Translational control mechanisms in cutaneous malignant melanoma: the role of eIF2α

Comprehensive analysis of single cell and bulk RNA sequencing reveals the heterogeneity of melanoma tumor microenvironment and predicts the response of immunotherapy

BACKGROUND

Tumor microenvironment (TME) heterogeneity is an important factor affecting the treatment response of immune checkpoint inhibitors (ICI). However, the TME heterogeneity of melanoma is still widely characterized.

METHODS

We downloaded the single-cell sequencing data sets of two melanoma patients from the GEO database, and used the "Scissor" algorithm and the "BayesPrism" algorithm to comprehensively analyze the characteristics of microenvironment cells based on single-cell and bulk RNA-seq data. The prediction model of immunotherapy response was constructed by machine learning and verified in three cohorts of GEO database.

RESULTS

We identified seven cell types. In the Scissor+ subtype cell population, the top three were T cells, B cells and melanoma cells. In the Scissor- subtype, there are more macrophages. By quantifying the characteristics of TME, significant differences in B cells between responders and non-responders were observed. The higher the proportion of B cells, the better the prognosis. At the same time, macrophages in the non-responsive group increased significantly. Finally, nine gene features for predicting ICI response were constructed, and their predictive performance was superior in three external validation groups.

CONCLUSION

Our study revealed the heterogeneity of melanoma TME and found a new predictive biomarker, which provided theoretical support and new insights for precise immunotherapy of melanoma patients.

A general method for quantitative fractionation of mammalian cells

Subcellular fractionation in combination with mass spectrometry-based proteomics is a powerful tool to study localization of key proteins in health and disease. Here we offered a reliable and rapid method for mammalian cell fractionation, tuned for such proteomic analyses. This method proves readily applicable to different cell lines in which all the cellular contents are accounted for, while maintaining nuclear and nuclear envelope integrity. We demonstrated the method's utility by quantifying the effects of a nuclear export inhibitor on nucleoplasmic and cytoplasmic proteomes.

Nano-Based Drug Delivery of Polyphenolic Compounds for Cancer Treatment: Progress, Opportunities, and Challenges

Polyphenols and their derivates, a kind of natural product distributed in herb plants, vegetables, and fruits, are the most abundant antioxidants in the human diet and have been found to display cancer-preventative effects in several epidemiological studies. The scientific community has also validated the anti-cancer bioactivities and low toxicities of polyphenolic compounds, including flavones, tannins, phenolic acids, and anthocyanins, through in vitro and in vivo studies. However, the low stability, weak targeting ability, poor solubility, and low bioavailability of pure polyphenolic agents have significantly impaired their treatment efficacy. Nowadays, nano-based technology has been applied to surmount these restrictions and maximize the treatment efficacy of polyphenols. In this review, we summarize the advantages and related mechanisms of polyphenols in cancer treatment. Moreover, aiming at the poor solubility and low bioavailability of pure polyphenols in vivo, the advantages of nano-based delivery systems and recent research developments are highlighted. Herein, particular emphasis is mainly placed on the most widely used nanomaterials in the delivery of natural products, including liposomes, micelles, and nanogels. Finally, we present an overview and the challenges of future implementations of nano-based delivery systems of polyphenolic compounds in the cancer therapeutic field.

The integrated stress response is activated in the salivary glands of Sjögren's syndrome patients

Introduction

Primary Sjögren's syndrome (SS) is an autoimmune exocrinopathy that affects the structure and function of salivary and lachrymal glands. Labial salivary gland (LSG) acinar cells from SS patients lose cellular homeostasis and experience endoplasmic reticulum and oxidative stress. The integrated cellular stress response (ISR) is an adaptive pathway essential for restoring homeostasis against various stress-inducing factors, including pro-inflammatory cytokines, and endoplasmic reticulum and oxidative stress. ISR activation leads eIF2α phosphorylation, which transiently blocks protein synthesis while allowing the ATF4 expression, which induces a gene expression program that seeks to optimize cellular recovery. PKR, HRI, GCN2, and PERK are the four sentinel stress kinases that control eIF2α phosphorylation. Dysregulation and chronic activation of ISR signaling have pathologic consequences associated with inflammation.

Methods

Here, we analyzed the activation of the ISR in LSGs of SS-patients and non-SS sicca controls, determining the mRNA, protein, and phosphorylated-protein levels of key ISR components, as well as the expression of some of ATF4 targets. Moreover, we performed a qualitative characterization of the distribution of ISR components in LSGs from both groups and evaluated if their levels correlate with clinical parameters.

Results

We observed that the four ISR sensors are expressed in LSGs of both groups. However, only PKR and PERK showed increased expression and/or activation in LSGs from SS-patients. eIF2α and p-eIF2α protein levels significantly increased in SS-patients; meanwhile components of the PP1c complex responsible for eIF2α dephosphorylation decreased. ATF4 mRNA levels were decreased in LSGs from SS-patients along with hypermethylation of the ATF4 promoter. Despite low mRNA levels, SS-patients showed increased levels of ATF4 protein and ATF4-target genes involved in the antioxidant response. The acinar cells of SS-patients showed increased staining intensity for PKR, p-PKR, p-PERK, p-eIF2α, ATF4, xCT, CHOP, and NRF2. Autoantibodies, focus score, and ESSDAI were correlated with p-PERK/PERK ratio and ATF4 protein levels.

Discussion

In summary, the results showed an increased ISR activation in LSGs of SS-patients. The increased protein levels of ATF4 and ATF4-target genes involved in the redox homeostasis could be part of a rescue response against the various stressful conditions to which the LSGs of SS-patients are subjected and promote cell survival.

Tomatine Displays Antitumor Potential in In Vitro Models of Metastatic Melanoma

There is a growing interest in the cytotoxic effects of bioactive glycoalkaloids, such as α-tomatine on tumor cells. Here, for the first time, we determine the antitumor potential of tomatine, a mixture of α-tomatine and dehydrotomatine, in metastatic melanoma (MM) cell lines harboring different BRAF and MC1R variants. We performed cytotoxicity experiments and annexin-V/propidium iodide staining to assess the apoptotic/necrotic status of the cells. ER stress and autophagy markers were revealed by Western Blot, whereas antiangiogenic and vascular-disrupting effects were evaluated through a capillary tube formation assay on matrigel and by ELISA kit for VEGF release determination. Cell invasion was determined by a Boyden chamber matrigel assay. Tomatine reduced 50% of cell viability and induced a concentration-dependent increase of apoptotic cells in the range of 0.5–1 μM in terms of α-tomatine. The extent of apoptosis was more than two-fold higher in ^V600BRAF-D184H/D184H MC1R cells than in BRAF wild-type cells and ^V600BRAF-MC1R wild-type cell lines. Additionally, tomatine increased the LC3I/II autophagy marker, p-eIF2α, and p-Erk1/2 levels in BRAF wild-type cells. Notably, tomatine strongly reduced cell invasion and melanoma-dependent angiogenesis by reducing VEGF release and tumor-stimulating effects on capillary tube formation. Collectively, our findings support tomatine as a potential antitumor agent in MM.

The Complex Role of Autophagy in Melanoma Evolution: New Perspectives From Mouse Models

Despite tremendous efforts in the last decade to improve treatments, melanoma still represents a major therapeutic challenge and overall survival of patients remains poor. Therefore, identifying new targets to counteract melanoma is needed. In this scenario, autophagy, the “self-eating” process of the cell, has recently arisen as new potential candidate in melanoma. Alongside its role as a recycling mechanism for dysfunctional and damaged cell components, autophagy also clearly sits at a crossroad with metabolism, thereby orchestrating cell proliferation, bioenergetics and metabolic rewiring, all hallmarks of cancer cells. In this regard, autophagy, both in tumor and host, has been flagged as an essential player in melanomagenesis and progression. To pave the way to a better understanding of such a complex interplay, the use of genetically engineered mouse models (GEMMs), as well as syngeneic mouse models, has been undoubtedly crucial. Herein, we will explore the latest discoveries in the field, with particular focus on the potential of these models in unraveling the contribution of autophagy in melanoma, along with the therapeutic advantages that may arise.

A New Look at the Structures of Old Sepsis Actors by Exploratory Data Analysis Tools

Sepsis is a life-threatening condition that accounts for numerous deaths worldwide, usually complications of common community infections (i.e., pneumonia, etc), or infections acquired during the hospital stay. Sepsis and septic shock, its most severe evolution, involve the whole organism, recruiting and producing a lot of molecules, mostly proteins. Proteins are dynamic entities, and a large number of techniques and studies have been devoted to elucidating the relationship between the conformations adopted by proteins and what is their function. Although molecular dynamics has a key role in understanding these relationships, the number of protein structures available in the databases is so high that it is currently possible to build data sets obtained from experimentally determined structures. Techniques for dimensionality reduction and clustering can be applied in exploratory data analysis in order to obtain information on the function of these molecules, and this may be very useful in immunology to better understand the structure-activity relationship of the numerous proteins involved in host defense, moreover in septic patients. The large number of degrees of freedom that characterize the biomolecules requires special techniques which are able to analyze this kind of data sets (with a small number of entries respect to the number of degrees of freedom). In this work we analyzed the ability of two different types of algorithms to provide information on the structures present in three data sets built using the experimental structures of allosteric proteins involved in sepsis. The results obtained by means of a principal component analysis algorithm and those obtained by a random projection algorithm are largely comparable, proving the effectiveness of random projection methods in structural bioinformatics. The usefulness of random projection in exploratory data analysis is discussed, including validation of the obtained clusters. We have chosen these proteins because of their involvement in sepsis and septic shock, aimed to highlight the potentiality of bioinformatics to point out new diagnostic and prognostic tools for the patients.

MITF controls the TCA cycle to modulate the melanoma hypoxia response

In response to the dynamic intra-tumor microenvironment, melanoma cells adopt distinct phenotypic states associated with differential expression of the microphthalmia-associated transcription factor (MITF). The response to hypoxia is driven by hypoxia-inducible transcription factors (HIFs) that reprogram metabolism and promote angiogenesis. HIF1α indirectly represses MITF that can activate HIF1α expression. Although HIF and MITF share a highly related DNA-binding specificity, it is unclear whether they co-regulate subset of target genes. Moreover, the genomewide impact of hypoxia on melanoma and whether melanoma cell lines representing different phenotypic states exhibit distinct hypoxic responses is unknown. Here we show that three different melanoma cell lines exhibit widely different hypoxia responses with only a core 23 genes regulated in common after 12 hr in hypoxia. Surprisingly, under hypoxia MITF is transiently up-regulated by HIF1α and co-regulates a subset of HIF targets including VEGFA. Significantly, we also show that MITF represses itself and also regulates SDHB to control the TCA cycle and suppress pseudo-hypoxia. Our results reveal a previously unsuspected role for MITF in metabolism and the network of factors underpinning the hypoxic response in melanoma.