A Boolean model explains phenotypic plasticity changes underlying hepatic cancer stem cells emergence.

In several carcinomas, including hepatocellular carcinoma, it has been demonstrated that cancer stem cells (CSCs) have enhanced invasiveness and therapy resistance compared to differentiated cancer cells. Mathematical-computational tools could be valuable for integrating experimental results and understanding the phenotypic plasticity mechanisms for CSCs emergence. Based on the literature review, we constructed a Boolean model that recovers eight stable states (attractors) corresponding to the gene expression profile of hepatocytes and mesenchymal cells in senescent, quiescent, proliferative, and stem-like states. The epigenetic landscape associated with the regulatory network was analyzed. We observed that the loss of p53, p16, RB, or the constitutive activation of ß-catenin and YAP1 increases the robustness of the proliferative stem-like phenotypes. Additionally, we found that p53 inactivation facilitates the transition of proliferative hepatocytes into stem-like mesenchymal phenotype. Thus, phenotypic plasticity may be altered, and stem-like phenotypes related to CSCs may be easier to attain following the mutation acquisition.

Engineering principles for rationally design therapeutic strategies against hepatocellular carcinoma.

The search for new therapeutic strategies against cancer has favored the emergence of rationally designed treatments. These treatments have focused on attacking cell plasticity mechanisms to block the transformation of epithelial cells into cancerous cells. The aim of these approaches was to control particularly lethal cancers such as hepatocellular carcinoma. However, they have not been able to control the progression of cancer for unknown reasons. Facing this scenario, emerging areas such as systems biology propose using engineering principles to design and optimize cancer treatments. Beyond the possibilities that this approach might offer, it is necessary to know whether its implementation at a clinical level is viable or not. Therefore, in this paper, we will review the engineering principles that could be applied to rationally design strategies against hepatocellular carcinoma, and discuss whether the necessary elements exist to implement them. In particular, we will emphasize whether these engineering principles could be applied to fight hepatocellular carcinoma.

Hybrid lineages of CD4+ T cells: a handbook update.

CD4+ T lymphocytes have been classified into several lineages, according to their gene expression profiles and their effector responses. Interestingly, recent evidence is showing that many lineages could yield hybrid phenotypes with unique properties and functions. It has been reported that such hybrid lineages might underlie pathologies or may function as effector cells with protection capacities against molecular threats. In this work, we reviewed the characteristics of the hybrid lineages reported in the literature, in order to identify the expression profiles that characterize them and the markers that could be used to identify them. We also review the differentiation cues that elicit their hybrid origin and what is known about their physiological roles.

Molecular tracking of insulin resistance and inflammation development on visceral adipose tissue.

Background: Visceral adipose tissue (VAT) is one of the most important sources of proinflammatory molecules in obese people and it conditions the appearance of insulin resistance and diabetes. Thus, understanding the synergies between adipocytes and VAT-resident immune cells is essential for the treatment of insulin resistance and diabetes. Methods: We collected information available on databases and specialized literature to construct regulatory networks of VAT resident cells, such as adipocytes, CD4+ T lymphocytes and macrophages. These networks were used to build stochastic models based on Markov chains to visualize phenotypic changes on VAT resident cells under several physiological contexts, including obesity and diabetes mellitus. Results: Stochastic models showed that in lean people, insulin produces inflammation in adipocytes as a homeostatic mechanism to downregulate glucose intake. However, when the VAT tolerance to inflammation is exceeded, adipocytes lose insulin sensitivity according to severity of the inflammatory condition. Molecularly, insulin resistance is initiated by inflammatory pathways and sustained by intracellular ceramide signaling. Furthermore, our data show that insulin resistance potentiates the effector response of immune cells, which suggests its role in the mechanism of nutrient redirection. Finally, our models show that insulin resistance cannot be inhibited by anti-inflammatory therapies alone. Conclusion: Insulin resistance controls adipocyte glucose intake under homeostatic conditions. However, metabolic alterations such as obesity, enhances insulin resistance in adipocytes, redirecting nutrients to immune cells, permanently sustaining local inflammation in the VAT.

Metabolic alterations impair differentiation and effector functions of CD8+ T cells.

CD8+ T lymphocytes are one of the main effector cells of the immune system, they protect the organism against intracellular threats such as viruses and bacteria, as well as neoplasms. It is currently well established that CD8+ T cells have distinct immune responses, given by their phenotypes Tc1, Tc2, Tc17, and TcReg. The cellular plasticity of such phenotypes depends on the presence of different combinations of cytokines in the extracellular medium. It is known that metabolic imbalances play an important role in immune response, but the precise role of metabolic disturbances on the differentiation and function of CD8+ T cells, however, has not been explored. In this work, we used a computational model to explore the potential effect of metabolic alterations such as hyperglycemia, high alcohol consumption, dyslipidemia, and diabetes on CD8+ T cell differentiation. Our model predicts that metabolic alterations preclude the effector function of all CD8+ T cell phenotypes except for TcReg cells. It also suggests that such inhibition originates from the increase of reactive oxygen species in response to metabolic stressors. Finally, we simulated the outcome of treating metabolic-inhibited CD8+ T cells with drugs targeting key molecules such as mTORC1, mTORC2, Akt, and others. We found that overstimulation of mTORC2 may restore cell differentiation and functions of all effector phenotypes, even in diabetic patients. These findings highlight the importance of our predictive model to find potential targets to strengthen immunosuppressed patients in chronic diseases, like diabetes.

Structural Analysis of SARS-CoV-2 ORF8 Protein: Pathogenic and Therapeutic Implications.

Current therapeutic strategies and vaccines against SARS-CoV-2 are mainly focused on the Spike protein despite there are other viral proteins with important roles in COVID-19 pathogenicity. For example, ORF8 restructures vesicular trafficking in the host cell, impacts intracellular immunity through the IFN-I signaling, and growth pathways through the mitogen-activated protein kinases (MAPKs). In this mini-review, we analyze the main structural similarities of ORF8 with immunological molecules such as IL-1, contributing to the immunological deregulation observed in COVID-19. We also propose that the blockage of some effector functions of ORF8 with Rapamycin, such as the mTORC1 activation through MAPKs 40 pathway, with Rapamycin, can be a promising approach to reduce COVID-19 mortality.

Dynamics of the Gene Regulatory Network of HIV-1 and the Role of Viral Non-coding RNAs on Latency Reversion.

The use of latency reversing agents (LRAs) is currently a promising approach to eliminate latent reservoirs of HIV-1. However, this strategy has not been successful in vivo. It has been proposed that cellular post-transcriptional mechanisms are implicated in the underperformance of LRAs, but it is not clear whether proviral regulatory elements like viral non-coding RNAs (vncRNAs) are also implicated. In order to visualize the complexity of the HIV-1 gene expression, we used experimental data to construct a gene regulatory network (GRN) of latent proviruses in resting CD4+ T cells. We then analyzed the dynamics of this GRN using Boolean and continuous mathematical models. Our simulations predict that vncRNAs are able to counteract the activity of LRAs, which may explain the failure of these compounds to reactivate latent reservoirs of HIV-1. Moreover, our results also predict that using inhibitors of histone methyltransferases, such as chaetocin, together with releasers of the positive transcription elongation factor (P-TEFb), like JQ1, may increase proviral reactivation despite self-repressive effects of vncRNAs.