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Review
. 2016 Sep 6;7(36):58586-58594.
doi: 10.18632/oncotarget.10850.

Clonal evolution of acute myeloid leukemia highlighted by latest genome sequencing studies

Affiliations
Review

Clonal evolution of acute myeloid leukemia highlighted by latest genome sequencing studies

Xuehong Zhang et al. Oncotarget. .

Abstract

Decades of years might be required for an initiated cell to become a fully-pledged, metastasized tumor. DNA mutations are accumulated during this process including background mutations that emerge scholastically, as well as driver mutations that selectively occur in a handful of cancer genes and confer the cell a growth advantage over its neighbors. A clone of tumor cells could be superseded by another clone that acquires new mutations and grows more aggressively. Tumor evolutional patterns have been studied for years using conventional approaches that focus on the investigation of a single or a couple of genes. Latest deep sequencing technology enables a global view of tumor evolution by deciphering almost all genome aberrations in a tumor. Tumor clones and the fate of each clone during tumor evolution can be depicted with the help of the concept of variant allele frequency. Here, we summarize the new insights of cancer evolutional progression in acute myeloid leukemia. Cancer evolution is currently thought to start from a clone that has accumulated the requisite somatically-acquired genetic aberrations through a series of increasingly disordered clinical and pathological phases, eventually leading to malignant transformation [1-3]. The observations in invasive colorectal cancer that usually emerges from an antecedent benign adenomatous polyp and in cervical cancer that proceeds through intraepithelial neoplasia support the idea of stepwise or linear cancerous progression [3-5]. Genetically, such progression is achieved by successive waves of clonal expansion during which cells acquire novel genomic alterations including single nucleotide variants (SNVs), small insertions and deletions (indels), and/or copy number variations (CNVs) [6]. The latest improvement in sequencing technology has allowed the deciphering of the whole exome or genome in different types of tumor and normal tissue pairs, providing detailed catalogue about genome aberrations during tumor initiation and progression, which have been reviewed in several papers [7-10]. Here, we focus on demonstrating the cancer clonal evolution pattern revealed by recent deep sequencing studies of samples from acute myeloid leukemia (AML) patients.

Keywords: acute myeloid leukemia; cancer genome; clonal evolution.

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Conflict of interest statement

We do not have any conflicts of interest.

Figures

Figure 1
Figure 1. Clonal evolution revealed by cancer genome studies
A. Five distinct clones successively emerged in an AML patient with clone 4 surviving chemotherapy and evolving into clone 5 by the acquisition of novel drug-resistant mutations. B. Four of five dipoid tumor cells harbor the variant nucleotide of Guanine on one of the two homogenous chromosomes at the position of reference nucleotide of Adenine. Current sequencing technology does not discriminate the homogenous chromosomes and results in 10 short reads with 4 of them carrying variant nucleotide of G and 6 carrying reference nucleotide of A. Therefore, the variant allele frequency (VAF), 40% here, is equal to half of the percentage of mutation-carrying tumor cells, which is 80%. C. Tumor clones can be detected from the density plot of VAF with each peak representing a clone that carries the mutations defined in that peak.
Figure 2
Figure 2. Schematic representation of the conversion between tumor clonal architecture and somatic mutation clusters
A. Tumor cells in the initial population comprise the identical set of mutations shown in magenta bars; B. A subset of tumor cells obtains a new set of mutations (cyan bars) to form clone 2; and C. some of which further acquire one more set of mutations to form clone 3 (purple bars). Numbers in the parentheses denote the assumed percentage of tumor cells carrying the corresponding set of mutations at the sampling time. The low part in each panel shows the VAF density plots and mutation clusters that correspond to the clonal structures shown in the upper part.
Figure 3
Figure 3. VAF clustering analysis of patients sequenced at two tumor stages
Three clusters of mutations are identified. The changes of VAF represent the clonal evolution from stage I to II.
Figure 4
Figure 4. Comparison of VAFs on autosomal and sex chromosomes
Whole genome sequencing was applied to tumor and peri-tumor tissues of a lung adenocarcinoma patient. VAFs were calculated for somatic mutations on autosomes (1-22 chromosomes) and sex chromosomes (X and Y chromosomes). Numbers in parenthesis are the number of somatic mutations detected on autosome and sex chromosomes. Sequencing was done on Illumina Hiseq platform with pair end 150 bp and overall depth reached 30x.

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