Similar Datasets
Project description:We investigated the route of neurotrophic cue delivery to the nerves
2020-02-13 | GSE140189 | GEO
Project description:Head and neck cancer neural reprogramming
| PRJNA589293 | ENA
Project description:mRNA: profiling the neural identity of cancer associated neurons miRNA: investigating the p53 dependant exosomal miRNA content
2020-02-13 | GSE134220 | GEO
Project description:Head and neck cancer neural reprogramming [ClariomSMouse]
| PRJNA588753 | ENA
Project description:neural reprogramming in head and neck cancer
| PRJNA554349 | ENA
Project description:The solid tumour microenvironment includes nerve fibres that arise from the peripheral nervous system1,2. Recent work indicates that newly formed adrenergic nerve fibres promote tumour growth, but the origin of these nerves and the mechanism of their inception are unknown1,3. Here, by comparing the transcriptomes of cancer-associated trigeminal sensory neurons with those of endogenous neurons in mouse models of oral cancer, we identified an adrenergic differentiation signature. We show that loss of TP53 leads to adrenergic transdifferentiation of tumour-associated sensory nerves through loss of the microRNA miR-34a. Tumour growth was inhibited by sensory denervation or pharmacological blockade of adrenergic receptors, but not by chemical sympathectomy of pre-existing adrenergic nerves. A retrospective analysis of samples from oral cancer revealed that p53 status was associated with nerve density, which was in turn associated with poor clinical outcomes. This crosstalk between cancer cells and neurons represents mechanism by which tumour-associated neurons are reprogrammed towards an adrenergic phenotype that can stimulate tumour progression, and is a potential target for anticancer therapy.
| S-EPMC9723538 | biostudies-literature
Project description:Solid tumors are complex collections of cells surrounded by benign tissues that influence and are influenced by the tumor. These surrounding cells include vasculature, immune cells, neurons, and other cell types, and are collectively known as the tumor microenvironment. Tumors manipulate their microenvironment for the benefit of the tumor. Autonomic neurons innervate and drive malignant growth in a variety of solid tumors. However, the mechanisms underlying neuron-tumor relationships are not well understood. Recently, Amit et al. described that trophic relationships between oral cavity squamous cell carcinomas (OCSCCs) and nearby autonomic neurons arise through direct signaling between tumors and local neurons. An inducible tumor model in which 4NQO was introduced into the drinking water of Trp53 knockout mice was used to model OCSCC-microenvironment interactions. Using this model, this group discovered that loss of p53 expression in OCSCC tumors resulted in increased nerve density within these tumors. This neuritogenesis was controlled by tumor-derived microRNA-laden extracellular vesicles (EVs). Specifically, EV-delivered miR-34a inhibited neuritogenesis, whereas EV-delivered miR-21 and miR-324 increased neuritogenesis. The neurons innervating p53-deficient OCSCC tumors were predominantly adrenergic and arose through the transdifferentiation of trigeminal sensory nerve fibers to adrenergic nerve fibers. This transdifferentiation corresponded with increased expression of neuron-reprogramming transcription factors, including POU5F1, KLF4, and ASCL1, which were overexpressed in the p53-deficient samples, and are proposed targets of miR-34a-mediated regulation. Human OCSCC samples enriched in adrenergic neuron markers are associated strongly with poor outcomes, thus demonstrating the relevance of these findings to cancer patients.
| S-EPMC7861575 | biostudies-literature
Project description:Ferroptosis is a newly defined form of cell death induced by iron-dependent accumulation of lethal lipid peroxidation. Ferroptosis represent a therapeutic strategy to suppress therapy-resistant cancer cells with more property of epithelial-mesenchymal transition (EMT). However, epigenetic reprogramming of EMT has been rarely studied in the context of ferroptosis susceptibility. Therefore, we examined the therapeutic potentiality of EMT epigenetic reprogramming in promoting ferroptosis in head and neck cancer (HNC) cells. The effects of ferroptosis inducers and EMT inhibition or induction were tested in HNC cell lines and mouse tumor xenograft models. These effects were analyzed concerning cell viability and death, lipid reactive oxygen species and iron production, labile iron pool, glutathione contents, NAD/NADH levels, and mRNA/protein expression. Cell density and the expression levels of E-cadherin, vimentin, and ZEB1 were associated with the different susceptibility to ferroptosis inducers. CDH1 silencing or ZEB1 overexpression increased the susceptibility to ferroptosis, whereas CDH overexpression or ZEB1 silencing decreased the susceptibility, in vitro and in vivo. Histone deacetylase SIRT1 gene silencing or pharmacological inhibition by EX-527 suppressed EMT and consequently decreased ferroptosis, whereas SIRT inducers, resveratrol and SRT1720, increased ferroptosis. MiR-200 family inhibitors induced EMT and increased ferroptosis susceptibility. In HNC cells with low expression of E-cadherin, the treatment of 5-azacitidine diminished the hypermethylation of CDH1, resulting in increased E-cadherin expression and decreased ferroptosis susceptibility. Our data suggest that epigenetic reprogramming of EMT contributes to promoting ferroptosis in HNC cells.
| S-EPMC7484553 | biostudies-literature
Project description:PurposeAlthough neural networks have shown remarkable performance in medical image analysis, their translation into clinical practice remains difficult due to their lack of interpretability. An emerging field that addresses this problem is Explainable AI.MethodsHere, we aimed to investigate the ability of Convolutional Neural Networks (CNNs) to classify head and neck cancer histopathology. To this end, we manually annotated 101 histopathological slides of locally advanced head and neck squamous cell carcinoma. We trained a CNN to classify tumor and non-tumor tissue, and another CNN to semantically segment four classes - tumor, non-tumor, non-specified tissue, and background. We applied Explainable AI techniques, namely Grad-CAM and HR-CAM, to both networks and explored important features that contributed to their decisions.ResultsThe classification network achieved an accuracy of 89.9% on previously unseen data. Our segmentation network achieved a class-averaged Intersection over Union score of 0.690, and 0.782 for tumor tissue in particular. Explainable AI methods demonstrated that both networks rely on features agreeing with the pathologist's expert opinion.ConclusionOur work suggests that CNNs can predict head and neck cancer with high accuracy. Especially if accompanied by visual explanations, CNNs seem promising for assisting pathologists in the assessment of cancer sections.
| S-EPMC10623808 | biostudies-literature
Project description:Recent studies showed that lipid metabolism reprogramming contributes to tumorigenicity and malignancy by interfering energy production, membrane formation, and signal transduction in cancers. HNSCCs are highly reliant on aerobic glycolysis and glutamine metabolism. However, the mechanisms underlying lipid metabolism reprogramming in HNSCCs remains obscure. The present review summarizes and discusses the "vital" cellular signaling roles of the lipid metabolism reprogramming in HNSCCs. We also address the differences between HNSCCs regions caused by anatomical heterogeneity. We enumerate these recent findings into our current understanding of lipid metabolism reprogramming in HNSCCs and introduce the new and exciting therapeutic implications of targeting the lipid metabolism.
| S-EPMC9524856 | biostudies-literature