Prediction of tumor metastasis from sequencing data in the era of genome sequencing
- PMID: 31204784
- DOI: 10.1093/bfgp/elz010
Prediction of tumor metastasis from sequencing data in the era of genome sequencing
Abstract
Tumor metastasis is the key reason for the high mortality rate of tumor. Growing number of scholars have begun to pay attention to the research on tumor metastasis and have achieved satisfactory results in this field. The advent of the era of sequencing has enabled us to study cancer metastasis at the molecular level, which is essential for understanding the molecular mechanism of metastasis, identifying diagnostic markers and therapeutic targets and guiding clinical decision-making. We reviewed the metastasis-related studies using sequencing data, covering detection of metastasis origin sites, determination of metastasis potential and identification of distal metastasis sites. These findings include the discovery of relevant markers and the presentation of prediction tools. Finally, we discussed the challenge of studying metastasis considering the difficulty of obtaining metastatic cancer data, the complexity of tumor heterogeneity and the uncertainty of sample labels.
Keywords: distant metastases; next-generation sequencing; prediction; tumor metastasis; tumor origin.
© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Similar articles
-
Progress and challenges of sequencing and analyzing circulating tumor cells.Cell Biol Toxicol. 2018 Oct;34(5):405-415. doi: 10.1007/s10565-017-9418-5. Epub 2017 Nov 22. Cell Biol Toxicol. 2018. PMID: 29168077 Free PMC article. Review.
-
Next generation sequencing in cancer: opportunities and challenges for precision cancer medicine.Scand J Clin Lab Invest Suppl. 2016;245:S84-91. doi: 10.1080/00365513.2016.1210331. Epub 2016 Aug 17. Scand J Clin Lab Invest Suppl. 2016. PMID: 27542004
-
Tracking the origin of simultaneous endometrial and ovarian cancer by next-generation sequencing - a case report.BMC Cancer. 2017 Jan 19;17(1):66. doi: 10.1186/s12885-017-3054-6. BMC Cancer. 2017. PMID: 28103826 Free PMC article.
-
Identification of indels in next-generation sequencing data.BMC Bioinformatics. 2015 Feb 13;16(1):42. doi: 10.1186/s12859-015-0483-6. BMC Bioinformatics. 2015. PMID: 25879703 Free PMC article.
-
The impact of sequencing on diagnosis and treatment of malignant melanoma.Expert Rev Mol Diagn. 2016;16(4):423-33. doi: 10.1586/14737159.2016.1147958. Epub 2016 Feb 19. Expert Rev Mol Diagn. 2016. PMID: 26822148 Review.
Cited by
-
Clinical Perspectives on Liquid Biopsy in Metastatic Colorectal Cancer.Front Genet. 2021 Jan 28;12:634642. doi: 10.3389/fgene.2021.634642. eCollection 2021. Front Genet. 2021. PMID: 33584829 Free PMC article. Review.
-
GASIDN: identification of sub-Golgi proteins with multi-scale feature fusion.BMC Genomics. 2024 Oct 30;25(1):1019. doi: 10.1186/s12864-024-10954-3. BMC Genomics. 2024. PMID: 39478465 Free PMC article.
-
Identification of breast cancer risk modules via an integrated strategy.Aging (Albany NY). 2019 Dec 20;11(24):12131-12146. doi: 10.18632/aging.102546. Epub 2019 Dec 20. Aging (Albany NY). 2019. PMID: 31860871 Free PMC article.
-
Editorial: Medical knowledge-assisted machine learning technologies in individualized medicine.Front Mol Biosci. 2023 Mar 24;10:1167730. doi: 10.3389/fmolb.2023.1167730. eCollection 2023. Front Mol Biosci. 2023. PMID: 37033449 Free PMC article. No abstract available.
-
Novel Methylation Biomarkers for Colorectal Cancer Prognosis.Biomolecules. 2021 Nov 19;11(11):1722. doi: 10.3390/biom11111722. Biomolecules. 2021. PMID: 34827720 Free PMC article. Review.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources