High Prevalence and Clinical Relevance of Genes Affected by Chromosomal Breaks in Colorectal Cancer

Abstract

Background: Cancer is caused by somatic DNA alterations such as gene point mutations, DNA copy number aberrations (CNA) and structural variants (SVs). Genome-wide analyses of SVs in large sample series with well-documented clinical information are still scarce. Consequently, the impact of SVs on carcinogenesis and patient outcome remains poorly understood. This study aimed to perform a systematic analysis of genes that are affected by CNA-associated chromosomal breaks in colorectal cancer (CRC) and to determine the clinical relevance of recurrent breakpoint genes.

Methods: Primary CRC samples of patients with metastatic disease from CAIRO and CAIRO2 clinical trials were previously characterized by array-comparative genomic hybridization. These data were now used to determine the prevalence of CNA-associated chromosomal breaks within genes across 352 CRC samples. In addition, mutation status of the commonly affected APC, TP53, KRAS, PIK3CA, FBXW7, SMAD4, BRAF and NRAS genes was determined for 204 CRC samples by targeted massive parallel sequencing. Clinical relevance was assessed upon stratification of patients based on gene mutations and gene breakpoints that were observed in >3% of CRC cases.

Results: In total, 748 genes were identified that were recurrently affected by chromosomal breaks (FDR <0.1). MACROD2 was affected in 41% of CRC samples and another 169 genes showed breakpoints in >3% of cases, indicating that prevalence of gene breakpoints is comparable to the prevalence of well-known gene point mutations. Patient stratification based on gene breakpoints and point mutations revealed one CRC subtype with very poor prognosis.

Conclusions: We conclude that CNA-associated chromosomal breaks within genes represent a highly prevalent and clinically relevant subset of SVs in CRC.

Fig 1. CNA-associated gene breakpoint detection.

(A) Array-CGH DNA copy number profile of one CRC sample. The X-axis depicts chromosomes 1–22 and X (numbered 23) with chromosome boundaries indicated by vertical dotted lines. The Y-axis depicts the log2 ratio of the amount of tumor DNA versus patient-matched normal DNA. Black dots represent individual array-CGH probe datapoints. The blue horizontal lines represent DNA segments, indicative for tumor DNA copy number aberrations when deviating from 0. The green arrow and bar indicate the region of chromosome 6 that is highlighted in Fig 1B. (B) Enlargement of Fig 1A (green bar). Vertical dotted red lines indicate genomic locations of CNA-associated chromosomal breakpoints, i.e. the genomic positions where log2 ratios of DNA segments change. (C) Frequency plot of CNA-associated chromosomal breakpoints on the q-arm of chromosome 13. The X-axis depicts the genomic position in Mb. The Y-axis depicts the chromosomal breakpoint frequencies across the cohort of 352 CRC samples. Breakpoint frequencies are indicated on array-CGH probe-level (vertical black bars) and on gene-level (horizontal red bars). Recurrent breakpoint genes (FDR<0.1) are named. The green arrow and bar indicate the PIBF1 region of chromosome 13q that is highlighted in Fig 1D. (D) Enlargement of Fig 1C (green bar), which illustrates that PIBF1 gene breakpoints are concentrated at the distal part of the gene. Neighbouring genes that do not harbor significant breakpoint recurrence rates are indicated in blue.

Fig 2. Gene breakpoint and gene mutation frequencies of the 25 most frequently affected genes in CRC.

Gene breakpoint frequencies (red bars) were based on the analysis of 352 CRC samples and gene mutation frequencies (blue bars) on the analysis of 204 samples. Genes marked with a “*” indicate a pool of genes that share probe(s) associated with chromosomal breakpoints: the PCMTD2* pool also includes LINC00266-1; PARK2* also includes PACRG; ZNF337* also includes NCOR1P1, FAM182A, FAM182B, FRG1B, MIR663A, MLLT10P1; CD99* also includes XG; PARP8* also includes EMB.

Fig 3. Clustering of 203 CRC patients by NBS based on gene breakpoints and gene mutations revealed four CRC subtypes.

(A) Co-clustering matrix of CRC samples generated by NBS analysis. The matrix color intensity represents the similarity score. The color bar on top indicates the groups of patients related to the four CRC subtypes (k = 4) as determined by hierarchical clustering after NBS analysis. (B) Kaplan-Meier plot for overall survival (in days) of CRC subtype 1 (n = 80 patients), subtype 2 (n = 45 patients), subtype 3 (n = 27 patients) and subtype 4 (n = 51 patients). There are significant differences in OS among the four CRC subtypes (log-rank P = 0.001), with poorest OS for subtype 3 CRC patients. (C) Kaplan-Meier plot for OS of CRC subtype 3 patients versus patients in other CRC subtypes, showing a hazard ratio (HR) of 2.17 and a median OS of 392 days versus 610 days, respectively (log-rank P = 0.0002).

Fig 4. Four distinct core modules of putative CRC driver genes were retrieved by Multi-Dendrix analysis.

The nodes comprise both gene breakpoints (red outline) and gene mutations (blue outline). Edges (grey lines) connect genes that are mutually exclusively affected. The thickness of the grey lines and the corresponding number reflect the robustness score. The strongest mutual exclusivity is observed between PIBF1 and TP53. Genes marked with a “*” indicate a pool of genes that share probe(s) associated with chromosomal breakpoints: the ZNF337* pool also includes NCOR1P1, FAM182A, FAM182B, FRG1B, MIR663A, MLLT10P1; ZNF519* also includes ANKRD20A5P, ANKRD30B.