Profiling cancer

Current Opinion in Cell Biology

Volumn 15, Issue 2, 2003, Pages 213-220

  Ciro, Marco ^a   Bracken, Adrian P ^a   Helin, Kristian ^a  

^a EUROPEAN INSTITUTE OF ONCOLOGY   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; CANCER; CANCER CLASSIFICATION; CANCER THERAPY; GENE EXPRESSION; HUMAN; MOLECULAR BIOLOGY; PRIORITY JOURNAL; REGULATORY MECHANISM; REVIEW; SURVIVAL TIME;

EID: 0037376902     PISSN: 09550674     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0955-0674(03)00007-3     Document Type: Review

References (37)

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13. Pomeroy S.L., Tamayo P., Gaasenbeek M., Sturla L.M., Angelo M., McLaughlin M.E., Kim J.Y., Goumnerova L.C., Black P.M., Lau C.et al. Prediction of central nervous system embryonal tumour outcome based on gene expression. Nature. 415:2002;436-442 This is an outstanding study, in which the authors first showed the feasibility of distinguishing medulloblastomas from other embryonal CNS (central nervous system) tumours on the basis of gene-expression profiling. They also demonstrated that expression analysis could be used to identify the desmoplastic medulloblastoma subclass among other medulloblastomas. Finally, they performed gene-expression profiling on 60 medulloblastomas with the aim of identifying a prognosis classifier. By a supervised learning approach they identified a prognosis classifier containing eight genes that with high significance could predict patient survival (only 13 out of 60 classification errors). Using the same set of medulloblastomas, the authors showed that the prognosis classifier substantially improved the currently available prognostic parameters for survival. An independent dataset confirming these studies could result in a very useful clinical tool to predict patient survival.
14. van't Veer L.J., Dai H., van de Vijver M.J., He Y.D., Hart A.A., Mao M., Peterse H.L., van der Kooy K., Marton M.J., Witteveen A.T.et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 415:2002;530-536 This outstanding paper offers a wonderful example of the enormous potential of gene-expression profiling for the prediction of clinical outcome of cancer patients. van't Veer and colleagues performed gene-expression profiling of 78 lymph-node-negative primary breast cancers and identified a group of 70 genes, which they called a 'poor prognosis' signature. They showed that this signature outperforms all currently used clinical parameters in predicting disease outcome and they suggested that if independent studies confirm their data, the poor prognosis signature will dramatically help in the determination of patients who would benefit from adjuvant therapy.
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26. •], the authors confirmed that the levels of one of the genes identified in their previous screen, EZH2, are highly expressed at both the mRNA and protein levels in metastatic prostate cancer as compared with the benign state. They correlated the high levels of EZH2 in clinically localised prostate cancers with poor prognosis. In agreement with a causal role of EZH2 in the formation of metastatic tumours, abrogation of EZH2 expression by small interfering RNA resulted in less proliferation of the prostate cancer cell line. However, control normal cells or non-metastatic prostate cancer cells were not tested in the experiments, and it is therefore not known if EZH2 is specifically required for metastatic prostate cells to grow or if it is required for normal cell growth.
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29. Lessnick S.L., Dacwag C.S., Golub T.R. The Ewing's sarcoma oncoprotein EWS/FLI induces a p53-dependent growth arrest in primary human fibroblasts. Cancer Cell. 1:2002;393-401 This paper is a good example of how microarray technology can be applied to model cellular systems with the aim of identifying cooperating mutations in human cancer. Ewing's sarcomas contain a small group of chromosomal translocations, of which the most common gives rise to the EWS/FLI fusion protein. Gene-expression profiling was performed using human diploid fibroblasts expressing EWS/FLI, and the authors found that the profiles resembled closely the profile of the cancer itself. The expression of EWS/FLI induced a growth arrest, suggesting that other genetic changes were required for tumourigenesis. Significantly, their gene-expression profiles revealed that p53 is transcriptionally upregulated upon EWS/FLI expression. Inhibition of p53 resulted in the abrogation of the growth arrest, supporting a role for p53 as a tumour suppressor in Ewing's sarcoma. This approach may be applied to several cancer models with the hope of identifying several other key cooperative mutations.
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35. Pollack J.R., Sørlie T., Perou C.M., Rees C.A., Jeffrey S.S., Lonning P.E., Tibshirani R., Botstein D., Borresen-Dale A.L., Brown P.O. Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proc. Natl. Acad. Sci. USA. 99:2002;12963-12968 In this paper the authors show a global analysis of genomic alterations across 6691 genes in 44 breast tumour and 10 breast cancer cell lines using CGH analysis. This approach allowed for the precise mapping of recurrent regions of DNA amplification and loss. In addition, by combining these data with gene-expression levels from a previous report [9], they showed that 62% of the amplified genes were also highly expressed. Furthermore, they report that 12% of all the variations in mRNA levels among breast tumours could be attributed to variation in gene copy number. Therefore, these data point to a stronger than previously expected influence of DNA copy number on the overall deregulated levels of gene expression in tumours.
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37. ••]), and the gene-expression ratios for the 70 poor prognosis genes were examined in more detail. This study shows that the previously identified 70 poor prognosis genes are more reliable as a prognosis predictor than previously used criteria, and suggest that the determination of the expression of these 70 genes might be a useful tool to decide on which patients would benefit from adjuvant therapy.