Surgery (RMH) - Research Publications

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    Cancer classification using the Immunoscore: a worldwide task force
    Galon, J ; Pages, F ; Marincola, FM ; Angell, HK ; Thurin, M ; Lugli, A ; Zlobec, I ; Berger, A ; Bifulco, C ; Botti, G ; Tatangelo, F ; Britten, CM ; Kreiter, S ; Chouchane, L ; Delrio, P ; Arndt, H ; Asslaber, M ; Maio, M ; Masucci, GV ; Mihm, M ; Vidal-Vanaclocha, F ; Allison, JP ; Gnjatic, S ; Hakansson, L ; Huber, C ; Singh-Jasuja, H ; Ottensmeier, C ; Zwierzina, H ; Laghi, L ; Grizzi, F ; Ohashi, PS ; Shaw, PA ; Clarke, BA ; Wouters, BG ; Kawakami, Y ; Hazama, S ; Okuno, K ; Wang, E ; O'Donnell-Tormey, J ; Lagorce, C ; Pawelec, G ; Nishimura, MI ; Hawkins, R ; Lapointe, R ; Lundqvist, A ; Khleif, SN ; Ogino, S ; Gibbs, P ; Waring, P ; Sato, N ; Torigoe, T ; Itoh, K ; Patel, PS ; Shukla, SN ; Palmqvist, R ; Nagtegaal, ID ; Wang, Y ; D'Arrigo, C ; Kopetz, S ; Sinicrope, FA ; Trinchieri, G ; Gajewski, TF ; Ascierto, PA ; Fox, BA (BMC, 2012-10-03)
    Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).
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    Refinement of the associations between risk of colorectal cancer and polymorphisms on chromosomes 1q41 and 12q13.13
    Spain, SL ; Carvajal-Carmona, LG ; Howarth, KM ; Jones, AM ; Su, Z ; Cazier, J-B ; Williams, J ; Aaltonen, LA ; Pharoah, P ; Kerr, DJ ; Cheadle, J ; Li, L ; Casey, G ; Vodicka, P ; Sieber, O ; Lipton, L ; Gibbs, P ; Martin, NG ; Montgomery, GW ; Young, J ; Baird, PN ; Morreau, H ; van Wezel, T ; Ruiz-Ponte, C ; Fernandez-Rozadilla, C ; Carracedo, A ; Castells, A ; Castellvi-Bel, S ; Dunlop, M ; Houlston, RS ; Tomlinson, IPM (OXFORD UNIV PRESS, 2012-02-15)
    In genome-wide association studies (GWASs) of colorectal cancer, we have identified two genomic regions in which pairs of tagging-single nucleotide polymorphisms (tagSNPs) are associated with disease; these comprise chromosomes 1q41 (rs6691170, rs6687758) and 12q13.13 (rs7163702, rs11169552). We investigated these regions further, aiming to determine whether they contain more than one independent association signal and/or to identify the SNPs most strongly associated with disease. Genotyping of additional sample sets at the original tagSNPs showed that, for both regions, the two tagSNPs were unlikely to identify a single haplotype on which the functional variation lay. Conversely, one of the pair of SNPs did not fully capture the association signal in each region. We therefore undertook more detailed analyses, using imputation, logistic regression, genealogical analysis using the GENECLUSTER program and haplotype analysis. In the 1q41 region, the SNP rs11118883 emerged as a strong candidate based on all these analyses, sufficient to account for the signals at both rs6691170 and rs6687758. rs11118883 lies within a region with strong evidence of transcriptional regulatory activity and has been associated with expression of PDGFRB mRNA. For 12q13.13, a complex situation was found: SNP rs7972465 showed stronger association than either rs11169552 or rs7136702, and GENECLUSTER found no good evidence for a two-SNP model. However, logistic regression and haplotype analyses supported a two-SNP model, in which a signal at the SNP rs706793 was added to that at rs11169552. Post-GWAS fine-mapping studies are challenging, but the use of multiple tools can assist in identifying candidate functional variants in at least some cases.