Oncotarget

Research Papers:

Pan-cancer analysis of intratumor heterogeneity associated with patient prognosis using multidimensional measures

Chie Kikutake, Minako Yoshihara, Tetsuya Sato, Daisuke Saito and Mikita Suyama _

PDF  |  HTML  |  Supplementary Files  |  How to cite  |  Order a Reprint

Oncotarget. 2018; 9:37689-37699. https://doi.org/10.18632/oncotarget.26485

Metrics: PDF 760 views  |   HTML 940 views  |   ?  


Abstract

Chie Kikutake1, Minako Yoshihara1, Tetsuya Sato1, Daisuke Saito1 and Mikita Suyama1

1Medical Institute of Bioregulation, Kyushu University, Fukuoka 812-8582, Japan

Correspondence to:

Mikita Suyama, email: mikita@bioreg.kyushu-u.ac.jp

Keywords: variant allele frequency (VAF); The Cancer Genome Atlas (TCGA); next-generation sequencing; intratumor heterogeneity; prognosis

Received: November 22, 2018     Accepted: December 04, 2018     Published: December 28, 2018

ABSTRACT

Human cancers accumulate various mutations during development and consist of highly heterogeneous cell populations. This phenomenon is called intratumor heterogeneity (ITH). ITH is known to be involved in tumor growth, progression, invasion, and metastasis, presenting obstacles to accurate diagnoses and effective treatments. Numerous studies have explored the dynamics of ITH, including constructions of phylogenetic trees in cancer samples using multiregional ultradeep sequencing and simulations of evolution using statistical models. Although ITH is associated with prognosis, it is still challenging to use the characteristics of ITH as prognostic factors because of difficulties in quantifying ITH precisely. In this study, we analyzed the relationship between patient prognosis and the distribution of variant allele frequencies (VAFs) in cancer samples (n = 6,064) across 16 cancer types registered in The Cancer Genome Atlas. To measure VAF distributions multidimensionally, we adopted parameters that define the shape of VAF distributions and evaluated the relationships between these parameters and prognosis. In seven cancer types, we found significant relationships between prognosis and VAF distributions. Moreover, we observed that samples with a larger amount of mutations were not necessarily linked to worse prognosis. By evaluating the ITH from multidimensional viewpoints, it will be possible to provide a more accurate prediction of cancer prognosis.


Creative Commons License All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.
PII: 26485