Comprehensive genomic analyses of a metastatic colon cancer to the lung by whole exome sequencing and gene expression analysis

Fang,Li  Tai; Lee,Sharon; Choi,Helen; Kim,Hong   Kwan; Jew,Gregory; Kang,Hio  Chung; Chen,Lin; Jablons,David; Kim,Il-Jin

doi:10.3892/ijo.2013.2150

Comprehensive genomic analyses of a metastatic colon cancer to the lung by whole exome sequencing and gene expression analysis

Authors:
- Li Tai Fang
- Sharon Lee
- Helen Choi
- Hong Kwan Kim
- Gregory Jew
- Hio Chung Kang
- Lin Chen
- David Jablons
- Il-Jin Kim
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Affiliations: Thoracic Oncology Laboratory, Department of Surgery, University of California, San Francisco, San Francisco, CA, USA, Life Technologies, Seattle, WA, USA
Published online on: October 25, 2013 https://doi.org/10.3892/ijo.2013.2150
Pages: 211-221

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Abstract

We performed whole exome sequencing and gene expression analysis on a metastatic colon cancer to the lung, along with the adjacent normal tissue of the lung. Whole exome sequencing uncovered 71 high-confidence non‑synonymous mutations. We selected 16 mutation candidates, and 13 out of 16 mutations were validated by targeted deep sequencing using the Ion Torrent PGM customized AmpliSeq panel. By integrating mutation, copy number and gene expression microarray data, we identified a JAZF1 mutation with a gain-of-copy, suggesting its oncogenic potential for the lung metastasis from colon cancer. Our pathway analyses showed that the identified mutations closely reflected characteristics of the metastatic site (lung) while mRNA gene expression patterns kept genetic information of its primary tumor (colon). The most significant gene expression network was the ‘Colorectal Cancer Metastasis Signaling’, containing 6 (ADCY2, ADCY9, APC, GNB5, K-ras and LRP6) out of the 71 mutated genes. Some of these mutated genes (ADCY9, ADCY2, GNB5, K-ras, HDAC6 and ARHGEF17) also belong to the ‘Phospholipase C Signaling’ network, which suggests that this pathway and its mutated genes may contribute to a lung metastasis from colon cancer.

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1.	Hanahan D and Weinberg RA: The hallmarks of cancer. Cell. 100:57–70. 2000. View Article : Google Scholar
2.	Nguyen DX, Bos PD and Massagué J: Metastasis: from dissemination to organ-specific colonization. Nat Rev Cancer. 9:274–284. 2009. View Article : Google Scholar : PubMed/NCBI
3.	Jemal A, Bray F, Center MM, et al: Global cancer statistics. CA Cancer J Clin. 61:69–90. 2011. View Article : Google Scholar
4.	Pao W and Girard N: New driver mutations in non-small-cell lung cancer. Lancet Oncol. 12:175–180. 2011. View Article : Google Scholar : PubMed/NCBI
5.	Choi H, Kratz J, Pham P, et al: Development of a rapid and practical mutation screening assay for human lung adenocarcinoma. Int J Oncol. 40:1900–1906. 2012.PubMed/NCBI
6.	Vogelstein B, Fearon ER, Hamilton SR, et al: Genetic alterations during colorectal-tumor development. N Engl J Med. 319:525–532. 1988. View Article : Google Scholar : PubMed/NCBI
7.	Barrett JC: Mechanisms of multistep carcinogenesis and carcinogen risk assessment. Environ Health Perspect. 100:9–20. 1993. View Article : Google Scholar : PubMed/NCBI
8.	Rudin CM, Durinck S, Stawiski EW, et al: Comprehensive genomic analysis identifies SOX2 as a frequently amplified gene in small-cell lung cancer. Nat Genet. 44:1111–1116. 2012. View Article : Google Scholar : PubMed/NCBI
9.	Imielinski M, Berger AH, Hammerman PS, et al: Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing. Cell. 150:1107–1120. 2012. View Article : Google Scholar : PubMed/NCBI
10.	Cancer Genome Atlas Network: Comprehensive molecular characterization of human colon and rectal cancer. Nature. 487:330–337. 2012. View Article : Google Scholar : PubMed/NCBI
11.	Bosco-Clément G, Zhang F, Chen Z, et al: Targeting gli transcription activation by small molecule suppresses tumor growth. Oncogene. May 20–2013.(Epub ahead of print).
12.	Irizarry RA, Hobbs B, Collin F, et al: Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 4:249–264. 2003. View Article : Google Scholar
13.	Saunders CT, Wong WS, Swamy S, et al: Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs. Bioinformatics. 28:1811–1817. 2012. View Article : Google Scholar : PubMed/NCBI
14.	Cibulskis K, Lawrence MS, Carter SL, et al: Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat Biotechnol. 31:213–219. 2013. View Article : Google Scholar : PubMed/NCBI
15.	Wang K, Li M and Hakonarson H: ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38:e1642010. View Article : Google Scholar : PubMed/NCBI
16.	Li H, Handsaker B, Wysoker A, et al: The sequence alignment/map format and samtools. Bioinformatics. 25:2078–2079. 2009. View Article : Google Scholar : PubMed/NCBI
17.	Sathirapongsasuti JF, Lee H, Horst BA, et al: Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV. Bioinformatics. 27:2648–2654. 2011. View Article : Google Scholar : PubMed/NCBI
18.	Mao JH, Kim IJ, Wu D, et al: FBXW7 targets mTOR for degradation and cooperates with PTEN in tumor suppression. Science. 321:1499–1502. 2008. View Article : Google Scholar : PubMed/NCBI
19.	Wang X, Zhou C, Qiu G, et al: Phospholipase c epsilon plays a suppressive role in incidence of colorectal cancer. Med Oncol. 29:1051–1058. 2012. View Article : Google Scholar : PubMed/NCBI
20.	Danielsen SA, Cekaite L, Ågesen TH, et al: Phospholipase c isozymes are deregulated in colorectal cancer-insights gained from gene set enrichment analysis of the transcriptome. PLoS One. 6:e244192011. View Article : Google Scholar : PubMed/NCBI
21.	Redon R, Ishikawa S, Fitch KR, et al: Global variation in copy number in the human genome. Nature. 444:444–454. 2006. View Article : Google Scholar : PubMed/NCBI
22.	Grarup N, Andersen G, Krarup NT, et al: Association testing of novel type 2 diabetes risk alleles in the jazf1, cdc123/camk1d, tspan8, thada, adamts9, and notch2 loci with insulin release, insulin sensitivity, and obesity in a population-based sample of 4,516 glucose-tolerant middle-aged Danes. Diabetes. 57:2534–2540. 2008. View Article : Google Scholar
23.	Zeggini E, Scott LJ, Saxena R, et al: Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet. 40:638–645. 2008. View Article : Google Scholar : PubMed/NCBI
24.	Gateva V, Sandling JK, Hom G, et al: A large-scale replication study identifies tnip1, prdm1, jazf1, uhrf1bp1 and il10 as risk loci for systemic lupus erythematosus. Nat Genet. 41:1228–1233. 2009. View Article : Google Scholar : PubMed/NCBI
25.	Chiang S, Ali R, Melnyk N, et al: Frequency of known gene rearrangements in endometrial stromal tumors. Am J Surg Pathol. 35:1364–1372. 2011. View Article : Google Scholar : PubMed/NCBI
26.	Soda M, Choi YL, Enomoto M, et al: Identification of the transforming EML4-ALK fusion gene in non-small-cell lung cancer. Nature. 448:561–566. 2007. View Article : Google Scholar : PubMed/NCBI
27.	Holzinger A, Maier EM, Bück C, et al: Mutations in the proenteropeptidase gene are the molecular cause of congenital enteropeptidase deficiency. Am J Hum Genet. 70:20–25. 2002. View Article : Google Scholar : PubMed/NCBI
28.	Bergethon K, Shaw AT, Ou SH, et al: ROS1 rearrangements define a unique molecular class of lung cancers. J Clin Oncol. 30:863–870. 2012. View Article : Google Scholar : PubMed/NCBI
29.	Oxnard GR, Binder A and Jänne PA: New targetable oncogenes in non-small-cell lung cancer. J Clin Oncol. 31:1097–1104. 2013. View Article : Google Scholar : PubMed/NCBI
30.	Awad MM, Katayama R, McTigue M, et al: Acquired resistance to crizotinib from a mutation in CD74-ROS1. N Engl J Med. 368:2395–2401. 2013. View Article : Google Scholar : PubMed/NCBI