EMT- and MET-related processes in nonepithelial tumors:Importance for disease progression, prognosis, and therapeutic opportunities

The epithelial-to mesenchymal (EMT) process is increasingly recognized for playing a key role in the progression, dissemination, and therapy resistance of epithelial tumors. Accumulating evidence suggests that EMT inducers also lead to a gain in mesenchymal properties and promote malignancy of nonepithelial tumors. In this review, we present and discuss current findings, illustrating the importance of EMT inducers in tumors originating from nonepithelial/mesenchymal tissues, including brain tumors, hematopoietic malignancies, and sarcomas. Among these tumors, the involvement of mesenchymal transition has been most extensively investigated in glioblastoma, providing proof for cell autonomous and microenvironment-derived stimuli that provoke EMT-like processes that regulate stem cell, invasive, and immunogenic properties as well as therapy resistance. The involvement of prominent EMT transcription factor families, such as TWIST, SNAI, and ZEB, in promoting therapy resistance and tumor aggressiveness has also been reported in lymphomas, leukemias, and sarcomas. A reverse process, resembling mesenchymal-to-epithelial transition (MET), seems particularly relevant for sarcomas, where (partial) epithelial differentiation is linked to less aggressive tumors and a better patient prognosis. Overall, a hybrid model in which more stable epithelial and mesenchymal intermediates exist likely extends to the biology of tumors originating from sources other than the epithelium. Deeper investigation and understanding of the EMT/ PMET machinery in nonepithelial tumors will shed light on the pathogenesis of these tumors, potentially paving the way toward the identification of clinically relevant biomarkers for prognosis and future therapeutic targets

Rapid, label-free classification of glioblastoma differentiation status combining confocal Raman spectroscopy and machine learning

Label-free identification of tumor cells using spectroscopic assays has emerged as a technological innovation with a proven ability for rapid implementation in clinical care. Machine learning facilitates the optimization of processing and interpretation of extensive data, such as various spectroscopy data obtained from surgical samples. The here-described preclinical work investigates the potential of machine learning algorithms combining confocal Raman spectroscopy to distinguish non-differentiated glioblastoma cells and their respective isogenic differentiated phenotype by means of confocal ultra-rapid measurements. For this purpose, we measured and correlated modalities of 1146 intracellular single-point measurements and sustainingly clustered cell components to predict tumor stem cell existence. By further narrowing a few selected peaks, we found indicative evidence that using our computational imaging technology is a powerful approach to detect tumor stem cells in vitro with an accuracy of 91.7% in distinct cell compartments, mainly because of greater lipid content and putative different protein structures. We also demonstrate that the presented technology can overcome intra- and intertumoral cellular heterogeneity of our disease models, verifying the elevated physiological relevance of our applied disease modeling technology despite intracellular noise limitations for future translational evaluatio

MYCBP2 expression correlated with inflammatory cell infiltration and prognosis immunotherapy in thyroid cancer patients

IntroductionImmune checkpoint inhibitors (ICIs) have shown promising results for the treatment of multiple cancers. ICIs and related therapies may also be useful for the treatment of thyroid cancer (TC). In TC, Myc binding protein 2 (MYCBP2) is correlated with inflammatory cell infiltration and cancer prognosis. However, the relationship between MYCBP2 expression and ICI efficacy in TC patients is unclear.MethodsWe downloaded data from two TC cohorts, including transcriptomic data and clinical prognosis data. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to predict the efficacy of ICIs in TC patients. MCPcounter, xCell, and quanTIseq were used to calculate immune cell infiltration scores. Gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA) were used to evaluate signaling pathway scores. Immunohistochemical (IHC) analysis and clinical follow up was used to identify the MYCBP2 protein expression status in patients and associated with clinical outcome.ResultsA higher proportion of MYCBP2-high TC patients were predicted ICI responders than MYCBP2-low patients. MYCBP2-high patients also had significantly increased infiltration of CD8+ T cells, cytotoxic lymphocytes (CTLs), B cells, natural killer (NK) cells and dendritic cells (DC)s. Compared with MYCBP2-low patients, MYCBP2-high patients had higher expression of genes associated with B cells, CD8+ T cells, macrophages, plasmacytoid dendritic cells (pDCs), antigen processing and presentation, inflammatory stimulation, and interferon (IFN) responses. GSEA and ssGSEA also showed that MYCBP2-high patients had significantly increased activity of inflammatory factors and signaling pathways associated with immune responses.In addiation, Patients in our local cohort with high MYCBP2 expression always had a better prognosis and greater sensitivity to therapy while compared to patients with low MYCBP2 expression after six months clinic follow up.ConclusionsIn this study, we found that MYCBP2 may be a predictive biomarker for ICI efficacy in TC patients. High MYCBP2 expression was associated with significantly enriched immune cell infiltration. MYCBP2 may also be involved in the regulation of signaling pathways associated with anti-tumor immune responses or the production of inflammatory factors

A comparative pharmaco-metabolomic study of glutaminase inhibitors in glioma stem-like cells confirms biological effectiveness but reveals differences in target-specificity

Abstract: Cancer cells upregulate anabolic processes to maintain high rates of cellular turnover. Limiting the supply of macromolecular precursors by targeting enzymes involved in biosynthesis is a promising strategy in cancer therapy. Several tumors excessively metabolize glutamine to generate precursors for nonessential amino acids, nucleotides, and lipids, in a process called glutaminolysis. Here we show that pharmacological inhibition of glutaminase (GLS) eradicates glioblastoma stem-like cells (GSCs), a small cell subpopulation in glioblastoma (GBM) responsible for therapy resistance and tumor recurrence. Treatment with small molecule inhibitors compound 968 and CB839 effectively diminished cell growth and in vitro clonogenicity of GSC neurosphere cultures. However, our pharmaco-metabolic studies revealed that only CB839 inhibited GLS enzymatic activity thereby limiting the influx of glutamine derivates into the TCA cycle. Nevertheless, the effects of both inhibitors were highly GLS specific, since treatment sensitivity markedly correlated with GLS protein expression. Strikingly, we found GLS overexpressed in in vitro GSC models as compared with neural stem cells (NSC). Moreover, our study demonstrates the usefulness of in vitro pharmaco-metabolomics to score target specificity of compounds thereby refining drug development and risk assessment

A comparative pharmaco-metabolomic study of glutaminase inhibitors in glioma stem-like cells confirms biological effectiveness but reveals differences in target-specificity

Abstract: Cancer cells upregulate anabolic processes to maintain high rates of cellular turnover. Limiting the supply of macromolecular precursors by targeting enzymes involved in biosynthesis is a promising strategy in cancer therapy. Several tumors excessively metabolize glutamine to generate precursors for nonessential amino acids, nucleotides, and lipids, in a process called glutaminolysis. Here we show that pharmacological inhibition of glutaminase (GLS) eradicates glioblastoma stem-like cells (GSCs), a small cell subpopulation in glioblastoma (GBM) responsible for therapy resistance and tumor recurrence. Treatment with small molecule inhibitors compound 968 and CB839 effectively diminished cell growth and in vitro clonogenicity of GSC neurosphere cultures. However, our pharmaco-metabolic studies revealed that only CB839 inhibited GLS enzymatic activity thereby limiting the influx of glutamine derivates into the TCA cycle. Nevertheless, the effects of both inhibitors were highly GLS specific, since treatment sensitivity markedly correlated with GLS protein expression. Strikingly, we found GLS overexpressed in in vitro GSC models as compared with neural stem cells (NSC). Moreover, our study demonstrates the usefulness of in vitro pharmaco-metabolomics to score target specificity of compounds thereby refining drug development and risk assessment

Identification of regulatory variants associated with genetic susceptibility to meningococcal disease.

Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes

A microsurgical procedure for middle cerebral artery occlusion by intraluminal monofilament insertion technique in the rat: a special emphasis on the methodology

INTRODUCTION: Although there are many experimental studies describing the methodology of the middle cerebral artery occlusion (MCAO) in the literature, only limited data on these distinct anatomical structures and the details of the surgical procedure in a step by step manner. The aim of the present study simply is to examine the surgical anatomy of MCAO model and its modifications in the rat. MATERIALS AND METHODS: Forty Sprague-Dawley rats were used; 20 during the training phase and 20 for the main study. The monofilament sutures were prepared as described in the literature. All surgical steps of the study were performed under the operating microscope, including insertion of monofilament into middle cerebral artery through the internal carotid artery. RESULTS: After an extensive training period, we lost two rats in four weeks. The effects of MCAO were confirmed by the evidence of severe motor deficit during the recovery period, and histopathological findings of infarction were proved in all 18 surviving rats. CONCLUSION: In this study, a microsurgical guideline of the MCAO model in the rat is provided with the detailed description of all steps of the intraluminal monofilament insertion method with related figures

Sensory Ion Channel Candidates Inform on the Clinical Course of Pancreatic Cancer and Present Potential Targets for Repurposing of FDA-Approved Agents

Background: Transient receptor potential channels (TRPs) have been demonstrated to take on functions in pancreatic adenocarcinoma (PAAD) biology. However, little data are available that validate the potential of TRP in a clinical translational setting. Methods: A TRPs-related gene signature was constructed based on the Cox regression using a TCGA-PAAD cohort and receiver operating characteristic (ROC) was used to evaluate the predictive ability of this model. Core genes of the signature were screened by a protein-to-protein interaction (PPI) network, and expression validated by two independent datasets. The mutation analysis and gene set enrichment analysis (GSEA) were conducted. Virtual interventions screening was performed to discover substance candidates for the identified target genes. Results: A four TRPs-related gene signature, which contained MCOLN1, PKD1, TRPC3, and TRPC7, was developed and the area under the curve (AUC) was 0.758. Kaplan–Meier analysis revealed that patients with elevated signature score classify as a high-risk group featuring significantly shorter recurrence free survival (RFS) time, compared to the low-risk patients (p < 0.001). The gene prediction model also had a good predictive capability for predicting shortened overall survival (OS) and disease-specific survival (DSS) (AUC = 0.680 and AUC = 0.739, respectively). GSEA enrichment revealed the core genes of the signature, TRPC3 and TRPC7, were involved in several cancer-related pathways. TRPC3 mRNA is elevated in cancer tissue compared to control tissue and augmented in tumors with lymph node invasion compared to tumors without signs of lymph node invasion. Virtual substance screening of FDA approved compounds indicates that four small molecular compounds might be potentially selective not only for TRPC3 protein but also as a potential binding partner to TRPC7 protein. Conclusions: Our computational pipeline constructed a four TRP-related gene signature that enables us to predict clinical prognostic value of hitherto unrecognized biomarkers for PAAD. Sensory ion channels TRPC3 and TRPC7 could be the potential therapeutic targets in pancreatic cancer and TRPC3 might be involved in dysregulating mitochondrial functions during PAAD genesis

Abstract 2496: Targeting brain tumor stem cells by interfering with choline metabolism: Evidence for an EMT-choline oncometabolic network

Glioblastoma (GBM) is the most lethal primary malignant brain tumor with a median survival of less than two years. High levels of therapy resistance, strong cellular invasiveness and rapid cell growth demand aggressive multimodal therapies involving resection as well as radio-chemotherapy. Recent evidence has pointed to the existence of brain tumor stem cells (BTSCs), a subpopulation of human brain tumors which is thought to be responsible for tumor dissemination, relapse and chemo resistance. BTSCs have been associated with the expression of mesenchymal features as a result of epithelial-mesenchymal transition (EMT). Using high resolution proton nuclear magnetic resonance spectroscopy (1H NMR) we compared the intracellular metabolic composition of GBM cells after induction vs. inhibition of EMT as well as under stem cell or differentiated conditions. We identified that both EMT and enrichment for stemness induces the cholinic phenotype which is characterized by high intracellular levels of phosphocholine and total choline derivatives. Furthermore, interference with choline metabolism by targeting choline kinase alpha (CHKα) reversed EMT in GBM cells as we observed reduced invasiveness, clonogenicity, and expression of EMT associated genes. Taken together, interfering with choline metabolism is a powerful strategy to suppress EMT and thus target BTSCs. Moreover, the newly identified BTSC-oncometabolic network could be used to non-invasively monitor the invasive properties of glioblastomas and the success of anti-BTSC therapy