CELLO: a longitudinal data analysis toolbox untangling cancer evolution

Abstract

The complex pattern of cancer evolution poses a huge challenge to precision oncology. Longitudinal sequencing of tumor samples allows us to monitor the dynamics of mutations that occurred during this clonal evolution process. Here, we present a versatile toolbox, namely CELLO (Cancer EvoLution for LOngitudinal data), accompanied with a step-by-step tutorial, to exemplify how to profile, analyze and visualize the dynamic change of somatic mutational landscape using longitudinal genomic sequencing data. Moreover, we customize the hypermutation detection module in CELLO to adapt targeted-DNA and whole-transcriptome sequencing data, and verify the extensive applicability of CELLO in published longitudinal datasets from brain, bladder and breast cancers. The entire tutorial and reusable programs in MATLAB, R and docker versions are open access at https://github.com/WangLabHKUST/CELLO.

Graphical abstract

Keywords

cancer evolution / genomics / longitudinal sequencing / bioinformatics

References

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SUPPLEMENTARY MATERIALS

The supplementary materials and corresponding software are available online at https://github.com/WangLabHKUST/CELLO.

AUTHOR CONTRIBUTIONS

J.W. conceptualized the project. B.J. reimplemented the MATLAB version of CELLO upon J.W.’s scripts used in the work published on Nature Genetics in 2016. D.S. developed the R package of CELLO, and Q.M. developed the docker for the R package. All authors have written and approved the manuscript.

ACKNOWLEDGEMENTS

This work is supported by the grants from the National Natural Science Foundation of China (31922088), Research Grant Council (N_HKUST606/17, 26102719, C7065-18GF, C4039-19GF), Innovation and Technology Commission (ITCPD/17-9, ITS/480/18FP), and Hong Kong Branch of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (SMSEGL20SC01).

COMPLIANCE WITH ETHICS GUIDELINES

The authors Biaobin Jiang, Dong Song, Quanhua Mu and Jiguang Wang declare that they have no conflict of interests.

The article does not contain any human or animal subjects performed by any of the authors.

RIGHTS & PERMISSIONS

2020 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature