Identification of IGF2 as Genomic Driver and Actionable Therapeutic Target in Hepatoblastoma.

Management of hepatoblastoma (HB), the most frequent pediatric liver cancer, is based on surgical resection and perioperative chemotherapy regimens. In this study, we aimed to identify actionable targets in HB and assess the efficacy of molecular therapies in preclinical models of HB. Paired tumor and adjacent tissues from 31 HBs and a validation set of 50 HBs were analyzed using RNA-seq, SNP, and methylation arrays. IGF2 overexpression was identified as the top targetable HB driver, present in 71% of HBs (22/31). IGF2high tumors displayed progenitor cell features and shorter recurrence-free survival. IGF2 overexpression was associated in 91% of cases with fetal promoter hypomethylation, ICR1 deregulation, 11p15.5 loss of heterozygosity or miR483-5p overexpression. The antitumor effect of xentuzumab (a monoclonal antibody targeting IGF1/2) alone or in combination with the conventional therapeutic agent cisplatin was assessed in HB cell lines, in PDX-derived HB organoids and in a xenograft HB murine model. The combination of xentuzumab with cisplatin showed strong synergistic antitumor effects in organoids and in IGF2high cell lines. In mice (n = 55), the combination induced a significant decrease in tumor volume and improved survival compared with cisplatin alone. These results suggest that IGF2 is an HB actionable driver and that, in preclinical models of HB, the combination of IGF1/2 inhibition with cisplatin induces superior antitumor effects than cisplatin monotherapy. Overall, our study provides a rationale for testing IGF2 inhibitors in combination with cisplatin in HB patients with IGF2 overexpression.

A temporal classifier predicts histopathology state and parses acute-chronic phasing in inflammatory bowel disease patients.

Previous studies have conducted time course characterization of murine colitis models through transcriptional profiling of differential expression. We characterize the transcriptional landscape of acute and chronic models of dextran sodium sulfate (DSS) and adoptive transfer (AT) colitis to derive temporal gene expression and splicing signatures in blood and colonic tissue in order to capture dynamics of colitis remission and relapse. We identify sub networks of patient-derived causal networks that are enriched in these temporal signatures to distinguish acute and chronic disease components within the broader molecular landscape of IBD. The interaction between the DSS phenotype and chronological time-point naturally defines parsimonious temporal gene expression and splicing signatures associated with acute and chronic phases disease (as opposed to ordinary time-specific differential expression/splicing). We show these expression and splicing signatures are largely orthogonal, i.e. affect different genetic bodies, and that using machine learning, signatures are predictive of histopathological measures from both blood and intestinal data in murine colitis models as well as an independent cohort of IBD patients. Through access to longitudinal multi-scale profiling from disease tissue in IBD patient cohorts, we can apply this machine learning pipeline to generation of direct patient temporal multimodal regulatory signatures for prediction of histopathological outcomes.

Biopsy and blood-based molecular biomarker of inflammation in IBD.

OBJECTIVE: IBD therapies and treatments are evolving to deeper levels of remission. Molecular measures of disease may augment current endpoints including the potential for less invasive assessments. DESIGN: Transcriptome analysis on 712 endoscopically defined inflamed (Inf) and 1778 non-inflamed (Non-Inf) intestinal biopsies (n=498 Crohn's disease, n=421 UC and 243 controls) in the Mount Sinai Crohn's and Colitis Registry were used to identify genes differentially expressed between Inf and Non-Inf biopsies and to generate a molecular inflammation score (bMIS) via gene set variance analysis. A circulating MIS (cirMIS) score, reflecting intestinal molecular inflammation, was generated using blood transcriptome data. bMIS/cirMIS was validated as indicators of intestinal inflammation in four independent IBD cohorts. RESULTS: bMIS/cirMIS was strongly associated with clinical, endoscopic and histological disease activity indices. Patients with the same histologic score of inflammation had variable bMIS scores, indicating that bMIS describes a deeper range of inflammation. In available clinical trial data sets, both scores were responsive to IBD treatment. Despite similar baseline endoscopic and histologic activity, UC patients with lower baseline bMIS levels were more likely treatment responders compared with those with higher levels. Finally, among patients with UC in endoscopic and histologic remission, those with lower bMIS levels were less likely to have a disease flare over time. CONCLUSION: Transcriptionally based scores provide an alternative objective and deeper quantification of intestinal inflammation, which could augment current clinical assessments used for disease monitoring and have potential for predicting therapeutic response and patients at higher risk of disease flares.

Ulcerative colitis is characterized by a plasmablast-skewed humoral response associated with disease activity.

B cells, which are critical for intestinal homeostasis, remain understudied in ulcerative colitis (UC). In this study, we recruited three cohorts of patients with UC (primary cohort, n = 145; validation cohort 1, n = 664; and validation cohort 2, n = 143) to comprehensively define the landscape of B cells during UC-associated intestinal inflammation. Using single-cell RNA sequencing, single-cell IgH gene sequencing and protein-level validation, we mapped the compositional, transcriptional and clonotypic landscape of mucosal and circulating B cells. We found major perturbations within the mucosal B cell compartment, including an expansion of naive B cells and IgG+ plasma cells with curtailed diversity and maturation. Furthermore, we isolated an auto-reactive plasma cell clone targeting integrin αvß6 from inflamed UC intestines. We also identified a subset of intestinal CXCL13-expressing TFH-like T peripheral helper cells that were associated with the pathogenic B cell response. Finally, across all three cohorts, we confirmed that changes in intestinal humoral immunity are reflected in circulation by the expansion of gut-homing plasmablasts that correlates with disease activity and predicts disease complications. Our data demonstrate a highly dysregulated B cell response in UC and highlight a potential role of B cells in disease pathogenesis.

Digital-resolution and highly sensitive detection of multiple exosomal small RNAs by DNA toehold probe-based photonic resonator absorption microscopy.

Small noncoding RNAs (snRNA) have been emerging as promising diagnostic biomarkers for detecting early stage cancer. Currently existing methods for snRNA detection, including northern blot, reverse transcription-polymerase chain reaction, microarrays and RNA-Seq, are limited to time-consuming, low sensitivity, expensive instrumentation or complex analysis of data. Herein, we present a rapid quantitative analysis of multiple liver cancer-associated exosomal snRNA by a nucleic acid toehold probe-based photonic resonator absorption microscopy (PRAM) assay, with digital resolution and high sensitivity. The assay relies on the use of three toehold probe-encoded gold nanoparticles (AuNPs) and addressable photonic crystal (PC) sensing chips. The presence of target snRNA will initiate toehold-mediated strand displacement reactions that trigger the capture of gold particles onto the PC surface, which is subsequently imaged by PRAM for digital counting of detected snRNA molecules. We achieved highly sensitive and selective detection of three snRNA targets in buffer with a 30 min assay protocol, with detection limits of 4.56 fM, 4.68 fM and 0.69 pM. Having confirmed our assay's performance for detection of snRNA targets spiked into exosomal RNA extracts, we demonstrated its capability for quantitative detection of the same targets from patient blood plasma samples. The approach offers a rapid, simple workflow that operates at room temperature with a single step without enzymatic amplification, while the detection instrument can be implemented as a low-cost portable system for point of care environments.

Molecular Characterization of Limited Ulcerative Colitis Reveals Novel Biology and Predictors of Disease Extension.

BACKGROUND AND AIMS: Disease extent varies in ulcerative colitis (UC) from proctitis to left-sided colitis to pancolitis and is a major prognostic factor. When the extent of UC is limited there is often a sharp demarcation between macroscopically involved and uninvolved areas and what defines this or subsequent extension is unknown. We characterized the demarcation site molecularly and determined genes associated with subsequent disease extension. METHODS: We performed RNA sequence analysis of biopsy specimens from UC patients with endoscopically and histologically confirmed limited disease, of which a subset later extended. Biopsy specimens were obtained from the endoscopically inflamed upper (proximal) limit of disease, immediately adjacent to the uninvolved colon, as well as at more proximal, endoscopically uninflamed colonic segments. RESULTS: Differentially expressed genes were identified in the endoscopically inflamed biopsy specimens taken at each patient's most proximal diseased site relative to healthy controls. Expression of these genes in the more proximal biopsy specimens transitioned back to control levels abruptly or gradually, the latter pattern supporting the concept that disease exists beyond the endoscopic disease demarcation site. The gradually transitioning genes were associated with inflammation, angiogenesis, glucuronidation, and homeodomain pathways. A subset of these genes in inflamed biopsy specimens was found to predict disease extension better than clinical features and were responsive to biologic therapies. Network analysis revealed critical roles for interferon signaling in UC inflammation and poly(ADP-ribose) polymerase 14 (PARP14) was a predicted key driver gene of extension. Higher PARP14 protein levels were found in inflamed biopsy specimens of patients with limited UC that subsequently extended. CONCLUSION: Molecular predictors of disease extension reveal novel strategies for disease prognostication and potential therapeutic targeting.

Unannotated small RNA clusters associated with circulating extracellular vesicles detect early stage liver cancer.

OBJECTIVE: Surveillance tools for early cancer detection are suboptimal, including hepatocellular carcinoma (HCC), and biomarkers are urgently needed. Extracellular vesicles (EVs) have gained increasing scientific interest due to their involvement in tumour initiation and metastasis; however, most extracellular RNA (exRNA) blood-based biomarker studies are limited to annotated genomic regions. DESIGN: EVs were isolated with differential ultracentrifugation and integrated nanoscale deterministic lateral displacement arrays (nanoDLD) and quality assessed by electron microscopy, immunoblotting, nanoparticle tracking and deconvolution analysis. Genome-wide sequencing of the largely unexplored small exRNA landscape, including unannotated transcripts, identified and reproducibly quantified small RNA clusters (smRCs). Their key genomic features were delineated across biospecimens and EV isolation techniques in prostate cancer and HCC. Three independent exRNA cancer datasets with a total of 479 samples from 375 patients, including longitudinal samples, were used for this study. RESULTS: ExRNA smRCs were dominated by uncharacterised, unannotated small RNA with a consensus sequence of 20 nt. An unannotated 3-smRC signature was significantly overexpressed in plasma exRNA of patients with HCC (p<0.01, n=157). An independent validation in a phase 2 biomarker case-control study revealed 86% sensitivity and 91% specificity for the detection of early HCC from controls at risk (n=209) (area under the receiver operating curve (AUC): 0.87). The 3-smRC signature was independent of alpha-fetoprotein (p<0.0001) and a composite model yielded an increased AUC of 0.93. CONCLUSION: These findings directly lead to the prospect of a minimally invasive, blood-only, operator-independent clinical tool for HCC surveillance, thus highlighting the potential of unannotated smRCs for biomarker research in cancer.

Transcriptomic characterization of cancer-testis antigens identifies MAGEA3 as a driver of tumor progression in hepatocellular carcinoma.

Cancer testis antigens (CTAs) are an extensive gene family with a unique expression pattern restricted to germ cells, but aberrantly reactivated in cancer tissues. Studies indicate that the expression (or re-expression) of CTAs within the MAGE-A family is common in hepatocellular carcinoma (HCC). However, no systematic characterization has yet been reported. The aim of this study is to perform a comprehensive profile of CTA de-regulation in HCC and experimentally evaluate the role of MAGEA3 as a driver of HCC progression. The transcriptomic analysis of 44 multi-regionally sampled HCCs from 12 patients identified high intra-tumor heterogeneity of CTAs. In addition, a subset of CTAs was significantly overexpressed in histologically poorly differentiated regions. Further analysis of CTAs in larger patient cohorts revealed high CTA expression related to worse overall survival and several other markers of poor prognosis. Functional analysis of MAGEA3 was performed in human HCC cell lines by gene silencing and in a genetic mouse model by overexpression of MAGEA3 in the liver. Knockdown of MAGEA3 decreased cell proliferation, colony formation and increased apoptosis. MAGEA3 overexpression was associated with more aggressive tumors in vivo. In conclusion MAGEA3 enhances tumor progression and should be considered as a novel therapeutic target in HCC.

Landscape of oncoviral genotype and co-infection via human papilloma and hepatitis B viral tumor in situ profiling.

The role of oncoviral genotype and co-infection driving oncogenesis remains unclear. We have developed a scalable, high throughput tool for sensitive and precise oncoviral genotype deconvolution. Using tumor RNA sequencing data, we applied it to 537 virally infected liver, cervical, and head and neck tumors, providing the first comprehensive integrative landscape of tumor-viral gene expression, viral antigen immunogenicity, patient survival, and mutational profiling organized by tumor oncoviral genotype. We find that HBV and HPV genotype and co-infection serve as significant predictors of patient survival and immune activation. Finally, we demonstrate that HPV genotype is more associated with viral oncogene expression than cancer type, implying that expression may be similar across episomal and stochastic integration-based infections. While oncoviral infections are known risk factors for oncogenesis, viral genotype and co-infection are shown to strongly associate with disease progression, patient survival, mutational signatures, and putative tumor neoantigen immunogenicity, facilitating novel clinical associations with infections.

Open Problems in Extracellular RNA Data Analysis: Insights From an ERCC Online Workshop.

We now know RNA can survive the harsh environment of biofluids when encapsulated in vesicles or by associating with lipoproteins or RNA binding proteins. These extracellular RNA (exRNA) play a role in intercellular signaling, serve as biomarkers of disease, and form the basis of new strategies for disease treatment. The Extracellular RNA Communication Consortium (ERCC) hosted a two-day online workshop (April 19-20, 2021) on the unique challenges of exRNA data analysis. The goal was to foster an open dialog about best practices and discuss open problems in the field, focusing initially on small exRNA sequencing data. Video recordings of workshop presentations and discussions are available (https://exRNA.org/exRNAdata2021-videos/). There were three target audiences: experimentalists who generate exRNA sequencing data, computational and data scientists who work with those groups to analyze their data, and experimental and data scientists new to the field. Here we summarize issues explored during the workshop, including progress on an effort to develop an exRNA data analysis challenge to engage the community in solving some of these open problems.

Intestinal Inflammation Modulates the Expression of ACE2 and TMPRSS2 and Potentially Overlaps With the Pathogenesis of SARS-CoV-2-related Disease.

BACKGROUND AND AIMS: The presence of gastrointestinal symptoms and high levels of viral RNA in the stool suggest active severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication within enterocytes. METHODS: Here, in multiple, large cohorts of patients with inflammatory bowel disease (IBD), we have studied the intersections between Coronavirus Disease 2019 (COVID-19), intestinal inflammation, and IBD treatment. RESULTS: A striking expression of ACE2 on the small bowel enterocyte brush border supports intestinal infectivity by SARS-CoV-2. Commonly used IBD medications, both biologic and nonbiologic, do not significantly impact ACE2 and TMPRSS2 receptor expression in the uninflamed intestines. In addition, we have defined molecular responses to COVID-19 infection that are also enriched in IBD, pointing to shared molecular networks between COVID-19 and IBD. CONCLUSIONS: These data generate a novel appreciation of the confluence of COVID-19- and IBD-associated inflammation and provide mechanistic insights supporting further investigation of specific IBD drugs in the treatment of COVID-19. Preprint doi: https://doi.org/10.1101/2020.05.21.109124.

DNA Methylation Profiling of Human Hepatocarcinogenesis.

BACKGROUND AND AIMS: Mutations in TERT (telomerase reverse transcriptase) promoter are established gatekeepers in early hepatocarcinogenesis, but little is known about other molecular alterations driving this process. Epigenetic deregulation is a critical event in early malignancies. Thus, we aimed to (1) analyze DNA methylation changes during the transition from preneoplastic lesions to early HCC (eHCC) and identify candidate epigenetic gatekeepers, and to (2) assess the prognostic potential of methylation changes in cirrhotic tissue. APPROACH AND RESULTS: Methylome profiling was performed using Illumina HumanMethylation450 (485,000 cytosine-phosphateguanine, 96% of known cytosine-phosphateguanine islands), with data available for a total of 390 samples: 16 healthy liver, 139 cirrhotic tissue, 8 dysplastic nodules, and 227 HCC samples, including 40 eHCC below 2cm. A phylo-epigenetic tree derived from the Euclidean distances between differentially DNA-methylated sites (n = 421,997) revealed a gradient of methylation changes spanning healthy liver, cirrhotic tissue, dysplastic nodules, and HCC with closest proximity of dysplasia to HCC. Focusing on promoter regions, we identified epigenetic gatekeeper candidates with an increasing proportion of hypermethylated samples (beta value > 0.5) from cirrhotic tissue (<1%), to dysplastic nodules (≥25%), to eHCC (≥50%), and confirmed inverse correlation between DNA methylation and gene expression for TSPYL5 (testis-specific Y-encoded-like protein 5), KCNA3 (potassium voltage-gated channel, shaker-related subfamily, member 3), LDHB (lactate dehydrogenase B), and SPINT2 (serine peptidase inhibitor, Kunitz type 2) (all P < 0.001). Unsupervised clustering of genome-wide methylation profiles of cirrhotic tissue identified two clusters, M1 and M2, with 42% and 58% of patients, respectively, which correlates with survival (P < 0.05), independent of etiology. CONCLUSIONS: Genome-wide DNA-methylation profiles accurately discriminate the different histological stages of human hepatocarcinogenesis. We report on epigenetic gatekeepers in the transition between dysplastic nodules and eHCC. DNA-methylation changes in cirrhotic tissue correlate with clinical outcomes.

Liquid biopsy in the clinical management of hepatocellular carcinoma.

With increasing knowledge on molecular tumour information, precision oncology has revolutionised the medical field over the past years. Liquid biopsy entails the analysis of circulating tumour components, such as circulating tumour DNA, tumour cells or tumour-derived extracellular vesicles, and has thus come as a handy tool for personalised medicine in many cancer entities. Clinical applications under investigation include early cancer detection, prediction of treatment response and molecular monitoring of the disease, for example, to comprehend resistance patterns and clonal tumour evolution. In fact, several tests for blood-based mutation profiling are already commercially available and have entered the clinical field.In the context of hepatocellular carcinoma, where access to tissue specimens remains mostly limited to patients with early stage tumours, liquid biopsy approaches might be particularly helpful. A variety of translational liquid biopsy studies have been carried out to address clinical needs, such as early hepatocellular carcinoma detection and prediction of treatment response. To this regard, methylation profiling of circulating tumour DNA has evolved as a promising surveillance tool for early hepatocellular carcinoma detection in populations at risk, which might soon transform the way surveillance programmes are implemented. This review summarises recent developments in the liquid biopsy oncological space and, in more detail, the potential implications in the clinical management of hepatocellular carcinoma. It further outlines technical peculiarities across liquid biopsy technologies, which might be helpful for interpretation by non-experts.

The transcriptomic response of cells to a drug combination is more than the sum of the responses to the monotherapies.

Our ability to discover effective drug combinations is limited, in part by insufficient understanding of how the transcriptional response of two monotherapies results in that of their combination. We analyzed matched time course RNAseq profiling of cells treated with single drugs and their combinations and found that the transcriptional signature of the synergistic combination was unique relative to that of either constituent monotherapy. The sequential activation of transcription factors in time in the gene regulatory network was implicated. The nature of this transcriptional cascade suggests that drug synergy may ensue when the transcriptional responses elicited by two unrelated individual drugs are correlated. We used these results as the basis of a simple prediction algorithm attaining an AUROC of 0.77 in the prediction of synergistic drug combinations in an independent dataset.

Tumor fitness, immune exhaustion and clinical outcomes: impact of immune checkpoint inhibitors.

Recently proposed tumor fitness measures, based on profiling neoepitopes for reactive viral epitope similarity, have been proposed to predict response to immune checkpoint inhibitors in melanoma and small-cell lung cancer. Here we applied these checkpoint based fitness measures to the matched checkpoint treatment naive Cancer Genome Atlas (TCGA) samples where cytolytic activity (CYT) imparts a known survival benefit. We observed no significant survival predictive power beyond that of overall patient tumor mutation burden, and furthermore, found no association between checkpoint based fitness and tumor T-cell infiltration, cytolytic activity, and abundance (tumor infiltrating lymphocyte, TIL, burden). In addition, we investigated the key assumption of viral epitope similarity driving immune response in the hepatitis B virally infected liver cancer TCGA cohort, and uncovered suggestive evidence that tumor neoepitopes actually dominate viral epitopes in putative immunogenicity and plausibly drive immune response and recruitment.

Intratumoral heterogeneity and clonal evolution in liver cancer.

Clonal evolution of a tumor ecosystem depends on different selection pressures that are principally immune and treatment mediated. We integrate RNA-seq, DNA sequencing, TCR-seq and SNP array data across multiple regions of liver cancer specimens to map spatio-temporal interactions between cancer and immune cells. We investigate how these interactions reflect intra-tumor heterogeneity (ITH) by correlating regional neo-epitope and viral antigen burden with the regional adaptive immune response. Regional expression of passenger mutations dominantly recruits adaptive responses as opposed to hepatitis B virus and cancer-testis antigens. We detect different clonal expansion of the adaptive immune system in distant regions of the same tumor. An ITH-based gene signature improves single-biopsy patient survival predictions and an expression survey of 38,553 single cells across 7 regions of 2 patients further reveals heterogeneity in liver cancer. These data quantify transcriptomic ITH and how the different components of the HCC ecosystem interact during cancer evolution.

Tumoral and immune heterogeneity in an anti-PD-1-responsive glioblastoma: a case study.

Clinical benefit of immune checkpoint blockade in glioblastoma (GBM) is rare, and we hypothesize that tumor clonal evolution and the immune microenvironment are key determinants of response. Here, we present a detailed molecular characterization of the intratumoral and immune heterogeneity in an IDH wild-type, MGMT-negative GBM patient who plausibly benefited from anti-PD-1 therapy with an unusually long 25-mo overall survival time. We leveraged multiplex immunohistochemistry, RNA-seq, and whole-exome data from the primary tumor and three resected regions of recurrent disease to survey regional tumor-immune interactions, genomic instability, mutation burden, and expression profiles. We found significant regional heterogeneity in the neoantigenic and immune landscape, with a differential T-cell signature among recurrent sectors, a uniform loss of focal amplifications in EGFR, and a novel subclonal EGFR mutation. Comparisons with recently reported correlates of checkpoint blockade in GBM and with TCGA-GBM revealed appreciable intratumoral heterogeneity that may have contributed to a differential PD-1 blockade response.

Gut microbiota density influences host physiology and is shaped by host and microbial factors.

To identify factors that regulate gut microbiota density and the impact of varied microbiota density on health, we assayed this fundamental ecosystem property in fecal samples across mammals, human disease, and therapeutic interventions. Physiologic features of the host (carrying capacity) and the fitness of the gut microbiota shape microbiota density. Therapeutic manipulation of microbiota density in mice altered host metabolic and immune homeostasis. In humans, gut microbiota density was reduced in Crohn's disease, ulcerative colitis, and ileal pouch-anal anastomosis. The gut microbiota in recurrent Clostridium difficile infection had lower density and reduced fitness that were restored by fecal microbiota transplantation. Understanding the interplay between microbiota and disease in terms of microbiota density, host carrying capacity, and microbiota fitness provide new insights into microbiome structure and microbiome targeted therapeutics. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Epigenetic regulation of brain region-specific microglia clearance activity.

The rapid elimination of dying neurons and nonfunctional synapses in the brain is carried out by microglia, the resident myeloid cells of the brain. Here we show that microglia clearance activity in the adult brain is regionally regulated and depends on the rate of neuronal attrition. Cerebellar, but not striatal or cortical, microglia exhibited high levels of basal clearance activity, which correlated with an elevated degree of cerebellar neuronal attrition. Exposing forebrain microglia to apoptotic cells activated gene-expression programs supporting clearance activity. We provide evidence that the polycomb repressive complex 2 (PRC2) epigenetically restricts the expression of genes that support clearance activity in striatal and cortical microglia. Loss of PRC2 leads to aberrant activation of a microglia clearance phenotype, which triggers changes in neuronal morphology and behavior. Our data highlight a key role of epigenetic mechanisms in preventing microglia-induced neuronal alterations that are frequently associated with neurodegenerative and psychiatric diseases.