Hypertonicity counteracts MCL 1 and renders BCL XL a synthetic lethal target in head and neck cancer

Head and neck squamous cell carcinoma (HNSCC) is an aggressive and difficult‐to‐treat cancer entity. Current therapies ultimately aim to activate the mitochondria‐controlled (intrinsic) apoptosis pathway, but complex alterations in intracellular signaling cascades and the extracellular microenvironment hamper treatment response. On the one hand, proteins of the BCL‐2 family set the threshold for cell death induction and prevent accidental cellular suicide. On the other hand, controlling a cell's readiness to die also determines whether malignant cells are sensitive or resistant to anticancer treatments. Here, we show that HNSCC cells upregulate the proapoptotic BH3‐only protein NOXA in response to hyperosmotic stress. Induction of NOXA is sufficient to counteract the antiapoptotic properties of MCL‐1 and switches HNSCC cells from dual BCL‐XL/MCL‐1 protection to exclusive BCL‐XL addiction. Hypertonicity‐induced functional loss of MCL‐1 renders BCL‐XL a synthetically lethal target in HNSCC, and inhibition of BCL‐XL efficiently kills HNSCC cells that poorly respond to conventional therapies. We identify hypertonicity‐induced upregulation of NOXA as link between osmotic pressure in the tumor environment and mitochondrial priming, which could perspectively be exploited to boost efficacy of anticancer drugs

A Proposed Multi-Level Predictive WKM_ID3 Algorithm, Toward Enhancing Supply Chain Management in Healthcare Field

This research proposes a multi-level predictive algorithm based on the k-means algorithm with multiple adaptations. The research highlights the main limitations of k-means and proposes a set of adaptations that enhance the clustering task results in accuracy with minimal centroid distance error. The study proposes three enhancements in selecting the number of clusters, identifying the initial point, and exploring the contributing features set. Moreover, prediction is performed through a multi-level paradigm targeting performance enhancement by following the partitioning approach. The research experimental study focused on applying the proposed algorithm to the healthcare supply chain as it is one of the most influential factors for health services delivery. The proposed algorithm is applied to a dataset that is offered by USAID which includes 31622 records with 104 attributes. The proposed algorithm aims to predict the valued information in the supply chain progress such as predicted delivery time, predicted delay time, and other vital attributes. The data source is the USAID dataset; however, the research utilized the dataset for multiple objectives in vital aspects prediction of the healthcare supply chain with an average accuracy of 97.45%

Small CD4 Mimetics Prevent HIV-1 Uninfected Bystander CD4+ T Cell Killing Mediated by Antibody-dependent Cell-mediated Cytotoxicity

Human immunodeficiency virus type 1 (HIV-1) infection causes a progressive depletion of CD4+ T cells. Despite its importance for HIV-1 pathogenesis, the precise mechanisms underlying CD4+ T-cell depletion remain incompletely understood. Here we make the surprising observation that antibody-dependent cell-mediated cytotoxicity (ADCC) mediates the death of uninfected bystander CD4+ T cells in cultures of HIV-1-infected cells. While HIV-1-infected cells are protected from ADCC by the action of the viral Vpu and Nef proteins, uninfected bystander CD4+T cells bind gp120 shed from productively infected cells and are efficiently recognized by ADCC-mediating antibodies. Thus, gp120 shedding represents a viral mechanism to divert ADCC responses towards uninfected bystander CD4+ T cells. Importantly, CD4-mimetic molecules redirect ADCC responses from uninfected bystander cells to HIV-1-infected cells; therefore, CD4-mimetic compounds might have therapeutic utility in new strategies aimed at specifically eliminating HIV-1-infected cells

Co-receptor Binding Site Antibodies Enable CD4-Mimetics to Expose Conserved Anti-cluster A ADCC Epitopes on HIV-1 Envelope Glycoproteins

Human immunodeficiency virus type 1 (HIV-1) has evolved a sophisticated strategy to conceal conserved epitopes of its envelope glycoproteins (Env) recognized by antibody-dependent cellular cytotoxicity (ADCC)-mediating antibodies. These antibodies, which are present in the sera of most HIV-1-infected individuals, preferentially recognize Env in its CD4-bound conformation. Accordingly, recent studies showed that small CD4-mimetics (CD4mc) able to “push” Env into this conformation sensitize HIV-1-infected cells to ADCC mediated by HIV+ sera. Here we test whether CD4mc also expose epitopes recognized by anti-cluster A monoclonal antibodies such as A32, thought to be responsible for the majority of ADCC activity present in HIV+ sera and linked to decreased HIV-1 transmission in the RV144 trial. We made the surprising observation that CD4mc are unable to enhance recognition of HIV-1-infected cells by this family of antibodies in the absence of antibodies such as 17b, which binds a highly conserved CD4-induced epitope overlapping the co-receptor binding site (CoRBS). Our results indicate that CD4mc initially open the trimeric Env enough to allow the binding of CoRBS antibodies but not anti-cluster A antibodies. CoRBS antibody binding further opens the trimeric Env, allowing anti-cluster A antibody interaction and sensitization of infected cells to ADCC. Therefore, ADCC responses mediated by cluster A antibodies in HIV-positive sera involve a sequential opening of the Env trimer on the surface of HIV-1-infected cells. The understanding of the conformational changes required to expose these vulnerable Env epitopes might be important in the design of new strategies aimed at fighting HIV-1