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Multi-target analysis of neoplasms for the evaluation of tumor progression: stochastic approach of biologic processes

1 Salmaniya Medical Complex, Department of Pathology, Manama, Bahrain
2 King’s college hospital, Department of Histopathology, London, SE5 9RS, United Kingdom

Considering tumor progression from a biologic perspective, it represents the acquisition of new capabilities relevant for a neoplasm to extend: invasion of the underlying stroma for intraepithelial lesions and the metastatic potential of already invasive tumors. A proper evaluation would then require the analysis of at least two samples taken at different times to assess the differences in the acquired capabilities of invasion and metastatic potential. The core mechanisms involved in this process would require maintaining the proliferation capacity for expansion and invasion, along with cellular survival and cytostasis-differentiation. These four principal mechanisms must cooperate in the same direction, and result from the interaction between tumor cells and the microenvironment, from which tumor-promoting and tumor-inhibiting signals can be observed; the balance of these signals will determine the evolution and, eventually, the progression of the neoplasm. These interactions are central elements for cellular selection, tumor progression, and intratumoral heterogeneity, which are best analyzed by stochastic models. Genome-wide analyses of tumors provide an overwhelming amount of information that should be targeted to biologically relevant processes in those four areas, integrating signals from tumor cells and microenvironment. Intratumoral cellular subpopulations and their selective interactions, the segregation of genetic alterations during clonal expansions, and the redundancy/pleiotropism of molecular pathways cooperate for the tumor progression taking place in an ischemic microenvironment that modifies the metabolic profile. The simultaneous analysis of multiple targets and next-generation sequencing offer the best practical approach for the evaluation of tumor progression, understanding their heterogeneity and cell segregation. This knowledge would constitute a substantial scientific background for better staging, clonal identification in metastatic disease, and future therapeutic planning.
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