A systems biology approach uncovers novel disease mechanisms in age-related macular degeneration.

Age-related macular degeneration (AMD) is a leading cause of blindness, affecting 200 million people worldwide. To identify genes that could be targeted for treatment, we created a molecular atlas at different stages of AMD. Our resource is comprised of RNA sequencing (RNA-seq) and DNA methylation microarrays from bulk macular retinal pigment epithelium (RPE)/choroid of clinically phenotyped normal and AMD donor eyes (n = 85), single-nucleus RNA-seq (164,399 cells), and single-nucleus assay for transposase-accessible chromatin (ATAC)-seq (125,822 cells) from the retina, RPE, and choroid of 6 AMD and 7 control donors. We identified 23 genome-wide significant loci differentially methylated in AMD, over 1,000 differentially expressed genes across different disease stages, and an AMD Müller state distinct from normal or gliosis. Chromatin accessibility peaks in genome-wide association study (GWAS) loci revealed putative causal genes for AMD, including HTRA1 and C6orf223. Our systems biology approach uncovered molecular mechanisms underlying AMD, including regulators of WNT signaling, FRZB and TLE2, as mechanistic players in disease.

Enrichment of oral-derived bacteria in inflamed colorectal tumors and distinct associations of Fusobacterium in the mesenchymal subtype.

While the association between colorectal cancer (CRC) features and Fusobacterium has been extensively studied, less is known of other intratumoral bacteria. Here, we leverage whole transcriptomes from 807 CRC samples to dually characterize tumor gene expression and 74 intratumoral bacteria. Seventeen of these species, including 4 Fusobacterium spp., are classified as orally derived and are enriched among right-sided, microsatellite instability-high (MSI-H), and BRAF-mutant tumors. Across consensus molecular subtypes (CMSs), integration of Fusobacterium animalis (Fa) presence and tumor expression reveals that Fa has the most significant associations in mesenchymal CMS4 tumors despite a lower prevalence than in immune CMS1. Within CMS4, the prevalence of Fa is uniquely associated with collagen- and immune-related pathways. Additional Fa pangenome analysis reveals that stress response genes and the adhesion FadA are commonly expressed intratumorally. Overall, this study identifies oral-derived bacteria as enriched in inflamed tumors, and the associations of bacteria and tumor expression are context and species specific.

Tissue cryopreservation using the 3M™ Novec™ 7000 freezing coolant offers a comparable and safe alternative to customary coolants.

Cryopreserving tissues for histology requires the use of coolants to buffer the sample from liquid nitrogen (LN2) and to control the rate of temperature decline. Several coolants sharing similar physical characteristics are available on the market; however, commonly used coolants are variably flammable and/or toxic and pose risks to personnel and facilities. The purpose of this study was to compare the performance of three commercially available coolants: hexane, 2-methylbutane (2 M), and 1-methoxyheptafluoropropane (N7000). Fresh mouse tissues were frozen by each method, for their ability to preserve microscopic architecture and to protect RNA from degradation were evaluated and compared to tissue characteristics obtained by direct immersion in LN2. Our results show that for most tissues, the N7000 freezing coolant provides equal or improved preservation of microscopic architecture. While snap-freezing tissues in LN2 provides superior RNA protection, no significant differences in RNA quality were seen between tissues frozen in hexane, 2 M, and N7000.

Single-cell dissection of cellular components and interactions shaping the tumor immune phenotypes in ovarian cancer.

Distinct T cell infiltration patterns, i.e., immune infiltrated, excluded, and desert, result in different responses to cancer immunotherapies. However, the key determinants and biology underpinning these tumor immune phenotypes remain elusive. Here, we provide a high-resolution dissection of the entire tumor ecosystem through single-cell RNA-sequencing analysis of 15 ovarian tumors. Immune-desert tumors are characterized by unique tumor cell-intrinsic features, including metabolic pathways and low antigen presentation, and an enrichment of monocytes and immature macrophages. Immune-infiltrated and -excluded tumors differ markedly in their T cell composition and fibroblast subsets. Furthermore, our study reveals chemokine receptor-ligand interactions within and across compartments as potential mechanisms mediating immune cell infiltration, exemplified by the tumor cell-T cell cross talk via CXCL16-CXCR6 and stromal-immune cell cross talk via CXCL12/14-CXCR4. Our data highlight potential molecular mechanisms that shape the tumor immune phenotypes and may inform therapeutic strategies to improve clinical benefit from cancer immunotherapies.

Generalized Additive Mixed Modeling of Longitudinal Tumor Growth Reduces Bias and Improves Decision Making in Translational Oncology.

Scientists working in translational oncology regularly conduct multigroup studies of mice with serially measured tumors. Longitudinal data collected can feature mid-study dropouts and complex nonlinear temporal response patterns. Parametric statistical models such as ones assuming exponential growth are useful for summarizing tumor volume over ranges for which the growth model holds, with the advantage that the model's parameter estimates can be used to summarize between-group differences in tumor volume growth with statistical measures of uncertainty. However, these same assumed growth models are too rigid to recapitulate patterns observed in many experiments, which in turn diminishes the effectiveness of their parameter estimates as summary statistics. To address this problem, we generalized such models by adopting a nonparametric approach in which group-level response trends for logarithmically scaled tumor volume are estimated as regression splines in a generalized additive mixed model. We also describe a novel summary statistic for group level splines over user-defined, experimentally relevant time ranges. This statistic reduces to the log-linear growth rate for data well described by exponential growth and also has a sampling distribution across groups that is well approximated by a multivariate Gaussian, thus facilitating downstream analysis. Real-data examples show that this nonparametric approach not only enhances fidelity in describing nonlinear growth scenarios but also improves statistical power to detect interregimen differences when compared with the simple exponential model so that it generalizes the linear mixed effects paradigm for analysis of log-linear growth to nonlinear scenarios in a useful way. SIGNIFICANCE: This work generalizes the statistical linear mixed modeling paradigm for summarizing longitudinally measured preclinical tumor volume studies to encompass studies with nonlinear and nonmonotonic group response patterns in a statistically rigorous manner.

Risk stratification biomarkers for Staphylococcus aureus bacteraemia.

OBJECTIVES: To identify risk stratification biomarkers to enrich for the subset of Staphylococcus aureus bacteraemia patients who develop deep-seated tissue infections with high morbidity and mortality to guide clinical trial enrolment and clinical management. METHODS: We evaluated the prognostic value of eight biomarkers for persistent bacteraemia, mortality and endovascular infection foci in a validation cohort of 160 patients with S. aureus bacteraemia enrolled consecutively over 3 years. RESULTS: High levels of IL-17A, IL-10 or soluble E-selectin at bacteraemia diagnosis correlated with the duration of positive blood cultures. When thresholds defined in an independent cohort were applied, these biomarkers were robust predictors of persistent bacteraemia or endovascular infection. High serum levels of IL-17A and IL-10 often preceded the radiographic diagnosis of infective endocarditis, suggesting potential utility for prioritising diagnostic radiographic imaging. High IL-8 was prognostic for all-cause mortality, while IL-17A and IL-10 were superior to clinical metrics in discriminating between attributable mortality and non-attributable mortality. High IL-17A and IL-10 identified more patients who developed microbiological failure or mortality than were identified by infective endocarditis diagnosis. CONCLUSION: These biomarkers offer potential utility to identify patients at risk of persistent bacteraemia to guide diagnostic imaging and clinical management. Low biomarker levels could be used to rule out the need for more invasive TEE imaging in patients at lower risk of infective endocarditis. These biomarkers could enable clinical trials by enriching for patients with the greatest need for novel therapies.

A Prognostic Model of Persistent Bacteremia and Mortality in Complicated Staphylococcus aureus Bloodstream Infection.

BACKGROUND: Staphylococcus aureus is a leading cause of bacteremia, yet there remains a significant knowledge gap in the identification of relevant biomarkers that predict clinical outcomes. Heterogeneity in the host response to invasive S. aureus infection suggests that specific biomarker signatures could be utilized to differentiate patients prone to severe disease, thereby facilitating earlier implementation of more aggressive therapies. METHODS: To further elucidate the inflammatory correlates of poor clinical outcomes in patients with S. aureus bacteremia, we evaluated the association between a panel of blood proteins at initial presentation of bacteremia and disease severity outcomes using 2 cohorts of patients with S. aureus bacteremia (n = 32 and n = 124). RESULTS: We identified 13 candidate proteins that were correlated with mortality and persistent bacteremia. Prognostic modeling identified interleukin (IL)-8 and CCL2 as the strongest individual predictors of mortality, with the combination of these biomarkers classifying fatal outcome with 89% sensitivity and 77% specificity (P < .0001). Baseline IL-17A levels were elevated in patients with persistent bacteremia (P < .0001), endovascular (P = .026) and metastatic tissue infections (P = .012). CONCLUSIONS: These results demonstrate the potential utility of selected biomarkers to distinguish patients with the highest risk for treatment failure and bacteremia-related complications, providing a valuable tool for clinicians in the management of S. aureus bacteremia. Additionally, these biomarkers could identify patients with the greatest potential to benefit from novel therapies in clinical trials.

Germline genetic polymorphisms influence tumor gene expression and immune cell infiltration.

Cancer immunotherapy has emerged as an effective therapy in a variety of cancers. However, a key challenge in the field is that only a subset of patients who receive immunotherapy exhibit durable response. It has been hypothesized that host genetics influences the inherent immune profiles of patients and may underlie their differential response to immunotherapy. Herein, we systematically determined the association of common germline genetic variants with gene expression and immune cell infiltration of the tumor. We identified 64,094 expression quantitative trait loci (eQTLs) that associated with 18,210 genes (eGenes) across 24 human cancers. Overall, eGenes were enriched for their being involved in immune processes, suggesting that expression of immune genes can be shaped by hereditary genetic variants. We identified the endoplasmic reticulum aminopeptidase 2 (ERAP2) gene as a pan-cancer type eGene whose expression levels stratified overall survival in a subset of patients with bladder cancer receiving anti-PD-L1 (atezolizumab) therapy. Finally, we identified 103 gene signature QTLs (gsQTLs) that were associated with predicted immune cell abundance within the tumor microenvironment. Our findings highlight the impact of germline SNPs on cancer-immune phenotypes and response to therapy; and these analyses provide a resource for integration of germline genetics as a component of personalized cancer immunotherapy.

High-Throughput and Sensitive Quantification of Circulating Tumor DNA by Microfluidic-Based Multiplex PCR and Next-Generation Sequencing.

Circulating tumor DNA (ctDNA) has potential to serve as a biomarker for noninvasive monitoring of treatment response and disease progression. However, broad clinical applicability of ctDNA has been limited by the low sensitivity, throughput, and patient coverage offered by existing ctDNA detection methods. Herein, we report the adaptation and characterization of the microfluidics multiplex PCR sequencing technology for high-throughput and sensitive quantitation of ctDNA. A multiplex PCR preamplification step was developed and incorporated into the microfluidics multiplex PCR sequencing work flow to enable low-input ctDNA analysis with enhanced sensitivity. An empirical bayesian model was developed to characterize both position and substitution-associated system errors specific to this platform and provided a tailored approach to greatly enhance the confidence and accuracy of variant calling for ctDNA analysis. Clinical validation of this platform for ctDNA mutation detection demonstrated an overall sensitivity of 92% and specificity of 100% when using mutation calls in the matched tumor tissues as a benchmark. Finally, we established an early proof of concept of clinical utility of this ctDNA work flow for monitoring disease progression using clinical trial samples. Our novel ctDNA work flow provides a high-throughput and sensitive platform that can be implemented in clinical trials for mutation detection and disease monitoring from plasma ctDNA.

CCAT1 is an enhancer-templated RNA that predicts BET sensitivity in colorectal cancer.

Colon tumors arise in a stepwise fashion from either discrete genetic perturbations or epigenetic dysregulation. To uncover the key epigenetic regulators that drive colon cancer growth, we used a CRISPR loss-of-function screen and identified a number of essential genes, including the bromodomain and extraterminal (BET) protein BRD4. We found that BRD4 is critical for colon cancer proliferation, and its knockdown led to differentiation effects in vivo. JQ1, a BET inhibitor, preferentially reduced growth in a subset of epigenetically dysregulated colon cancers characterized by the CpG island methylator phenotype (CIMP). Integrated transcriptomic and genomic analyses defined a distinct superenhancer in CIMP+ colon cancers that regulates cMYC transcription. We found that the long noncoding RNA colon cancer-associated transcript 1 (CCAT1) is transcribed from this superenhancer and is exquisitely sensitive to BET inhibition. Concordantly, cMYC transcription and cell growth were tightly correlated with the presence of CCAT1 RNA in a variety of tumor types. Taken together, we propose that CCAT1 is a clinically tractable biomarker for identifying patients who are likely to benefit from BET inhibitors.

A comprehensive transcriptional portrait of human cancer cell lines.

Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic responses. Although substantial effort has been made to define the genomic constitution of cancer cell line panels, the transcriptome remains understudied. Here we describe RNA sequencing and single-nucleotide polymorphism (SNP) array analysis of 675 human cancer cell lines. We report comprehensive analyses of transcriptome features including gene expression, mutations, gene fusions and expression of non-human sequences. Of the 2,200 gene fusions catalogued, 1,435 consist of genes not previously found in fusions, providing many leads for further investigation. We combine multiple genome and transcriptome features in a pathway-based approach to enhance prediction of response to targeted therapeutics. Our results provide a valuable resource for studies that use cancer cell lines.

MBASED: allele-specific expression detection in cancer tissues and cell lines.

Allele-specific gene expression, ASE, is an important aspect of gene regulation. We developed a novel method MBASED, meta-analysis based allele-specific expression detection for ASE detection using RNA-seq data that aggregates information across multiple single nucleotide variation loci to obtain a gene-level measure of ASE, even when prior phasing information is unavailable. MBASED is capable of one-sample and two-sample analyses and performs well in simulations. We applied MBASED to a panel of cancer cell lines and paired tumor-normal tissue samples, and observed extensive ASE in cancer, but not normal, samples, mainly driven by genomic copy number alterations.

Diverse modes of genomic alteration in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a heterogeneous disease with high mortality rate. Recent genomic studies have identified TP53, AXIN1, and CTNNB1 as the most frequently mutated genes. Lower frequency mutations have been reported in ARID1A, ARID2 and JAK1. In addition, hepatitis B virus (HBV) integrations into the human genome have been associated with HCC. RESULTS: Here, we deep-sequence 42 HCC patients with a combination of whole genome, exome and transcriptome sequencing to identify the mutational landscape of HCC using a reasonably large discovery cohort. We find frequent mutations in TP53, CTNNB1 and AXIN1, and rare but likely functional mutations in BAP1 and IDH1. Besides frequent hepatitis B virus integrations at TERT, we identify translocations at the boundaries of TERT. A novel deletion is identified in CTNNB1 in a region that is heavily mutated in multiple cancers. We also find multiple high-allelic frequency mutations in the extracellular matrix protein LAMA2. Lower expression levels of LAMA2 correlate with a proliferative signature, and predict poor survival and higher chance of cancer recurrence in HCC patients, suggesting an important role of the extracellular matrix and cell adhesion in tumor progression of a subgroup of HCC patients. CONCLUSIONS: The heterogeneous disease of HCC features diverse modes of genomic alteration. In addition to common point mutations, structural variations and methylation changes, there are several virus-associated changes, including gene disruption or activation, formation of chimeric viral-human transcripts, and DNA copy number changes. Such a multitude of genomic events likely contributes to the heterogeneous nature of HCC.

Integrated exome and transcriptome sequencing reveals ZAK isoform usage in gastric cancer.

Gastric cancer is the second leading cause of worldwide cancer mortality, yet the underlying genomic alterations remain poorly understood. Here we perform exome and transcriptome sequencing and SNP array assays to characterize 51 primary gastric tumours and 32 cell lines. Meta-analysis of exome data and previously published data sets reveals 24 significantly mutated genes in microsatellite stable (MSS) tumours and 16 in microsatellite instable (MSI) tumours. Over half the patients in our collection could potentially benefit from targeted therapies. We identify 55 splice site mutations accompanied by aberrant splicing products, in addition to mutation-independent differential isoform usage in tumours. ZAK kinase isoform TV1 is preferentially upregulated in gastric tumours and cell lines relative to normal samples. This pattern is also observed in colorectal, bladder and breast cancers. Overexpression of this particular isoform activates multiple cancer-related transcription factor reporters, while depletion of ZAK in gastric cell lines inhibits proliferation. These results reveal the spectrum of genomic and transcriptomic alterations in gastric cancer, and identify isoform-specific oncogenic properties of ZAK.

Integrative analysis of two cell lines derived from a non-small-lung cancer patient--a panomics approach.

Cancer cells derived from different stages of tumor progression may exhibit distinct biological properties, as exemplified by the paired lung cancer cell lines H1993 and H2073. While H1993 was derived from chemo-naive metastasized tumor, H2073 originated from the chemo-resistant primary tumor from the same patient and exhibits strikingly different drug response profile. To understand the underlying genetic and epigenetic bases for their biological properties, we investigated these cells using a wide range of large-scale methods including whole genome sequencing, RNA sequencing, SNP array, DNA methylation array, and de novo genome assembly. We conducted an integrative analysis of both cell lines to distinguish between potential driver and passenger alterations. Although many genes are mutated in these cell lines, the combination of DNA- and RNA-based variant information strongly implicates a small number of genes including TP53 and STK11 as likely drivers. Likewise, we found a diverse set of genes differentially expressed between these cell lines, but only a fraction can be attributed to changes in DNA copy number or methylation. This set included the ABC transporter ABCC4, implicated in drug resistance, and the metastasis associated MET oncogene. While the rich data content allowed us to reduce the space of hypotheses that could explain most of the observed biological properties, we also caution there is a lack of statistical power and inherent limitations in such single patient case studies.

A quartet of PIF bHLH factors provides a transcriptionally centered signaling hub that regulates seedling morphogenesis through differential expression-patterning of shared target genes in Arabidopsis.

Dark-grown seedlings exhibit skotomorphogenic development. Genetic and molecular evidence indicates that a quartet of Arabidopsis Phytochrome (phy)-Interacting bHLH Factors (PIF1, 3, 4, and 5) are critically necessary to maintaining this developmental state and that light activation of phy induces a switch to photomorphogenic development by inducing rapid degradation of the PIFs. Here, using integrated ChIP-seq and RNA-seq analyses, we have identified genes that are direct targets of PIF3 transcriptional regulation, exerted by sequence-specific binding to G-box (CACGTG) or PBE-box (CACATG) motifs in the target promoters genome-wide. In addition, expression analysis of selected genes in this set, in all triple pif-mutant combinations, provides evidence that the PIF quartet members collaborate to generate an expression pattern that is the product of a mosaic of differential transcriptional responsiveness of individual genes to the different PIFs and of differential regulatory activity of individual PIFs toward the different genes. Together with prior evidence that all four PIFs can bind to G-boxes, the data suggest that this collective activity may be exerted via shared occupancy of binding sites in target promoters.

Genome-wide analysis of glucocorticoid receptor-binding sites in myotubes identifies gene networks modulating insulin signaling.

Glucocorticoids elicit a variety of biological responses in skeletal muscle, including inhibiting protein synthesis and insulin-stimulated glucose uptake and promoting proteolysis. Thus, excess or chronic glucocorticoid exposure leads to muscle atrophy and insulin resistance. Glucocorticoids propagate their signal mainly through glucocorticoid receptors (GR), which, upon binding to ligands, translocate to the nucleus and bind to genomic glucocorticoid response elements to regulate the transcription of nearby genes. Using a combination of chromatin immunoprecipitation sequencing and microarray analysis, we identified 173 genes in mouse C2C12 myotubes. The mouse genome contains GR-binding regions in or near these genes, and gene expression is regulated by glucocorticoids. Eight of these genes encode proteins known to regulate distinct signaling events in insulin/insulin-like growth factor 1 pathways. We found that overexpression of p85α, one of these eight genes, caused a decrease in C2C12 myotube diameters, mimicking the effect of glucocorticoids. Moreover, reducing p85α expression by RNA interference in C2C12 myotubes significantly compromised the ability of glucocorticoids to inhibit Akt and p70 S6 kinase activity and reduced glucocorticoid induction of insulin receptor substrate 1 phosphorylation at serine 307. This phosphorylation is associated with insulin resistance. Furthermore, decreasing p85α expression abolished glucocorticoid inhibition of protein synthesis and compromised glucocorticoid-induced reduction of cell diameters in C2C12 myotubes. Finally, a glucocorticoid response element was identified in the p85α GR-binding regions. In summary, our studies identified GR-regulated transcriptional networks in myotubes and showed that p85α plays a critical role in glucocorticoid-induced insulin resistance and muscle atrophy in C2C12 myotubes.

Genome-wide analysis of glucocorticoid receptor binding regions in adipocytes reveal gene network involved in triglyceride homeostasis.

Glucocorticoids play important roles in the regulation of distinct aspects of adipocyte biology. Excess glucocorticoids in adipocytes are associated with metabolic disorders, including central obesity, insulin resistance and dyslipidemia. To understand the mechanisms underlying the glucocorticoid action in adipocytes, we used chromatin immunoprecipitation sequencing to isolate genome-wide glucocorticoid receptor (GR) binding regions (GBRs) in 3T3-L1 adipocytes. Furthermore, gene expression analyses were used to identify genes that were regulated by glucocorticoids. Overall, 274 glucocorticoid-regulated genes contain or locate nearby GBR. We found that many GBRs were located in or nearby genes involved in triglyceride (TG) synthesis (Scd-1, 2, 3, GPAT3, GPAT4, Agpat2, Lpin1), lipolysis (Lipe, Mgll), lipid transport (Cd36, Lrp-1, Vldlr, Slc27a2) and storage (S3-12). Gene expression analysis showed that except for Scd-3, the other 13 genes were induced in mouse inguinal fat upon 4-day glucocorticoid treatment. Reporter gene assays showed that except Agpat2, the other 12 glucocorticoid-regulated genes contain at least one GBR that can mediate hormone response. In agreement with the fact that glucocorticoids activated genes in both TG biosynthetic and lipolytic pathways, we confirmed that 4-day glucocorticoid treatment increased TG synthesis and lipolysis concomitantly in inguinal fat. Notably, we found that 9 of these 12 genes were induced in transgenic mice that have constant elevated plasma glucocorticoid levels. These results suggested that a similar mechanism was used to regulate TG homeostasis during chronic glucocorticoid treatment. In summary, our studies have identified molecular components in a glucocorticoid-controlled gene network involved in the regulation of TG homeostasis in adipocytes. Understanding the regulation of this gene network should provide important insight for future therapeutic developments for metabolic diseases.

Estrogen receptor beta binds to and regulates three distinct classes of target genes.

Estrogen receptor beta (ERbeta) has potent antiproliferative and anti-inflammatory properties, suggesting that ERbeta-selective agonists might be a new class of therapeutic and chemopreventive agents. To understand how ERbeta regulates genes, we identified genes regulated by the unliganded and liganded forms of ERalpha and ERbeta in U2OS cells. Microarray data demonstrated that virtually no gene regulation occurred with unliganded ERalpha, whereas many genes were regulated by estradiol (E(2)). These results demonstrated that ERalpha requires a ligand to regulate a single class of genes. In contrast, ERbeta regulated three classes of genes. Class I genes were regulated primarily by unliganded ERbeta. Class II genes were regulated only with E(2), whereas class III genes were regulated by both unliganded ERbeta and E(2). There were 453 class I genes, 258 class II genes, and 83 class III genes. To explore the mechanism whereby ERbeta regulates different classes of genes, chromatin immunoprecipitation-sequencing was performed to identify ERbeta binding sites and adjacent transcription factor motifs in regulated genes. AP1 binding sites were more enriched in class I genes, whereas ERE, NFkappaB1, and SP1 sites were more enriched in class II genes. ERbeta bound to all three classes of genes, demonstrating that ERbeta binding is not responsible for differential regulation of genes by unliganded and liganded ERbeta. The coactivator NCOA2 was differentially recruited to several target genes. Our findings indicate that the unliganded and liganded forms of ERbeta regulate three classes of genes by interacting with different transcription factors and coactivators.