Aprepitant, An Antiemetic Agent, Interferes with Metal Ion Homeostasis of Candida Auris and Displays Potent Synergistic Interactions With Azole Drugs

With the rapid increase in the frequency of azole-resistant species, combination therapy appears to be a promising tool to augment the antifungal activity of azole drugs against resistant Candida species. Here, we report the effect of aprepitant, an antiemetic agent, on the antifungal activities of azole drugs against the multidrug-resistant Candida auris. Aprepitant reduced the minimum inhibitory concentration (MIC) of itraconazole in vitro, by up to eight-folds. Additionally, the aprepitant/itraconazole combination interfered significantly with the biofilm-forming ability of C. auris by 95 ± 0.13%, and significantly disrupted mature biofilms by 52 ± 0.83%, relative to the untreated control. In a Caenorhabditis elegans infection model, the aprepitant/itraconazole combination significantly prolonged the survival of infected nematodes by ~90% (five days postinfection) and reduced the fungal burden by ~92% relative to the untreated control. Further, this novel drug combination displayed broad-spectrum synergistic interactions against other medically important Candida species such as C. albicans, C. krusei, C. tropicalis, and C. parapsilosis (ƩFICI ranged from 0.08 to 0.31). Comparative transcriptomic profiling and mechanistic studies indicated aprepitant/itraconazole interferes significantly with metal ion homeostasis and compromises the ROS detoxification ability of C. auris. This study presents aprepitant as a novel, potent, and broadspectrum azole chemosensitizing agent that warrants further investigation

cTULIP: application of a human-based RNA-seq primary tumor classification tool for cross-species primary tumor classification in canine

IntroductionThe domestic dog, Canis familiaris, is quickly gaining traction as an advantageous model for use in the study of cancer, one of the leading causes of death worldwide. Naturally occurring canine cancers share clinical, histological, and molecular characteristics with the corresponding human diseases.MethodsIn this study, we take a deep-learning approach to test how similar the gene expression profile of canine glioma and bladder cancer (BLCA) tumors are to the corresponding human tumors. We likewise develop a tool for identifying misclassified or outlier samples in large canine oncological datasets, analogous to that which was developed for human datasets.ResultsWe test a number of machine learning algorithms and found that a convolutional neural network outperformed logistic regression and random forest approaches. We use a recently developed RNA-seq-based convolutional neural network, TULIP, to test the robustness of a human-data-trained primary tumor classification tool on cross-species primary tumor prediction. Our study ultimately highlights the molecular similarities between canine and human BLCA and glioma tumors, showing that protein-coding one-to-one homologs shared between humans and canines, are sufficient to distinguish between BLCA and gliomas.DiscussionThe results of this study indicate that using protein-coding one-to-one homologs as the features in the input layer of TULIP performs good primary tumor prediction in both humans and canines. Furthermore, our analysis shows that our selected features also contain the majority of features with known clinical relevance in BLCA and gliomas. Our success in using a human-data-trained model for cross-species primary tumor prediction also sheds light on the conservation of oncological pathways in humans and canines, further underscoring the importance of the canine model system in the study of human disease

Cholesterol Sulfotransferase SULT2B1b Modulates Sensitivity to Death Receptor Ligand TNFα in Castration-Resistant Prostate Cancer

Cholesterol sulfotransferase, SULT2B1b, has been demonstrated to modulate both androgen receptor activity and cell growth properties. However, the mechanism(s) by which SULT2B1b alters these properties within prostate cancer cells has not been described. Furthermore, specific advantages of SULT2B1b expression in prostate cancer cells is not understood. In these studies, single-cell mRNA sequencing (scRNA-seq) was conducted to compare the transcriptomes of SULT2B1b knockdown (KD) versus Control KD LNCaP cells. Over 2,000 differentially expressed (DE) genes were identified along with alterations in numerous canonical pathways, including the death receptor signaling pathway. The studies herein demonstrate that SULT2B1b KD increases tumor necrosis factor alpha (TNF) expression in prostate cancer cells and results in NF-κB activation in a TNF-dependent manner. More importantly, SULT2B1b KD significantly enhances TNF-mediated apoptosis in both TNF-sensitive LNCaP cells and TNF-resistant C4–2 cells. Overexpression of SULT2B1b in LNCaP cells also decreases sensitivity to TNF-mediated cell death, suggesting that SULT2B1b modulates pathways dictating the TNF sensitivity capacity of prostate cancer cells. Probing human prostate cancer patient datasets further support this work by providing evidence that SULT2B1b expression is inversely correlated with TNF-related genes, including TNF, CD40LG, FADD, and NFKB1. Together, these data provide evidence that SULT2B1b expression in prostate cancer cells enhances resistance to TNF and may provide a growth advantage. In addition, targeting SULT2B1b may induce an enhanced therapeutic response to TNF treatment in advanced prostate cancer

Simplified MethylRAD Sequencing to Detect Changes in DNA Methylation at Enhancer Elements in Differentiating Embryonic Stem Cells

Differential DNA methylation is characteristic of gene regulatory regions, such as enhancers, which mostly constitute low or intermediate CpG content in their DNA sequence. Consequently, quantification of changes in DNA methylation at these sites is challenging. Given that DNA methylation across most of the mammalian genome is maintained, the use of genome-wide bisulfite sequencing to measure fractional changes in DNA methylation at specific sites is an overexertion which is both expensive and cumbersome. Here, we developed a MethylRAD technique with an improved experimental plan and bioinformatic analysis tool to examine regional DNA methylation changes in embryonic stem cells (ESCs) during differentiation. The transcriptional silencing of pluripotency genes (PpGs) during ESC differentiation is accompanied by PpG enhancer (PpGe) silencing mediated by the demethylation of H3K4me1 by LSD1. Our MethylRAD data show that in the presence of LSD1 inhibitor, a significant fraction of LSD1-bound PpGe fails to gain DNA methylation. We further show that this effect is mostly observed in PpGes with low/intermediate CpG content. Underscoring the sensitivity and accuracy of MethylRAD sequencing, our study demonstrates that this method can detect small changes in DNA methylation in regulatory regions, including those with low/intermediate CpG content, thus asserting its use as a method of choice for diagnostic purposes

Lansoprazole interferes with fungal respiration and acts synergistically with amphotericin B against multidrug-resistant Candida auris

ABSTRACTCandida auris has emerged as a problematic fungal pathogen associated with high morbidity and mortality. Amphotericin B (AmB) is the most effective antifungal used to treat invasive fungal candidiasis, with resistance rarely observed among clinical isolates. However, C. auris possesses extraordinary resistant profiles against all available antifungal drugs, including AmB. In our pursuit of potential solutions, we screened a panel of 727 FDA-approved drugs. We identified the proton pump inhibitor lansoprazole (LNP) as a potent enhancer of AmB’s activity against C. auris. LNP also potentiates the antifungal activity of AmB against other medically important species of Candida and Cryptococcus. Our investigations into the mechanism of action unveiled that LNP metabolite(s) interact with a crucial target in the mitochondrial respiratory chain (complex III, known as cytochrome bc1). This interaction increases oxidative stress within fungal cells. Our results demonstrated the critical role of an active respiratory function in the antifungal activity of LNP. Most importantly, LNP restored the efficacy of AmB in an immunocompromised mouse model, resulting in a 1.7-log (∼98%) CFU reduction in the burden of C. auris in the kidneys. Our findings strongly advocate for a comprehensive evaluation of LNP as a cytochrome bc1 inhibitor for combating drug-resistant C. auris infections

Lansoprazole interferes with fungal respiration and acts synergistically with amphotericin B against multidrug-resistant Candida auris

International audienceCandida auris has emerged as a problematic fungal pathogen associated with high morbidity and mortality. Amphotericin B (AmB) is the most effective antifungal used to treat invasive fungal candidiasis, with resistance rarely observed among clinical isolates. However, C. auris possesses extraordinary resistant profiles against all available antifungal drugs, including AmB. In our pursuit of potential solutions, we screened a panel of 727 FDA-approved drugs. We identified the proton pump inhibitor lansoprazole (LNP) as a potent enhancer of AmB’s activity against C. auris. LNP also potentiates the antifungal activity of AmB against other medically important species of Candida and Cryptococcus. Our investigations into the mechanism of action unveiled that LNP metabolite(s) interact with a crucial target in the mitochondrial respiratory chain (complex III, known as cytochrome bc1). This interaction increases oxidative stress within fungal cells. Our results demonstrated the critical role of an active respiratory function in the antifungal activity of LNP. Most importantly, LNP restored the efficacy of AmB in an immunocompromised mouse model, resulting in a 1.7-log (∼98%) CFU reduction in the burden of C. auris in the kidneys. Our findings strongly advocate for a comprehensive evaluation of LNP as a cytochrome bc1 inhibitor for combating drug-resistant C. auris infections

synNotch-programmed iPSC-derived NK cells usurp TIGIT and CD73 activities for glioblastoma therapy

Abstract Severe heterogeneity within glioblastoma has spurred the notion that disrupting the interplay between multiple elements on immunosuppression is at the core of meaningful anti-tumor responses. T cell immunoreceptor with Ig and ITIM domains (TIGIT) and its glioblastoma-associated antigen, CD155, form a highly immunosuppressive axis in glioblastoma and other solid tumors, yet targeting of TIGIT, a functionally heterogeneous receptor on tumor-infiltrating immune cells, has largely been ineffective as monotherapy, suggesting that disruption of its inhibitory network might be necessary for measurable responses. It is within this context that we show that the usurpation of the TIGIT − CD155 axis via engineered synNotch-mediated activation of induced pluripotent stem cell-derived natural killer (NK) cells promotes transcription factor-mediated activation of a downstream signaling cascade that results in the controlled, localized blockade of CD73 to disrupt purinergic activity otherwise resulting in the production and accumulation of immunosuppressive extracellular adenosine. Such “decoy” receptor engages CD155 binding to TIGIT, but tilts inhibitory TIGIT/CD155 interactions toward activation via downstream synNotch signaling. Usurping activities of TIGIT and CD73 promotes the function of adoptively transferred NK cells into intracranial patient-derived models of glioblastoma and enhances their natural cytolytic functions against this tumor to result in complete tumor eradication. In addition, targeting both receptors, in turn, reprograms the glioblastoma microenvironment via the recruitment of T cells and the downregulation of M2 macrophages. This study demonstrates that TIGIT/CD155 and CD73 are targetable receptor partners in glioblastoma. Our data show that synNotch-engineered pluripotent stem cell-derived NK cells are not only effective mediators of anti-glioblastoma responses within the setting of CD73 and TIGIT/CD155 co-targeting, but represent a powerful allogeneic treatment option for this tumor

Table_1_cTULIP: application of a human-based RNA-seq primary tumor classification tool for cross-species primary tumor classification in canine.xlsx

IntroductionThe domestic dog, Canis familiaris, is quickly gaining traction as an advantageous model for use in the study of cancer, one of the leading causes of death worldwide. Naturally occurring canine cancers share clinical, histological, and molecular characteristics with the corresponding human diseases.MethodsIn this study, we take a deep-learning approach to test how similar the gene expression profile of canine glioma and bladder cancer (BLCA) tumors are to the corresponding human tumors. We likewise develop a tool for identifying misclassified or outlier samples in large canine oncological datasets, analogous to that which was developed for human datasets.ResultsWe test a number of machine learning algorithms and found that a convolutional neural network outperformed logistic regression and random forest approaches. We use a recently developed RNA-seq-based convolutional neural network, TULIP, to test the robustness of a human-data-trained primary tumor classification tool on cross-species primary tumor prediction. Our study ultimately highlights the molecular similarities between canine and human BLCA and glioma tumors, showing that protein-coding one-to-one homologs shared between humans and canines, are sufficient to distinguish between BLCA and gliomas.DiscussionThe results of this study indicate that using protein-coding one-to-one homologs as the features in the input layer of TULIP performs good primary tumor prediction in both humans and canines. Furthermore, our analysis shows that our selected features also contain the majority of features with known clinical relevance in BLCA and gliomas. Our success in using a human-data-trained model for cross-species primary tumor prediction also sheds light on the conservation of oncological pathways in humans and canines, further underscoring the importance of the canine model system in the study of human disease.</p

DataSheet_1_cTULIP: application of a human-based RNA-seq primary tumor classification tool for cross-species primary tumor classification in canine.pdf

IntroductionThe domestic dog, Canis familiaris, is quickly gaining traction as an advantageous model for use in the study of cancer, one of the leading causes of death worldwide. Naturally occurring canine cancers share clinical, histological, and molecular characteristics with the corresponding human diseases.MethodsIn this study, we take a deep-learning approach to test how similar the gene expression profile of canine glioma and bladder cancer (BLCA) tumors are to the corresponding human tumors. We likewise develop a tool for identifying misclassified or outlier samples in large canine oncological datasets, analogous to that which was developed for human datasets.ResultsWe test a number of machine learning algorithms and found that a convolutional neural network outperformed logistic regression and random forest approaches. We use a recently developed RNA-seq-based convolutional neural network, TULIP, to test the robustness of a human-data-trained primary tumor classification tool on cross-species primary tumor prediction. Our study ultimately highlights the molecular similarities between canine and human BLCA and glioma tumors, showing that protein-coding one-to-one homologs shared between humans and canines, are sufficient to distinguish between BLCA and gliomas.DiscussionThe results of this study indicate that using protein-coding one-to-one homologs as the features in the input layer of TULIP performs good primary tumor prediction in both humans and canines. Furthermore, our analysis shows that our selected features also contain the majority of features with known clinical relevance in BLCA and gliomas. Our success in using a human-data-trained model for cross-species primary tumor prediction also sheds light on the conservation of oncological pathways in humans and canines, further underscoring the importance of the canine model system in the study of human disease.</p

Lansoprazole interferes with fungal respiration and acts synergistically with amphotericin B against multidrug-resistant <i>Candida auris</i>

Candida auris has emerged as a problematic fungal pathogen associated with high morbidity and mortality. Amphotericin B (AmB) is the most effective antifungal used to treat invasive fungal candidiasis, with resistance rarely observed among clinical isolates. However, C. auris possesses extraordinary resistant profiles against all available antifungal drugs, including AmB. In our pursuit of potential solutions, we screened a panel of 727 FDA-approved drugs. We identified the proton pump inhibitor lansoprazole (LNP) as a potent enhancer of AmB’s activity against C. auris. LNP also potentiates the antifungal activity of AmB against other medically important species of Candida and Cryptococcus. Our investigations into the mechanism of action unveiled that LNP metabolite(s) interact with a crucial target in the mitochondrial respiratory chain (complex III, known as cytochrome bc1). This interaction increases oxidative stress within fungal cells. Our results demonstrated the critical role of an active respiratory function in the antifungal activity of LNP. Most importantly, LNP restored the efficacy of AmB in an immunocompromised mouse model, resulting in a 1.7-log (∼98%) CFU reduction in the burden of C. auris in the kidneys. Our findings strongly advocate for a comprehensive evaluation of LNP as a cytochrome bc1 inhibitor for combating drug-resistant C. auris infections.</p