm,Cancer,Malignant Neoplasm,Tumor,Tumors,Benign Neoplasms,Malignancy,Malignant Neoplasms,Neoplasia,Neoplasm,Neoplasms, Benign,Cancers,Malignancies,Neoplasias,Neoplasm, Benign,Neoplasm, Malignant,Neoplasms, Malignant
D011379 Prognosis A prediction of the probable outcome of a disease based on a individual's condition and the usual course of the disease as seen in similar situations. Prognostic Factor,Prognostic Factors,Factor, Prognostic,Factors, Prognostic,Prognoses
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D045744 Cell Line, Tumor A cell line derived from cultured tumor cells. Tumor Cell Line,Cell Lines, Tumor,Line, Tumor Cell,Lines, Tumor Cell,Tumor Cell Lines
D018740 Genetic Heterogeneity The presence of apparently similar characters for which the genetic evidence indicates that different genes or different genetic mechanisms are involved in different pedigrees. In clinical settings genetic heterogeneity refers to the presence of a variety of genetic defects which cause the same disease, often due to mutations at different loci on the same gene, a finding common to many human diseases including ALZHEIMER DISEASE; CYSTIC FIBROSIS; LIPOPROTEIN LIPASE DEFICIENCY, FAMILIAL; and POLYCYSTIC KIDNEY DISEASES. (Rieger, et al., Glossary of Genetics: Classical and Molecular, 5th ed; Segen, Dictionary of Modern Medicine, 1992) Heterogeneity, Genetic,Genetic Heterogeneities,Heterogeneities, Genetic
D020641 Polymorphism, Single Nucleotide A single nucleotide variation in a genetic sequence that occurs at appreciable frequency in the population. SNPs,Single Nucleotide Polymorphism,Nucleotide Polymorphism, Single,Nucleotide Polymorphisms, Single,Polymorphisms, Single Nucleotide,Single Nucleotide Polymorphisms

Related Publications

Pierre Martinez, and Christopher Kimberley, and Nicolai J BirkBak, and Andrea Marquard, and Zoltan Szallasi, and Trevor A Graham
January 2016, Genes, chromosomes & cancer,
Pierre Martinez, and Christopher Kimberley, and Nicolai J BirkBak, and Andrea Marquard, and Zoltan Szallasi, and Trevor A Graham
May 2020, Nucleic acids research,
Pierre Martinez, and Christopher Kimberley, and Nicolai J BirkBak, and Andrea Marquard, and Zoltan Szallasi, and Trevor A Graham
July 2014, Nucleic acids research,
Pierre Martinez, and Christopher Kimberley, and Nicolai J BirkBak, and Andrea Marquard, and Zoltan Szallasi, and Trevor A Graham
January 2010, Methods in molecular biology (Clifton, N.J.),
Pierre Martinez, and Christopher Kimberley, and Nicolai J BirkBak, and Andrea Marquard, and Zoltan Szallasi, and Trevor A Graham
January 2012, Cancer informatics,
Pierre Martinez, and Christopher Kimberley, and Nicolai J BirkBak, and Andrea Marquard, and Zoltan Szallasi, and Trevor A Graham
April 2014, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie,
Pierre Martinez, and Christopher Kimberley, and Nicolai J BirkBak, and Andrea Marquard, and Zoltan Szallasi, and Trevor A Graham
June 2019, Animals : an open access journal from MDPI,
Pierre Martinez, and Christopher Kimberley, and Nicolai J BirkBak, and Andrea Marquard, and Zoltan Szallasi, and Trevor A Graham
January 2013, PloS one,
Pierre Martinez, and Christopher Kimberley, and Nicolai J BirkBak, and Andrea Marquard, and Zoltan Szallasi, and Trevor A Graham
August 2017, Proceedings of the National Academy of Sciences of the United States of America,
Pierre Martinez, and Christopher Kimberley, and Nicolai J BirkBak, and Andrea Marquard, and Zoltan Szallasi, and Trevor A Graham
June 2022, Trends in biotechnology,
Copied contents to your clipboard!