No abstract

No abstract

Exacerbated pro-inflammatory immune response contributes to COVID-19 pathology. However, despite the mounting evidence about SARS-CoV-2 infecting the human gut, little is known about the antiviral programs triggered in this organ. To address this gap, we performed single-cell transcriptomics of SARS-CoV-2-infected intestinal organoids. We identified a subpopulation of enterocytes as the prime target of SARS-CoV-2 and, interestingly, found the lack of positive correlation between susceptibility to infection and the expression of ACE2. Infected cells activated strong proinflammatory programs and produced interferon, while expression of interferon-stimulated genes was limited to bystander cells due to SARS-CoV-2 suppressing the autocrine action of interferon. These findings reveal that SARS-CoV-2 curtails the immune response and highlights the gut as a pro-inflammatory reservoir that should be considered to fully understand SARS-CoV-2 pathogenesis.

Nuclear Factor kappa B (NF-κB) signaling is frequently deregulated in a variety of cancers and is constitutively active in estrogen receptor negative (ER-) breast cancer subtypes. These molecular subtypes of breast cancer are associated with poor overall survival. We focused on mechanisms of NF-κB regulation by microRNAs (miRNAs), which regulate eukaryotic gene expression at the post-transcriptional level. In a previous genome-wide miRNA screen, we had identified miR-30c-2-3p as one of the strongest negative regulators of NF-κB signaling. Here we have uncovered the underlying molecular mechanisms and its consequences in breast cancer. In vitro results show that miR-30c-2-3p directly targets both TNFRSF1A-associated via death domain (TRADD), an adaptor protein of the TNFR/NF-κB signaling pathway, and the cell cycle protein Cyclin E1 (CCNE1). Ectopic expression of miR-30c-2-3p downregulated essential cytokines IL8, IL6, CXCL1, and reduced cell proliferation as well as invasion in MDA-MB-231 breast cancer cells. RNA interference (RNAi) induced silencing of TRADD phenocopied the effects on invasion and cytokine expression caused by miR-30c-2-3p, while inhibition of CCNE1 phenocopied the effects on cell proliferation. We further confirmed the tumor suppressive role of this miRNA using a dataset of 781 breast tumors, where higher expression was associated with better survival in breast cancer patients. In summary we have elucidated the mechanism by which miR-30c-2-3p negatively regulates NF-κB signaling and cell cycle progression in breast cancer.

The success of T cell-based cancer immunotherapy is limited by tumor's resistance against killing by cytotoxic T lymphocytes (CTLs). Tumor-immune resistance is mediated by cell surface ligands that engage immune-inhibitory receptors on T cells. These ligands represent potent targets for therapeutic inhibition. So far, only few immune-suppressive ligands have been identified. We here describe a rapid high-throughput siRNA-based screening approach that allows a comprehensive identification of ligands on human cancer cells that inhibit CTL-mediated tumor cell killing. We exemplarily demonstrate that CCR9, which is expressed in many cancers, exerts strong immune-regulatory effects on T cell responses in multiple tumors. Unlike PDL1, which inhibits TCR signaling, CCR9 regulates STAT signaling in T cells, resulting in reduced T-helper-1 cytokine secretion and reduced cytotoxic capacity. Moreover, inhibition of CCR9 expression on tumor cells facilitated immunotherapy of human tumors by tumor-specific T cells in vivo. Taken together, this method allows a rapid and comprehensive determination of immune-modulatory genes in human tumors which, as an entity, represent the ‘immune modulatome’ of cancer.

The reverse phase protein array (RPPA) approach was employed for a quantitative analysis of 71 cancer-relevant proteins and phosphoproteins in 84 non-small cell lung cancer (NSCLC) cell lines and by monitoring the activation state of selected receptor tyrosine kinases, PI3K/AKT and MEK/ERK1/2 signaling, cell cycle control, apoptosis, and DNA damage. Additional information on NSCLC cell lines such as that of transcriptomic data, genomic aberrations, and drug sensitivity was analyzed in the context of proteomic data using supervised and non-supervised approaches for data analysis. First, the unsupervised analysis of proteomic data indicated that proteins clustering closely together reflect well-known signaling modules, e.g. PI3K/AKT- and RAS/RAF/ERK-signaling, cell cycle regulation, and apoptosis. However, mutations of EGFR, ERBB2, RAF, RAS, TP53, and PI3K were found dispersed across different signaling pathway clusters. Merely cell lines with an amplification of EGFR and/or ERBB2 clustered closely together on the proteomic, but not on the transcriptomic level. Secondly, supervised data analysis revealed that sensitivity towards anti-EGFR drugs generally correlated better with high level EGFR phosphorylation than with EGFR abundance itself. High level phosphorylation of RB and high abundance of AURKA were identified as candidates that can potentially predict sensitivity towards the aurora kinase inhibitor VX680. Examples shown demonstrate that the RPPA approach presents a useful platform for targeted proteomics with high potential for biomarker discovery. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

Endoplasmic reticulum (ER) plays an essential role in cell function and survival. Accumulation of unfolded or misfolded proteins in the lumen of the ER activates the unfolded protein response (UPR), resulting in ER stress and subsequent apoptosis. The alkylphosphocholine erufosine is a known Akt-mTOR inhibitor in oral squamous cell carcinoma (OSCC). In the present study, we evaluate erufosine’s role to induce ER and mitochondrial stress leading to autophagy, apoptosis, and ROS induction. The cellular toxicity of erufosine was determined in two OSCC cell lines and gene expression and enrichment analyses were performed. A positive enrichment of ER stress upon erufosine exposure was observed, which was verified at protein levels for the ER stress sensors and their downstream mediators. Knockdown and pharmacological inhibition of the ER stress sensors PERK and XBP1 revealed their involvement into erufosine’s cellular effects, including proliferation, apoptosis, and autophagy induction. Autophagy was confirmed by increased acidic vacuoles and LC3-B levels. Upon erufosine exposure, calcium influx into the cytoplasm of the two OSCC cell lines was seen. Apoptosis was confirmed by nuclear staining, Annexin-V, and immunoblotting of caspases. The induction of mitochondrial stress upon erufosine exposure was predicted by gene set enrichment analysis (GSEA) and shown by erufosine’s effect on mitochondrial membrane potential, ATP, and ROS production in OSCC cells. These data show that ER and mitochondrial targeting by erufosine represents a new facet of its mechanism of action as well as a promising new framework in the treatment of head and neck cancers.

Somatic copy number alterations frequently occur in the cancer genome affecting not only oncogenic or tumor suppressive genes, but also passenger and potential codriver genes. An intrinsic feature resulting from such genomic perturbations is the deregulation in the metabolism of tumor cells. In this study, we have shown that metabolic and cancer-causing genes are unexpectedly often proximally positioned in the chromosome and share loci with coaltered copy numbers across multiple cancers (19 cancer types from The Cancer Genome Atlas). We have developed an analysis pipeline, Identification of Metabolic Cancer Genes (iMetCG), to infer the functional impact on metabolic remodeling from such coamplifications and codeletions and delineate genes driving cancer metabolism from those that are neutral. Using our identified metabolic genes, we were able to classify tumors based on their tissue and developmental origins. These metabolic genes were similar to known cancer genes in terms of their network connectivity, isoform frequency, and evolutionary features. We further validated these identified metabolic genes by (i) using gene essentiality data from several tumor cell lines, (ii) showing that these identified metabolic genes are strong indicators for patient survival, and (iii) observing a significant overlap between our identified metabolic genes and known cancer-metabolic genes. Our analyses revealed a hitherto unknown generic mechanism for large-scale metabolic reprogramming in cancer cells based on linear gene proximities between cancer-causing and -metabolic genes. We have identified 119 new metabolic cancer genes likely to be involved in rewiring cancer cell metabolism.