Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data.
Tumors are made of evolving and heterogeneous populations of cells which arise from successive appearance and expansion of subclonal populations, following acquisition of mutations conferring them a selective advantage. Those subclonal populations can be sensitive or resistant to different treatment...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2019-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0224143 |
| _version_ | 1811173544986411008 |
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| author | Judith Abécassis Anne-Sophie Hamy Cécile Laurent Benjamin Sadacca Hélène Bonsang-Kitzis Fabien Reyal Jean-Philippe Vert |
| author_facet | Judith Abécassis Anne-Sophie Hamy Cécile Laurent Benjamin Sadacca Hélène Bonsang-Kitzis Fabien Reyal Jean-Philippe Vert |
| author_sort | Judith Abécassis |
| collection | DOAJ |
| description | Tumors are made of evolving and heterogeneous populations of cells which arise from successive appearance and expansion of subclonal populations, following acquisition of mutations conferring them a selective advantage. Those subclonal populations can be sensitive or resistant to different treatments, and provide information about tumor aetiology and future evolution. Hence, it is important to be able to assess the level of heterogeneity of tumors with high reliability for clinical applications. In the past few years, a large number of methods have been proposed to estimate intra-tumor heterogeneity from whole exome sequencing (WES) data, but the accuracy and robustness of these methods on real data remains elusive. Here we systematically apply and compare 6 computational methods to estimate tumor heterogeneity on 1,697 WES samples from the cancer genome atlas (TCGA) covering 3 cancer types (breast invasive carcinoma, bladder urothelial carcinoma, and head and neck squamous cell carcinoma), and two distinct input mutation sets. We observe significant differences between the estimates produced by different methods, and identify several likely confounding factors in heterogeneity assessment for the different methods. We further show that the prognostic value of tumor heterogeneity for survival prediction is limited in those datasets, and find no evidence that it improves over prognosis based on other clinical variables. In conclusion, heterogeneity inference from WES data on a single sample, and its use in cancer prognosis, should be considered with caution. Other approaches to assess intra-tumoral heterogeneity such as those based on multiple samples may be preferable for clinical applications. |
| first_indexed | 2024-04-10T17:48:42Z |
| format | Article |
| id | doaj.art-6da48fd0b1834220943fc85d7bbb4881 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-10T17:48:42Z |
| publishDate | 2019-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-6da48fd0b1834220943fc85d7bbb48812023-02-02T22:58:14ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-011411e022414310.1371/journal.pone.0224143Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data.Judith AbécassisAnne-Sophie HamyCécile LaurentBenjamin SadaccaHélène Bonsang-KitzisFabien ReyalJean-Philippe VertTumors are made of evolving and heterogeneous populations of cells which arise from successive appearance and expansion of subclonal populations, following acquisition of mutations conferring them a selective advantage. Those subclonal populations can be sensitive or resistant to different treatments, and provide information about tumor aetiology and future evolution. Hence, it is important to be able to assess the level of heterogeneity of tumors with high reliability for clinical applications. In the past few years, a large number of methods have been proposed to estimate intra-tumor heterogeneity from whole exome sequencing (WES) data, but the accuracy and robustness of these methods on real data remains elusive. Here we systematically apply and compare 6 computational methods to estimate tumor heterogeneity on 1,697 WES samples from the cancer genome atlas (TCGA) covering 3 cancer types (breast invasive carcinoma, bladder urothelial carcinoma, and head and neck squamous cell carcinoma), and two distinct input mutation sets. We observe significant differences between the estimates produced by different methods, and identify several likely confounding factors in heterogeneity assessment for the different methods. We further show that the prognostic value of tumor heterogeneity for survival prediction is limited in those datasets, and find no evidence that it improves over prognosis based on other clinical variables. In conclusion, heterogeneity inference from WES data on a single sample, and its use in cancer prognosis, should be considered with caution. Other approaches to assess intra-tumoral heterogeneity such as those based on multiple samples may be preferable for clinical applications.https://doi.org/10.1371/journal.pone.0224143 |
| spellingShingle | Judith Abécassis Anne-Sophie Hamy Cécile Laurent Benjamin Sadacca Hélène Bonsang-Kitzis Fabien Reyal Jean-Philippe Vert Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data. PLoS ONE |
| title | Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data. |
| title_full | Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data. |
| title_fullStr | Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data. |
| title_full_unstemmed | Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data. |
| title_short | Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data. |
| title_sort | assessing reliability of intra tumor heterogeneity estimates from single sample whole exome sequencing data |
| url | https://doi.org/10.1371/journal.pone.0224143 |
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