DNA and MicroRNA Microarray Technologies in Diagnostics and Prediction for Patients with Renal Cell Carcinoma
Authors:
O. Slabý 1; M. Svoboda 1; J. Michálek 2; R. Vyzula 1
Authors place of work:
Klinika komplexní onkologické péče, Masarykův onkologický ústav, Brno2 Univerzitní centrum buněčné imunoterapie, Masarykova univerzita, Brno
1
Published in the journal:
Klin Onkol 2009; 22(5): 202-209
Category:
Reviews
Summary
Renal cell carcinoma accounts for approximately 3% of adult cancers and has the highest lethality of urological malignancies. Research focusing on carcinogenesis and development of renal cell carcinoma has led to the identification of the key signalling pathways and consequently targeted cancer therapy which improves time to progression or overall survival of renal cell carcinoma patients. Today, microarray technologies are some of the most efficient methods used in gene expression studies. Through one microarray experiment we can simultaneously determine the expression of thousands of genes, thus facilitating research of examined biological models. The most frequently used of the microarray technologies are DNA microarrays enabling global analysis of the mRNA (messenger RNA) expression, while recently, microarray platforms modified to detect short non coding RNAs (microRNAs) have been employed (microRNA microarrays). MicroRNAs significantly affect the behaviour of tumour cells by post transcriptional regulation of the gene expression. In the research into renal cell carcinoma, microarray technologies have been applied in more than twenty studies over the past five years. These papers describe the potential of microarrays to distinguish tumour tissue from normal renal parenchyma, to classify renal cell carcinomas according to histological subtypes, to identify expression profiles predicting metastasizing in primary renal tumours, and to determine the prognosis of particular renal cell carcinoma patients. The aim of this review is to summarize the results from microarray studies of renal cell carcinoma realized to date and to present their potential usage in diagnostic and therapeutic protocols.
Key words:
renal cell carcinoma – DNA microarrays – microRNA microarrays – prognosis – prediction
Zdroje
1. Dušek L, Mužík J, Kukásek M et al. Český národní webový portál epidemiologie nádorů [online]. Masarykova univerzita, 10. 1. 2008. http://www.svod.cz.
2. Yan BC, Mackinnon AC, Al-Ahmadie HA. Recent developments in the pathology of renal tumors: morphology and molecular characteristics of select entities. Arch Pathol Lab Med 2009; 133: 1026–32.
3. Bukowski RM. Prognostic factors for survival in metastatic renal cell carcinoma: update 2008. Cancer 2009; 115: 2273–2281.
4. Richie JP, Jonasch E, Kantoff PW. Renal Cell Carcinoma. In: Kufe WD, Bast RC, Hait WN et al. Holland-Frei Cancer Medicine, 7th ed. Hamilton (Canada): BC Decker 2006: 1401–1410.
5. Motzer RJ, Hutson TE, Tomczak P et al. Overall survival and updated results for sunitinib compared with interferon alfa in patients with metastatic renal cell carcinoma. J Clin Oncol 2009; 27: 3584–3590.
6. Escudier B, Eisen T, Stadler WM et al. Sorafenib for treatment of renal cell carcinoma: Final efficacy and safety results of the phase III treatment approaches in renal cancer global evaluation trial. J Clin Oncol 2009; 27: 3312–3318.
7. Hudes G, Carducci M, Tomczak P et al. Temsirolimus, interferon alfa, or both for advanced renal-cell carcinoma. N Engl J Med 2007; 356: 2271–2281.
8. Amato RJ. Vaccine therapy for renal cancer. Expert Rev Vaccines 2008; 7: 925–935.
9. Jones J, Libermann TA. Genomics of renal cell cancer: the biology behind and the therapy ahead. Clin Cancer Res 2007; 13: 685s–692s.
10. Jones J, Pantuck AJ. Genomics and proteomics in renal cell carcinoma: diagnosis, prognosis, and treatment selection. Curr Urol Rep 2008; 9: 9–14.
11. Svoboda M, Michálek J. Úvod do technologie DNA čipů. Lék a Techn 2004; 35: 67–75.
12. Perez-Diez A, Morgun A, Shulzhenko N. Microarrays for cancer diagnosis and classification. Adv Exp Med Biol 2007; 593: 74–85.
13. Virtanen C, Woodgett J. Clinical uses of microarrays in cancer research. Methods Mol Med 2008; 141: 87–113.
14. van't Veer LJ, Dai H, van de Vijver MJ et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002; 415: 530–536.
15. Slabý O. Pokroky v čipových technologiích znamenají pokroky v biomedicínském výzkumu i klinické diagnostice. Klin Onkol 2007; 2: 235–236.
16. Slaby O, Krekac D, Hrstka R et al. Zapojení mikroRNA do patogeneze nádorových onemocnění a možnosti jejich využití v diagnostické a prediktivní onkologii. Čas Lék Čes 2008; 147: 25–31.
17. Garzon R, Calin GA, Croce CM. MicroRNAs in Cancer. Annu Rev Med 2009; 60: 167–179.
18. Bartels CL, Tsongalis GJ. MicroRNAs: novel biomarkers for human cancer. Clin Chem 2009; 55: 623–631.
19. Brown BD, Naldini L. Exploiting and antagonizing microRNA regulation for therapeutic and experimental applications. Nat Rev Genet 2009; 10: 578–585.
20. Tibshirani R. A simple method for assessing sample sizes in microarray experiments. BMC Bioinformatics 2006; 7: 106.
21. Hardiman G. Microarrays Technologies 2006: an overview. Pharmacogenomics 2006; 7: 1153–8.
22. Tichý B, Svoboda M, Mayer J et al. Odběr a zpracování vzorků pro expresní DNA čipy. Klin Onkol 2006; 19 (Suppl 2): 350–354.
23. Lukešová Š, Kopecký O, Dvořák J et al. Význam genetických mutací a podstata poruchy angiogeneze u světlobuněčného karcinomu ledviny. Klin Onkol 2006; 19: 290–292.
24. Křepelová A. Dědičné formy nádorů ledvin – spektrum predispozičních genů a jejich testování. Klin Onkol 2006; 19 (Suppl): 82–84.
25. Jung M, Mollenkopf HJ, Grimm C et al. MicroRNA profiling of clear cell renal cell cancer identifies a robust signature to define renal malignancy. J Cell Mol Med 2009. In press.
26. Boer JM, Huber WK, Sultmann H et al. Identification and classification of differentially expressed genes in renal cell carcinoma by expression profiling on a global human 31,500-element cDNA array. Genome Res 2001; 11: 1861–1870.
27. Skubitz KM, Zimmermann W, Kammerer R et al. Differential gene expression identifies subgroups of renal cell carcinoma. J Lab Clin Med 2006; 147: 250–267.
28. Liou LS, Shi T, Duan ZH et al. Microarray gene expression profiling and analysis in renal cell carcinoma. BMC Urol 2004; 4: 9.
29. Higgins JP, Shinghal R, Gill H et al. Gene expression patterns in renal cell carcinoma assessed by complementary DNA microarray. Am J Pathol 2003; 162: 925–932.
30. Schuetz AN, Yin Goen Q, Amin MB et al. Molecular classification of renal tumors by gene expression profiling. J Mol Diagn 2005; 7: 206–218.
31. Gieseg MA, Cody T, Man MZ et al. Expression profiling of human renal carcinomas with functional taxonomic analysis. BMC Bioinformatics 2002; 3: 26.
32. Diegmann J, Tomiuk S, Sanjmyatav J et al. Comparative transcriptional and functional profiling of clear cell and papillary renal cell carcinoma. Int J Mol Med 2006; 18: 395-403.
33. Lenburg ME, Liou LS, Gerry NP et al. Previously unidentified changes in renal cell carcinoma gene expression identified by parametric analysis of microarray data. BMC Cancer 2003; 3: 31.
34. Jones J, Otu H, Spentzos D et al. Gene signatures of progression and metastasis in renal cell cancer. Clin Cancer Res 2005; 11: 5730–5739.
35. Copland JA, Luxon BA, Ajani L et al. Genomic profiling identifies alterations in TGFbeta signaling through loss of TGFbeta receptor expression in human renal cell carcinogenesis and progression. Oncogene 2003; 22: 8053–8062.
36. Roemer A, Schwettmann L, Jung M et al. Increased mRNA expression of ADAMs in renal cell carcinoma and their association with clinical outcome. Oncol Rep 2004; 11: 529–536.
37. Gottardo F, Liu CG, Ferracin M et al. Micro RNA profiling in kidney and bladder cancers. Urol Oncol 2007; 25: 387–392.
38. Nakada C, Matsuura K, Tsukamoto Y et al. Genome-wide microRNA expression profiling in renal cell carcinoma: significant down-regulation of miR-141 and miR-200c. J Pathol 2008; 216: 418–427.
39. Chow TF, Youssef YM, Lianidou E et al. Differential Expression Profiling of microRNAs and Their Potential Involvement in Renal Cell Carcinoma Pathogenesis. Clin Biochem 2009. In press.
40. Sultmann H, von Heydebreck A, Huber W et al. Gene expression in kidney cancer is associated with cytogenetic abnormalities, metastasis formation, and patient survival. Clin Cancer Res 2005; 11: 646–655.
41. Petillo D, Kort EJ, Anema J et al. MicroRNA profiling of human kidney cancer subtypes. Int J Oncol 2009; 35: 109–114.
42. Takahashi M, Rhodes DR, Furge KA et al. Gene expression profiling of clear cell renal cell carcinoma: gene identification and prognostic classification. Proc Natl Acad Sci U S A 2001; 98: 9754–9759.
43. Vasselli JR, Shih JH, Iyengar SR et al. Predicting survival in patients with metastatic kidney cancer by gene-expression profiling in the primary tumor. Proc Natl Acad Sci U S A 2003; 100: 6958–6963.
44. Yao M, Tabuchi H, Nagashima Y et al. Gene expression analysis of renal carcinoma: adipose differentiation related protein as a potential diagnostic and prognostic biomarker for clear-cell renal carcinoma. J Pathol 2005; 205: 377–387.
45. Yao M, Huang Y, Shioi K et al. Expression of adipose differentiation related protein: a predictor of cancer-specific survival in clear cell renal carcinoma. Clin Cancer Res 2007; 13: 152–160.
46. Kosari F, Parker AS, Kube DM et al. Clear cell renal cell carcinoma: gene expression analyses identify a potential signature for tumor aggressiveness. Clin Cancer Res 2005; 11: 5128–5139.
47. Moch H, Artibani W, Delahunt B et al. Reassessing the Current UICC/AJCC TNM Staging for Renal Cell Carcinoma. Eur Urol 2009. In press.
48. Ramaswamy S, Ross KN, Lander ES et al. A molecular signature of metastasis in primary solid tumors. Nat Genet 2003; 33: 49–54.
Štítky
Paediatric clinical oncology Surgery Clinical oncologyČlánok vyšiel v časopise
Clinical Oncology
2009 Číslo 5
- Spasmolytic Effect of Metamizole
- Metamizole at a Glance and in Practice – Effective Non-Opioid Analgesic for All Ages
- Metamizole in perioperative treatment in children under 14 years – results of a questionnaire survey from practice
- Current Insights into the Antispasmodic and Analgesic Effects of Metamizole on the Gastrointestinal Tract
- Obstacle Called Vasospasm: Which Solution Is Most Effective in Microsurgery and How to Pharmacologically Assist It?
Najčítanejšie v tomto čísle
- Rectal Neuroendocrine Tumours
- Chronic Gastrointestinal Toxicity after External-Beam Radiation Therapy for Prostate Cancer
- Evaporation of Selected Cytotoxic Drugs and Permeation of Protective Gloves – Research into the Occupational Risks of Health Care Personnel Handling Hazardous Cytotoxic Drugs (CYTO Project)
- Proteomic Analysis of Cancer Cells