Prediction of tumor metastasis from sequencing data in the era of genome sequencing

Author:

Yuan Linlin1,Guo Fei1,Wang Lei2,Zou Quan34ORCID

Affiliation:

1. College of Intelligence and Computing, Tianjin University, Tianjin, China

2. College of Computer Engineering & Applied Mathematics, Changsha University, Changsha, China

3. Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China

4. Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China

Abstract

AbstractTumor 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.

Funder

Natural Science Foundation of China

National Key R&D Program of China

Publisher

Oxford University Press (OUP)

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