Small molecules that interfere with microtubule dynamics, such as Taxol and the Vinca alkaloids, are widely used in cell biology research and as clinical anticancer drugs. However, their activity cannot be restricted to specific target cells, which also causes severe side effects in chemotherapy. Here, we introduce the photostatins, inhibitors that can be switched on and off in vivo by visible light, to optically control microtubule dynamics. Photostatins modulate microtubule dynamics with a subsecond response time and control mitosis in living organisms with single-cell spatial precision. In longer-term applications in cell culture, photostatins are up to 250 times more cytotoxic when switched on with blue light than when kept in the dark. Therefore, photostatins are both valuable tools for cell biology, and are promising as a new class of precision chemotherapeutics whose toxicity may be spatiotemporally constrained using light.

Key Points Aged neutrophils exhibit a distinct, highly reactive phenotype that depends on age-related changes in their molecular repertoire. This specific phenotype of aged neutrophils enables them to serve as “first responders” in inflammatory reactions.

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In the context of precision medicine with immunotherapies there is an increasing need for companion diagnostic tests to identify potential therapy responders and avoid treatment coming along with severe adverse events for non-responders. Here, we present a retrospective case study to discover image-based signatures for developing a potential companion diagnostic test for ipilimumab (IPI) in malignant melanoma. Signature discovery is based on digital pathology and fully automatic quantitative image analysis using virtual multiplexing as well as machine learning and deep learning on whole-slide images. We systematically correlated the patient outcome data with potentially relevant local image features using a Tissue Phenomics approach with a sound cross validation procedure for reliable performance evaluation. Besides uni-variate models we also studied combinations of signatures in several multi-variate models. The most robust and best performing model was a decision tree model based on relative densities of CD8+ tumor infiltrating lymphocytes in the intra-tumoral infiltration region. Our results are well in agreement with observations described in previously published studies regarding the predictive value of the immune contexture, and thus, provide predictive potential for future development of a companion diagnostic test.

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