The microRNA-183/96/182 cluster inhibits lung cancer progression and metastasis by inducing an interleukin-2-mediated antitumor CD8+ cytotoxic T-cell response.

One of the mechanisms by which cancer cells acquire hyperinvasive and migratory properties with progressive loss of epithelial markers is the epithelial-to-mesenchymal transition (EMT). We have previously reported that in different cancer types, including nonsmall cell lung cancer (NSCLC), the microRNA-183/96/182 cluster (m96cl) is highly repressed in cells that have undergone EMT. In the present study, we used a novel conditional m96cl mouse to establish that loss of m96cl accelerated the growth of Kras mutant autochthonous lung adenocarcinomas. In contrast, ectopic expression of the m96cl in NSCLC cells results in a robust suppression of migration and invasion in vitro, and tumor growth and metastasis in vivo. Detailed immune profiling of the tumors revealed a significant enrichment of activated CD8+ cytotoxic T lymphocytes (CD8+ CTLs) in m96cl-expressing tumors, and m96cl-mediated suppression of tumor growth and metastasis was CD8+ CTL-dependent. Using coculture assays with naïve immune cells, we show that m96cl expression drives paracrine stimulation of CD8+ CTL proliferation and function. Using tumor microenvironment-associated gene expression profiling, we identified that m96cl elevates the interleukin-2 (IL2) signaling pathway and results in increased IL2-mediated paracrine stimulation of CD8+ CTLs. Furthermore, we identified that the m96cl modulates the expression of IL2 in cancer cells by regulating the expression of transcriptional repressors Foxf2 and Zeb1, and thereby alters the levels of secreted IL2 in the tumor microenvironment. Last, we show that in vivo depletion of IL2 abrogates m96cl-mediated activation of CD8+ CTLs and results in loss of metastatic suppression. Therefore, we have identified a novel mechanistic role of the m96cl in the suppression of lung cancer growth and metastasis by inducing an IL2-mediated systemic CD8+ CTL immune response.

Structure-based classification predicts drug response in EGFR-mutant NSCLC.

Epidermal growth factor receptor (EGFR) mutations typically occur in exons 18-21 and are established driver mutations in non-small cell lung cancer (NSCLC)1-3. Targeted therapies are approved for patients with 'classical' mutations and a small number of other mutations4-6. However, effective therapies have not been identified for additional EGFR mutations. Furthermore, the frequency and effects of atypical EGFR mutations on drug sensitivity are unknown1,3,7-10. Here we characterize the mutational landscape in 16,715 patients with EGFR-mutant NSCLC, and establish the structure-function relationship of EGFR mutations on drug sensitivity. We found that EGFR mutations can be separated into four distinct subgroups on the basis of sensitivity and structural changes that retrospectively predict patient outcomes following treatment with EGFR inhibitors better than traditional exon-based groups. Together, these data delineate a structure-based approach for defining functional groups of EGFR mutations that can effectively guide treatment and clinical trial choices for patients with EGFR-mutant NSCLC and suggest that a structure-function-based approach may improve the prediction of drug sensitivity to targeted therapies in oncogenes with diverse mutations.

PancanQTLv2.0: a comprehensive resource for expression quantitative trait loci across human cancers.

Expression quantitative trait locus (eQTL) analysis is a powerful tool used to investigate genetic variations in complex diseases, including cancer. We previously developed a comprehensive database, PancanQTL, to characterize cancer eQTLs using The Cancer Genome Atlas (TCGA) dataset, and linked eQTLs with patient survival and GWAS risk variants. Here, we present an updated version, PancanQTLv2.0 (https://hanlaboratory.com/PancanQTLv2/), with advancements in fine-mapping causal variants for eQTLs, updating eQTLs overlapping with GWAS linkage disequilibrium regions and identifying eQTLs associated with drug response and immune infiltration. Through fine-mapping analysis, we identified 58 747 fine-mapped eQTLs credible sets, providing mechanic insights of gene regulation in cancer. We further integrated the latest GWAS Catalog and identified a total of 84 592 135 linkage associations between eQTLs and the existing GWAS loci, which represents a remarkable ∼50-fold increase compared to the previous version. Additionally, PancanQTLv2.0 uncovered 659516 associations between eQTLs and drug response and identified 146948 associations between eQTLs and immune cell abundance, providing potentially clinical utility of eQTLs in cancer therapy. PancanQTLv2.0 expanded the resources available for investigating gene expression regulation in human cancers, leading to advancements in cancer research and precision oncology.

GPEdit: the genetic and pharmacogenomic landscape of A-to-I RNA editing in cancers.

Altered A-to-I RNA editing has been widely observed in many human cancers and some editing sites are associated with drug sensitivity, implicating its therapeutic potential. Increasing evidence has demonstrated that a quantitative trait loci mapping approach is effective to understanding the genetic basis of RNA editing. We systematically performed RNA editing quantitative trait loci (edQTL) analysis in 33 human cancer types for >10 000 cancer samples and identified 320 029 edQTLs. We also identified 1688 ed-QTLs associated with patient overall survival and 4672 ed-QTLs associated with GWAS risk loci. Furthermore, we demonstrated the associations between RNA editing and >1000 anti-cancer drug response with ∼3.5 million significant associations. We developed GPEdit (https://hanlab.uth.edu/GPEdit/) to facilitate a global map of the genetic and pharmacogenomic landscape of RNA editing. GPEdit is a user-friendly and comprehensive database that provides an opportunity for a better understanding of the genetic impact and the effects on drug response of RNA editing in cancers.

INO80 governs superenhancer-mediated oncogenic transcription and tumor growth in melanoma.

Superenhancers (SEs) are large genomic regions with a high density of enhancer marks. In cancer, SEs are found near oncogenes and dictate cancer gene expression. However, how oncogenic SEs are regulated remains poorly understood. Here, we show that INO80, a chromatin remodeling complex, is required for SE-mediated oncogenic transcription and tumor growth in melanoma. The expression of Ino80, the SWI/SNF ATPase, is elevated in melanoma cells and patient melanomas compared with normal melanocytes and benign nevi. Furthermore, Ino80 silencing selectively inhibits melanoma cell proliferation, anchorage-independent growth, tumorigenesis, and tumor maintenance in mouse xenografts. Mechanistically, Ino80 occupies >90% of SEs, and its occupancy is dependent on transcription factors such as MITF and Sox9. Ino80 binding reduces nucleosome occupancy and facilitates Mediator recruitment, thus promoting oncogenic transcription. Consistently, genes co-occupied by Ino80 and Med1 are selectively expressed in melanomas compared with melanocytes. Together, our results reveal an essential role of INO80-dependent chromatin remodeling in SE function and suggest a novel strategy for disrupting SEs in cancer treatment.

A Multi-Omics Perspective of Quantitative Trait Loci in Precision Medicine.

Quantitative trait loci (QTL) analysis is an important approach to investigate the effects of genetic variants identified through an increasing number of large-scale, multidimensional 'omics data sets. In this 'big data' era, the research community has identified a significant number of molecular QTLs (molQTLs) and increased our understanding of their effects. Herein, we review multiple categories of molQTLs, including those associated with transcriptome, post-transcriptional regulation, epigenetics, proteomics, metabolomics, and the microbiome. We summarize approaches to identify molQTLs and to infer their causal effects. We further discuss the integrative analysis of molQTLs through a multi-omics perspective. Our review highlights future opportunities to better understand the functional significance of genetic variants and to utilize the discovery of molQTLs in precision medicine.

Adverse events associated with potential drugs for COVID-19: a case study from real-world data.

The coronavirus disease 2019 (COVID-19) has resulted as a global pandemic. The World Health Organization announced the most promising drugs in SOLIDARITY for the global trial, and several other drugs are under investigation through ongoing clinical trials to prove the effectiveness and safety of potential therapeutics. Here, we depicted the safety profile of these drugs and investigated their associated adverse events (AEs). We observed the associated AEs in different organs/systems, especially in skin and subcutaneous tissue, immune system and musculoskeletal and connective tissue. Furthermore, we observed strong bias of AEs in different groups of sex and age. Our study provides knowledge of the toxicity of potential COVID-19 drugs. While these drugs hold promise to fight the global pandemic, healthcare providers should pay attention to AEs to maximize the treatment benefit while minimizing toxicity.

HeRA: an atlas of enhancer RNAs across human tissues.

Enhancer RNA (eRNA) is a type of long non-coding RNA transcribed from DNA enhancer regions. Despite critical roles of eRNA in gene regulation, the expression landscape of eRNAs in normal human tissue remains unexplored. Using numerous samples from the Genotype-Tissue Expression project, we characterized 45 411 detectable eRNAs and identified tens of thousands of associations between eRNAs and traits, including gender, race, and age. We constructed a co-expression network to identify millions of putative eRNA regulators and target genes across different tissues. We further constructed a user-friendly data portal, Human enhancer RNA Atlas (HeRA, https://hanlab.uth.edu/HeRA/). In HeRA, users can search, browse, and download the eRNA expression profile, trait-related eRNAs, and eRNA co-expression network by searching the eRNA ID, gene symbol, and genomic region in one or multiple tissues. HeRA is the first data portal to characterize eRNAs from 9577 samples across 54 human tissues and facilitates functional and mechanistic investigations of eRNAs.

APAatlas: decoding alternative polyadenylation across human tissues.

Alternative polyadenylation (APA) is an RNA-processing mechanism on the 3' terminus that generates distinct isoforms of mRNAs and/or other RNA polymerase II transcripts with different 3'UTR lengths. Widespread APA affects post-transcriptional gene regulation in mRNA translation, stability, and localization, and exhibits strong tissue specificity. However, no existing database provides comprehensive information about APA events in a large number of human normal tissues. Using the RNA-seq data from the Genotype-Tissue Expression project, we systematically identified APA events from 9475 samples across 53 human tissues and examined their associations with multiple traits and gene expression across tissues. We further developed APAatlas, a user-friendly database (https://hanlab.uth.edu/apa/) for searching, browsing and downloading related information. APAatlas will help the biomedical research community elucidate the functions and mechanisms of APA events in human tissues.

CD73 expression defines immune, molecular, and clinicopathological subgroups of lung adenocarcinoma.

INTRODUCTION: CD73 is a membrane-bound enzyme crucial in adenosine generation. The adenosinergic pathway plays a critical role in immunosuppression and in anti-tumor effects of immune checkpoint inhibitors (ICI). Here, we interrogated CD73 expression in a richly annotated cohort of human lung adenocarcinoma (LUAD) and its association with clinicopathological, immune, and molecular features to better understand the role of this immune marker in LUAD pathobiology. MATERIALS AND METHODS: Protein expression of CD73 was evaluated by immunohistochemistry in 106 archived LUADs from patients that underwent surgical treatment without neoadjuvant therapy. Total CD73 (T +) was calculated as the average of luminal (L +) and basolateral (BL +) percentage membrane expression scores for each LUAD and was used to classify tumors into three groups based on the extent of T CD73 expression (high, low, and negative). RESULTS: CD73 expression was significantly and progressively increased across normal-appearing lung tissue, adenomatous atypical hyperplasia, adenocarcinoma in situ, minimally invasive adenocarcinoma, and LUAD. In LUAD, BL CD73 expression was associated with an increase in PD-L1 expression in tumor cells and increase of tumor-associated immune cells. Stratification of LUADs based on T CD73 extent also revealed that tumors with high expression of this enzyme overall exhibited significantly elevated immune infiltration and PD-L1 protein expression. Immune profiling demonstrated that T-cell inflammation and adenosine signatures were significantly higher in CD73-expressing lung adenocarcinomas relative to those lacking CD73. CONCLUSION: Our study suggests that higher CD73 expression is associated with an overall augmented host immune response, suggesting potential implications in the immune pathobiology of early stage lung adenocarcinoma. Our findings warrant further studies to explore the role of CD73 in immunotherapeutic response of LUAD.

Pancan-meQTL: a database to systematically evaluate the effects of genetic variants on methylation in human cancer.

DNA methylation is an important epigenetic mechanism for regulating gene expression. Aberrant DNA methylation has been observed in various human diseases, including cancer. Single-nucleotide polymorphisms can contribute to tumor initiation, progression and prognosis by influencing DNA methylation, and DNA methylation quantitative trait loci (meQTL) have been identified in physiological and pathological contexts. However, no database has been developed to systematically analyze meQTLs across multiple cancer types. Here, we present Pancan-meQTL, a database to comprehensively provide meQTLs across 23 cancer types from The Cancer Genome Atlas by integrating genome-wide genotype and DNA methylation data. In total, we identified 8 028 964 cis-meQTLs and 965 050 trans-meQTLs. Among these, 23 432 meQTLs are associated with patient overall survival times. Furthermore, we identified 2 214 458 meQTLs that overlap with known loci identified through genome-wide association studies. Pancan-meQTL provides a user-friendly web interface (http://bioinfo.life.hust.edu.cn/Pancan-meQTL/) that is convenient for browsing, searching and downloading data of interest. This database is a valuable resource for investigating the roles of genetics and epigenetics in cancer.

The genetic and pharmacogenomic landscape of snoRNAs in human cancer.

Emerging evidence has revealed significant roles for small nucleolar RNAs (snoRNAs) in tumorigenesis. However, the genetic and pharmacogenomic landscape of snoRNAs has not been characterized. Using the genotype and snoRNA expression data from The Cancer Genome Atlas, we characterized the effects of genetic variants on snoRNAs across 29 cancer types and further linked related alleles with patient survival as well as genome-wide association study risk loci. Furthermore, we characterized the impact of snoRNA expression on drug response in patients to facilitate the clinical utility of snoRNAs in cancer. We also developed a user-friendly data resource, GPSno (http://hanlab.uth.edu/GPSno), with multiple modules for researchers to visualize, browse, and download multi-dimensional data. Our study provides a comprehensive genetic and pharmacogenomic landscape of snoRNAs, which will shed light on future clinical considerations for the development of snoRNA-based targeted therapies.

CircView: a visualization and exploration tool for circular RNAs.

Circular RNAs (circRNAs) are novel rising stars of noncoding RNAs, which are highly abundant and evolutionarily conserved across species. Number of publications related to circRNAs increased sharply in recent years, representing emerging focuses in the field. Therefore, tools, pipelines and databases have been developed to identify and store circRNAs. However, there is no existing tool to visualize and explore circRNAs. Therefore, we introduce CircView, a user-friendly visualization tool for circRNAs detected from existing tools. CircView enables users to visualize circRNAs and to quantify number of samples with detected circRNAs. CircView allows users to explore circRNAs detected by unique or multiple tools. Furthermore, CircView allows users to view the regulatory elements, such as microRNA response elements and RNA-binding protein binding sites. CircView is a unique tool to visualize and explore circRNAs, which helps users to better understand potential functions of circRNAs and design the functional experiments.

THO Complex-Dependent Posttranscriptional Control Contributes to Vascular Smooth Muscle Cell Fate Decision.

RATIONALE: Modulation of vascular smooth muscle cell (VSMC) phenotype plays a fundamental role in vascular development and diseases. Although extensive studies uncovered the roles of transcriptional regulation in VSMC-specific gene expression, how posttranscriptional regulation contributes to VSMC fate decisions remains to be determined. OBJECTIVE: To establish THO complex-dependent VSMC gene expression as a novel regulatory basis controlling VSMC phenotypes. METHODS AND RESULTS: Immunohistochemical staining against THOC2 and THOC5, 2 components of the THO complex, revealed a dramatic reduction in their expression in human arteries undergoing carotid endarterectomy compared with normal internal mammary arteries. Silencing of THOC2 or THOC5 led to dedifferentiation of VSMCs in vitro, characterized by decreased VSMC marker gene expression and increased migration and proliferation. Furthermore, RNA high-throughput sequencing (Seq) revealed that THOC5 silencing closely resembled the gene expression changes induced on PDGF (platelet-derived growth factor)-BB/PDGF-DD treatments in cultured VSMCs. Mechanistically, THOC2 and THOC5 physically interacted with and functionally relied on each other to bind to specific motifs on VSMC marker gene mRNAs. Interestingly, mRNAs that lost THOC2 or THOC5 binding during VSMC dedifferentiation were enriched for genes important for the differentiated VSMC phenotype. Last, THOC5 overexpression in injured rat carotid arteries significantly repressed loss of VSMC marker gene expression and neointima formation. CONCLUSIONS: Our data introduce dynamic binding of THO to VSMC marker gene mRNAs as a novel mechanism contributing to VSMC phenotypic switching and imply THOC5 as a potential intervention node for vascular diseases.

tRic: a user-friendly data portal to explore the expression landscape of tRNAs in human cancers.

Transfer RNAs (tRNAs) play critical roles in human cancer. Currently, no database provides the expression landscape and clinical relevance of tRNAs across a variety of human cancers. Utilizing miRNA-seq data from The Cancer Genome Atlas, we quantified the relative expression of tRNA genes and merged them into the codon level and amino level across 31 cancer types. The expression of tRNAs is associated with clinical features of patient smoking history and overall survival, and disease stage, subtype, and grade. We further analysed codon frequency and amino acid frequency for each protein coding gene and linked alterations of tRNA expression with protein translational efficiency. We include these data resources in a user-friendly data portal, tRic (tRNA in cancer, https://hanlab.uth.edu/tRic/ or http://bioinfo.life.hust.edu.cn/tRic/), which can be of significant interest to the research community.

PancanQTL: systematic identification of cis-eQTLs and trans-eQTLs in 33 cancer types.

Expression quantitative trait locus (eQTL) analysis, which links variations in gene expression to genotypes, is essential to understanding gene regulation and to interpreting disease-associated loci. Currently identified eQTLs are mainly in samples of blood and other normal tissues. However, no database comprehensively provides eQTLs in large number of cancer samples. Using the genotype and expression data of 9196 tumor samples in 33 cancer types from The Cancer Genome Atlas (TCGA), we identified 5 606 570 eQTL-gene pairs in the cis-eQTL analysis and 231 210 eQTL-gene pairs in the trans-eQTL analysis. We further performed survival analysis and identified 22 212 eQTLs associated with patient overall survival. Furthermore, we linked the eQTLs to genome-wide association studies (GWAS) data and identified 337 131 eQTLs that overlap with existing GWAS loci. We developed PancanQTL, a user-friendly database (http://bioinfo.life.hust.edu.cn/PancanQTL/), to store cis-eQTLs, trans-eQTLs, survival-associated eQTLs and GWAS-related eQTLs to enable searching, browsing and downloading. PancanQTL could help the research community understand the effects of inherited variants in tumorigenesis and development.

Single-cell reconstruction of differentiation trajectory reveals a critical role of ETS1 in human cardiac lineage commitment.

BACKGROUND: Cardiac differentiation from human pluripotent stem cells provides a unique opportunity to study human heart development in vitro and offers a potential cell source for cardiac regeneration. Compared to the large body of studies investigating cardiac maturation and cardiomyocyte subtype-specific induction, molecular events underlying cardiac lineage commitment from pluripotent stem cells at early stage remain poorly characterized. RESULTS: In order to uncover key molecular events and regulators controlling cardiac lineage commitment from a pluripotent state during differentiation, we performed single-cell RNA-Seq sequencing and obtained high-quality data for 6879 cells collected from 6 stages during cardiac differentiation from human embryonic stem cells and identified multiple cell subpopulations with distinct molecular features. Through constructing developmental trajectory of cardiac differentiation and putative ligand-receptor interactions, we revealed crosstalk between cardiac progenitor cells and endoderm cells, which could potentially provide a cellular microenvironment supporting cardiac lineage commitment at day 5. In addition, computational analyses of single-cell RNA-Seq data unveiled ETS1 (ETS Proto-Oncogene 1) activation as an important downstream event induced by crosstalk between cardiac progenitor cells and endoderm cells. Consistent with the findings from single-cell analysis, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) against ETS1 revealed genomic occupancy of ETS1 at cardiac structural genes at day 9 and day 14, whereas ETS1 depletion dramatically compromised cardiac differentiation. CONCLUSION: Together, our study not only characterized the molecular features of different cell types and identified ETS1 as a crucial factor induced by cell-cell crosstalk contributing to cardiac lineage commitment from a pluripotent state, but may also have important implications for understanding human heart development at early embryonic stage, as well as directed manipulation of cardiac differentiation in regenerative medicine.

LNCediting: a database for functional effects of RNA editing in lncRNAs.

RNA editing is a widespread post-transcriptional mechanism that can make a single base change on specific nucleotide sequence in an RNA transcript. RNA editing events can result in missense codon changes and modulation of alternative splicing in mRNA, and modification of regulatory RNAs and their binding sites in noncoding RNAs. Recent computational studies accurately detected more than 2 million A-to-I RNA editing sites from next-generation sequencing (NGS). However, the vast majority of these RNA editing sites have unknown functions and are in noncoding regions of the genome. To provide a useful resource for the functional effects of RNA editing in long noncoding RNAs (lncRNAs), we systematically analyzed the A-to-I editing sites in lncRNAs across human, rhesus, mouse, and fly, and observed an appreciable number of RNA editing sites which can significantly impact the secondary structures of lncRNAs and lncRNA-miRNA interactions. All the data were compiled into LNCediting, a user-friendly database (http://bioinfo.life.hust.edu.cn/LNCediting/). LNCediting provides customized tools to predict functional effects of novel editing sites in lncRNAs. We hope that it will become an important resource for exploring functions of RNA editing sites in lncRNAs.

Multiregion gene expression profiling reveals heterogeneity in molecular subtypes and immunotherapy response signatures in lung cancer.

Intra-tumor heterogeneity may be present at all molecular levels. Genomic intra-tumor heterogeneity at the exome level has been reported in many cancer types, but comprehensive gene expression intra-tumor heterogeneity has not been well studied. Here, we delineated the gene expression intra-tumor heterogeneity by exploring gene expression profiles of 35 tumor regions from 10 non-small cell lung cancer tumors (three or four regions/tumor), including adenocarcinoma, squamous cell carcinoma, large-cell carcinoma, and pleomorphic carcinoma of the lung. Using Affymetrix Gene 1.0 ST arrays, we generated the gene expression data for every sample. Inter-tumor heterogeneity was generally higher than intra-tumor heterogeneity, but some tumors showed a substantial level of intra-tumor heterogeneity. The analysis of various clinically relevant gene expression signatures including molecular subtype, epithelial-to-mesenchymal transition, and anti-PD-1 resistance signatures also revealed heterogeneity between different regions of the same tumor. The gene expression intra-tumor heterogeneity we observed was associated with heterogeneous tumor microenvironments represented by stromal and immune cells infiltrated. Our data suggest that RNA-based prognostic or predictive molecular tests should be carefully conducted in consideration of the gene expression intra-tumor heterogeneity.

Integrated MicroRNA-mRNA Profiling Identifies Oncostatin M as a Marker of Mesenchymal-Like ER-Negative/HER2-Negative Breast Cancer.

MicroRNAs (miRNAs) simultaneously modulate different oncogenic networks, establishing a dynamic system of gene expression and pathway regulation. In this study, we analyzed global miRNA and messenger RNA (mRNA) expression profiles of 17 cell lines representing different molecular breast cancer subtypes. Spearman's rank correlation test was used to evaluate the correlation between miRNA and mRNA expression. Hierarchical clustering and pathway analysis were also performed. Publicly available gene expression profiles (n = 699) and tumor tissues (n = 80) were analyzed to assess the relevance of key miRNA-regulated pathways in human breast cancer. We identified 39 significantly deregulated miRNAs, and the integration between miRNA and mRNA data revealed the importance of immune-related pathways, particularly the Oncostatin M (OSM) signaling, associated with mesenchymal-like breast cancer cells. OSM levels correlated with genes involved in the inflammatory response, epithelial-to-mesenchymal transition (EMT), and epidermal growth factor (EGF) signaling in human estrogen receptor (ER)-negative/human epidermal growth factor receptor 2 (HER2)-negative breast cancer. Our results suggest that the deregulation of specific miRNAs may cooperatively impair immune and EMT pathways. The identification of the OSM inflammatory pathway as an important mediator of EMT in triple-negative breast cancer (TNBC) may provide a novel potential opportunity to improve therapeutic strategies.