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• W2014710069 abstract "The human genome sequence is now available, virtually complete. Why should oncologists bother about this data bank? Until now most research in molecular carcinogenesis has been directed at discovering and characterizing single ‘cancer’ genes. Virtually all established diagnostic techniques in molecular cancer pathology suffer from the limitation that they only tell us what we are specifically looking for. It may well be that a chosen molecular marker may be less relevant than another one which was not ordered by the clinician, or was not considered by the pathologist. Colon cancer is a nice example to illustrate this issue. For example, patients with stage III colon cancer seem to derive more benefit from adjuvant therapy if their tumours retain a wild-type K-ras sequence [1.Steeg P.S. Abrams J.S. Cancer prognostics: past, present and p27.Nat Med. 1997; 3: 152-154Crossref PubMed Scopus (108) Google Scholar, 2.Ahnen D.J. Feigl P. Quan G. et al.Ki ras mutation and p53 mutation overexpression predict the clinical behaviour of colorectal cancer: a Southwest Oncology Group Study.Cancer Res. 1998; 58: 1149-1158PubMed Google Scholar]. Interestingly, colon cancer with a wild-type K-ras status will also derive particular benefit from epidermal growth factor receptor (EGFR)-targeted treatment. Colon cancers with microsatellite instability may be less aggressive than tumours with stable microsatellites. Retention of 18q alleles in microsatellite-stable tumours, and mutations of the gene for type II TGF-β1 receptor in node-positive microsatellite-instable colon cancers both point to a more favourable prognosis after adjuvant chemotherapy. A glance at this literature shows that in most papers the molecular marker of interest was carefully studied, and one or the other additional gene included in the analysis, but no such study provided an overall appraisal of all molecular markers of potential clinical value in this cancer. The established molecular diagnostic techniques are mostly too laborious to permit the comprehensive screening of a tumour biopsy sample for all possible types of genetic marker. A new approach would be to screen cancer specimens for all possible ‘gene’ problems, i.e. to obtain individual comprehensive cancer gene expression profiles, at the RNA expression level (also known as ‘signatures’). This is now possible with microarray gene profiling [3.Fey M.F. Impact of the Human Genome Project on the clinical management of sporadic cancers.Lancet Oncol. 2002; 3: 349-356Abstract Full Text Full Text PDF PubMed Scopus (11) Google Scholar, 4.Quackenbush J. Microarray analysis and tumor classification.N Engl J Med. 2006; 354: 2463-2472Crossref PubMed Scopus (384) Google Scholar]. In contrast to the study of single genes and their proteins, molecular tumour profiling is a large-scale analysis of gene expression in a tumour using DNA microarrays (Figure 1). DNA microarrays typically consist of rows and rows of oligonucleotide sequence strands, or cDNA sequences lined up in dots on a silicon chip or glass slide [3.Fey M.F. Impact of the Human Genome Project on the clinical management of sporadic cancers.Lancet Oncol. 2002; 3: 349-356Abstract Full Text Full Text PDF PubMed Scopus (11) Google Scholar, 4.Quackenbush J. Microarray analysis and tumor classification.N Engl J Med. 2006; 354: 2463-2472Crossref PubMed Scopus (384) Google Scholar, 5.Sotiriou C. Piccart M.J. Taking gene-expression profiling to the clinic: when will molecular profile signatures become relevant for patient care?.Nat Rev Cancer. 2007; 7: 545-553Crossref PubMed Scopus (400) Google Scholar, 6.Staudt L. Molecular diagnosis of the hematologic cancers.N Engl J Med. 2003; 348: 1777-1785Crossref PubMed Scopus (185) Google Scholar]. Oligonucleotide sequences or cDNAs on the chip permit specific hybridization to labelled mRNAs of interest extracted from a biopsy. Arrays can accommodate up to 30 000 specific sequences on a single chip, either chosen randomly or deliberately ‘biased’ to represent theme parks of genes typically expressed in a cell type of interest, e.g. ‘lymphoid genes’ in B cells (‘Lymphochip’) [6.Staudt L. Molecular diagnosis of the hematologic cancers.N Engl J Med. 2003; 348: 1777-1785Crossref PubMed Scopus (185) Google Scholar]. The Lymphochip is a cDNA microarray containing selected genes preferentially expressed in lymphoid cells [7.Alizadeh A.A. Eisen M.B. Davis R.E. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling.Nature. 2000; 403: 503-511Crossref PubMed Scopus (8087) Google Scholar, 8.Shipp M.A. Ross K.N. Tamayo P. et al.Diffuse large B-cell lymphoma outcome predicted by gene-expression profiling and supervised machine learning.Nat Med. 2002; 8: 68-74Crossref PubMed Scopus (2057) Google Scholar]. Analysis of gene expression in various lymphoid malignancies yields an orderly picture of gene expression patterns in particular types of lymphoma, reflecting lineage characteristics, stage of maturation of lymphoid cells and proliferation signatures. Diffuse large B-cell lymphoma (DLBCL, a clinically heterogeneous group of lymphomas despite their morphological similarity) can be split into subtypes with gene expression profiles typical either of germinal centre B cells, or of activated B cells. DLBCL expression signatures differ markedly between patients who were cured, and those who eventually relapsed [8.Shipp M.A. Ross K.N. Tamayo P. et al.Diffuse large B-cell lymphoma outcome predicted by gene-expression profiling and supervised machine learning.Nat Med. 2002; 8: 68-74Crossref PubMed Scopus (2057) Google Scholar]. The promise is that such expression profiles or ‘signatures’ offer more precise prognostic information than established prognostic factors, such as the International Prognostic Index in NHL (Figure 2), and eventually translate into concepts of refined differentially targeted therapy. Likewise, one invasive ductal breast cancer specimen may look deceptively similar to another one on histology, but the fate of the two women may be totally different. This is due to inherent biological differences of the two tumours hidden in their genome, which may be elusive to morphological examination. Variation in gene transcription programmes governed by specific somatic gene alterations accounts for much of the biological diversity in human tumours. The study of gene expression patterns in human breast cancer specimens displays distinct molecular portraits, or gene expression profiles providing molecular ‘fingerprints’ [9.van ‘t Veer L.J. Dai H. van de Vijver M.J. et al.Gene expression profiling predicts clinical outcome of breast cancer.Nature. 2002; 415: 530-536Crossref PubMed Scopus (7849) Google Scholar]. Tumours may be clustered by sharing gene expression patterns, and it is likely that such subgroups comprise clinically distinct subtypes or entities of breast cancer. It also turns out that the overall gene expression pattern of a breast cancer case is by and large retained in its metastases. Figure 2 shows an analysis where T1–2 N0 tumours that had or had not relapsed within 5 years after diagnosis and primary treatment, show clearly distinct gene expression profiles, respectively. Breast cancers of the basal-like cell type, which often express neither hormone receptors nor HER2 (‘triple-negative breast cancer’) cannot be readily identified by histology, but exhibit specific gene expression profiles detectable on microarray analysis [10.Rakha E.A. Reis-Filho J.S. Ellis I.O. Basal-like breast cancer: a critical review.J Clin Oncol. 2008; 26: 2568-2581Crossref PubMed Scopus (705) Google Scholar]. A few words of caution on the chip technology are warranted. Currently, molecular diagnostics with DNA microarrays do not displace time-honoured diagnostic tools such as morphology and related techniques, as the demands on bioinformatics to handle the impressive data flow are considerable, and costs still excessive [3.Fey M.F. Impact of the Human Genome Project on the clinical management of sporadic cancers.Lancet Oncol. 2002; 3: 349-356Abstract Full Text Full Text PDF PubMed Scopus (11) Google Scholar, 5.Sotiriou C. Piccart M.J. Taking gene-expression profiling to the clinic: when will molecular profile signatures become relevant for patient care?.Nat Rev Cancer. 2007; 7: 545-553Crossref PubMed Scopus (400) Google Scholar]. The clinical relevance of this technology and the new data it creates will undoubtedly need to be refined, and tested in appropriate clinical trials. Although global gene expression profiling of cancers with the DNA chip technology is now a reality, the detailed characterization of single genes and their proteins with a possible role in the molecular pathology of cancers is far from being old hat. New strategies to detect and characterize human proteins in biological material (including clinical specimens) are now mandatory and indeed on the horizon. As a concept, proteomics is on the road to providing a new wave of fascinating data with a great potential for cancer medicine, since, similar to cDNA microchips, proteomic analysis provides a survey of protein production in a tumour specimen, hence specific protein production signatures." @default.
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• W2014710069 title "VI. DNA microarray technology. Principles and application to the analysis of malignant tumours (with special emphasis on lymphoma)" @default.
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