期刊论文详细信息
BMC Medical Genomics
Intratumoral genetic heterogeneity in metastatic melanoma is accompanied by variation in malignant behaviors
Andreas Behren3  Jonathan Cebon5  Alexander Dobrovic1  Ian D Davis2  Otavia L Caballero6  Hongdo Do1  Pu-Han Lo3  Christopher Hudson3  Matthew Anaka4 
[1]Department of Pathology, University of Melbourne, Parkville, Victoria 3010, Australia
[2]Current Address: Monash University and Eastern Health, Box Hill, Victoria 3128, Australia
[3]Cancer Immuno-biology Lab, Ludwig Institute for Cancer Research Melbourne, Austin Branch, Melbourne, Victoria 3084, Australia
[4]Department of Medicine, Austin Health, University of Melbourne, Parkville, Victoria 3010, Australia
[5]Ludwig Institute For Cancer Research, Level 5, Olivia Newton-John Cancer & Wellness Centre, Studley Road, Heidelberg, Victoria 3084, Australia
[6]Department of Neurosurgery, John Hopkins University School of Medicine, Baltimore, MD 21231, USA
关键词: Clonal;    Copy number;    Mutation profiling;    Heterogeneity;    Microarray;    Melanoma;   
Others  :  1091799
DOI  :  10.1186/1755-8794-6-40
 received in 2013-04-21, accepted in 2013-09-19,  发布年份 2013
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【 摘 要 】

Background

Intratumoral heterogeneity is a major obstacle for the treatment of cancer, as the presence of even minor populations that are insensitive to therapy can lead to disease relapse. Increased clonal diversity has been correlated with a poor prognosis for cancer patients, and we therefore examined genetic, transcriptional, and functional diversity in metastatic melanoma.

Methods

Amplicon sequencing and SNP microarrays were used to profile somatic mutations and DNA copy number changes in multiple regions from metastatic lesions. Clonal genetic and transcriptional heterogeneity was also assessed in single cell clones from early passage cell lines, which were then subjected to clonogenicity and drug sensitivity assays.

Results

MAPK pathway and tumor suppressor mutations were identified in all regions of the melanoma metastases analyzed. In contrast, we identified copy number abnormalities present in only some regions in addition to homogeneously present changes, suggesting ongoing genetic evolution following metastatic spread. Copy number heterogeneity from a tumor was represented in matched cell line clones, which also varied in their clonogenicity and drug sensitivity. Minor clones were identified based on dissimilarity to the parental cell line, and these clones were the most clonogenic and least sensitive to drugs. Finally, treatment of a polyclonal cell line with paclitaxel to enrich for drug-resistant cells resulted in the adoption of a gene expression profile with features of one of the minor clones, supporting the idea that these populations can mediate disease relapse.

Conclusion

Our results support the hypothesis that minor clones might have major consequences for patient outcomes in melanoma.

【 授权许可】

   
2013 Anaka et al.; licensee BioMed Central Ltd.

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【 参考文献 】
  • [1]Vogelstein B, Kinzler KW: The multistep nature of cancer. Trends Genet 1993, 9:138-141.
  • [2]Merlo LM, Pepper JW, Reid BJ, Maley CC: Cancer as an evolutionary and ecological process. Nat Rev Cancer 2006, 6:924-935.
  • [3]Maley CC, Galipeau PC, Finley JC, Wongsurawat VJ, Li X, Sanchez CA, Paulson TG, Blount PL, Risques RA, Rabinovitch PS, Reid BJ: Genetic clonal diversity predicts progression to esophageal adenocarcinoma. Nat Genet 2006, 38:468-473.
  • [4]Yachida S, Jones S, Bozic I, Antal T, Leary R, Fu B, Kamiyama M, Hruban RH, Eshleman JR, Nowak MA, et al.: Distant metastasis occurs late during the genetic evolution of pancreatic cancer. Nature 2010, 467:1114-1117.
  • [5]Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E, Martinez P, Matthews N, Stewart A, Tarpey P, et al.: Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 2012, 366:883-892.
  • [6]Berger MF, Hodis E, Heffernan TP, Deribe YL, Lawrence MS, Protopopov A, Ivanova E, Watson IR, Nickerson E, Ghosh P, et al.: Melanoma genome sequencing reveals frequent PREX2 mutations. Nature 2012, 485:502-506.
  • [7]Hodis E, Watson IR, Kryukov GV, Arold ST, Imielinski M, Theurillat JP, Nickerson E, Auclair D, Li L, Place C, et al.: A landscape of driver mutations in melanoma. Cell 2012, 150:251-263.
  • [8]Sabatino M, Zhao Y, Voiculescu S, Monaco A, Robbins P, Karai L, Nickoloff BJ, Maio M, Selleri S, Marincola FM, Wang E: Conservation of genetic alterations in recurrent melanoma supports the melanoma stem cell hypothesis. Cancer Res 2008, 68:122-131.
  • [9]Takata M, Morita R, Takehara K: Clonal heterogeneity in sporadic melanomas as revealed by loss-of-heterozygosity analysis. Int J Cancer 2000, 85:492-497.
  • [10]Fusi A, Berdel R, Havemann S, Nonnenmacher A, Keilholz U: Enhanced detection of BRAF-mutants by pre-PCR cleavage of wild-type sequences revealed circulating melanoma cells heterogeneity. Eur J Cancer 2011, 47:1971-1976.
  • [11]Wilmott JS, Tembe V, Howle JR, Sharma R, Thompson JF, Rizos H, Lo RS, Kefford RF, Scolyer RA, Long GV: Intratumoral molecular heterogeneity in a BRAF-mutant, BRAF inhibitor-resistant melanoma: a case illustrating the challenges for personalized medicine. Mol Cancer Ther 2012, 11:2704-2708.
  • [12]Ceol CJ, Houvras Y, Jane-Valbuena J, Bilodeau S, Orlando DA, Battisti V, Fritsch L, Lin WM, Hollmann TJ, Ferre F, et al.: The histone methyltransferase SETDB1 is recurrently amplified in melanoma and accelerates its onset. Nature 2011, 471:513-517.
  • [13]Macgregor S, Montgomery GW, Liu JZ, Zhao ZZ, Henders AK, Stark M, Schmid H, Holland EA, Duffy DL, Zhang M, et al.: Genome-wide association study identifies a new melanoma susceptibility locus at 1q21.3. Nat Genet 2011, 43:1114-1118.
  • [14]Luker KE, Pica CM, Schreiber RD, Piwnica-Worms D: Overexpression of IRF9 confers resistance to antimicrotubule agents in breast cancer cells. Cancer Res 2001, 61:6540-6547.
  • [15]Takeda M, Mizokami A, Mamiya K, Li YQ, Zhang J, Keller ET, Namiki M: The establishment of two paclitaxel-resistant prostate cancer cell lines and the mechanisms of paclitaxel resistance with two cell lines. Prostate 2007, 67:955-967.
  • [16]Kreso A, O’Brien CA, van Galen P, Gan O, Notta F, Brown AM, Ng K, Ma J, Wienholds E, Dunant C, et al.: Variable Clonal Repopulation Dynamics Influence Chemotherapy Response in Colorectal Cancer. Science 2012, 339:543-548.
  • [17]Diaz LA Jr, Williams RT, Wu J, Kinde I, Hecht JR, Berlin J, Allen B, Bozic I, Reiter JG, Nowak MA, et al.: The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers. Nature 2012, 486:537-540.
  • [18]Villanueva J, Vultur A, Lee JT, Somasundaram R, Fukunaga-Kalabis M, Cipolla AK, Wubbenhorst B, Xu X, Gimotty PA, Kee D, et al.: Acquired resistance to BRAF inhibitors mediated by a RAF kinase switch in melanoma can be overcome by cotargeting MEK and IGF-1R/PI3K. Cancer Cell 2010, 18:683-695.
  • [19]Vergani E, Vallacchi V, Frigerio S, Deho P, Mondellini P, Perego P, Cassinelli G, Lanzi C, Testi MA, Rivoltini L, et al.: Identification of MET and SRC activation in melanoma cell lines showing primary resistance to PLX4032. Neoplasia 2011, 13:1132-1142.
  • [20]Gibbs P, Hutchins AM, Dorian KT, Vaughan HA, Davis ID, Silvapulle M, Cebon JS: MAGE-12 and MAGE-6 are frequently expressed in malignant melanoma. Melanoma Res 2000, 10:259-264.
  • [21]Wang Y, Carlton VE, Karlin-Neumann G, Sapolsky R, Zhang L, Moorhead M, Wang ZC, Richardson AL, Warren R, Walther A, et al.: High quality copy number and genotype data from FFPE samples using Molecular Inversion Probe (MIP) microarrays. BMC Med Genomics 2009, 2:8. BioMed Central Full Text
  • [22]Smyth GK: Limma: linear models for microarray data. In Bioinformatics and Computational Biology Solutions using R and Bioconductor. Edited by Gentleman R, Carey V, Dudoit S, Irizarry R, Huber W. New York: Springer; 2005:397-420.
  • [23]Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP: Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 2005, 102:15545-15550.
  • [24]Loman NJ, Misra RV, Dallman TJ, Constantinidou C, Gharbia SE, Wain J, Pallen MJ: Performance comparison of benchtop high-throughput sequencing platforms. Nat Biotechnol 2012, 30:434-439.
  • [25]McLaren W, Pritchard B, Rios D, Chen Y, Flicek P, Cunningham F: Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics 2010, 26:2069-2070.
  • [26]Sim NL, Kumar P, Hu J, Henikoff S, Schneider G, Ng PC: SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res 2012, 40:W452-W457.
  • [27]Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR: A method and server for predicting damaging missense mutations. Nat Methods 2010, 7:248-249.
  • [28]Do H, Dobrovic A: Dramatic reduction of sequence artefacts from DNA isolated from formalin-fixed cancer biopsies by treatment with uracil- DNA glycosylase. Oncotarget 2012, 3:546-558.
  • [29]Do H, Dobrovic A: Limited copy number-high resolution melting (LCN-HRM) enables the detection and identification by sequencing of low level mutations in cancer biopsies. Mol Cancer 2009, 8:82. BioMed Central Full Text
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