Cancer classification using the Immunoscore: a worldwide task force

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).

β-glucan triggers spondylarthritis and Crohn's disease-like ileitis in SKG mice

The spondylarthritides (SpA), including ankylosing spondylitis (AS), psoriatic arthritis (PsA), reactive arthritis, and arthritis associated with inflammatory bowel disease, cause chronic inflammation of the large peripheral and axial joints, eyes, skin, ileum, and colon. Genetic studies reveal common candidate genes for AS, PsA, and Crohn's disease, including IL23R, IL12B, STAT3, and CARD9, all of which are associated with interleukin-23 (IL-23) signaling downstream of the dectin 1 β-glucan receptor. In autoimmune-prone SKG mice with mutated ZAP-70, which attenuates T cell receptor signaling and increases the autoreactivity of T cells in the peripheral repertoire, IL-17-dependent inflammatory arthritis developed after dectin 1-mediated fungal infection. This study was undertaken to determine whether SKG mice injected with 1,3-β-glucan (curdlan) develop evidence of SpA, and the relationship of innate and adaptive autoimmunity to this process.

Haematopoietic stem cell transplantation: activity in Switzerland compared with surrounding European countries

Haematopoietic stem cell transplantation (HSCT) is a highly specialised procedure used to treat malignancies of the lymphohaematopoietic system as well as some acquired and inherited disorders of the blood. This analysis by the Swiss Blood Stem Cell Transplantation Group, based on data from 2008-2011, describes, treatment rates in Switzerland for specific indications and compares this with data from Germany, France, Italy and the Netherlands, corrected for the size of the population. Differences in transplant rates, in rates for particular indications, and in the use of specific transplant technologies such as use of unrelated donors, use of cord blood or mismatched family donors are described. These data are put in correlation with donor availability from international registries and with number of transplant teams and number of procedures per team all corrected for population size.