The American Joint Committee on Cancer/Union Internationale Contre le Cancer (AJCC/UICC) TNM staging system provides the most reliable guidelines for the routine prognostication and treatment of colorectal carcinoma. This traditional tumour staging summarizes data on tumour burden (T), the presence of cancer cells in draining and regional lymph nodes (N) and evidence for distant metastases (M). However, it is now recognized that the clinical outcome can vary significantly among patients within the same stage. The current classification provides limited prognostic information and does not predict response to therapy. Multiple ways to classify cancer and to distinguish different subtypes of colorectal cancer have been proposed, including morphology, cell origin, molecular pathways, mutation status and gene expression-based stratification. These parameters rely on tumour-cell characteristics. Extensive literature has investigated the host immune response against cancer and demonstrated the prognostic impact of the in situ immune cell infiltrate in tumours. A methodology named ‘Immunoscore’ has been defined to quantify the in situ immune infiltrate. In colorectal cancer, the Immunoscore may add to the significance of the current AJCC/UICC TNM classification, since it has been demonstrated to be a prognostic factor superior to the AJCC/UICC TNM classification. An international consortium has been initiated to validate and promote the Immunoscore in routine clinical settings. The results of this international consortium may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune). © 2013 The Authors. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

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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).

CUTL1, also known as CDP, Cut, or Cux-1, is a homeodomain transcriptional regulator known to be involved in development and cell cycle progression. Here we report that CUTL1 activity is associated with increased migration and invasiveness in numerous tumor cell lines, both in vitro and in vivo. Furthermore, we identify CUTL1 as a transcriptional target of transforming growth factor beta and a mediator of its promigratory effects. CUTL1 activates a transcriptional program regulating genes involved in cell motility, invasion, and extracellular matrix composition. CUTL1 expression is significantly increased in high-grade carcinomas and is inversely correlated with survival in breast cancer. This suggests that CUTL1 plays a central role in coordinating a gene expression program associated with cell motility and tumor progression.

Validation of immunohistochemistry (IHC) assays is a subject that is of great importance to clinical practice as well as basic research and clinical trials. When applied to clinical practice and focused on patient safety, validation of IHC assays creates objective evidence that IHC assays used for patient care are "fit-for-purpose." Validation of IHC assays needs to be properly informed by and modeled to assess the purpose of the IHC assay, which will further determine what sphere of validation is required, as well as the scope, type, and tier of technical validation. These concepts will be defined in this review, part 3 of the 4-part series "Evolution of Quality Assurance for Clinical Immunohistochemistry in the Era of Precision Medicine."

In breast cancer, overexpression of the small heat shock protein, HSP-27, is associated with increased anchorage-independent growth, increased invasiveness, and resistance to chemotherapeutic drugs and is associated with poor prognosis and reduced disease-free survival. Therefore, factors that increase the expression of HSP-27 in breast cancer are likely to affect the prognosis and outcome of treatment. In this study, we show a strong correlation between elevated levels of the Brn-3b POU transcription factor and high levels of HSP-27 protein in manipulated MCF-7 breast cancer cells as well as in human breast biopsies. Conversely, HSP-27 is decreased on loss of Brn-3b. In cotransfection assays, Brn-3b can strongly transactivate the HSP-27 promoter, supporting a role for direct regulation of HSP-27 expression. Brn-3b also cooperates with the estrogen receptor (ER) to facilitate maximal stimulation of the HSP-27 promoter, with significantly enhanced activity of this promoter observed on coexpression of Brn-3b and ER compared with either alone. RNA interference and site-directed mutagenesis support the requirement for the Brn-3b binding site on the HSP-27 promoter, which facilitates maximal transactivation either alone or on interaction with the ER. Chromatin immunoprecipitation provides evidence for association of Brn-3b with the HSP-27 promoter in the intact cell. Thus, Brn-3b can, directly and indirectly (via interaction with the ER), activate HSP-27 expression, and this may represent one mechanism by which Brn-3b mediates its effects in breast cancer cells.

Delay of growth was rarely observed in teenagers with pituitary adenomas. At the onset of the disease, many girls complained of oligoamenorrhoea and galactorrhoea, while headache and delay of pubertal development were the symptoms more frequently referred by boys. Surgery alone was effective in a minority of patients and adjuvant therapies were helpful to obtain the remission of the disease in many cases. In patients with PRL-secreting pituitary adenoma, medical treatment, both as first choice or as adjuvant therapy, normalizes serum PRL levels in 14/27 (52%) cases.

Nowadays, radiation treatment is beginning to intensively use MRI thanks to its greater ability to discriminate healthy and diseased soft-tissues. Leksell Gamma Knife® is a radio-surgical device, used to treat different brain lesions, which are often inaccessible for conventional surgery, such as benign or malignant tumors. Currently, the target to be treated with radiation therapy is contoured with slice-by-slice manual segmentation on MR datasets. This approach makes the segmentation procedure time consuming and operator-dependent. The repeatability of the tumor boundary delineation may be ensured only by using automatic or semiautomatic methods, supporting clinicians in the treatment planning phase. This article proposes a semiautomatic segmentation method, based on the unsupervised Fuzzy C-Means clustering algorithm. Our approach helps segment the target and automatically calculates the lesion volume. To evaluate the performance of the proposed approach, segmentation tests on 15 MR datasets were performed, using both area-based and distance-based metrics, obtaining the following average values: Similarity Index=95.59%, Jaccard Index=91.86%, Sensitivity=97.39%, Specificity=94.30%, Mean Absolute Distance=0.246[pixels], Maximum Distance=1.050[pixels], and Hausdorff Distance=1.365[pixels]