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Cytokine therapy emerged as a leading approach to interfere with disease progression and recurrence in select types of cancers. The advance of cytokine therapies such as those based on IL-2 and IFN-alpha was enabled by the molecular biology revolution and in turn, resulted in deeper understanding of the complex relationship between immunity and tumor progression. The tantalizing heterogeneity of the clinical response to cytokines, ranging from complete remissions to refractoriness shows the importance of understanding the molecular biomarker criteria associated with responsiveness and warrants reconsideration of cytokine therapies by using a focused, stratified medicine approach. In addition, a profound systemic impact of cytokines on immune as well as non-immune cells, transcending the beneficial effect on immunity against tumor-associated antigens (TAA), limits the therapeutic index and wider applicability of this approach. There are generally two categories of cytokines applied to cancer: first, those aimed to modify the tumor progression directly or indirectly via immune stimulation; secondly, biomolecules used as supportive therapy usually in conjunction with other therapies that may affect the bone marrow function. Herein, we outline several key features of the first category, focusing on those cytokines approved for clinical use. [ABSTRACT FROM AUTHOR]

Clinical characterization of breast cancer patients related to their risk and profiles is an important part for making their correct prognostic assessments. This paper first proposes a prognostic index obtained when it is applied a flexible non-linear time-to-event model and compares it to a widely used linear survival estimator. This index underpins different stratification methodologies including informed clustering utilising the principle of learning metrics, regression trees and recursive application of the log-rank test. Missing data issue was overcome using multiple imputation, which was applied to a neural network model of survival fitted to a data set for breast cancer (n=743). It was found the three methodologies broadly agree, having however important differences. [ABSTRACT FROM AUTHOR]