Pericyte phenotype switching alleviates immunosuppression and sensitizes vascularized tumors to immunotherapy in preclinical models.

T cell-based immunotherapies are a promising therapeutic approach for multiple malignancies, but their efficacy is limited by tumor hypoxia arising from dysfunctional blood vessels. Here, we report that cell-intrinsic properties of a single vascular component, namely the pericyte, contribute to the control of tumor oxygenation, macrophage polarization, vessel inflammation, and T cell infiltration. Switching pericyte phenotype from a synthetic to a differentiated state reverses immune suppression and sensitizes tumors to adoptive T cell therapy, leading to regression of melanoma in mice. In melanoma patients, improved survival is correlated with enhanced pericyte maturity. Importantly, pericyte plasticity is regulated by signaling pathways converging on Rho kinase activity, with pericyte maturity being inducible by selective low-dose therapeutics that suppress pericyte MEK, AKT, or notch signaling. We also show that low-dose targeted anticancer therapy can durably change the tumor microenvironment without inducing adaptive resistance, creating a highly translatable pathway for redosing anticancer targeted therapies in combination with immunotherapy to improve outcome.

A robust gene expression signature for NASH in liver expression data.

Non-Alcoholic Fatty Liver Disease (NAFLD) is a progressive liver disease that affects up to 30% of worldwide population, of which up to 25% progress to Non-Alcoholic SteatoHepatitis (NASH), a severe form of the disease that involves inflammation and predisposes the patient to liver cirrhosis. Despite its epidemic proportions, there is no reliable diagnostics that generalizes to global patient population for distinguishing NASH from NAFLD. We performed a comprehensive multicohort analysis of publicly available transcriptome data of liver biopsies from Healthy Controls (HC), NAFLD and NASH patients. Altogether we analyzed 812 samples from 12 different datasets across 7 countries, encompassing real world patient heterogeneity. We used 7 datasets for discovery and 5 datasets were held-out for independent validation. Altogether we identified 130 genes significantly differentially expressed in NASH versus a mixed group of NAFLD and HC. We show that our signature is not driven by one particular group (NAFLD or HC) and reflects true biological signal. Using a forward search we were able to downselect to a parsimonious set of 19 mRNA signature with mean AUROC of 0.98 in discovery and 0.79 in independent validation. Methods for consistent diagnosis of NASH relative to NAFLD are urgently needed. We showed that gene expression data combined with advanced statistical methodology holds the potential to serve basis for development of such diagnostic tests for the unmet clinical need.

A Multi-mRNA Prognostic Signature for Anti-TNFα Therapy Response in Patients with Inflammatory Bowel Disease.

BACKGROUND: Anti-TNF-alpha (anti-TNFα) therapies have transformed the care and management of inflammatory bowel disease (IBD). However, they are expensive and ineffective in greater than 50% of patients, and they increase the risk of infections, liver issues, arthritis, and lymphoma. With 1.6 million Americans suffering from IBD and global prevalence on the rise, there is a critical unmet need in the use of anti-TNFα therapies: a test for the likelihood of therapy response. Here, as a proof-of-concept, we present a multi-mRNA signature for predicting response to anti-TNFα treatment to improve the efficacy and cost-to-benefit ratio of these biologics. METHODS: We surveyed public data repositories and curated four transcriptomic datasets (n = 136) from colonic and ileal mucosal biopsies of IBD patients (pretreatment) who were subjected to anti-TNFα therapy and subsequently adjudicated for response. We applied a multicohort analysis with a leave-one-study-out (LOSO) approach, MetaIntegrator, to identify significant differentially expressed (DE) genes between responders and non-responders and then used a greedy forward search to identify a parsimonious gene signature. We then calculated an anti-TNFα response (ATR) score based on this parsimonious gene signature to predict responder status and assessed discriminatory performance via an area-under-receiver operating-characteristic curve (AUROC). RESULTS: We identified 324 significant DE genes between responders and non-responders. The greedy forward search yielded seven genes that robustly distinguish anti-TNFα responders from non-responders, with an AUROC of 0.88 (95% CI: 0.70-1). The Youden index yielded a mean sensitivity of 91%, mean specificity of 76%, and mean accuracy of 86%. CONCLUSIONS: Our findings suggest that there is a robust transcriptomic signature for predicting anti-TNFα response in mucosal biopsies from IBD patients prior to treatment initiation. This seven-gene signature should be further investigated for its potential to be translated into a predictive test for clinical use.

Transcriptomic similarities and differences in host response between SARS-CoV-2 and other viral infections.

The pandemic 2019 novel coronavirus disease (COVID-19) shares certain clinical characteristics with other acute viral infections. We studied the whole-blood transcriptomic host response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using RNAseq from 24 healthy controls and 62 prospectively enrolled patients with COVID-19. We then compared these data to non-COVID-19 viral infections, curated from 23 independent studies profiling 1,855 blood samples covering six viruses (influenza, respiratory syncytial virus (RSV), human rhinovirus (HRV), severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1), Ebola, dengue). We show gene expression changes in COVID-19 versus non-COVID-19 viral infections are highly correlated (r = 0.74, p < 0.001). However, we also found 416 genes specific to COVID-19. Inspection of top genes revealed dynamic immune evasion and counter host responses specific to COVID-19. Statistical deconvolution of cell proportions maps many cell type proportions concordantly shifting. Discordantly increased in COVID-19 were CD56bright natural killer cells and M2 macrophages. The concordant and discordant responses mapped out here provide a window to explore the pathophysiology of the host response to SARS-CoV-2.

Identification of novel ΔNp63α-regulated miRNAs using an optimized small RNA-Seq analysis pipeline.

Advances in high-throughput sequencing have enabled profiling of microRNAs (miRNAs), however, a consensus pipeline for sequencing of small RNAs has not been established. We built and optimized an analysis pipeline using Partek Flow, circumventing the need for analyzing data via scripting languages. Our analysis assessed the effect of alignment reference, normalization method, and statistical model choice on biological data. The pipeline was evaluated using sequencing data from HaCaT cells transfected with either a non-silencing control or siRNA against ΔNp63α, a p53 family member protein which is highly expressed in non-melanoma skin cancer and shown to regulate a number of miRNAs. We posit that 1) alignment and quantification to the miRBase reference provides the most robust quantitation of miRNAs, 2) normalizing sample reads via Trimmed Mean of M-values is the most robust method for accurate downstream analyses, and 3) use of the lognormal with shrinkage statistical model effectively identifies differentially expressed miRNAs. Using our pipeline, we identified previously unrecognized regulation of miRs-149-5p, 18a-5p, 19b-1-5p, 20a-5p, 590-5p, 744-5p and 93-5p by ΔNp63α. Regulation of these miRNAs was validated by RT-qPCR, substantiating our small RNA-Seq pipeline. Further analysis of these miRNAs may provide insight into ΔNp63α's role in cancer progression. By defining the optimal alignment reference, normalization method, and statistical model for analysis of miRNA sequencing data, we have established an analysis pipeline that may be carried out in Partek Flow or at the command line. In this manner, our pipeline circumvents some of the major hurdles encountered during small RNA-Seq analysis.

ΔNp63α and microRNAs: leveraging the epithelial-mesenchymal transition.

The epithelial-mesenchymal transition (EMT) is a cellular reprogramming mechanism that is an underlying cause of cancer metastasis. Recent investigations have uncovered an intricate network of regulation involving the TGFß, Wnt, and Notch signaling pathways and small regulatory RNA species called microRNAs (miRNAs). The activity of a transcription factor vital to the maintenance of epithelial stemness, ΔNp63α, has been shown to modulate the activity of these EMT pathways to either repress or promote EMT. Furthermore, ΔNp63α is a known regulator of miRNA, including those directly involved in EMT. This review discusses the evidence of ΔNp63α as a master regulator of EMT components and miRNA, highlighting the need for a deeper understanding of its role in EMT. This expanded knowledge may provide a basis for new developments in the diagnosis and treatment of metastatic cancer.

Modulation of miRNA-155 alters manganese nanoparticle-induced inflammatory response.

Regulation of gene expression by non-coding RNAs, such as microRNAs (miRNAs), is increasingly being examined in a variety of disciplines. Here we evaluated changes in miRNA expression following metallic nanoparticle (NP) exposure in a mouse neuronal co-culture model. Exposure to manganese (Mn) NPs resulted in oxidative stress, inflammation, and toxicity. Next-generation sequencing (NGS) following an 8 h exposure to Mn NPs (low and high doses) revealed several miRNA candidates that modulate NP induced responses. The lead candidate identified was miR-155, which showed a dose dependent decrease in expression upon Mn exposure. Introduction of a miR-155 mimic into the co-culture to restore miR-155 expression completely abrogated the Mn NP-induced gene and protein expression of inflammatory markers TNF-α and IL-6. Taken together, this study is the first report where global NP-induced miRNA expression changes were used to identify and then modulate negative impacts of metallic NP exposure in a neuronal model. These findings demonstrate that unique miRNA expression profiles provide novel targets for manipulating gene and protein expression, and therefore provide the potential of modifying cellular responses to NP exposure.