Publications

Nucleic acids are a class of drugs that can modulate gene and protein expression by various mechanisms, namely, RNAi, mRNA degradation by RNase H cleavage, splice modulation, and steric blocking of protein binding or mRNA translation, thus exhibiting immense potential to treat various genetic and rare diseases. Unlike protein-targeted therapeutics, the clinical use of nucleic acids relies on Watson-Crick sequence recognition to regulate aberrant gene expression and impede protein translation. Though promising, targeted delivery remains a bottleneck for the clinical adoption of nucleic acid-based therapeutics. To overcome the delivery challenges associated with nucleic acids, various chemical modifications and bioconjugation-based delivery strategies have been explored. Currently, liver targeting by N-acetyl galactosamine (GalNAc) conjugation has been at the forefront for the treatment of rare and various metabolic diseases, which has led to FDA approval of four nucleic acid drugs. In addition, various other bioconjugation strategies have been explored to facilitate active organ and cell-enriched targeting. This review briefly covers the different classes of nucleic acids, their mechanisms of action, and their challenges. We also elaborate on recent advances in bioconjugation strategies in developing a diverse set of ligands for targeted delivery of nucleic acid drugs.

MicroRNAs (miRNAs) have been implicated in human disorders, from cancers to infectious diseases. Targeting miRNAs or their target genes with small molecules offers opportunities to modulate dysregulated cellular processes linked to diseases. Yet, predicting small molecules associated with miRNAs remains challenging due to the small size of small molecule-miRNA datasets. Herein, we develop a generalized deep learning framework, sChemNET, for predicting small molecules affecting miRNA bioactivity based on chemical structure and sequence information. sChemNET overcomes the limitation of sparse chemical information by an objective function that allows the neural network to learn chemical space from a large body of chemical structures yet unknown to affect miRNAs. We experimentally validated small molecules predicted to act on miR-451 or its targets and tested their role in erythrocyte maturation during zebrafish embryogenesis. We also tested small molecules targeting the miR-181 network and other miRNAs using in-vitro and in-vivo experiments. We demonstrate that our machine-learning framework can predict bioactive small molecules targeting miRNAs or their targets in humans and other mammalian organisms.

The tumor microenvironment (TME) is a heterogeneous ecosystem containing cancer cells, immune cells, stromal cells, cytokines, and chemokines which together govern tumor progression and response to immunotherapies. Methyltransferase-like 3 (METTL3), a core catalytic subunit for RNA N6-methyladenosine (m6A) modification, plays a crucial role in regulating various physiological and pathological processes. Whether and how METTL3 regulates the TME and anti-tumor immunity in non-small-cell lung cancer (NSCLC) remain poorly understood. Here, we report that METTL3 elevates expression of pro-tumorigenic chemokines including CXCL1, CXCL5, and CCL20, and destabilizes PD-L1 mRNA in an m6A-dependent manner, thereby shaping a non-inflamed TME. Thus, inhibiting METTL3 reprograms a more inflamed TME that renders anti-PD-1 therapy more effective in several murine lung tumor models. Clinically, NSCLC patients who exhibit low-METTL3 expression have a better prognosis when receiving anti-PD-1 therapy. Collectively, our study highlights targeting METTL3 as a promising strategy to improve immunotherapy in NSCLC patients.

Severe COVID-19 leads to widespread transcriptomic changes in the human brain, mimicking diminished cognitive performance. As long noncoding RNAs (lncRNAs) play crucial roles in the regulation of gene expression, identification of the lncRNAs differentially expressed upon COVID-19 may nominate key regulatory nodes underpinning cognitive changes. Here we identify hundreds of lncRNAs differentially expressed in the brains of COVID-19 patients relative to uninfected age/sex-matched controls, many of which are associated with decreased cognitive performance and inflammatory cytokine response. Our analyses reveal pervasive transcriptomic changes in lncRNA expression upon severe COVID-19, which may serve as key regulators of neurocognitive changes in the brain.

The landscape of non-coding mutations in cancer progression and immune evasion is largely unexplored. Here, we identify transcrptome-wide somatic and germline 3' untranslated region (3'-UTR) variants from 375 gastric cancer patients from The Cancer Genome Atlas. By performing gene expression quantitative trait loci (eQTL) and immune landscape QTL (ilQTL) analysis, we discover 3'-UTR variants with cis effects on expression and immune landscape phenotypes, such as immune cell infiltration and T cell receptor diversity. Using a massively parallel reporter assay, we distinguish between causal and correlative effects of 3'-UTR eQTLs in immune-related genes. Our approach identifies numerous 3'-UTR eQTLs and ilQTLs, providing a unique resource for the identification of immunotherapeutic targets and biomarkers. A prioritized ilQTL variant signature predicts response to immunotherapy better than standard-of-care PD-L1 expression in independent patient cohorts, showcasing the untapped potential of non-coding mutations in cancer.

Interactions between tumor and stromal cells are well known to play a prominent roles in progression of pancreatic ductal adenocarcinoma (PDAC). As knowledge of stromal crosstalk in PDAC has evolved, it has become clear that cancer associated fibroblasts can play both tumor promoting and tumor suppressive roles through a combination of paracrine crosstalk and juxtacrine interactions involving direct physical contact. Another major contributor to dismal survival statistics for PDAC is development of resistance to chemotherapy drugs. Though less is known about how the acquisition of chemoresistance impacts upon tumor-stromal crosstalk. Here, we use 3D co-culture geometries to recapitulate juxtacrine interactions between epithelial and stromal cells. In particular, extracellular matrix (ECM) overlay cultures in which stromal cells (pancreatic stellate cells, or normal human fibroblasts) are placed adjacent to PDAC cells (PANC1), result in direct heterotypic cell adhesions accompanied by dramatic fibroblast contractility which leads to highly condensed macroscopic multicellular aggregates as detected using particle image velocimetry (PIV) analysis to quantify cell velocities over the course of time lapse movie sequences. To investigate how drug resistance impacts these juxtacrine interactions we contrast cultures in which PANC1 are substituted with a drug resistant subline (PANC1-OR) previously established in our lab. We find that heterotypic cell-cell interactions are highly suppressed in drug-resistant cells relative to the parental PANC1 cells. To investigate further we conduct RNA-seq and bioinformatics analysis to identify differential gene expression in PANC1 and PANC1-OR, which shows that negative regulation of cell adhesion molecules, consistent with increased epithelial mesenchymal transition (EMT), is also consistent with loss of hetrotypic cell-cell contact necessary for the contractile behavior observed in drug naïve cultures. Overall these findings elucidate the role of drug-resistance in inhibiting an avenue of stromal crosstalk which is associated with tumor suppression and also help to establish cell culture conditions useful for further mechanistic investigation.

MicroRNAs (miRNAs) are small RNAs that are often dysregulated in many diseases, including cancers. They are highly tissue-specific and stable, thus, making them particularly useful as biomarkers. As the spatial transcriptomics field advances, protocols that enable highly sensitive and spatially resolved detection become necessary to maximize the information gained from samples. This is especially true of miRNAs where the location their expression within tissue can provide prognostic value with regard to patient outcome. Equally as important as detection are ways to assess and visualize the miRNA's spatial information in order to leverage the power of spatial transcriptomics over that of traditional nonspatial bulk assays. We present a highly sensitive methodology that simultaneously quantitates and spatially detects seven miRNAs in situ on formalin-fixed paraffin-embedded tissue sections. This method utilizes rolling circle amplification (RCA) in conjunction with a dual scanning approach in nanoliter well arrays with embedded hydrogel posts. The hydrogel posts are functionalized with DNA probes that enable the detection of miRNAs across a large dynamic range (4 orders of magnitude) and a limit of detection of 0.17 zeptomoles (1.7 × 10-4 attomoles). We applied our methodology coupled with a data analysis pipeline to K14-Cre Brca1f/fTp53f/f murine breast tumors to showcase the information gained from this approach.

Interactions between tumor and stromal cells are well known to play prominent roles in progression of pancreatic ductal adenocarcinoma (PDAC). As knowledge of stromal crosstalk in PDAC has evolved, it has become clear that cancer associated fibroblasts can play both tumor promoting and tumor suppressive roles through a combination of paracrine crosstalk and juxtacrine interactions involving direct physical contact. Another major contributor to dismal survival statistics for PDAC is development of resistance to chemotherapy drugs, though less is known about how the acquisition of chemoresistance impacts upon tumor-stromal crosstalk. Here, we use time lapse imaging and image analysis to study how co-culture geometry impacts interactions between epithelial and stromal cells. We show that extracellular matrix (ECM) overlay cultures in which stromal cells (pancreatic stellate cells, or normal human fibroblasts) are placed adjacent to PDAC cells (PANC1) result in direct heterotypic cell adhesions accompanied by dramatic fibroblast contractility. We analyze these interactions in co-cultures using particle image velocimetry (PIV) analysis to quantify cell velocities over the course of time lapse movie sequences. We further contrast co-cultures of PANC1 with those containing a drug resistant subline (PANC1-OR) previously established in our lab and find that heterotypic cell-cell interactions are suppressed in the latter relative to the parental line. We use RNA-seq and bioinformatics analysis to identify differential gene expression in PANC1 and PANC1-OR, which shows that negative regulation of cell adhesion molecules, consistent with increased epithelial mesenchymal transition (EMT), is also correlated with reduction in the hetrotypic cell-cell contact necessary for the contractile behavior observed in drug naïve cultures. Overall these findings elucidate the role of drug-resistance in inhibiting an avenue of stromal crosstalk which is associated with tumor suppression and also help to establish cell culture conditions useful for further mechanistic investigation.

Aging is associated with decreased health span, and despite the recent advances made in understanding the mechanisms of aging, no antiaging drug has been approved for therapy. Therefore, strategies to promote a healthy life in aging are desirable. Previous work has shown that chronic treatment with extracellular vesicles (EVs) from young mice prolongs lifespan in old mice, but the mechanism of action of this effect on liver metabolism is not known. Here we investigated the role of treatment with EVs derived from young sedentary (EV-C) or exercised (EV-EX) mice in the metabolism of old mice and aimed to identify key youthful-associated microRNA (miRNA) cargos that could promote healthy liver function. We found that aged mice treated with either EV-C or EV-EX had higher insulin sensitivity, higher locomotor activity resulting in longer distance traveled in the cage, and a lower respiratory exchange ratio compared to mice treated with EVs from aged mice (EV-A). In the liver, treatment with young-derived EVs reduced aging-induced liver fibrosis. We identified miR-30c in the EVs as a possible youth-associated miRNA as its level was higher in circulating EVs of young mice. Treatment of aged mice with EVs transfected with miR-30c mimic reduced stellate cell activation in the liver and reduced fibrosis compared to EV-negative control by targeting Foxo3. Our results suggest that by delivering juvenile EVs to old mice, we can improve their liver health. Moreover, we identified miR-30c as a candidate for antiaging liver therapy.

Liver disease, including hepatocellular carcinoma (HCC), is a major global health concern, claiming approximately 2 million lives worldwide annually, yet curative treatments remain elusive. In this study, we aimed to investigate the role of microRNA-21-5p (miR-21) in metabolic dysfunction-associated steatotic liver disease (previously NAFLD), metabolic-associated steatohepatitis (previously NASH), and HCC within the context of a Western high-fat diet, without additional choline (HFD) and offering potential therapeutic insights. We found that reduced miR-21 levels correlated with liver disease progression in WT mice fed on HFD, while miR-21 knockout mice showed exacerbated metabolic dysfunction, including obesity, hepatomegaly, hyperglycemia, insulin resistance, steatosis, fibrosis, and HCC. Our study reveals that miR-21 plays a protective role in metabolic syndrome and in the progression of liver disease to cancer. MiR-21 directly targets Transforming growth factor beta-induced (Tgfbi), a gene also known to be significantly upregulated and a potential oncogene in HCC. Further, our study showed that intervention with the administration of a miR-21 mimic in WT livers effectively improves insulin sensitivity, steatosis, fibrosis, Tgfbi expression and tumor burden in HFD conditions. These findings indicate that miR-21 could serve as an effective strategy to delay or prevent liver disease in high-fat-diet environments.