Bojan Losic

Genome-wide mapping of methylated adenine residues in pathogenic Escherichia coli using single-molecule real-time sequencing

Single-molecule real-time (SMRT) DNA sequencing allows the systematic detection of chemical modifications such as methylation but has not previously been applied on a genome-wide scale. We used this approach to detect 49,311 putative 6-methyladenine (m6A) residues and 1,407 putative 5-methylcytosine (m5C) residues in the genome of a pathogenic Escherichia coli strain. We obtained strand-specific information for methylation sites and a quantitative assessment of the frequency of methylation at each modified position. We deduced the sequence motifs recognized by the methyltransferase enzymes present in this strain without prior knowledge of their specificity. Furthermore, we found that deletion of a phage-encoded methyltransferase-endonuclease (restriction-modification; RM) system induced global transcriptional changes and led to gene amplification, suggesting that the role of RM systems extends beyond protecting host genomes from foreign DNA.

Massive parallel sequencing uncovers actionable FGFR2–PPHLN1 fusion and ARAF mutations in intrahepatic cholangiocarcinoma

Intrahepatic cholangiocarcinoma (iCCA) is a fatal bile duct cancer with dismal prognosis and limited therapeutic options. By performing RNA- and exome-sequencing analyses, we report a novel fusion event, FGFR2-PPHLN1 (16%), and damaging mutations in the ARAF oncogene (11%). Here we demonstrate that the chromosomal translocation t(10;12)(q26;q12) leading to FGFR2-PPHLN1 fusion possesses transforming and oncogenic activity, which is successfully inhibited by a selective FGFR2 inhibitor in vitro. Among the ARAF mutations, N217I and G322S lead to activation of the pathway and N217I shows oncogenic potential in vitro. Screening of a cohort of 107 iCCA patients reveals that FGFR2 fusions represent the most recurrent targetable alteration (45%, 17/107), while they are rarely present in other primary liver tumours (0/100 of hepatocellular carcinoma (HCC); 1/21 of mixed iCCA-HCC). Taken together, around 70% of iCCA patients harbour at least one actionable molecular alteration (FGFR2 fusions, IDH1/2, ARAF, KRAS, BRAF and FGF19) that is amenable for therapeutic targeting.

Cardiometabolic risk loci share downstream cis- and trans-gene regulation across tissues and diseases

Genetic variation and coronary artery disease Most genetic variants lie outside protein-coding genes, but their effects, especially in human health, are not well understood. Franzén et al. examined gene expression in tissues affected by coronary artery disease (CAD). They found that individuals with loci that have been associated with CAD in genome-wide analyses had different patterns of tissue-specific gene expression than individuals without these genetic variants. Similarly, tissues not associated with CAD did not have CAD-like expression patterns. Thus, tissue-specific data can be used to dissect the genetic effects that predispose individuals to CAD. Science, this issue p. 827 A gene expression survey in patients with coronary artery disease reveals how genetic variation affects the risk of heart failure. Genome-wide association studies (GWAS) have identified hundreds of cardiometabolic disease (CMD) risk loci. However, they contribute little to genetic variance, and most downstream gene-regulatory mechanisms are unknown. We genotyped and RNA-sequenced vascular and metabolic tissues from 600 coronary artery disease patients in the Stockholm-Tartu Atherosclerosis Reverse Networks Engineering Task study (STARNET). Gene expression traits associated with CMD risk single-nucleotide polymorphism (SNPs) identified by GWAS were more extensively found in STARNET than in tissue- and disease-unspecific gene-tissue expression studies, indicating sharing of downstream cis-/trans-gene regulation across tissues and CMDs. In contrast, the regulatory effects of other GWAS risk SNPs were tissue-specific; abdominal fat emerged as an important gene-regulatory site for blood lipids, such as for the low-density lipoprotein cholesterol and coronary artery disease risk gene PCSK9. STARNET provides insights into gene-regulatory mechanisms for CMD risk loci, facilitating their translation into opportunities for diagnosis, therapy, and prevention.

Biopsy transcriptome expression profiling to identify kidney transplants at risk of chronic injury: a multicentre, prospective study

BACKGROUND Chronic injury in kidney transplants remains a major cause of allograft loss. The aim of this study was to identify a gene set capable of predicting renal allografts at risk of progressive injury due to fibrosis. METHODS This Genomics of Chronic Allograft Rejection (GoCAR) study is a prospective, multicentre study. We prospectively collected biopsies from renal allograft recipients (n=204) with stable renal function 3 months after transplantation. We used microarray analysis to investigate gene expression in 159 of these tissue samples. We aimed to identify genes that correlated with the Chronic Allograft Damage Index (CADI) score at 12 months, but not fibrosis at the time of the biopsy. We applied a penalised regression model in combination with permutation-based approach to derive an optimal gene set to predict allograft fibrosis. The GoCAR study is registered with ClinicalTrials.gov, number NCT00611702. FINDINGS We identified a set of 13 genes that was independently predictive for the development of fibrosis at 1 year (ie, CADI-12 ≥2). The gene set had high predictive capacity (area under the curve [AUC] 0·967), which was superior to that of baseline clinical variables (AUC 0·706) and clinical and pathological variables (AUC 0·806). Furthermore routine pathological variables were unable to identify which histologically normal allografts would progress to fibrosis (AUC 0·754), whereas the predictive gene set accurately discriminated between transplants at high and low risk of progression (AUC 0·916). The 13 genes also accurately predicted early allograft loss (AUC 0·842 at 2 years and 0·844 at 3 years). We validated the predictive value of this gene set in an independent cohort from the GoCAR study (n=45, AUC 0·866) and two independent, publically available expression datasets (n=282, AUC 0·831 and n=24, AUC 0·972). INTERPRETATION Our results suggest that this set of 13 genes could be used to identify kidney transplant recipients at risk of allograft loss before the development of irreversible damage, thus allowing therapy to be modified to prevent progression to fibrosis. FUNDING National Institutes of Health.

Identification of an Immune-specific Class of Hepatocellular Carcinoma, Based on Molecular Features

BACKGROUND & AIMS Agents that induce an immune response against tumors by altering T-cell regulation have increased survival times of patients with advanced-stage tumors, such as melanoma or lung cancer. We aimed to characterize molecular features of immune cells that infiltrate hepatocellular carcinomas (HCCs) to determine whether these types of agents might be effective against liver tumors. METHODS We analyzed HCC samples from 956 patients. We separated gene expression profiles from tumor, stromal, and immune cells using a non-negative matrix factorization algorithm. We then analyzed the gene expression pattern of inflammatory cells in HCC tumor samples. We correlated expression patterns with the presence of immune cell infiltrates and immune regulatory molecules, determined by pathology and immunohistochemical analyses, in a training set of 228 HCC samples. We validated the correlation in a validation set of 728 tumor samples. Using data from 190 tumors in the Cancer Genome Atlas, we correlated immune cell gene expression profiles with numbers of chromosomal aberrations (based on single-nucleotide polymorphism array) and mutations (exome sequence data). RESULTS We found approximately 25% of HCCs to have markers of an inflammatory response, with high expression levels of the CD274 molecule (programmed death-ligand 1) and programmed cell death 1, markers of cytolytic activity, and fewer chromosomal aberrations. We called this group of tumors the Immune class. It contained 2 subtypes, characterized by markers of an adaptive T-cell response or exhausted immune response. The exhausted immune response subclass expressed many genes regulated by transforming growth factor beta 1 that mediate immunosuppression. We did not observe any differences in numbers of mutations or expression of tumor antigens between the immune-specific class and other HCCs. CONCLUSIONS In an analysis of HCC samples from 956 patients, we found almost 25% to express markers of an inflammatory response. We identified 2 subclasses, characterized by adaptive or exhausted immune responses. These findings indicate that some HCCs might be susceptible to therapeutic agents designed to block the regulatory pathways in T cells, such as programmed death-ligand 1, programmed cell death 1, or transforming growth factor beta 1 inhibitors.

A Systems Approach Identifies Networks and Genes Linking Sleep and Stress: Implications for Neuropsychiatric Disorders

Sleep dysfunction and stress susceptibility are comorbid complex traits that often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multilevel organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J × A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type-specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests that the interplay among sleep, stress, and neuropathology emerges from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework for interrogating the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders.

A functional genomics predictive network model identifies regulators of inflammatory bowel disease

A major challenge in inflammatory bowel disease (IBD) is the integration of diverse IBD data sets to construct predictive models of IBD. We present a predictive model of the immune component of IBD that informs causal relationships among loci previously linked to IBD through genome-wide association studies (GWAS) using functional and regulatory annotations that relate to the cells, tissues, and pathophysiology of IBD. Our model consists of individual networks constructed using molecular data generated from intestinal samples isolated from three populations of patients with IBD at different stages of disease. We performed key driver analysis to identify genes predicted to modulate network regulatory states associated with IBD, prioritizing and prospectively validating 12 of the top key drivers experimentally. This validated key driver set not only introduces new regulators of processes central to IBD but also provides the integrated circuits of genetic, molecular, and clinical traits that can be directly queried to interrogate and refine the regulatory framework defining IBD.

Phase 2 Trial of Gemcitabine, Cisplatin, plus Ipilimumab in Patients with Metastatic Urothelial Cancer and Impact of DNA Damage Response Gene Mutations on Outcomes

BACKGROUND Chemotherapy may exert immunomodulatory effects, thereby combining favorably with the immune checkpoint blockade. The pharmacodynamic effects of such combinations, and potential predictive biomarkers, remain unexplored. OBJECTIVE To determine the safety, efficacy, and immunomodulatory effects of gemcitabine and cisplatin (GC) plus ipilimumab and explore the impact of somatic DNA damage response gene alterations on antitumor activity. DESIGN, SETTING, AND PARTICIPANTS Multicenter single arm phase 2 study enrolling 36 chemotherapy-naïve patients with metastatic urothelial cancer. Peripheral blood flow cytometry was performed serially on all patients and whole exome sequencing of archival tumor tissue was performed on 28/36 patients. INTERVENTION Two cycles of GC followed by four cycles of GC plus ipilimumab. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS The primary endpoint was 1-yr overall survival (OS). Secondary endpoints included safety, objective response rate, and progression-free survival. RESULTS AND LIMITATIONS Grade ≥3 adverse events occurred in 81% of patients, the majority of which were hematologic. The objective response rate was 69% and 1-yr OS was 61% (lower bound 90% confidence interval: 51%). On exploratory analysis, there were no significant changes in the composition and frequency of circulating immune cells after GC alone. However, there was a significant expansion of circulating CD4 cells with the addition of ipilimumab which correlated with improved survival. The response rate was significantly higher in patients with deleterious somatic DNA damage response mutations (sensitivity=47.6%, specificity=100%, positive predictive value=100%, and negative predictive value=38.9%). Limitations are related to the sample size and single-arm design. CONCLUSIONS GC+ipilimumab did not achieve the primary endpoint of a lower bound of the 90% confidence interval for 1-yr OS of >60%. However, within the context of a small single-arm trial, the results may inform current approaches combining chemotherapy plus immunotherapy from the standpoint of feasibility, appropriate cytotoxic backbones, and potential predictive biomarkers. TRIAL REGISTRATION ClinicalTrials.gov NCT01524991. PATIENT SUMMARY Combining chemotherapy and immune checkpoint blockade in patients with metastatic urothelial cancer is feasible. Further studies are needed to refine optimal combinations and evaluate tests that might identify patients most likely to benefit.

Insights into beta cell regeneration for diabetes via integration of molecular landscapes in human insulinomas

Although diabetes results in part from a deficiency of normal pancreatic beta cells, inducing human beta cells to regenerate is difficult. Reasoning that insulinomas hold the “genomic recipe” for beta cell expansion, we surveyed 38 human insulinomas to obtain insights into therapeutic pathways for beta cell regeneration. An integrative analysis of whole-exome and RNA-sequencing data was employed to extensively characterize the genomic and molecular landscape of insulinomas relative to normal beta cells. Here, we show at the pathway level that the majority of the insulinomas display mutations, copy number variants and/or dysregulation of epigenetic modifying genes, most prominently in the polycomb and trithorax families. Importantly, these processes are coupled to co-expression network modules associated with cell proliferation, revealing candidates for inducing beta cell regeneration. Validation of key computational predictions supports the concept that understanding the molecular complexity of insulinoma may be a valuable approach to diabetes drug discovery.Diabetes results in part from a deficiency of functional pancreatic beta cells. Here, the authors study the genomic and epigenetic landscapes of human insulinomas to gain insight into possible pathways for therapeutic beta cell regeneration, highlighting epigenetic genes and pathways.

Single-cell profiling of peanut-responsive T cells in patients with peanut allergy reveals heterogeneous effector TH2 subsets

Background: The contribution of phenotypic variation of peanut‐specific T cells to clinical allergy or tolerance to peanut is not well understood. Objectives: Our objective was to comprehensively phenotype peanut‐specific T cells in the peripheral blood of subjects with and without peanut allergy (PA). Methods: We obtained samples from patients with PA, including a cohort undergoing baseline peanut challenges for an immunotherapy trial (Consortium of Food Allergy Research [CoFAR] 6). Subjects were confirmed as having PA, or if they passed a 1‐g peanut challenge, they were termed high‐threshold subjects. Healthy control (HC) subjects were also recruited. Peanut‐responsive T cells were identified based on CD154 expression after 6 to 18 hours of stimulation with peanut extract. Cells were analyzed by using flow cytometry and single‐cell RNA sequencing. Results: Patients with PA had tissue‐ and follicle‐homing peanut‐responsive CD4+ T cells with a heterogeneous pattern of TH2 differentiation, whereas control subjects had undetectable T‐cell responses to peanut. The PA group had a delayed and IL‐2–dependent upregulation of CD154 on cells expressing regulatory T (Treg) cell markers, which was absent in HC or high‐threshold subjects. Depletion of Treg cells enhanced cytokine production in HC subjects and patients with PA in vitro, but cytokines associated with highly differentiated TH2 cells were more resistant to Treg cell suppression in patients with PA. Analysis of gene expression by means of single‐cell RNA sequencing identified T cells with highly correlated expression of IL4, IL5, IL9, IL13, and the IL‐25 receptor IL17RB. Conclusions: These results demonstrate the presence of highly differentiated TH2 cells producing TH2‐associated cytokines with functions beyond IgE class‐switching in patients with PA. A multifunctional TH2 response was more evident than a Treg cell deficit among peanut‐responsive T cells.