Modelling approaches in tumor microenvironment.


Journal of Cancer Immunology and Therapy is an academic journal and aims to publish most complete and reliable source of information on the discoveries and current developments in the mode of original articles, review articles, case reports, short communications, etc. in all areas of the field and making them freely available through online without any restrictions or any other subscriptions to researchers worldwide. The journal selects the articles to be published with a single bind, peer review system, following the practices of good scholarly journals. It supports the open access policy of making scientific research accessible to one and all. 

We are sharing one of the most cited article from our journal. Article entitled “Modelling approaches in tumor microenvironment.” was well written by Dr. Ioannis Xenarios.


For decades, cancer research has been focused on understanding the neoplastic transformation of normal cells into cancerous ones from a cell-centric perspective. However, it is increasingly evident that the surrounding tumor microenvironment (TME) is equally important for tumor growth, progression and dissemination. The TME is a complex and heterogeneous system of interplaying elements strongly intertwined with normal processes of the surrounding hosting tissue. Cancerous cells and stromal cells, including different types of infiltrating immune cells and resident tissue cells, interact with each other and with extracellular matrix components in a very convoluted way. In addition, all of these cells may have phenotypically distinct variants exhibiting variability in cell traits, such as cell-cell adhesion, migration capability, proliferation rate and responsiveness to specific treatments; the composition of the cell population can differ between different regions of the tumor and between different tumors of the same or different patients, which result in both intratumor and across tumor heterogeneity. Altogether, the complexity and heterogeneity of the TME hinder the elucidation of cancer driving mechanisms and biomarkers and render the tumor behavior difficult to anticipate. Ultimately, that slows down the development of novel cancer therapies and makes difficult the choice of suitable treatments for specific patients. Mathematical and computational models may help on describing, explaining and predicting cancer in a new generation of experimental design assisted by computer simulations. These novel experimental and computational approaches face new challenges in the era of precision medicine and personalized cancer therapies, such as capturing the spatiotemporal structure of the TME, vertical and horizontal integration of multiple-omics data and dealing with heterogeneity at both intratumor and patient population level.

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