The use of automated quantitative analysis to evaluate epithelial-to-mesenchymal transition associated proteins in clear cell renal cell carcinoma

PLoS ONE

Volumn 7, Issue 2, 2012, Pages

  O'Mahony, Fiach C ^a   Faratian, Dana ^a   Varley, James ^a   Nanda, Jyoti ^a   Theodoulou, Marianna ^a   Riddick, Antony C P ^a   Harrison, David J ^a   Stewart, Grant D ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BETA CATENIN; CELL PROTEIN; TRANSCRIPTION FACTOR SLUG; TRANSCRIPTION FACTOR SNAIL; UVOMORULIN; WT1 PROTEIN; CANCER ANTIBODY; TUMOR PROTEIN;

ADULT; AGED; ARTICLE; AUTOMATED QUANTITATIVE ANALYSIS; AUTOMATION; CANCER CELL; CANCER PROGNOSIS; CANCER RESEARCH; CLUSTER ANALYSIS; CONTROLLED STUDY; DISEASE ASSOCIATION; DISEASE COURSE; DNA MICROARRAY; EPITHELIAL MESENCHYMAL TRANSITION; FEMALE; GENE EXPRESSION; HUMAN; HUMAN CELL; HUMAN TISSUE; IMMUNOFLUORESCENCE; KAPLAN MEIER METHOD; KIDNEY CARCINOMA; MAJOR CLINICAL STUDY; MALE; MULTIVARIATE ANALYSIS; NUCLEOTIDE SEQUENCE; PROGRESSION FREE SURVIVAL; PROPORTIONAL HAZARDS MODEL; PROTEIN BLOOD LEVEL; PROTEIN EXPRESSION; PROTEIN TARGETING; STROMA CELL; TISSUE MICROARRAY; DISEASE FREE SURVIVAL; FLUORESCENT ANTIBODY TECHNIQUE; GENE EXPRESSION REGULATION; GENETIC DATABASE; GENETICS; IMMUNOLOGY; KIDNEY TUMOR; METABOLISM; METHODOLOGY; MIDDLE AGED; NONPARAMETRIC TEST; PATHOLOGY; PHENOTYPE; REPRODUCIBILITY;

ADULT; AGED; AGED, 80 AND OVER; ANTIBODIES, NEOPLASM; AUTOMATION; CARCINOMA, RENAL CELL; CLUSTER ANALYSIS; DATABASES, GENETIC; DISEASE-FREE SURVIVAL; EPITHELIAL-MESENCHYMAL TRANSITION; FEMALE; FLUORESCENT ANTIBODY TECHNIQUE; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; KIDNEY NEOPLASMS; MALE; MIDDLE AGED; MULTIVARIATE ANALYSIS; NEOPLASM PROTEINS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PHENOTYPE; PROPORTIONAL HAZARDS MODELS; REPRODUCIBILITY OF RESULTS; STATISTICS, NONPARAMETRIC;

EID: 84857428218     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0031557     Document Type: Article

References (35)

1. Jemal A, Siegel R, Xu J, Ward E, (2010) Cancer statistics, 2010. CA Cancer J Clin 60: 277-300.
2. CancerResearchUK (2010) Kidney cancer statistics- UK. Accessed: 2010 September.
3. Jayson M, Sanders H, (1998) Increased incidence of serendipitously discovered renal cell carcinoma. Urology 51: 203-205.
4. Chin AI, Lam JS, Figlin RA, Belldegrun AS, (2006) Surveillance strategies for renal cell carcinoma patients following nephrectomy. Rev Urol 8: 1-7.
5. Linehan WM, Bratslavsky G, Pinto PA, Schmidt LS, Neckers L, et al. (2010) Molecular diagnosis and therapy of kidney cancer. Annu Rev Med 61: 329-343.
6. Linehan WM, Srinivasan R, Schmidt LS, (2010) The genetic basis of kidney cancer: a metabolic disease. Nat Rev Urol 7: 277-285.
7. Renshaw AA, Richie JP, (1999) Subtypes of renal cell carcinoma. Different onset and sites of metastatic disease. Am J Clin Pathol 111: 539-543.
8. Stewart GD, O'Mahony FC, Powles T, Riddick AC, Harrison DJ, et al. (2011) What can molecular pathology contribute to the management of renal cell carcinoma? Nat Rev Urol 8: 255-265.
9. Rosner I, Bratslavsky G, Pinto PA, Linehan WM, (2009) The clinical implications of the genetics of renal cell carcinoma. Urol Oncol 27: 131-136.
10. Banumathy G, Cairns P, (2010) Signaling pathways in renal cell carcinoma. Cancer Biol Ther 10.
11. Brannon AR, Reddy A, Seiler M, Arreola A, Moore DT, et al. (2010) Molecular Stratification of Clear Cell Renal Cell Carcinoma by Consensus Clustering Reveals Distinct Subtypes and Survival Patterns. Genes Cancer 1: 152-163.
12. Takahashi M, Rhodes DR, Furge KA, Kanayama H, Kagawa S, et al. (2001) Gene expression profiling of clear cell renal cell carcinoma: gene identification and prognostic classification. Proc Natl Acad Sci U S A 98: 9754-9759.
13. Yao M, Tabuchi H, Nagashima Y, Baba M, Nakaigawa N, et al. (2005) Gene expression analysis of renal carcinoma: adipose differentiation-related protein as a potential diagnostic and prognostic biomarker for clear-cell renal carcinoma. J Pathol 205: 377-387.
14. Zhao H, Zongming M, Tibshirani R, Higgins JP, Ljungberg B, et al. (2009) Alteration of gene expression signatures of cortical differentiation and wound response in lethal clear cell renal cell carcinomas. PLoS One 4: e6039.
15. Tun HW, Marlow LA, von Roemeling CA, Cooper SJ, Kreinest P, et al. (2010) Pathway signature and cellular differentiation in clear cell renal cell carcinoma. PLoS One 5: e10696.
16. Thiery JP, (2003) Epithelial-mesenchymal transitions in development and pathologies. Curr Opin Cell Biol 15: 740-746.
17. Truong LD, Shen SS, (2011) Immunohistochemical diagnosis of renal neoplasms. Arch Pathol Lab Med 135: 92-109.
18. Faratian D, Bown JL, Smith VA, Langdon SP, Harrison DJ, (2010) Cancer systems biology. Methods Mol Biol 662: 245-263.
19. Faratian D, Um I, Wilson DS, Mullen P, Langdon SP, et al. (2011) Phosphoprotein pathway profiling of ovarian carcinoma for the identification of potential new targets for therapy. Eur J Cancer 47: 1420-1431.
20. Faratian D, Goltsov A, Lebedeva G, Sorokin A, Moodie S, et al. (2009) Systems biology reveals new strategies for personalizing cancer medicine and confirms the role of PTEN in resistance to trastuzumab. Cancer Res 69: 6713-6720.
21. Mertz KD, Demichelis F, Kim R, Schraml P, Storz M, et al. (2007) Automated immunofluorescence analysis defines microvessel area as a prognostic parameter in clear cell renal cell cancer. Hum Pathol 38: 1454-1462.
22. Kluger HM, Siddiqui SF, Angeletti C, Sznol M, Kelly WK, et al. (2008) Classification of renal cell carcinoma based on expression of VEGF and VEGF receptors in both tumor cells and endothelial cells. Lab Invest 88: 962-972.
23. Kononen J, Bubendorf L, Kallioniemi A, Barlund M, Schraml P, et al. (1998) Tissue microarrays for high-throughput molecular profiling of tumor specimens. Nat Med 4: 844-847.
24. Camp RL, Chung GG, Rimm DL, (2002) Automated subcellular localization and quantification of protein expression in tissue microarrays. Nat Med 8: 1323-1327.
25. Altman DG, Lausen B, Sauerbrei W, Schumacher M, (1994) Dangers of using "optimal" cutpoints in the evaluation of prognostic factors. J Natl Cancer Inst 86: 829-835.
26. Camp RL, Dolled-Filhart M, Rimm DL, (2004) X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization. Clin Cancer Res 10: 7252-7259.
27. Etzioni R, Kooperberg C, Pepe M, Smith R, Gann PH, (2003) Combining biomarkers to detect disease with application to prostate cancer. Biostatistics 4: 523-538.
28. Kattan MW, (2003) Judging new markers by their ability to improve predictive accuracy. J Natl Cancer Inst 95: 634-635.
29. Kim MK, Kim S, (2002) Immunohistochemical profile of common epithelial neoplasms arising in the kidney. Appl Immunohistochem Mol Morphol 10: 332-338.
30. Murphy D, (2002) Gene expression studies using microarrays: principles, problems, and prospects. Adv Physiol Educ 26: 256-270.
31. Polyak K, Weinberg RA, (2009) Transitions between epithelial and mesenchymal states: acquisition of malignant and stem cell traits. Nat Rev Cancer 9: 265-273.
32. Thiery JP, Sleeman JP, (2006) Complex networks orchestrate epithelial-mesenchymal transitions. Nat Rev Mol Cell Biol 7: 131-142.
33. Mikami S, Katsube KI, Oya M, Ishida M, Kosaka T, et al. (2011) Expression of Snail and Slug in renal cell carcinoma: E-cadherin repressor Snail is associated with cancer invasion and prognosis. Lab Invest.
34. Dubois-Marshall S, Thomas JS, Faratian D, Harrison DJ, Katz E, (2011) Two possible mechanisms of epithelial to mesenchymal transition in invasive ductal breast cancer. Clin Exp Metastasis (In Press).
35. Pepe MS, Feng Z, Janes H, Bossuyt PM, Potter JD, (2008) Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design. J Natl Cancer Inst 100: 1432-1438.