Eukaryotic initiation factor 6 regulates mechanical responses in endothelial cells

The repertoire of extratranslational functions of components of the protein synthesis apparatus is expanding to include control of key cell signaling networks. However, very little is known about noncanonical functions of members of the protein synthesis machinery in regulating cellular mechanics. We demonstrate that the eukaryotic initiation factor 6 (eIF6) modulates cellular mechanobiology. eIF6-depleted endothelial cells, under basal conditions, exhibit unchanged nascent protein synthesis, polysome profiles, and cytoskeleton protein expression, with minimal effects on ribosomal biogenesis. In contrast, using traction force and atomic force microscopy, we show that loss of eIF6 leads to reduced stiffness and force generation accompanied by cytoskeletal and focal adhesion defects. Mechanistically, we show that eIF6 is required for the correct spatial mechanoactivation of ERK1/2 via stabilization of an eIF6–RACK1–ERK1/2–FAK mechanocomplex, which is necessary for force-induced remodeling. These results reveal an extratranslational function for eIF6 and a novel paradigm for how mechanotransduction, the cellular cytoskeleton, and protein translation constituents are linked.

Identification of cytokeratin24 as a tumor suppressor for the management of head and neck cancer

To improve management of head and neck squamous cell carcinoma patients, we need to increase our understanding of carcinogenesis, to identify biomarkers, and drug targets. This study aimed to identify novel biomarkers by providing transcriptomics profiles of matched primary tumors, lymph node metastasis, and non-malignant tissue of 20 HNSCC patients as well as by bioinformatic analyses of a TCGA HNSCC cohort, comprising 554 patients. We provide cancer cell signaling networks differentially expressed in tumors versus metastases, such as mesenchymal–epithelial transition, and structural integrity networks. As a proof of principle study, we exploited the data sets and performed functional analyses of a novel cytokeratin, cytokeratin24 (cKRT24), which had not been described as biomarker for tumors before. Survival analysis revealed that low cKRT24 expression correlated with poor overall survival in HNSCC. Experimentally, downregulation of cKRT24 in primary tumors, metastases, and HNSCC cell lines was verified on mRNA and protein level. Cloning and ectopic overexpression of cKRT24 not only affected viability and growth of HNSSC cell lines, but also inhibited tumor growth in murine xenograft studies. We conclude that cKRT24 functions as a tumor suppressor in HNSCC, and may serve as an additional prognostic biomarker and novel target to support current HNSCC treatments.

Deep Hidden Physics Modeling of Cell Signaling Networks

: According to the WHO, cancer is the second most common cause of death worldwide. The social and economic damage caused by cancer is high and rising. In Europe, the annual direct medical expenses alone amount to more than €129 billion. This results in an urgent need for new and sustainable therapeutics, which is currently not met by the pharmaceutical industry; only 3.4% of cancer drugs entering Phase I clinical trials get to market. Phosphorylation sites are parts of the core machinery of kinase signaling networks, which are known to be dysfunctional in all types of cancer. Indeed, kinases are the second most common drug target, yet, because these inhibitors block all functions of a protein, they commonly lead to the development of resistance and increased toxicity. To facilitate global and mechanistic modeling of cancer and clinically relevant cell signaling networks, the community will have to develop sophisticated data-driven deep-learning and mechanistic computational models that generate in silico probabilistic predictions of molecular signaling network rearrangements causally implicated in cancer.

The role of PP2A variants to predict outcome in patients (pts) with metastatic colorectal cancer (mCRC): Data from FIRE-3 and TRIBE trials.

3581 Background: Protein phosphatase 2A (PP2A) is a serine/threonine phosphatase with functions that counter-balance kinase-mediated phosphorylation throughout cell signaling networks. PP2A was reported to upregulate the angiogenesis, while negatively regulate the pathways downstream of receptor tyrosine kinases at multiple nodes. Previous studies showed PP2A variants were associated with the increased risk of cancer. Therefore, we hypothesized that PP2A variants may predict first-line treatment outcome in mCRC pts treated with bevacizumab (bev)/cetuximab (cet)-based chemotherapy. Methods: Genomic DNA from blood samples of pts enrolled in two independent randomized trials, TRIBE (bev arm, n=215, as discovery cohort) and FIRE-3 (bev arm, n=107, as validation cohort; cet arm, n=129, as control cohort), was genotyped through the OncoArray, a customized array manufactured by Illumina including approximately 530K SNP markers. The impact on outcome of 17 selected SNPs in 3 main PP2A core subunits (PPP2CA, PPP2R1B, PPP2R1A), one phosphatase activator (PPP2R4) and 2 endogenous inhibitors (TIPRL, CIP2A) was analyzed. Results: In the discovery cohort, pts with PPP2R4 rs2541164 A/A (N=16) showed significantly shorter overall survival (15.3 vs 27.3 months) compared to carriers of any G allele (N=198) in both univariate (hazard ratio [HR]=1.8; 95% confidence interval [CI]: 1.1-3.1; p=0.02) and multivariate (HR=2.4; 95%CI: 1.4-4.4; p=0.006) analysis. These data were validated in the FIRE-3 bev cohort in both univariate (A/A vs. Any G: 17.3 vs 39.9 months, HR=2.8, 95%CI: 1.4-5.9, p=0.004) and multivariate (HR=4.3, 95%CI: 1.5-12.2, p=0.0095) analysis. Conversely, pts carrying CIP2A rs13069780 C/C (N=24) only showed significantly longer progression-free survival (17.7 vs 12.3 months) than carriers of any T allele (n=105) in the FIRE-3 cet cohort in both univariate (HR=0.6; 95%CI 0.4-0.99; p=0.04) and multivariate (HR=0.5; 95%CI 0.3-0.94; p=0.02) analysis, but no association were observed in the bev cohort of TRIBE and FIRE-3. Conclusions: Our study demonstrated for the first time that PPP2R4 polymorphisms could predict outcomes of bev-based treatment in mCRC patients; Meanwhile CIP2A polymorphism could predict outcomes of cet-based treatment in mCRC patients. These findings support a possible role of the PP2A variants in contributing to resistance to anti-VEGF/EGFR treatment.

Exploring Extreme Signaling Failures in Intracellular Molecular Networks

Developing novel methods for the analysis of intracellular signaling networks is essential for understanding interconnected biological processes that underlie complex human disorders. A fundamental goal of this research is to quantify the vulnerability of a signaling network to the dysfunction of one or multiple molecules, when the dysfunction is defined as an incorrect response to the input signals. In this study, we propose an efficient algorithm to identify the extreme signaling failures that can induce the most detrimental impact on the physiological function of a molecular network. The algorithm basically finds the molecules, or groups of molecules, with the maximum vulnerability, i.e., the highest probability of causing the network failure, when they are dysfunctional. We propose another algorithm that efficiently accounts for signaling feedbacks in this analysis. The algorithms are tested on two experimentally verified ERBB and T cell signaling networks. Surprisingly, results reveal that as the number of concurrently dysfunctional molecules increases, the maximum vulnerability values quickly reach to a plateau following an initial increase. This suggests the specificity of vulnerable molecule (s) involved, as a specific number of faulty molecules cause the most detrimental damage to the function of the network. Increasing a random number of simultaneously faulty molecules does not further deteriorate the function of the network. Such a group of specific molecules whose dysfunction causes the extreme signaling failures can better elucidate the molecular mechanisms underlying the pathogenesis of complex trait disorders, and can offer new insights for the development of novel therapeutics.

Nonlinear delay differential equations and their application to modeling biological network motifs

Biological regulatory systems, such as cell signaling networks, nervous systems and ecological webs, consist of complex dynamical interactions among many components. Network motif models focus on small sub-networks to provide quantitative insight into overall behavior. However, such models often overlook time delays either inherent to biological processes or associated with multi-step interactions. Here we systematically examine explicit-delay versions of the most common network motifs via delay differential equation (DDE) models, both analytically and numerically. We find many broadly applicable results, including parameter reduction versus canonical ordinary differential equation (ODE) models, analytical relations for converting between ODE and DDE models, criteria for when delays may be ignored, a complete phase space for autoregulation, universal behaviors of feedforward loops, a unified Hill-function logic framework, and conditions for oscillations and chaos. We conclude that explicit-delay modeling simplifies the phenomenology of many biological networks and may aid in discovering new functional motifs.

DNA or Protein Methylation-Dependent Regulation of Activator Protein-1 Function

Epigenetic regulation and modification govern the transcriptional mechanisms that promote disease initiation and progression, but can also control the oncogenic processes, cell signaling networks, immunogenicity, and immune cells involved in anti-inflammatory and anti-tumor responses. The study of epigenetic mechanisms could have important implications for the development of potential anti-inflammatory treatments and anti-cancer immunotherapies. In this review, we have described the key role of epigenetic progression: DNA methylation, histone methylation or modification, and protein methylation, with an emphasis on the activator protein-1 (AP-1) signaling pathway. Transcription factor AP-1 regulates multiple genes and is involved in diverse cellular processes, including survival, differentiation, apoptosis, and development. Here, the AP-1 regulatory mechanism by DNA, histone, or protein methylation was also reviewed. Various methyltransferases activate or suppress AP-1 activities in diverse ways. We summarize the current studies on epigenetic alterations, which regulate AP-1 signaling during inflammation, cancer, and autoimmune diseases, and discuss the epigenetic mechanisms involved in the regulation of AP-1 signaling.

Androgen action in cell fate and communication during prostate development at single-cell resolution

Androgens/androgen receptor (AR) mediated signaling pathways are essential for prostate development, morphogenesis, and regeneration. Specifically, stromal AR-signaling has been shown to be essential for prostatic initiation. However, the molecular mechanisms underlying AR-initiated mesenchymal-epithelial interactions in prostate development remain unclear. Here, using a newly generated mouse model, we directly addressed the fate and role of genetically marked AR-expressing cells during embryonic prostate development. Androgen signaling-initiated signaling pathways were identified in mesenchymal niche populations at single cell transcriptomic resolution. The dynamic cell-signaling networks regulated by stromal AR were characterized in regulating prostatic epithelial bud formation. Pseudotime analyses further revealed the differentiation trajectory and fate of AR-expressing cells in both prostatic mesenchymal and epithelial cell populations. Specifically, the cellular properties of Zeb1-expressing progenitors were assessed. Selective deletion of AR signaling in a subpopulation mesenchymal rather than epithelial cells dysregulates the expression of the master regulators and significantly impairs prostatic bud formation. These data provide novel, high-resolution evidence demonstrating the important role of mesenchymal androgen signaling as cellular niches controlling prostate early development by initiating dynamic mesenchyme-epithelia cell interactions.

The role of death domain proteins in host response upon SARS-CoV-2 infection: modulation of programmed cell death and translational applications

The current pandemic of novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) poses a significant global public health threat. While urgent regulatory measures in control of the rapid spread of this virus are essential, scientists around the world have quickly engaged in this battle by studying the molecular mechanisms and searching for effective therapeutic strategies against this deadly disease. At present, the exact mechanisms of programmed cell death upon SARS-CoV-2 infection remain to be elucidated, though there is increasing evidence suggesting that cell death pathways play a key role in SARS-CoV-2 infection. There are several types of programmed cell death, including apoptosis, pyroptosis, and necroptosis. These distinct programs are largely controlled by the proteins of the death domain (DD) superfamily, which play an important role in viral pathogenesis and host antiviral response. Many viruses have acquired the capability to subvert the program of cell death and evade the host immune response, mainly by virally encoded gene products that control cell signaling networks. In this mini-review, we will focus on SARS-CoV-2, and discuss the implication of restraining the DD-mediated signaling network to potentially suppress viral replication and reduce tissue damage.