Genomics and proteomics in renal cell carcinoma: Diagnosis, prognosis, and treatment selection

Current Urology Reports

Volumn 9, Issue 1, 2008, Pages 9-14

  Jones, Jon ^b   Pantuck, Allan J ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b NONE

Author keywords

[No Author keywords available]

Indexed keywords

ALPHA INTERFERON; INTERLEUKIN 2; SORAFENIB; SUNITINIB; TEMSIROLIMUS;

CANCER CLASSIFICATION; CANCER DIAGNOSIS; CANCER GENETICS; CANCER SURGERY; DNA MICROARRAY; GENE EXPRESSION; HISTOPATHOLOGY; HUMAN; KIDNEY CARCINOMA; PROGNOSIS; PROTEOMICS; REVIEW; TREATMENT RESPONSE;

CARCINOMA, RENAL CELL; GENOMICS; HUMANS; KIDNEY NEOPLASMS; PROGNOSIS; PROTEOMICS;

EID: 38349059246     PISSN: 15272737     EISSN: 15346285     Source Type: Journal    
DOI: 10.1007/s11934-008-0004-5     Document Type: Review

References (43)

1. •• 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. The first three studies cited here are of paramount importance to the molecularly targeted treatment of metastatic renal cell carcinoma (RCC) with sunitinib and sorafenib, which improved progression-free survival in patients with metastatic RCC compared with placebo. Compared with interferon alfa, temsirolimus improved overall survival among patients with metastatic RCC and a poor prognosis.
2. •• Motzer RJ, Hutson TE, Tomczak P, et al.: Sunitinib versus interferon alfa in metastatic renal-cell carcinoma. N Engl J Med, 2007, 356:115-124. See the above annotation.
3. •• Escudier B, Eisen T, Stadler WM, et al.: Sorafenib in advanced clear-cell renal-cell carcinoma. N Engl J Med 2007, 356:125-134. See the above annotation.
4. •• Ransohoff DF: Rules of evidence for cancer molecular-marker discovery and validation. Nat Rev Cancer 2004, 4:309-314. Excellent manuscript on the challenges assessing studies with high-throughput data and how problems might be avoided.
5. Jemal A, Siegel R, Ward E, et al.: Cancer statistics, 2006. CA Cancer J Clin 2006, 56:106-130.
6. • Lam JS, Shvarts O, Leppert JT, et al.: Renal cell carcinoma 2005: new frontiers in staging, prognostication, and targeted molecular therapy. J Urol 2005, 173:1853-1862. This review highlights controversies and provides an update on current staging modalities, prognostic factors, and targeted molecular therapy for RCC.
7. Janzen NK, Kim HL, Figlin RA, et al.: Surveillance after radical or partial nephrectomy for localized renal cell carcinoma and management of recurrent disease. Urol Clin North Am 2003, 30:843-852.
8. Amin MB, Tamboli P, Javidan J, et al.: Prognostic impact of histologic subtyping of adult renal epithelial neoplasms: an experience of 405 cases. Am J Surg Pathol 2002, 26:281-291.
9. Ramaswamy S, Golub TR: DNA microarrays in clinical oncology. J Clin Oncol 2002, 20:1932-1941.
10. Golub TR, Slonim DK, Tamayo P, et al.: Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 1999, 286:531-537.
11. Skubitz KM, Skubitz AP: Differential gene expression in renal-cell cancer. J Lab Clin Med 2002, 140:52-64.
12. Liou LS, Shi T, Duan ZH, et al.: Microarray gene expression profiling and analysis in renal cell carcinoma. BMC Urol 2004, 4:9.
13. 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.
14. 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.
15. • Sültmann 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. DNA microarray study. Distinct gene expression signatures were associated with chromosomal abnormalities of tumor cells, metastasis formation, and patient survival. The data highlight the benefit of microarrays to detect novel tumor classes and identify genes associated with patient variables and tumor properties.
16. • 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. DNA microarray study. Gene signatures were identified for each RCC subtype with 100% accuracy. A gene pattern ("metastatic signature") derived from primary tumor was very accurate in classifying tumors with and without metastases at the time of surgery. A previously described "global" metastatic signature derived by another group from various non-RCC tumors was validated in RCC.
17. Pantuck AJ, Zisman A, Belldegrun AS: The changing natural history of renal cell carcinoma. J Urol 2001, 166:1611-1623.
18. 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.
19. Gieseg MA, Cody T, Man MZ, et al.: Expression profiling of human renal carcinomas with functional taxonomic analysis. BMC Bioinformatics 2002, 3:26.
20. 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.
21. Takahashi M, Yang XJ, Sugimura J, et al.: Molecular subclassification of kidney tumors and the discovery of new diagnostic markers. Oncogene 2003, 22:6810-6818.
22. Young AN, Amin MB, Moreno CS, et al.: Expression profiling of renal epithelial neoplasms: a method for tumor classification and discovery of diagnostic molecular markers. Am J Pathol 2001, 158: 1639-1651.
23. 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.
24. Yang XJ, Tan MH, Kim HL, et al.: A molecular classification of papillary renal cell carcinoma. Cancer Res 2005, 65:5628-5637.
25. 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.
26. 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.
27. 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.
28. 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.
29. Ramaswamy S, Ross KN, Lander ES, et al.: A molecular signature of metastasis in primary solid tumors. 2003 Nat Genet, 33:49-54.
30. Jackson D, Zheng Y, Lyo D, et al.: Suppression of cell migration by protein kinase Cdelta. Oncogene 2005, 24:3067-3072.
31. Kruger JS, Reddy KB: Distinct mechanisms mediate the initial and sustained phases of cell migration in epidermal growth factor receptor-overexpressing cells. Mol Cancer Res 2003, 1:801-809.
32. Kumar V, Pandey P, Sabatini D, et al.: Functional interaction between RAFT1/FRAP/mTOR and protein kinase cdelta in the regulation of cap-dependent initiation of translation. Embo J 2000, 19:1087-1097.
33. Mingo-Sion AM, Ferguson HA, Koller E, et al.: PKCdelta and mTOR interact to regulate stress and IGF-I induced IRS-1 Ser312 phosphorylation in breast cancer cells. Breast Cancer Res Treat 2005, 91:259-269.
34. Petricoin EF, Zoon KC, Kohn EC, et al.: Clinical proteomics: translating benchside promise into bedside reality. Nat Rev Drug Discov 2002, 1:683-695.
35. Seibert V, Wiesner A, Buschmann T, et al.: Surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI TOF-MS) and ProteinChip technology in proteomics research. Pathol Res Pract 2004, 200:83-94.
36. Kolch W, Mischak H, Pitt AR: The molecular make-up of a tumour: proteomics in cancer research. Clin Sci (Lond) 2005, 108:369-383.
37. Cho WC, Cheng CH: Oncoproteomics: current trends and future perspectives. Expert Rev Proteomics 2007, 4:401-410.
38. Tolson J, Bogumil R, Brunst E, et al.: Serum protein profiling by SELDI mass spectrometry: detection of multiple variants of serum amyloid alpha in renal cancer patients. Lab Invest 2004, 84:845-856.
39. Won Y, Song HJ, Kang TW, et al.: Pattern analysis of serum proteome distinguishes renal cell carcinoma from other urologic diseases and healthy persons. Proteomics 2003, 3:2310-2316.
40. Engwegen JY, Mehra N, Haanen JB, et al.: Validation of SELDI-TOF MS serum protein profiles for renal cell carcinoma in new populations. Lab Invest 2007, 87:161-172.
41. Shi T, Dong F, Liou LS, et al.: Differential protein profiling in renal-cell carcinoma. Mol Carcinog 2004, 40:47-61.
42. Sarto C, Valsecchi C, Magni F, et al.: Expression of heat shock protein 27 in human renal cell carcinoma. Proteomics 2004, 4:2252-2260.
43. Jones J, Otu HH, Grall F, et al.: Proteomic identification of interleukin-2 therapy response in metastatic renal cell cancer. J Urol, In press.