Cancer phylogenetic inference using copy number alterations detected from DNA sequencing data
Cancer is an evolutionary process involving the accumulation of diverse somatic mutations and clonal evolution over time. Phylogenetic inference from samples obtained from an individual patient offers a powerful approach to unraveling the intricate evolutionary history of cancer and provides insight...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Cancer Pathogenesis and Therapy |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949713224000272 |
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| author | Bingxin Lu |
| author_facet | Bingxin Lu |
| author_sort | Bingxin Lu |
| collection | DOAJ |
| description | Cancer is an evolutionary process involving the accumulation of diverse somatic mutations and clonal evolution over time. Phylogenetic inference from samples obtained from an individual patient offers a powerful approach to unraveling the intricate evolutionary history of cancer and provides insights that can inform cancer treatment. Somatic copy number alterations (CNAs) are important in cancer evolution and are often used as markers, alone or with other somatic mutations, for phylogenetic inferences, particularly in low-coverage DNA sequencing data. Many phylogenetic inference methods using CNAs detected from bulk or single-cell DNA sequencing data have been developed over the years. However, there have been no systematic reviews on these methods. To summarize the state-of-the-art of the field and inform future development, this review presents a comprehensive survey on the major challenges in inference, different types of methods, and applications of these methods. The challenges are discussed from the aspects of input data, models of evolution, and inference algorithms. The different methods are grouped according to the markers used for inference and the types of the reconstructed trees. The applications include using phylogenetic inference to understand intra-tumor heterogeneity, metastasis, treatment resistance, and early cancer development. This review also sheds light on future directions of cancer phylogenetic inference using CNAs, including the improvement of scalability, the utilization of new types of data, and the development of more realistic models of evolution. |
| format | Article |
| id | doaj-art-dbb1927a8fe846248f59568c0d294a72 |
| institution | Kabale University |
| issn | 2949-7132 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Cancer Pathogenesis and Therapy |
| spelling | doaj-art-dbb1927a8fe846248f59568c0d294a722025-01-06T04:09:11ZengElsevierCancer Pathogenesis and Therapy2949-71322025-01-01311629Cancer phylogenetic inference using copy number alterations detected from DNA sequencing dataBingxin Lu0School of Biosciences and Medicine, University of Surrey, Guildford GU2 7XH, UK; Surrey Institute for People-Centred Artificial Intelligence, University of Surrey, Guildford GU2 7XH, UK; Corresponding author: School of Biosciences and Medicine, University of Surrey, Guildford GU2 7XH, UK.Cancer is an evolutionary process involving the accumulation of diverse somatic mutations and clonal evolution over time. Phylogenetic inference from samples obtained from an individual patient offers a powerful approach to unraveling the intricate evolutionary history of cancer and provides insights that can inform cancer treatment. Somatic copy number alterations (CNAs) are important in cancer evolution and are often used as markers, alone or with other somatic mutations, for phylogenetic inferences, particularly in low-coverage DNA sequencing data. Many phylogenetic inference methods using CNAs detected from bulk or single-cell DNA sequencing data have been developed over the years. However, there have been no systematic reviews on these methods. To summarize the state-of-the-art of the field and inform future development, this review presents a comprehensive survey on the major challenges in inference, different types of methods, and applications of these methods. The challenges are discussed from the aspects of input data, models of evolution, and inference algorithms. The different methods are grouped according to the markers used for inference and the types of the reconstructed trees. The applications include using phylogenetic inference to understand intra-tumor heterogeneity, metastasis, treatment resistance, and early cancer development. This review also sheds light on future directions of cancer phylogenetic inference using CNAs, including the improvement of scalability, the utilization of new types of data, and the development of more realistic models of evolution.http://www.sciencedirect.com/science/article/pii/S2949713224000272Clonal evolutionPhylogenetic inferenceSomatic mutationCopy number changeChromosomal instability |
| spellingShingle | Bingxin Lu Cancer phylogenetic inference using copy number alterations detected from DNA sequencing data Cancer Pathogenesis and Therapy Clonal evolution Phylogenetic inference Somatic mutation Copy number change Chromosomal instability |
| title | Cancer phylogenetic inference using copy number alterations detected from DNA sequencing data |
| title_full | Cancer phylogenetic inference using copy number alterations detected from DNA sequencing data |
| title_fullStr | Cancer phylogenetic inference using copy number alterations detected from DNA sequencing data |
| title_full_unstemmed | Cancer phylogenetic inference using copy number alterations detected from DNA sequencing data |
| title_short | Cancer phylogenetic inference using copy number alterations detected from DNA sequencing data |
| title_sort | cancer phylogenetic inference using copy number alterations detected from dna sequencing data |
| topic | Clonal evolution Phylogenetic inference Somatic mutation Copy number change Chromosomal instability |
| url | http://www.sciencedirect.com/science/article/pii/S2949713224000272 |
| work_keys_str_mv | AT bingxinlu cancerphylogeneticinferenceusingcopynumberalterationsdetectedfromdnasequencingdata |