Genomic and transcriptomic analysis of imatinib resistance in gastrointestinal stromal tumors

Abstract

Gastrointestinal stromal tumors represent the most common mesenchymal tumor of the digestive tract, driven by gain-of-function mutations in KIT. Despite its proven benefits, half of the patients treated with imatinib show disease progression within 2 years due to secondary resistance mutations in KIT. It remains unclear how the genomic and transcriptomic features change during the acquisition of imatinib resistance. Here, we performed exome sequencing and microarray transcription analysis for four imatinib-resistant cell lines and one cell line briefly exposed to imatinib. We also performed exome sequencing of clinical tumor samples. The cell line briefly exposed to imatinib exhibited few single-nucleotide variants and copy-number alterations, but showed marked upregulation of genes related to detoxification and downregulation of genes involved in cell cycle progression. Meanwhile, resistant cell lines harbored numerous genomic changes: amplified genes related to detoxification and deleted genes with cyclin-dependent kinase activity. Some variants in the resistant samples were traced back to the drug-sensitive samples, indicating the presence of ancestral subpopulations. The subpopulations carried variants associated with cell death. Pre-existing cancer cells with genetic alterations promoting apoptosis resistance may serve as a basis whereby cancer cells with critical mutations, such as secondary KIT mutations, can establish full imatinib resistance. © 2017 The Authors Genes, Chromosomes and Cancer Published by Wiley Periodicals, Inc.

Figure 1

Statistics of SNVs/indels, CNAs, and transcripts. The parental cell line (T1) was used as the background set to identify all types of alterations. The culture time shown is expressed in weeks. Asterisks (*) indicate cell lines with secondary KIT mutations known to cause drug resistance. (A) Graphs regarding SNVs/indels, which show the number of SNVs/indels and the distributions of their VAFs. Nonsilent mutations were composed of nonsynonymous, stop gain/loss, frame‐shift, and splicing mutations. (B) Graphs depicting CNAs with the number and total length of CNA segments and the distribution of their log cnRs. (C) Graphs illustrating gene expression, which show the numbers of DETs with >2‐ and 4‐fold changes and the distribution of log exRs for genes with >2‐fold changes. For reference, we drew a line indicating the number of all expressed transcripts in microarrays on the right axis. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 2

Heatmaps across cell lines. Boxes represent the results of GSEA. (A) SNVs: The SNV heatmap depicts VAFs across cell lines for nonsilent SNVs observed in at least one cell line. The vertical axis represents genes. The heatmap for synonymous SNVs is shown in Supporting Information Figure S5. (B) CNAs: the CNA heatmap depicts log cnRs for the CNA‐fragment regions. The vertical axis represents CNA‐fragment regions called in at least one cell line. (C) Expression levels: the DEG heatmap depicts log exRs for genes with >4‐fold expression changes. The vertical axis represents genes with expression changes in at least one cell line. The gray color in the heatmap indicates values filtered by data‐quality check. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 3

Evolutionary analysis and model of GIST imatinib resistance. (A) Phylogenetic tree and SNVs traceable to T1. The root of the tree can be assumed as T1 or located near T1. SNVs that can be tracked back to T1 are shown in the table, where the percentages of VAFs from ultra‐deep sequencing are filled in the cells. VAFs shown in yellow are nearly 50%, which indicates that all cells in the cell lines should have a variant. VAFs shown in red correspond to the VAFs of the same SNVs in T117 and T1. For reference, we listed the secondary KIT mutations, where the symbol “–” indicates VAFs below the detection limit of NGS. (B) A possible evolutionary model. A strong tribe pre‐exists at the indicated percentages, resisting cell death under imatinib exposure. A small number of cells in the tribe with secondary KIT mutations (possibility 1 shown in the figure) or cells that have acquired the mutations (possibility 2) ultimately dominate the population. During the evolutionary process, they may change their early transcriptional responses and be later selected based on genetic alterations. [Color figure can be viewed at wileyonlinelibrary.com]