We characterize different tumour types in search for multi-tumour drug targets, in particular aiming for drug repurposing and novel drug combinations. Starting from 11 tumour types from The Cancer Genome Atlas, we obtain three clusters based on transcriptomic correlation profiles. A network-based analysis, integrating gene expression profiles and protein interactions of cancer-related genes, allows us to define three cluster-specific signatures, with genes belonging to NF-κB signaling, chromosomal instability, ubiquitin-proteasome system, DNA metabolism, and apoptosis biological processes. These signatures have been characterized by different approaches based on mutational, pharmacological and clinical evidences, demonstrating the validity of our selection. Moreover, we define new pharmacological strategies validated by in vitro experiments that show inhibition of cell growth in two tumour cell lines, with significant synergistic effect. Our study thus provides a list of genes and pathways that could possibly be used, singularly or in combination, for the design of novel treatment strategies.

MicroRNA‐34a‐5p regulates the G1/S checkpoint in non‐small cell lung cancer (NSCLC) cells. Forced expression of miR‐34a‐5p enhances p21 expression and promotes cellular senescence, whereas knockout of miR‐34a‐5p decreases senescence and increases apoptosis. This suggests that p21 is the main effector of a senescence‐apoptosis switch in NSCLC cells; however, the molecular mechanisms controlling this switch are unclear. In this work, we propose a Boolean model of G1/S checkpoint regulation, contemplating the regulatory influences of p21 by miR‐34a‐5p. The predicted probabilities of our model are in excellent agreement with experimental data. Our model supports that p21 is the main effector of a senescence/apoptosis switch and that the disruption of the positive feedback involving ATM, miR‐34a‐5p, and the histone deacetylase HDAC1 abrogates senescence.

The epithelial–mesenchymal transition (EMT) is a cellular programme on which epithelial cells undergo a phenotypic transition to mesenchymal ones acquiring metastatic properties such as mobility and invasion. TGF-β signalling can promote the EMT process. However, the dynamics of the concentration response of TGF-β-induced EMT is not well explained. In this work, we propose a logical model of TGF-β dose dependence of EMT in MCF10A breast cells. The model outcomes agree with experimentally observed phenotypes for the wild-type and perturbed/mutated cases. As important findings of the model, it predicts the coexistence of more than one hybrid state and that the circuit between TWIST1 and miR-129 is involved in their stabilization. Thus, miR-129 should be considered as a phenotypic stability factor. The circuit TWIST1/miR-129 associates with ZEB1-mediated circuits involving miRNAs 200, 1199, 340, and the protein GRHL2 to stabilize the hybrid state. Additionally, we found a possible new autocrine mechanism composed of the circuit involving TGF-β, miR-200, and SNAIL1 that contributes to the stabilization of the mesenchymal state. Therefore, our work can extend our comprehension of TGF-β-induced EMT in MCF10A cells to potentially improve the strategies for breast cancer treatment.

We simulate in two dimensions the wetting behavior of a liquid droplet placed on a solid surface structured by a regular distribution of pillars. For this purpose, as in a recent study, we used the Potts Hamiltonian formalism. We focused our investigations on the transition between the wetting regimes characteristic of the super-repellent property of our surfaces. We determined several physical variables influencing such a property and we also built the wetting phase diagrams of which two different states and a transition zone were identified. The transition happens between a Cassie–Baxter state (CB) and the Wenzel state. We also show that the wetting transition is affected by fluctuations and liquid compressibility.

Experimental evidence indicates that aging leads to accumulation of senescent cells in tissues and they develop a secretory phenotype (also known as SASP, for senescence-associated secretory phenotype) that can contribute to chronic inflammation and diseases. Recent results have showed that markers of senescence in astrocytes from aged brains are increased in brains with Alzheimer’s disease. These studies strongly involved the stress kinase p38MAPK in the regulation of the secretory phenotype of astrocytes, yet the molecular mechanisms underlying the onset of senescence and SASP activation remain unclear. In this work, we propose a discrete logical model for astrocyte senescence determined by the level of DNA damage (reparable or irreparable DNA strand breaks) where the kinase p38MAPK plays a central role in the regulation of senescence and SASP. The model produces four alternative stable states: proliferation, transient cycle arrest, apoptosis and senescence (and SASP) computed from its inputs representing DNA damages. Perturbations of the model were performed through gene gain or loss of functions and compared with results concerning cultures of normal and mutant astrocytes showing agreement in most cases. Moreover, the model allows some predictions that remain to be tested experimentally.