Genomika ve výzkumu mnohočetného myelomu

Mnohočetný myelom je druhé nejčastější hematoonkologické onemocnění. Je to velmi heterogenní onemocnění charakterizované komplexitou genomu, opakujícími se amplifikacemi a/nebo delecemi, které vedou k rozdílnému klinickému projevu nemoci, ale i přežití u pacientů. Zejména nové metody genomiky hrají klíčovou roli v pochopení příčin patogeneze, progrese nemoci, ale i klasifikace MM.

Klíčová slova:
mnohočetný myelom – real-time PCR – SNP – GEP – patogeneze – prognóza

Tato práce byla podpořena granty MŠMT LC06027, MSM0021622434, granty IGA MZd NS10387, NS10406, NS10408 a GAČR GAP304/10/1395.

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Autoři: S. Ševčíková ¹; P. Němec ^1,2; L. Pour ³; R. Hájek ^1,3,4
Působiště autorů: Babak Myeloma Group, Department of Pathological Physiology, Faculty of Medicine, Masaryk University, Brno, Czech Republic ¹; Department of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic ²; Department of Internal Medicine – Hematooncology, University Hospital Brno, Czech Republic ³; Laboratory of Experimental Hematology and Cell Immunotherapy, Department of Clinical Hematology, University Hospital Brno, Czech Republic ⁴
Vyšlo v časopise: Klin Onkol 2011; 24(Supplementum 1): 34-38

Souhrn

Zdroje

1. Munshi NC, Avet-Loiseau H. Genomics in multiple myeloma. Clin Cancer Res 2011; 17(6): 1234–1242.

2. Davies FE, Dring AM, Li C et al. Insights into multistep transformation of MGUS to myeloma using microarray expression analysis. Blood 2003; 102(13): 4504–4511.

3. Zhan F, Hardin J, Kordsmeier B et al. Global gene expression profiling of multiple myeloma, monoclonal gammopathy of undetermined significance, and normal bone marrow plasma cells. Blood 2002; 99(5): 1745–1757.

4. Bergsagel PL, Kuehl WM, Zhan F et al. Cyclin D dysregulation: an early and unifying pathogenic event in multiple myeloma. Blood 2005; 106(1): 296–303.

5. Zhan F, Huang Y, Colla S et al. The molecular classification of multiple myeloma. Blood 2006; 108(6): 2020–2028.

6. Shaughnessy JD Jr, Zhan F, Burington BE et al. A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1. Blood 2007; 109(6): 2276–2284.

7. Chng WJ, Santana-Dávila R, Van Wier SA et al. Prognostic factors for hyperdiploid-myeloma: effects of chromosome 13 deletions and IgH translocations. Leukemia 2006; 20(5): 807–813.

8. Chng WJ, Ahmann GJ, Henderson K et al. Clinical implication of centrosome amplification in plasma cell neoplasm. Blood 2006; 107(9): 3669–3675.

9. Bustin SA. A–Z of quantitative PCR. 5th ed. California: IUL Biotechnology Series, La Jolla 2004–2006.

10. Kleppe K, Ohtsuka E, Kleppe R et al. Studies on polynucleotides XCVL. Repair replication of short sythetic DNA’s as catalysed by DNA polymerases. J Mol Biol 1971; 56(2): 341–361.

11. Saiki RK, Scharf S, Faloona F et al. Enzymatic amplification of beta-globin genomic sequences and restriction site analysis for diagnosis of sickle cell anemia. Science 1985; 230(4732): 1350–1354.

12. Mullis KB, Faloona FA. Specific synthesis of DNA in vitro via a polymerase catalyzed chain reaction. Methods Enzymol 1987; 155: 335–350.

13. Higuchi R, Dollinger G, Walsh PS et al. Simultaneous amplification and detection of specific DNA sequences. Biotechnology 1992; 10(4): 413–417.

14. Higuchi R, Fockler C, Dollinger G et al. Kinetic PCR analysis: real-time monitoring of DNA amplification reactions. Biotechnology 1993; 11(9): 1026–1030.

15. Ely S. Using aspirates for multiple myeloma research probably excludes important data. Br J Haematol 2006; 134(2): 238–246.

16. Sorrig R, Hermansen N, Hother C et al. CD138+ cell separation affects cancer gene expression in human myeloma cell lines. Haematologica 2010; 95 (Suppl 2): 137.

17. Bustin SA, Benes V, Garson JA et al. The MIQE guidelines: minimum information for publication of qunatitative real-time PCR experiments. Clin Chem 2009; 55(4): 611–622.

18. Pfaffl MW. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res 2001; 29(9): e45.

19. Ramsay G. DNA chips: state-of-the art. Nat Biotechnol 1998; 16(1): 40–44.