The immune score as a new possible approach for the classification of cancer

The outcome prediction in cancer is usually achieved by evaluating tissue samples obtained during surgical removal of the primary tumor focusing on their histopathological characteristics. 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, this classification provides limited prognostic information in estimating the outcome in cancer and does not predict response to therapy. It is recognized that cancer outcomes can vary significantly among patients within the same stage. Recently, many reports suggest that cancer development is controlled by the host's immune system underlying the importance of including immunological biomarkers for the prediction of prognosis and response to therapy. Data collected from large cohorts of human cancers demonstrated that the immune-classification has a prognostic value that may be superior to the AJCC/UICC TNM-classification. Thus, it is imperative to begin incorporating immune scoring as a prognostic factor and to introduce this parameter as a marker to classify cancers, as part of the routine diagnostic and prognostic assessment of tumors. At the same time, the inherent complexity of quantitative immunohistochemistry, in conjunction with variable assay protocols across laboratories, the different immune cell types analyzed, different region selection criteria, and variable ways to quantify immune infiltration underscore the urgent need to reach assay harmonization. In an effort to promote the immunoscore in routine clinical settings worldwide, the Society for Immunotherapy of Cancer (SITC), the European Academy of Tumor Immunology, the Cancer and Inflammation Program, the National Cancer Institute, National Institutes of Health, USA and "La Fondazione Melanoma" will jointly initiate a task force on Immunoscoring as a New Possible Approach for the Classification of Cancer that will take place in Naples, Italy, February 13th, 2012. The expected outcome will include a concept manuscript that will be distributed to all interested participants for their contribution before publication outlining the goal and strategy to achieve this effort; a preliminary summary to be presented during the "Workshop on Tumor Microenvironment" prior to the SITC annual meeting on October 24th - 25th 2012 in Bethesda, Maryland, USA and finally a "Workshop on Immune Scoring" to be held in Naples in December of 2012 leading to the preparation of a summary document providing recommendations for the harmonization and implementation of the Immune Score as a new component for the classification of cancer

The prognostic impact of anti-cancer immune response: a novel classification of cancer patients

Until now, the anatomic extent of tumor (TNM classification) has been, by far, the most important factor to predict the prognosis of colorectal cancer patients. However, in recent years, data collected from large cohorts of human cancers demonstrated that the immune contexture of the primary tumors is an essential prognostic factor for patients' disease-free and overall survival. Global analysis of tumor microenvironment showed that the nature, the functional orientation, the density, and the location of adaptive immune cells within distinct tumor regions influence the risk of relapse events. An immune classification of the patients was proposed based on the density and the immune cell location within the tumor. The immune classification has a prognostic value that is superior to the TNM classification, and tumor invasion is statistically dependent on the host immune reaction. Tumor and immunological markers predicted by systems biology methods are involved in the shaping of an efficient immune reaction and can serve as targets for novel therapeutic approaches. Thus, the strength of the immune reaction could advance our understanding of cancer evolution and have important consequences in clinical practice

Innovation, low energy buildings and intermediaries in Europe: systematic case study review

As buildings throughout their lifecycle account for circa 40% of total energy use in Europe, reducing energy use of the building stock is a key task. This task is, however, complicated by a range of factors, including slow renewal and renovation rates of buildings, multiple non- coordinated actors, conservative building practices, and limited competence to innovate. Drawing from academic literature published during 2005-2015, this article carries out a systematic review of case studies on low energy innovations in the European residential building sector, analysing their drivers. Specific attention is paid to intermediary actors in facilitating innovation processes and creating new opportunities. The study finds that qualitative case study literature on low energy building innovation has been limited, particularly regarding the existing building stock. Environmental concerns, EU, national and local policies have been the key drivers; financial, knowledge and social sustainability and equity drivers have been of modest importance; while design, health and comfort, and market drivers have played a minor role. Intermediary organisations and individuals have been important through five processes: (1) facilitating individual building projects, (2) creating niche markets, (3) implementing new practices in social housing stock, (4) supporting new business model creation, and (5) facilitating building use post construction. The intermediaries have included both public and private actors, while local authority agents have acted as intermediaries in several cases

Tumour invasiveness, the local and systemic environment and the basis of staging systems in colorectal cancer

background: The present study aimed to examine the relationship between tumour invasiveness (T stage), the local and systemic environment and cancer-specific survival (CSS) of patients with primary operable colorectal cancer. methods: The tumour microenvironment was examined using measures of the inflammatory infiltrate (Klintrup-Makinen (KM) grade and Immunoscore), tumour stroma percentage (TSP) and tumour budding. The systemic inflammatory environment was examined using modified Glasgow Prognostic Score (mGPS) and neutrophil:lymphocyte ratio (NLR). A 5-year CSS was examined. results: A total of 331 patients were included. Increasing T stage was associated with colonic primary, N stage, poor differentiation, margin involvement and venous invasion (P<0.05). T stage was significantly associated with KM grade (P=0.001), Immunoscore (P=0.016), TSP (P=0.006), tumour budding (P<0.001), and elevated mGPS and NLR (both P<0.05). In patients with T3 cancer, N stage stratified survival from 88 to 64%, whereas Immunoscore and budding stratified survival from 100 to 70% and from 91 to 56%, respectively. The Glasgow Microenvironment Score, a score based on KM grade and TSP, stratified survival from 93 to 58%. conclusions: Although associated with increasing T stage, local and systemic tumour environment characteristics, and in particular Immunoscore, budding, TSP and mGPS, are stage-independent determinants of survival and may be utilised in the staging of patients with primary operable colorectal cancer

Th Inducing POZ-Kruppel Factor (ThPOK) Is a Key Regulator of the Immune Response since the Early Steps of Colorectal Carcinogenesis

We purposed to evaluate the role of Th inducing POZ-Kruppel Factor (ThPOK), a transcriptional regulator of T cell fate, in tumour-induced immune system plasticity in colorectal carcinogenesis. The amounts of CD4+, CD8+ and CD56+ and ThPOK+ cells infiltrate in normal colorectal mucosa (NM), in dysplastic aberrant crypt foci (microadenomas, MA), the earliest detectable lesions in colorectal carcinogenesis, and in colorectal carcinomas (CRC), were measured, and the colocalization of ThPOK with the above-mentioned markers of immune cells was evaluated using confocal microscopy. Interestingly, ThPOK showed a prominent increase since MA. A strong colocalization of ThPOK with CD4 both in NM and in MA was observed, weaker in carcinomas. Surprisingly, there was a peak in the colocalization levels of ThPOK with CD8 in MA, which was evident, although to a lesser extent, in carcinomas, too. In conclusion, according to the data of the present study, ThPOK may be considered a central regulator of the earliest events in the immune system during colorectal cancer development, decreasing the immune response against cancer cells

Genome Expression Pathway Analysis Tool – Analysis and visualization of microarray gene expression data under genomic, proteomic and metabolic context

<p>Abstract</p> <p>Background</p> <p>Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation.</p> <p>Results</p> <p>We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at <url>http://gepat.sourceforge.net</url>.</p> <p>Conclusion</p> <p>GEPAT is a modular, scalable and professional-grade software integrating analysis and interpretation of microarray gene expression data. An installation available for academic users can be found at <url>http://gepat.bioapps.biozentrum.uni-wuerzburg.de</url>.</p

Immunological network signatures of cancer progression and survival

<p>Abstract</p> <p>Background</p> <p>The immune contribution to cancer progression is complex and difficult to characterize. For example in tumors, immune gene expression is detected from the combination of normal, tumor and immune cells in the tumor microenvironment. Profiling the immune component of tumors may facilitate the characterization of the poorly understood roles immunity plays in cancer progression. However, the current approaches to analyze the immune component of a tumor rely on incomplete identification of immune factors.</p> <p>Methods</p> <p>To facilitate a more comprehensive approach, we created a ranked immunological relevance score for all human genes, developed using a novel strategy that combines text mining and information theory. We used this score to assign an immunological grade to gene expression profiles, and thereby quantify the immunological component of tumors. This immunological relevance score was benchmarked against existing manually curated immune resources as well as high-throughput studies. To further characterize immunological relevance for genes, the relevance score was charted against both the human interactome and cancer information, forming an expanded interactome landscape of tumor immunity. We applied this approach to expression profiles in melanomas, thus identifying and grading their immunological components, followed by identification of their associated protein interactions.</p> <p>Results</p> <p>The power of this strategy was demonstrated by the observation of early activation of the adaptive immune response and the diversity of the immune component during melanoma progression. Furthermore, the genome-wide immunological relevance score classified melanoma patient groups, whose immunological grade correlated with clinical features, such as immune phenotypes and survival.</p> <p>Conclusions</p> <p>The assignment of a ranked immunological relevance score to all human genes extends the content of existing immune gene resources and enriches our understanding of immune involvement in complex biological networks. The application of this approach to tumor immunity represents an automated systems strategy that quantifies the immunological component in complex disease. In so doing, it stratifies patients according to their immune profiles, which may lead to effective computational prognostic and clinical guides.</p

Tumor immunosurveillance in human cancers

Until now, the anatomic extent of tumor (TNM classification) has been by far the most important factor to predict the prognosis of colorectal cancer patients. However, in recent years, data collected from large cohorts of human cancers demonstrated that the immune contexture of the primary tumors is an essential prognostic factor for patients’ disease-free and overall survival. Tumoral and immunological markers predicted by systems biology methods are involved in the shaping of an efficient immune reaction and can serve as targets for novel therapeutic approaches. Global analysis of tumor microenvironment showed that the nature, the functional orientation, the density, and the location of adaptive immune cells within distinct tumor regions influence the risk of relapse events. The density and the immune cell location within the tumor have a prognostic value that is superior to the TNM classification, and tumor invasion is statistically dependent on the host-immune reaction. Thus, the strength of the immune reaction could advance our understanding of cancer evolution and have important consequences in clinical practice