Abstract
Background
Longitudinal next generation sequencing of cancer patient samples has enhanced our understanding of the evolution and progression of various cancers. As a result, and due to our increasing knowledge of heterogeneity, such sampling is becoming increasingly common in research and clinical trial sample collections. Traditionally, the evolutionary analysis of these cohorts involves the use of an aligner followed by subsequent stringent downstream analyses. However, this can lead to large levels of information loss due to the vast mutational landscape that characterises tumour samples.
Design
Here, we propose an alignment-free approach for sequence comparison - a well-established approach in a range of biological applications including typical phylogenetic classification. Such methods could be used to compare information collated in raw sequence files to allow an unsupervised assessment of the evolutionary trajectory of patient genomic profiles.
Results
In order to highlight this utility in cancer research we have applied our alignment-free approach using a previously established metric, Jensen-Shannon divergence, and a metric novel to this area, Hellinger distance, to two longitudinal cancer patient cohorts in glioma and clear cell renal cell carcinoma using our software, NUQA.
Conclusion
We hypothesise that this approach has the potential to reveal novel information about the heterogeneity and evolutionary trajectory of spatiotemporal tumour samples, potentially revealing early events in tumorigenesis and the origins of metastases and recurrences.
Longitudinal next generation sequencing of cancer patient samples has enhanced our understanding of the evolution and progression of various cancers. As a result, and due to our increasing knowledge of heterogeneity, such sampling is becoming increasingly common in research and clinical trial sample collections. Traditionally, the evolutionary analysis of these cohorts involves the use of an aligner followed by subsequent stringent downstream analyses. However, this can lead to large levels of information loss due to the vast mutational landscape that characterises tumour samples.
Design
Here, we propose an alignment-free approach for sequence comparison - a well-established approach in a range of biological applications including typical phylogenetic classification. Such methods could be used to compare information collated in raw sequence files to allow an unsupervised assessment of the evolutionary trajectory of patient genomic profiles.
Results
In order to highlight this utility in cancer research we have applied our alignment-free approach using a previously established metric, Jensen-Shannon divergence, and a metric novel to this area, Hellinger distance, to two longitudinal cancer patient cohorts in glioma and clear cell renal cell carcinoma using our software, NUQA.
Conclusion
We hypothesise that this approach has the potential to reveal novel information about the heterogeneity and evolutionary trajectory of spatiotemporal tumour samples, potentially revealing early events in tumorigenesis and the origins of metastases and recurrences.
| Original language | English |
|---|---|
| Journal | Molecular Biology and Evolution |
| Early online date | 19 Aug 2019 |
| DOIs | |
| Publication status | Early online date - 19 Aug 2019 |
UN SDGs
This output contributes to the following Sustainable Development Goal(s)
Access to Document
- NUQA: Estimating cancer spatial and temporal heterogeneity and evolution through alignment-free methods
© 2019 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
