The relationship between cytokine and neutrophil gene network distinguishes SARS-CoV-2-infected patients by sex and age

The fact that the COVID-19 fatality rate varies by sex and age is poorly understood. Notably, the outcome of SARS-CoV-2 infections mostly depends on the control of cytokine storm and the increasingly recognized pathological role of uncontrolled neutrophil activation. Here, we used an integrative approach with publicly available RNA-Seq data sets of nasopharyngeal swabs and peripheral blood leukocytes from patients with SARS-CoV-2, according to sex and age. Female and young patients infected by SARS-CoV-2 exhibited a larger number of differentially expressed genes (DEGs) compared with male and elderly patients, indicating a stronger immune modulation. Among them, we found an association between upregulated cytokine/chemokine- and downregulated neutrophil-related DEGs. This was correlated with a closer relationship between female and young subjects, while the relationship between male and elderly patients was closer still. The association between these cytokine/chemokines and neutrophil DEGs is marked by a strongly correlated interferome network. Here, female patients exhibited reduced transcriptional levels of key proinflammatory/neutrophil-related genes, such as CXCL8 receptors (CXCR1 and CXCR2), IL-1β, S100A9, ITGAM, and DBNL, compared with male patients. These genes are well known to be protective against inflammatory damage. Therefore, our work suggests specific immune-regulatory pathways associated with sex and age of patients infected with SARS-CoV-2 and provides a possible association between inverse modulation of cytokine/chemokine and neutrophil transcriptional signatures.

Normothermic Ex-vivo Kidney Perfusion in a Porcine Auto-Transplantation Model Preserves the Expression of Key Mitochondrial Proteins: An Unbiased Proteomics Analysis

Normothermic ex-vivo kidney perfusion (NEVKP) results in significantly improved graft function in porcine auto-transplant models of donation after circulatory death injury compared with static cold storage (SCS); however, the molecular mechanisms underlying these beneficial effects remain unclear. We performed an unbiased proteomics analysis of 28 kidney biopsies obtained at three time points from pig kidneys subjected to 30 min of warm ischemia, followed by 8 h of NEVKP or SCS, and auto-transplantation. 70/6593 proteins quantified were differentially expressed between NEVKP and SCS groups (false discovery rate < 0.05). Proteins increased in NEVKP mediated key metabolic processes including fatty acid ß-oxidation, the tricarboxylic acid cycle, and oxidative phosphorylation. Comparison of our findings with external datasets of ischemia-reperfusion and other models of kidney injury confirmed that 47 of our proteins represent a common signature of kidney injury reversed or attenuated by NEVKP. We validated key metabolic proteins (electron transfer flavoprotein subunit beta and carnitine O-palmitoyltransferase 2, mitochondrial) by immunoblotting. Transcription factor databases identified members of the peroxisome proliferator-activated receptors (PPAR) family of transcription factors as the upstream regulators of our dataset, and we confirmed increased expression of PPARA, PPARD, and RXRA in NEVKP with reverse transcription polymerase chain reaction. The proteome-level changes observed in NEVKP mediate critical metabolic pathways. These effects may be coordinated by PPAR-family transcription factors and may represent novel therapeutic targets in ischemia-reperfusion injury.

Association between renin-angiotensin system and chronic lung allograft dysfunction

Chronic lung allograft dysfunction (CLAD) is the major cause of death after lung transplantation. Angiotensin II (AngII), the main effector of the renin-angiotensin (RA) system, elicits fibrosis in both kidney and lung. We identified 6 AngII-regulated proteins (RHOB, BST1, LYPA1, GLNA, TSP1, LAMB1) increased in urine of patients with kidney allograft fibrosis. We hypothesized that RA system is active in CLAD and that AngII-regulated proteins are increased in bronchoalveolar lavage fluid (BAL) of CLAD patients.We performed immunostaining of AngII receptors (AGTR1 and AGTR2) and TSP1/GLNA in 10 CLAD lungs and 5 controls. Using mass spectrometry, we quantified peptides corresponding to AngII-regulated proteins in BAL of 40 lung transplant recipients (CLAD, stable and acute lung allograft dysfunction (ALAD)). Machine learning algorithms were developed to predict CLAD based on BAL peptide concentrations.Immunostaining demonstrated significantly more AGTR1+ cells in CLAD versus control lungs (p=0.02). TSP1 and GLNA immunostaining positively correlated with the degree of lung fibrosis (R²=0.42 and 0.57, respectively). In BAL, we noted a trend toward higher concentrations of AngII-regulated peptides in patients with CLAD at the time of bronchoscopy, and significantly higher concentrations of BST1, GLNA and RHOB peptides in patients that developed CLAD at follow-up (p<0.05). Support vector machine classifier discriminated CLAD from stable and ALAD patients at the time of bronchoscopy with AUC 0.86, and accurately predicted subsequent CLAD development (AUC 0.97).Proteins involved in the RA system are increased in CLAD lung and BAL. AngII-regulated peptides measured in BAL may accurately identify patients with CLAD and predict subsequent CLAD development.

Zinc finger protein-440 promotes cartilage degenerative mechanisms in human facet and knee osteoarthritis chondrocytes

OBJECTIVES

To investigate the role of zinc finger protein 440 (ZNF440) in the pathophysiology of cartilage degeneration during facet joint (FJ) and knee osteoarthritis (OA).

METHODS

Expression of ZNF440 in FJ and knee cartilage was determined by immunohistochemistry, quantitative (q)PCR, and Western blotting (WB). Human chondrocytes isolated from FJ and knee OA cartilage were cultured and transduced with ZNF440 or control plasmid, or transfected with ZNF440 or control small interfering RNA (siRNA), with/without interleukin (IL)-1β. Gene and protein levels of catabolic, anabolic and apoptosis markers were determined by qPCR or WB, respectively. In silico analyses were performed to determine compounds with potential to inhibit expression of ZNF440.

RESULTS

ZNF440 expression was increased in both FJ and knee OA cartilage compared to control cartilage. In vitro, overexpression of ZNF440 significantly increased expression of MMP13 and PARP p85, and decreased expression of COL2A1. Knockdown of ZNF440 with siRNA partially reversed the catabolic and cell death phenotype of human knee and FJ OA chondrocytes stimulated with IL-1β. In silico analysis followed by validation assays identified scriptaid as a compound with potential to downregulate the expression of ZNF440. Validation experiments showed that scriptaid reduced the expression of ZNF440 in OA chondrocytes and concomitantly reduced the expression of MMP13 and PARP p85 in human knee OA chondrocytes overexpressing ZNF440.

CONCLUSIONS

The expression of ZNF440 is significantly increased in human FJ and knee OA cartilage and may regulate cartilage degenerative mechanisms. Furthermore, scriptaid reduces the expression of ZNF440 and inhibits its destructive effects in OA chondrocytes.

MicroRNA-34a-5p Promotes Joint Destruction During Osteoarthritis

Objective

MicroRNA‐34a‐5p (miR‐34a‐5p) expression is elevated in the synovial fluid of patients with late‐stage knee osteoarthritis (OA); however, its exact role and therapeutic potential in OA remain to be fully elucidated. This study was undertaken to examine the role of miR‐34a‐5p in OA pathogenesis.

Methods

Expression of miR‐34a‐5p was determined in joint tissues and human plasma (n = 71). Experiments using miR‐34a‐5p mimic or antisense oligonucleotide (ASO) treatment were performed in human OA chondrocytes, fibroblast‐like synoviocytes (FLS) (n = 7–9), and mouse OA models, including destabilization of the medial meniscus (DMM; n = 22) and the accelerated, more severe model of mice fed a high‐fat diet and subjected to DMM (n = 11). Wild‐type (WT) mice (n = 9) and miR‐34a–knockout (KO) mice (n = 11) were subjected to DMM. Results were expressed as the mean ± SEM and analyzed by t‐test or analysis of variance, with appropriate post hoc tests. P values less than 0.05 were considered significant. RNA sequencing was performed on WT and KO mouse chondrocytes.

Results

Expression of miR‐34a‐5p was significantly increased in the plasma, cartilage, and synovium of patients with late‐stage OA and in the cartilage and synovium of mice subjected to DMM. Plasma miR‐34a‐5p expression was significantly increased in obese patients with late‐stage OA, and in the plasma and knee joints of mice fed a high‐fat diet. In human OA chondrocytes and FLS, miR‐34a‐5p mimic increased key OA pathology markers, while miR‐34a‐5p ASO improved cellular gene expression. Intraarticular miR‐34a‐5p mimic injection induced an OA‐like phenotype. Conversely, miR‐34a‐5p ASO injection imparted cartilage‐protective effects in the DMM and high‐fat diet/DMM models. The miR‐34a–KO mice exhibited protection against DMM‐induced cartilage damage. RNA sequencing of WT and KO chondrocytes revealed a putative miR‐34a‐5p signaling network.

Conclusion

Our findings provide comprehensive evidence of the role and therapeutic potential of miR‐34a‐5p in OA.

BioPAX-Parser: parsing and enrichment analysis of BioPAX pathways

SUMMARY

Biological pathways are fundamental for learning about healthy and disease states. Many existing formats support automatic software analysis of biological pathways, e.g. BioPAX (Biological Pathway Exchange). Although some algorithms are available as web application or stand-alone tools, no general graphical application for the parsing of BioPAX pathway data exists. Also, very few tools can perform pathway enrichment analysis (PEA) using pathway encoded in the BioPAX format. To fill this gap, we introduce BiP (BioPAX-Parser), an automatic and graphical software tool aimed at performing the parsing and accessing of BioPAX pathway data, along with PEA by using information coming from pathways encoded in BioPAX.

AVAILABILITY AND IMPLEMENTATION

BiP is freely available for academic and non-profit organizations at https://gitlab.com/giuseppeagapito/bip under the LGPL 2.1, the GNU Lesser General Public License.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Integrative analysis of layers of data in hepatocellular carcinoma reveals pathway dependencies

BACKGROUND

The broader use of high-throughput technologies has led to improved molecular characterization of hepatocellular carcinoma (HCC). 

AIM

To comprehensively analyze and characterize all publicly available genomic, gene expression, methylation, miRNA and proteomic data in HCC, covering 85 studies and 3355 patient sample profiles, to identify the key dysregulated genes and pathways they affect. 

METHODS

We collected and curated all well-annotated and publicly available high-throughput datasets from PubMed and Gene Expression Omnibus derived from human HCC tissue. Comprehensive pathway enrichment analysis was performed using pathDIP for each data type (genomic, gene expression, methylation, miRNA and proteomic), and the overlap of pathways was assessed to elucidate pathway dependencies in HCC.

RESULTS

We identified a total of 8733 abstracts retrieved by the search on PubMed on HCC for the different layers of data on human HCC samples, published until December 2016. The common key dysregulated pathways in HCC tissue across different layers of data included epidermal growth factor (EGFR) and β1-integrin pathways. Genes along these pathways were significantly and consistently dysregulated across the different types of high-throughput data and had prognostic value with respect to overall survival. Using CTD database, estradiol would best modulate and revert these genes appropriately.

CONCLUSION

By analyzing and integrating all available high-throughput genomic, transcriptomic, miRNA, methylation and proteomic data from human HCC tissue, we identified EGFR, β1-integrin and axon guidance as pathway dependencies in HCC. These are master regulators of key pathways in HCC, such as the mTOR, Ras/Raf/MAPK and p53 pathways. The genes implicated in these pathways had prognostic value in HCC, with Netrin and Slit3 being novel proteins of prognostic importance to HCC. Based on this integrative analysis, EGFR, and β1-integrin are master regulators that could serve as potential therapeutic targets in HCC.

A Network Biology Approach to Understanding the Tissue-Specific Roles of Non-Coding RNAs in Arthritis

Discovery of non-coding RNAs continues to provide new insights into some of the key molecular drivers of musculoskeletal diseases. Among these, microRNAs have received widespread attention for their roles in osteoarthritis and rheumatoid arthritis. With evidence to suggest that long non-coding RNAs and circular RNAs function as competing endogenous RNAs to sponge microRNAs, the net effect on gene expression in specific disease contexts can be elusive. Studies to date have focused on elucidating individual long non-coding-microRNA-gene target axes and circular RNA-microRNA-gene target axes, with a paucity of data integrating experimentally validated effects of non-coding RNAs. To address this gap, we curated recent studies reporting non-coding RNA axes in chondrocytes from human osteoarthritis and in fibroblast-like synoviocytes from human rheumatoid arthritis. Using an integrative computational biology approach, we then combined the findings into cell- and disease-specific networks for in-depth interpretation. We highlight some challenges to data integration, including non-existent naming conventions and out-of-date databases for non-coding RNAs, and some successes exemplified by the International Molecular Exchange Consortium for protein interactions. In this perspective article, we suggest that data integration is a useful in silico approach for creating non-coding RNA networks in arthritis and prioritizing interactions for further in vitro and in vivo experimentation in translational research.

Mechanical Stiffness Controls Dendritic Cell Metabolism and Function

Stiffness in the tissue microenvironment changes in most diseases and immunological conditions, but its direct influence on the immune system is poorly understood. Here, we show that static tension impacts immune cell function, maturation, and metabolism. Bone-marrow-derived and/or splenic dendritic cells (DCs) grown in vitro at physiological resting stiffness have reduced proliferation, activation, and cytokine production compared with cells grown under higher stiffness, mimicking fibro-inflammatory disease. Consistently, DCs grown under higher stiffness show increased activation and flux of major glucose metabolic pathways. In DC models of autoimmune diabetes and tumor immunotherapy, tension primes DCs to elicit an adaptive immune response. Mechanistic workup identifies the Hippo-signaling molecule, TAZ, as well as Ca²⁺-related ion channels, including potentially PIEZO1, as important effectors impacting DC metabolism and function under tension. Tension also directs the phenotypes of monocyte-derived DCs in humans. Thus, mechanical stiffness is a critical environmental cue of DCs and innate immunity.

Comprehensive pathway enrichment analysis workflows: COVID-19 case study

The coronavirus disease 2019 (COVID-19) outbreak due to the novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been classified as a pandemic disease by the World Health Organization on the 12th March 2020. This world-wide crisis created an urgent need to identify effective countermeasures against SARS-CoV-2. In silico methods, artificial intelligence and bioinformatics analysis pipelines provide effective and useful infrastructure for comprehensive interrogation and interpretation of available data, helping to find biomarkers, explainable models and eventually cures. One class of such tools, pathway enrichment analysis (PEA) methods, helps researchers to find possible key targets present in biological pathways of host cells that are targeted by SARS-CoV-2. Since many software tools are available, it is not easy for non-computational users to choose the best one for their needs. In this paper, we highlight how to choose the most suitable PEA method based on the type of COVID-19 data to analyze. We aim to provide a comprehensive overview of PEA techniques and the tools that implement them.

Rho-GTPase pathways may differentiate treatment response to TNF-alpha and IL-17A inhibitors in psoriatic arthritis

Biological therapies have dramatically improved the therapeutic landscape of psoriatic arthritis (PsA); however, 40–50% of patients are primary non-responders with response rates declining significantly with each successive biological therapy. Therefore, there is a pressing need to develop a coherent strategy for effective initial and subsequent selection of biologic agents. We interrogated 40 PsA patients initiating either tumour necrosis factor inhibitors (TNFi) or interleukin-17A inhibitors (17Ai) for active PsA. Patients achieving low disease activity according to the Disease Activity Index for PsA (DAPSA) at 3 months were classified as responders. Baseline and 3-month CD4⁺ transcript profiling were performed, and novel signaling pathways were identified using a multi-omics profiling and integrative computational analysis approach. Using transcriptomic data at initiation of therapy, we identified over 100 differentially expressed genes (DEGs) that differentiated IL-17Ai response from non-response and TNFi response from non-response. Integration of cell-type-specific DEGs with protein–protein interactions and further comprehensive pathway enrichment analysis revealed several pathways. Rho GTPase signaling pathway exhibited a strong signal specific to IL-17Ai response and the genes, RAC1 and ROCKs, are supported by results from prior research. Our detailed network and pathway analyses have identified the rewiring of Rho GTPase pathways as potential markers of response to IL17Ai but not TNFi. These results need further verification.

Towards a unified open access dataset of molecular interactions

The International Molecular Exchange (IMEx) Consortium provides scientists with a single body of experimentally verified protein interactions curated in rich contextual detail to an internationally agreed standard. In this update to the work of the IMEx Consortium, we discuss how this initiative has been working in practice, how it has ensured database sustainability, and how it is meeting emerging annotation challenges through the introduction of new interactor types and data formats. Additionally, we provide examples of how IMEx data are being used by biomedical researchers and integrated in other bioinformatic tools and resources.

Sequencing identifies a distinct signature of circulating microRNAs in early radiographic knee osteoarthritis

OBJECTIVE

MicroRNAs act locally and systemically to impact osteoarthritis (OA) pathophysiology, but comprehensive profiling of the circulating miRNome in early vs late stages of OA has yet to be conducted. Sequencing has emerged as the preferred method for microRNA profiling since it offers high sensitivity and specificity. Our objective was to sequence the miRNome in plasma from 91 patients with early [Kellgren-Lawrence (KL) grade 0 or 1 (n = 41)] or late [KL grade 3 or 4 (n = 50)] symptomatic radiographic knee OA to identify unique microRNA signatures in each disease state.

DESIGN

MicroRNA libraries were prepared using the QIAseq miRNA Library Kit and sequenced on the Illumina NextSeq 550. Counts were produced for microRNAs captured in miRBase and for novel microRNAs. Statistical, bioinformatics, and computational biology approaches were used to refine and interpret the final list of microRNAs.

RESULTS

From 215 differentially expressed microRNAs (FDR < 0.01), 97 microRNAs showed an increase or decrease in expression in ≥85% of samples in the early OA group as compared to the median expression in the late OA group. Increasing this threshold to ≥95%, seven microRNAs were identified: hsa-miR-335-3p, hsa-miR-199a-5p, hsa-miR-671-3p, hsa-miR-1260b, hsa-miR-191-3p, hsa-miR-335-5p, and hsa-miR-543. Four novel microRNAs were present in ≥50% of early OA samples and had 27 predicted gene targets in common with the prioritized set of predicted gene targets from the 97 microRNAs, suggesting common underlying mechanisms.

CONCLUSION

Sequencing of well-characterized patient cohorts produced unbiased profiling of the circulating miRNome and identified a unique panel of 11 microRNAs in early radiographic knee OA.

GSOAP: a tool for visualization of gene set over-representation analysis

Motivation

Gene sets over-representation analysis (GSOA) is a common technique of enrichment analysis that measures the overlap between a gene set and selected instances (e.g. pathways). Despite its popularity, there is currently no established standard for visualization of GSOA results.

Results

Here, we propose a visual exploration of the GSOA results by showing the relationships among the enriched instances, while highlighting important instance attributes, such as significance, closeness (centrality) and clustering.

Availability and implementation

GSOAP is implemented as an R package and is available at https://github.com/tomastokar/gsoap.

Extracellular Matrix Injury of Kidney Allografts in Antibody-Mediated Rejection: A Proteomics Study

BACKGROUND

Antibody-mediated rejection (AMR) accounts for >50% of kidney allograft loss. Donor-specific antibodies (DSA) against HLA and non-HLA antigens in the glomeruli and the tubulointerstitium cause AMR while inflammatory cytokines such as TNFα trigger graft injury. The mechanisms governing cell-specific injury in AMR remain unclear.

METHODS

Unbiased proteomic analysis of laser-captured and microdissected glomeruli and tubulointerstitium was performed on 30 for-cause kidney biopsy specimens with early AMR, acute cellular rejection (ACR), or acute tubular necrosis (ATN).

RESULTS

A total of 107 of 2026 glomerular and 112 of 2399 tubulointerstitial proteins was significantly differentially expressed in AMR versus ACR; 112 of 2026 glomerular and 181 of 2399 tubulointerstitial proteins were significantly dysregulated in AMR versus ATN (P<0.05). Basement membrane and extracellular matrix (ECM) proteins were significantly decreased in both AMR compartments. Glomerular and tubulointerstitial laminin subunit γ-1 (LAMC1) expression decreased in AMR, as did glomerular nephrin (NPHS1) and receptor-type tyrosine-phosphatase O (PTPRO). The proteomic analysis revealed upregulated galectin-1, which is an immunomodulatory protein linked to the ECM, in AMR glomeruli. Anti-HLA class I antibodies significantly increased cathepsin-V (CTSV) expression and galectin-1 expression and secretion in human glomerular endothelial cells. CTSV had been predicted to cleave ECM proteins in the AMR glomeruli. Glutathione S-transferase ω-1, an ECM-modifying enzyme, was significantly increased in the AMR tubulointerstitium and in TNFα-treated proximal tubular epithelial cells.

CONCLUSIONS

Basement membranes are often remodeled in chronic AMR. Proteomic analysis performed on laser-captured and microdissected glomeruli and tubulointerstitium identified early ECM remodeling, which may represent a new therapeutic opportunity.

47. UNCOVERING A NOVEL ROLE FOR HLA-G IN BRAIN METASTASES

Brain metastases (BM) are the most common brain tumour in adults and are ten times more likely to develop than primary brain tumours. More than 20% of patients with cancer will develop BM with the three most common sources being primary cancers of the lung, breast, and melanoma. Unfortunately, current treatment options for BM do not effectively eradicate BM, with a mere median overall survival time of 12 months in treated patients. This indicates the need for better and more effective therapies against BM. Using patient-derived cell lines established from surgically removed brain metastatic tumours of lung-, breast- and melanoma-BM patients, we generated patient-derived orthotopic murine xenograft (PDX) models of lung-, breast-, and melanoma-BM. From these PDX models, we isolated a rare population of stem-like brain metastasis initiating cells (BMICs) we termed “pre-metastatic”, that had traveled from their primary/orthotopic tumours and lodged in the brain but had not yet developed into mature BM. Transcriptomic analyses performed on pre-metastatic and non-pre-metastatic BMICs from lung, breast and melanoma PDX models of BM, identified a set of deregulated genes exclusive only to pre-metastatic BMICs. Further analysis revealed HLA-G as being commonly up-regulated only during the pre-metastatic stage of the lung-, breast-, and melanoma-BM cascade. In vitro and in vivo analyses demonstrated that HLA-G knock-down reduced the proliferation and survival of BMICs from all BM cohorts, and attenuated the establishment of mature brain metastatic tumours, implying a crucial role for HLA-G in the formation of BM. Developing a therapeutic strategy that targets HLA-G in BM may prove effective at completely eliminating brain metastatic cells at an early stage of the BM cascade, thereby turning a fatal disease into an eminently more treatable one.

The IMEx Coronavirus interactome: an evolving map of Coronaviridae-Host molecular interactions

The current Coronavirus Disease 2019 (COVID-19) pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions enables studying fine-grained resolution of the mechanisms behind the virus biology and the human organism response. Here we present a curated dataset of physical molecular interactions, manually extracted by IMEx Consortium curators focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family. Currently, the dataset comprises over 2,200 binarized interactions extracted from 86 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website ( www.ebi.ac.uk/intact ), and will be continuously updated as research on COVID-19 progresses.

SAT0359 THE ASSOCIATION BETWEEN IMAGING SUB-PHENOTYPES OF PSORIATIC ARTHRITIS AND GENE EXPRESSION PROFILES

Background:

Heterogeneity is a hallmark of psoriatic arthritis (PsA), which is reflected in diverse clinical, imaging and molecular features that may reflect disease course and response to treatment. We hypothesized that specific molecular pathways underlie the various manifestations of PsA.

Objectives:

To create a model for accurate and biologically meaningful sub-phenotyping of PsA using imaging and molecular data. Specifically, we aimed to identify imaging sub-phenotypes in patients with PsA and determine their association with whole blood mRNA expression markers.

Methods:

55 patients with PsA ready to initiate treatment for active disease were prospectively recruited. An ultrasound assessment of the extent of musculoskeletal inflammation in 64 joints, 34 tendons and 16 entheses was performed. Sonographic inflammation (in greyscale and Doppler) of the following domains was graded for: a) synovitis; b) peri-tendonitis; c) tenosynovitis; and d) enthesitis. A global inflammatory score was calculated for each tissue domain. Peripheral blood was profiled with RNAseq, and gene expression data were obtained. Analyses were performed in two stages: 1) Unsupervised cluster analysis was performed using hierarchial and k-means to define imaging sub-phenotypes in PsA that reflected the predominant tissue involved; 2) Principal component analysis with ellipses was used to determine the association between imaging-defined clusters and peripheral blood gene expression profile.

Results:

The patients could be divided into 3 groups based on unsupervised hierarchical and k-means clustering of images indicating the predominant involved tissue (Figure 1): 1) Enthesitis predominant (N=13 [24%]); 2) Peri-tendonitis predominant (N=11 [20%]); 3); Synovitis predominant (N=31 [56%]). Patients in the synovitis predominant group had more nail involvement, while those in the peri-tendonitis group had the highest number of clinically active joints (Table 1). Unsupervised clustering of gene expression data identified three clusters that partially overlapped with the imaging clustering (Figure 2). Overall, 344 genes were differentially expressed (p<0.05) in two of the three comparisons between the imaging clusters.

Table 1.

Clinical Features by Imaging Clustering

VariableEnthesitis predominantcluster(N=13)Peritendonitis predominant cluster(N=11)Synovitis predominant cluster(N=31)Age (years)47 (14)49 (16)45 (20)Sex: Female8 (61.5%)5 (45.5%)15 (48.4%)PsA duration (years)1.2 (1.5)1.6 (11.5)0.8 (3.7)BMI29.4 (6.8)25 (8.1)26.1 (8.4)Nail lesions3 (23.1%)5 (45.5%)17 (54.8%)PASI1.2 (2.7)1.2 (3.2)2.8 (7.8)Tender joint count6 (9)11 (5)3 (6)Swollen joint count2 (6)10 (7)3 (6)Dactylitis3 (23.1%)4 (36.4%)7 (22.6%)Enthesitis count3 (3)1 (4)0 (2)Enthesitis12 (92.3%)7 (63.6%)15 (48.4%)hsCRP2.9 (8.8)8.5 (21.5)3.6 (9.4)

Median (IQ range) and frequencies (%)

Bolded=Statistically different between the 3 groups (p<0.05)

Conclusion:

We identified three different imaging clusters based on the predominant tissue involved in patients with active PsA. Distinct gene expression profiles may underlie these imaging clusters seen in PsA.

Acknowledgments:

The study was supported by a Discovery Grant from the National Psoriasis Foundation.

Disclosure of Interests:

Lihi Eder Grant/research support from: Abbvie, Lily, Janssen, Amgen, Novartis, Consultant of: Janssen, Speakers bureau: Abbvie, Lily, Janssen, Amgen, Novartis, Quan Li: None declared, Sara Rahmati: None declared, Iris Eshed: None declared, Proton Rahman Grant/research support from: Janssen and Novartis, Consultant of: Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, and Pfizer., Speakers bureau: Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, Pfizer, Igor Jurisica Grant/research support from: IBM, Vinod Chandran Grant/research support from: Abbvie, Celgene, Consultant of: Abbvie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lily, Janssen, Novartis, Pfizer, UCB, Employee of: Spouse employed by Eli Lily

OP0305 RHO-GTPASE PATHWAYS MAY DIFFERENTIATE RESPONDER AND NON-RESPONDERS TO TUMOUR NECROSIS FACTOR INHIBITOR (TNFI) AND INTERLEUKIN-17A INHIBITOR (IL-17AI) THERAPY IN PSORIATIC ARTHRITIS (PSA)

Background:

In PsA there is a pressing need to develop a coherent strategy for identifying initial and subsequent biologic responders. PsA patients present substantial heterogeneity in response to biologics, and molecular subtyping will help to identify the right patient for the right treatment.

Objectives:

To identify transcript profiles (biomarkers) that will select TNFi and IL-17Ai responders in PsA using baseline CD4+ cells; and elucidate novel signaling pathways relevant to biologic disease modifying antirheumatic drug (bDMARD) response using a systems biology approach.

Methods:

Consenting patients initiating TNFi agents (20 patients) or IL-17Ai agents (20 patients) with moderate-to-severe PsA were assessed with a comprehensive standardized protocol at baseline and at 3 months. Responder to bDMARDs was defined by Disease Activity index for PSoriatic Arthritis (DAPSA) score of less than 14 (low disease activity). Global transcript profiling was performed on all patients prior to initiation of and 3 months post bDMARDs. We mapped RNA-seq reads to the hg19 reference genome using STAR and quantified transcripts with Cufflinks. The transcripts per million (TPM) values were log-transformed for statistical analyses

Results:

The demographics of PsA patients for both treatment groups are presented (Table 1). Differentially expressed genes (DEGs) were identified using the limma tool for TNFi and IL-17Ai responders and non-responders (Figure 1) as well as DEGs that differentiated TNFi from IL-17Ai response and non-response. Integration of differential gene expression data with tissue-specific protein-protein interactions (IID version 2018-11) identified 117 and 132 DEGs between responders and non-responders to TNFi and IL-17Ai treatments, respectively. Comprehensive pathway enrichment analysis of these genes using pathDIP (v 4.1) revealed 576 (out of 5380) pathways enriched in 117 DEGs between responders and non-responders to TNFi, and 125 pathways enriched in 132 DEGs between responders and non-responders to IL-17Ai. Interestingly, while these two gene lists share only 17 genes, they have 79 enriched pathways in common suggesting potential effect of two different treatments on similar pathways but through different pathway members (Figure 2). Moreover, it suggests potential importance of the 17 shared genes in association with these pathways. Most of these pathways are related to innate and adaptive immune system, and to “osteoclast differentiation”. Among 46 pathways specific to response to IL-17Ai, multiple Rho-GTPase-related pathways were identified. It has been shown that experimental inhibition of ROCK2, a target of Rho-GTPase family is effective in psoriatic disease through regulation of IL-17/23/10, but not IL-6 and TNFα.

Table 1.

Demographics of psoriatic arthritis (PsA) patients.

IL-17AiTNFiNumber of PsA patients2020Gender (% female)55%75%Mean Age (Years)55.9 (9.5)56.8 (7.9)Mean Disease Duration (Years)10.4 (6.9)7.3 (7.9)Mean DAPSA baseline38.8 (17.5)45.6 (28.9)Responders (%) (DAPSA <14)35%65%Biologic naïve (%)40%60%Figure 1.

PCA plots illustrating that DEGs of CD4+ cells can differentiate responders from non-responders when treated with:A.IL-17Ai; andB.TNFi.

Figure 2.

Over-represented terms in significantly enriched pathways considering DEGs between:A.IL-17i responders and non-responders (125 pathways);B.TNFi responders and non-responders (576 pathways).

Conclusion:

Integration of cell-specific transcriptomic data with protein networks represents a very promising strategy for identifying biologic responders and pathways involved in predicting response that may have identified the Rho-GTP pathway as a potential marker to guide the choice of biologic agents for individual patients.

Disclosure of Interests:

Sara Rahmati: None declared, Darren O’Rielly: None declared, Quan Li: None declared, Dianne Codner: None declared, Amanda Dohey: None declared, Kari Jenkins: None declared, Igor Jurisica Grant/research support from: IBM, Dafna D Gladman Grant/research support from: AbbVie, Amgen Inc., BMS, Celgene Corporation, Janssen, Novartis, Pfizer, UCB – grant/research support, Consultant of: AbbVie, Amgen Inc., BMS, Celgene Corporation, Janssen, Novartis, Pfizer, UCB – consultant, Vinod Chandran Grant/research support from: Abbvie, Celgene, Consultant of: Abbvie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lily, Janssen, Novartis, Pfizer, UCB, Employee of: Spouse employed by Eli Lily, Proton Rahman Grant/research support from: Janssen and Novartis, Consultant of: Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, and Pfizer., Speakers bureau: Abbott, AbbVie, Amgen, BMS, Celgene, Lilly, Janssen, Novartis, Pfizer

Urinary proteomics links keratan sulfate degradation and lysosomal enzymes to early type 1 diabetes

Diabetes is the leading cause of end-stage renal disease worldwide. Our understanding of the early kidney response to chronic hyperglycemia remains incomplete. To address this, we first investigated the urinary proteomes of otherwise healthy youths with and without type 1 diabetes and subsequently examined the enriched pathways that might be dysregulated in early disease using systems biology approaches. This cross-sectional study included two separate cohorts for the discovery (N = 30) and internal validation (N = 30) of differentially excreted proteins. Discovery proteomics was performed on a Q Exactive Plus hybrid quadrupole-orbitrap mass spectrometer. We then searched the pathDIP, KEGG, and Reactome databases to identify enriched pathways in early diabetes; the Integrated Interactions Database to retrieve protein-protein interaction data; and the PubMed database to compare fold changes of our signature proteins with those published in similarly designed studies. Proteins were selected for internal validation based on pathway enrichment and availability of commercial enzyme-linked immunosorbent assay kits. Of the 2451 proteins identified, 576 were quantified in all samples from the discovery cohort; 34 comprised the urinary signature for early diabetes after Benjamini-Hochberg adjustment (Q < 0.05). The top pathways associated with this signature included lysosome, glycosaminoglycan degradation, and innate immune system (Q < 0.01). Notably, all enzymes involved in keratan sulfate degradation were significantly elevated in urines from youths with diabetes (|fold change| > 1.6). Increased urinary excretion of monocyte differentiation antigen CD14, hexosaminidase A, and lumican was also observed in the validation cohort (P < 0.05). Twenty-one proteins from our signature have been reported elsewhere as potential mediators of early diabetes. In this study, we identified a urinary proteomic signature for early type 1 diabetes, of which lysosomal enzymes were major constituents. Our findings highlight novel pathways such as keratan sulfate degradation in the early kidney response to hyperglycemia.

Germline Mutation in MUS81 Resulting in Impaired Protein Stability is Associated with Familial Breast and Thyroid Cancer

Multiple primary thyroid cancer (TC) and breast cancer (BC) are commonly diagnosed, and the lifetime risk for these cancers is increased in patients with a positive family history of both TC and BC. Although this phenotype is partially explained by TP53 or PTEN mutations, a significant number of patients are negative for these alterations. We judiciously recruited patients diagnosed with BC and/or TC having a family history of these tumors and assessed their whole-exome sequencing. After variant prioritization, we selected MUS81 c.1292G>A (p.R431H) for further investigation. This variant was genotyped in a healthy population and sporadic BC/TC tissues and investigated at the protein level and cellular models. MUS81 c.1292G>A was the most frequent variant (25%) and the strongest candidate due to its function of double-strand break repair. This variant was confirmed in four relatives from two families. MUS81 p.R431H protein exhibited lower expression levels in tumors from patients positive for the germline variant, compared with wild-type BC, and normal breast and thyroid tissues. Using cell line models, we showed that c.1292G>A induced protein instability and affected DNA damage response. We suggest that MUS81 is a novel candidate involved in familial BC/TC based on its low frequency in healthy individuals and proven effect in protein stability.

Split Intein-Mediated Protein Ligation for detecting protein-protein interactions and their inhibition

Here, to overcome many limitations accompanying current available methods to detect protein-protein interactions (PPIs), we develop a live cell method called Split Intein-Mediated Protein Ligation (SIMPL). In this approach, bait and prey proteins are respectively fused to an intein N-terminal fragment (IN) and C-terminal fragment (IC) derived from a re-engineered split intein GP41-1. The bait/prey binding reconstitutes the intein, which splices the bait and prey peptides into a single intact protein that can be detected by regular protein detection methods such as Western blot analysis and ELISA, serving as readouts of PPIs. The method is robust and can be applied not only in mammalian cell lines but in animal models such as C. elegans. SIMPL demonstrates high sensitivity and specificity, and enables exploration of PPIs in different cellular compartments and tracking of kinetic interactions. Additionally, we establish a SIMPL ELISA platform that enables high-throughput screening of PPIs and their inhibitors.

Protein-protein interactions are fundamental to the regulation of protein activity and cellular phyisology. Here the authors present Split Intein-Mediated Protein Ligation, which uses bait and prey proteins fused to intein fragments to generate single intact proteins upon interaction.

Physiological Tau Interactome in Brain and Its Link to Tauopathies

Alzheimer's disease (AD) and most of the other tauopathies are incurable neurodegenerative diseases with unpleasant symptoms and consequences. The common hallmark of all of these diseases is tau pathology, but its connection with disease progress has not been completely understood so far. Therefore, uncovering novel tau-interacting partners and pathology affected molecular pathways can reveal the causes of diseases as well as potential targets for the development of AD treatment. Despite the large number of known tau-interacting partners, a limited number of studies focused on in vivo tau interactions in disease or healthy conditions are available. Here, we applied an in vivo cross-linking approach, capable of capturing weak and transient protein-protein interactions, to a unique transgenic rat model of progressive tau pathology similar to human AD. We have identified 175 potential novel and known tau-interacting proteins by MALDI-TOF mass spectrometry. Several of the most promising candidates for possible drug development were selected for validation by coimmunoprecipitation and colocalization experiments in animal and cellular models. Three proteins, Baiap2, Gpr37l1, and Nptx1, were confirmed as novel tau-interacting partners, and on the basis of their known functions and implications in neurodegenerative or psychiatric disorders, we proposed their potential role in tau pathology.

Extensive rewiring of the EGFR network in colorectal cancer cells expressing transforming levels of KRASG13D

Protein-protein-interaction networks (PPINs) organize fundamental biological processes, but how oncogenic mutations impact these interactions and their functions at a network-level scale is poorly understood. Here, we analyze how a common oncogenic KRAS mutation (KRASG13D) affects PPIN structure and function of the Epidermal Growth Factor Receptor (EGFR) network in colorectal cancer (CRC) cells. Mapping >6000 PPIs shows that this network is extensively rewired in cells expressing transforming levels of KRASG13D (mtKRAS). The factors driving PPIN rewiring are multifactorial including changes in protein expression and phosphorylation. Mathematical modelling also suggests that the binding dynamics of low and high affinity KRAS interactors contribute to rewiring. PPIN rewiring substantially alters the composition of protein complexes, signal flow, transcriptional regulation, and cellular phenotype. These changes are validated by targeted and global experimental analysis. Importantly, genetic alterations in the most extensively rewired PPIN nodes occur frequently in CRC and are prognostic of poor patient outcomes.

pathDIP 4: an extended pathway annotations and enrichment analysis resource for human, model organisms and domesticated species

PathDIP was introduced to increase proteome coverage of literature-curated human pathway databases. PathDIP 4 now integrates 24 major databases. To further reduce the number of proteins with no curated pathway annotation, pathDIP integrates pathways with physical protein-protein interactions (PPIs) to predict significant physical associations between proteins and curated pathways. For human, it provides pathway annotations for 5366 pathway orphans. Integrated pathway annotation now includes six model organisms and ten domesticated animals. A total of 6401 core and ortholog pathways have been curated from the literature or by annotating orthologs of human proteins in the literature-curated pathways. Extended pathways are the result of combining these pathways with protein-pathway associations that are predicted using organism-specific PPIs. Extended pathways expand proteome coverage from 81 088 to 120 621 proteins, making pathDIP 4 the largest publicly available pathway database for these organisms and providing a necessary platform for comprehensive pathway-enrichment analysis. PathDIP 4 users can customize their search and analysis by selecting organism, identifier and subset of pathways. Enrichment results and detailed annotations for input list can be obtained in different formats and views. To support automated bioinformatics workflows, Java, R and Python APIs are available for batch pathway annotation and enrichment analysis. PathDIP 4 is publicly available at http://ophid.utoronto.ca/pathDIP.

The IMEx coronavirus interactome: an evolving map of Coronaviridae-host molecular interactions

The current coronavirus disease of 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus (SARS-CoV)-2, has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions can provide fine-grained resolution of the mechanisms behind the virus biology and the human organism response. We present a curated dataset of physical molecular interactions focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family that has been manually extracted by International Molecular Exchange (IMEx) Consortium curators. Currently, the dataset comprises over 4400 binarized interactions extracted from 151 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website (https://www.ebi.ac.uk/intact) and will be continuously updated as research on COVID-19 progresses.

mirDIP 4.1-integrative database of human microRNA target predictions

MicroRNAs are important regulators of gene expression, achieved by binding to the gene to be regulated. Even with modern high-throughput technologies, it is laborious and expensive to detect all possible microRNA targets. For this reason, several computational microRNA-target prediction tools have been developed, each with its own strengths and limitations. Integration of different tools has been a successful approach to minimize the shortcomings of individual databases. Here, we present mirDIP v4.1, providing nearly 152 million human microRNA-target predictions, which were collected across 30 different resources. We also introduce an integrative score, which was statistically inferred from the obtained predictions, and was assigned to each unique microRNA-target interaction to provide a unified measure of confidence. We demonstrate that integrating predictions across multiple resources does not cumulate prediction bias toward biological processes or pathways. mirDIP v4.1 is freely available at http://ophid.utoronto.ca/mirDIP/.

Immune-enrichment of non-small cell lung cancer baseline biopsies for multiplex profiling define prognostic immune checkpoint combinations for patient stratification

Background

Permanence of front-line management of lung cancer by immunotherapies requires predictive companion diagnostics identifying immune-checkpoints at baseline, challenged by the size and heterogeneity of biopsy specimens.

Methods

An innovative, tumor heterogeneity reducing, immune-enriched tissue microarray was constructed from baseline biopsies, and multiplex immunofluorescence was used to profile 25 immune-checkpoints and immune-antigens.

Results

Multiple immune-checkpoints were ranked, correlated with antigen presenting and cytotoxic effector lymphocyte activity, and were reduced with advancing disease. Immune-checkpoint combinations on TILs were associated with a marked survival advantage. Conserved combinations validated on more than 11,000 lung, breast, gastric and ovarian cancer patients demonstrate the feasibility of pan-cancer companion diagnostics.

Conclusions

In this hypothesis-generating study, deepening our understanding of immune-checkpoint biology, comprehensive protein-protein interaction and pathway mapping revealed that redundant immune-checkpoint interactors associate with positive outcomes, providing new avenues for the deciphering of molecular mechanisms behind effects of immunotherapeutic agents targeting immune-checkpoints analyzed.

Electronic supplementary material

The online version of this article (10.1186/s40425-019-0544-x) contains supplementary material, which is available to authorized users.

Failed immune responses across multiple pathologies share pan-tumor and circulating lymphocytic targets

Rationale Tumor infiltrating lymphocytes are widely associated with positive outcomes, yet carry key indicators of a systemic failed immune response against unresolved cancer. Cancer immunotherapies can reverse their tolerance phenotypes, while preserving tumor-reactivity and neoantigen-specificity shared with circulating immune cells. Objectives We performed comprehensive transcriptomic analyses to identify gene signatures common to circulating and tumor infiltrating lymphocytes in the context of clear cell renal cell carcinoma. Modulated genes also associated with disease outcome were validated in other cancer types. Findings Using bioinformatics, we identified practical diagnostic markers and actionable targets of the failed immune response. On circulating lymphocytes, three genes, LEF1, FASLG, and MMP9, could efficiently stratify patients from healthy control donors. From their associations with resistance to cancer immunotherapies and microbial infections, we uncovered not only pan-cancer, but pan-pathology failed immune response profiles. A prominent lymphocytic matrix metallopeptidase cell migration pathway, is central to a panoply of diseases and tumor immunogenicity, correlates with multi-cancer recurrence, and identifies a feasible, non-invasive approach to pan-pathology diagnoses. Conclusions The non-invasive differently expressed genes we have identified warrant future investigation towards the development of their potential in precision diagnostics and precision pan-disease immunotherapeutics.

TP53 mutations in high grade serous ovarian cancer and impact on clinical outcomes: a comparison of next generation sequencing and bioinformatics analyses

Objective

Mutations in TP53 are found in the majority of high grade serous ovarian cancers, leading to gain of function or loss of function of its protein product, p53, involved in oncogenesis. There have been conflicting reports as to the impact of the type of these on prognosis. We aim to further elucidate this relationship in our cohort of patients.

Methods

229 patients with high grade serous ovarian cancer underwent tumor profiling through an institutional molecular screening program with targeted next generation sequencing. TP53 mutations were classified using methods previously described in the literature. Immunohistochemistry on formalin-fixed paraffin embedded tissue was used to assess for TP53 mutation. Using divisive hierarchal clustering, we generated patient clusters with similar clinicopathologic characteristics to investigate differences in outcomes.

Results

Six different classification schemes of TP53 mutations were studied. These did not show an association with first platinum-free interval or overall survival. Next generation sequencing reliably predicted mutation in 80% of cases, similar to the proportion detected by immunohistochemistry. Divisive hierarchical clustering generated four main clusters, with cluster 3 having a significantly worse prognosis (p<0.0001; log-rank test). This cluster had a higher concentration of gain of function mutations and these patients were less likely to have undergone optimal debulking surgery.

Conclusions

Different classifications of TP53 mutations did not show an impact on outcomes in this study. Immunohistochemistry was a good predictor for TP53 mutation. Cluster analysis showed that a subgroup of patients with gain of function mutations (cluster 3) had a worse prognosis.

IID 2018 update: context-specific physical protein-protein interactions in human, model organisms and domesticated species

Knowing the set of physical protein-protein interactions (PPIs) that occur in a particular context-a tissue, disease, or other condition-can provide valuable insights into key research questions. However, while the number of identified human PPIs is expanding rapidly, context information remains limited, and for most non-human species context-specific networks are completely unavailable. The Integrated Interactions Database (IID) provides one of the most comprehensive sets of context-specific human PPI networks, including networks for 133 tissues, 91 disease conditions, and many other contexts. Importantly, it also provides context-specific networks for 17 non-human species including model organisms and domesticated animals. These species are vitally important for drug discovery and agriculture. IID integrates interactions from multiple databases and datasets. It comprises over 4.8 million PPIs annotated with several types of context: tissues, subcellular localizations, diseases, and druggability information (the latter three are new annotations not available in the previous version). This update increases the number of species from 6 to 18, the number of PPIs from ∼1.5 million to ∼4.8 million, and the number of tissues from 30 to 133. IID also now supports topology and enrichment analyses of returned networks. IID is available at http://ophid.utoronto.ca/iid.

The complex landscape of microRNAs in articular cartilage: biology, pathology, and therapeutic targets

The disabling degenerative disease osteoarthritis (OA) is prevalent among the global population. Articular cartilage degeneration is a central feature of OA; therefore, a better understanding of the mechanisms that maintain cartilage homeostasis is vital for developing effective therapeutic interventions. MicroRNAs (miRs) modulate cell signaling pathways and various processes in articular cartilage via posttranscriptional repression of target genes. As dysregulated miRs frequently alter the homeostasis of articular cartilage, modulating select miRs presents a potential therapeutic opportunity for OA. Here, we review key miRs that have been shown to modulate cartilage-protective or -destructive mechanisms and signaling pathways. Additionally, we use an integrative computational biology approach to provide insight into predicted miR gene targets that may contribute to OA pathogenesis, and highlight the complexity of miR signaling in OA by generating both unique and overlapping gene targets of miRs that mediate protective or destructive effects. Early OA detection would enable effective prevention; thus, miRs are being explored as diagnostic biomarkers. We discuss these ongoing efforts and the applicability of miR mimics and antisense inhibitors as potential OA therapeutics.

Abstract A26: Identification of a novel therapeutic target in lung adenocarcinoma

The reactivation of biologic signaling events that occur throughout fetal development has been observed during malignant cell transformation and tumor progression. Transcription factors are typically at the hub of these signaling events, such as NKX2-1 and several ETS transcription factors. ELF3 is an uncharacterized ETS family member that is highly expressed during fetal lung development and could play a biologic role in lung cancer based on its location within the recurrently gained chromosome 1q. We hypothesize that ELF3 is a novel oncogenic transcription factor and a therapeutic target.

Multiple independent datasets encompassing 1,685 clinical samples of lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), small cell lung cancer, and nonmalignant lung tissues were analyzed to establish the frequency of ELF3 overexpression and underlying genetic mechanisms of selection. ELF3 overexpression was validated by immunohistochemistry. Associations with patient survival were tested using the log-rank method. Isogenic cell lines were established to assess oncogenic phenotypes including tumor growth in a xenograft model. Protein-protein interaction (PPI) networks were constructed around ELF3, and integrated pathway analysis was performed to decipher the signaling network disruptions resulting from ELF3 overexpression.

ELF3 overexpression was frequently observed in LUAD (&gt;2-fold: BCCA 73% TCGA 40%), but was not observed in other lung cancer subtypes. Similarly, high ELF3 expression was significantly associated with poor overall survival of LUAD patients (p&lt;0.0001), but not LUSC patients. These clinical associations prompted further examination of ELF3 in the LUAD subtype of lung cancer. ELF3 knockdown in LUAD cell lines resulted in significantly reduced proliferation, viability, and anchorage-independent growth, demonstrating that ELF3 regulates oncogenic phenotypes. Loss of ELF3 abolished the ability of LUAD cells to establish tumors in xenograft mouse models, demonstrating the requirement of ELF3 expression for tumor growth. ELF3 overexpression is associated with remodeling of 23 direct PPI networks, resulting in loss of interaction with proteins such as NFKB1 and MYC, while forming new interactions with NKX2-1, HOXA5 and ERBB3. Pathway analysis suggests a transcriptional reprogramming from inflammatory and MAPK signallng in nonmalignant and ELF3-low tissues, to adhesion and motility pathways in transformed tissues displaying high ELF3 expression. Core pathways included cell cycle, apoptosis, WNT, and NOTCH signaling, agreeing with our cell models. While mutations in ELF3 were rare, up to 80% of LUAD patients harbored focal amplification, DNA gain, and/or promoter hypomethylation at the ELF3 locus, which resulted in transcript overexpression.

We have deciphered the oncogenic role of ELF3 in LUAD. Its requirement for tumor growth in our model indicates that therapeutic targeting of ELF3 could benefit the 73% of patients who display ELF3 overexpression.

Citation Format: Katey S.S. Enfield, Erin A. Marshall, Christine Anderson, Kevin W. Ng, Sara Rahmati, Zhaolin Xu, Calum E. MacAulay, Stephen Lam, William W. Lockwood, Raj Chari, Aly Karsan, Igor Jurisica, Wan L. Lam. Identification of a novel therapeutic target in lung adenocarcinoma [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr A26.

Ubiquitin ligase RNF8 suppresses Notch signaling to regulate mammary development and tumorigenesis

The E3 ubiquitin ligase RNF8 plays critical roles in maintaining genomic stability by promoting the repair of DNA double-strand breaks (DSBs) through ubiquitin signaling. Abnormal activation of Notch signaling and defective repair of DSBs promote breast cancer risk. Here, we found that low expression of the full-length RNF8 correlated with poor prognosis for breast cancer patients. Our data revealed that in addition to its role in the repair of DSBs, RNF8 regulated Notch1 signaling and cell-fate determination of mammary luminal progenitors. Mechanistically, RNF8 acted as a negative regulator of Notch signaling by ubiquitylating the active NOTCH1 protein (N1ICD), leading to its degradation. Consistent with abnormal activation of Notch signaling and impaired repair of DSBs in Rnf8-mutant mammary epithelial cells, we observed increased risk of mammary tumorigenesis in mouse models for RNF8 deficiency. Notably, deficiency of RNF8 sensitized breast cancer cells to combination of pharmacological inhibitors of Notch signaling and poly(ADP-ribose) polymerase (PARP), suggesting implications for treatment of breast cancer associated with impaired RNF8 expression or function.

Therapeutic Targeting of the Premetastatic Stage in Human Lung-to-Brain Metastasis

Brain metastases (BM) result from the spread of primary tumors to the brain and are a leading cause of cancer mortality in adults. Secondary tissue colonization remains the main bottleneck in metastatic development, yet this "premetastatic" stage of the metastatic cascade, when primary tumor cells cross the blood-brain barrier and seed the brain before initiating a secondary tumor, remains poorly characterized. Current studies rely on specimens from fully developed macrometastases to identify therapeutic options in cancer treatment, overlooking the potentially more treatable "premetastatic" phase when colonizing cancer cells could be targeted before they initiate the secondary brain tumor. Here we use our established brain metastasis initiating cell (BMIC) models and gene expression analyses to characterize premetastasis in human lung-to-BM. Premetastatic BMIC engaged invasive and epithelial developmental mechanisms while simultaneously impeding proliferation and apoptosis. We identified the dopamine agonist apomorphine to be a potential premetastasis-targeting drug. In vivo treatment with apomorphine prevented BM formation, potentially by targeting premetastasis-associated genes KIF16B, SEPW1, and TESK2 Low expression of these genes was associated with poor survival of patients with lung adenocarcinoma. These results illuminate the cellular and molecular dynamics of premetastasis, which is subclinical and currently impossible to identify or interrogate in human patients with BM. These data present several novel therapeutic targets and associated pathways to prevent BM initiation.Significance: These findings unveil molecular features of the premetastatic stage of lung-to-brain metastases and offer a potential therapeutic strategy to prevent brain metastases. Cancer Res; 78(17); 5124-34. ©2018 AACR.

Abstract 44: Characterization and targeting of a temporal micro-metastatic signature in human brain metastases

Metastases to the brain (BM) are the most common neoplasms to affect the adult central nervous system, arising in 40% of cancer patients and at a rate 10 times greater than primary brain tumors. Despite the prevalence and poor survival rates, therapeutic strategies for BM remain limited, and a substantial cause is the lack of proper preclinical models available to interrogate the intricacies of BM development. Previous work in our lab utilized BM samples from patient-derived lung-to-brain metastases to successfully establish clinically relevant in vivo models of BM. Here we further characterized the cells responsible for BM, termed brain metastasis initiation cells (BMIC). Patient-derived BMICs were injected via intracranial (BT), intracardiac (IC) and intrathoracic (IT) routes into NOD/SCID mice and re-isolated at different stages of metastatic progression. We isolated cells from primary lung tumors (LT), cells injected via intra-thoracic route that crossed the blood brain barrier to seed the brain forming micro-metastases (BMIT), and cells injected via intracardiac route that seeded large macro-metastases (BMIC). Through RNA sequencing we determined cells from BMIT (micro-metastasis stage) to retain a vastly different genetic profile compared to BMICs isolated at other stages of metastasis. Several of these genes belonged to pathways implicated in autonomic central nervous system neoplasms and neural development. Through connectivity mapping of BMIT profiles we discovered drugs that could inhibit the micro-metatsasis signature, and further in vitro validation revealed apomorphine to reduce BMIC sphere formation and proliferation. In vivo treatment with apomorphine blocked both micro- and macro-metastatic stages of our BMIC model. Of 5 BMIT genes identified to be specifically targeted by apomorphine, KIF16B, TESK2 and SEPW1 were shown to have significant value when applied as an independent prognostic signature in a cohort of lung adenocarcinoma patients. Future work will further validate the efficacy of apomorphine in targeting BMICs in primary lung cancer patient samples. With this work we present a possible new avenue for therapeutic targeting toward the prevention of BM development, where it is anticipated to transform a uniformly fatal disease into one that is eminently more treatable.

Citation Format: Mohini Singh, Chitra Venugopal, Tomas Tokar, Nicole McFarlane, Minomi Subhapanditha, David Bakhshinyan, Maleeha Qazi, Parvez Vora, Neil Savage, Naresh K. Murty, Igor Jurisica, Sheila K. Singh. Characterization and targeting of a temporal micro-metastatic signature in human brain metastases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 44.

In silico cancer research towards 3R

BACKGROUND

Improving our understanding of cancer and other complex diseases requires integrating diverse data sets and algorithms. Intertwining in vivo and in vitro data and in silico models are paramount to overcome intrinsic difficulties given by data complexity. Importantly, this approach also helps to uncover underlying molecular mechanisms. Over the years, research has introduced multiple biochemical and computational methods to study the disease, many of which require animal experiments. However, modeling systems and the comparison of cellular processes in both eukaryotes and prokaryotes help to understand specific aspects of uncontrolled cell growth, eventually leading to improved planning of future experiments. According to the principles for humane techniques milestones in alternative animal testing involve in vitro methods such as cell-based models and microfluidic chips, as well as clinical tests of microdosing and imaging. Up-to-date, the range of alternative methods has expanded towards computational approaches, based on the use of information from past in vitro and in vivo experiments. In fact, in silico techniques are often underrated but can be vital to understanding fundamental processes in cancer. They can rival accuracy of biological assays, and they can provide essential focus and direction to reduce experimental cost.

MAIN BODY

We give an overview on in vivo, in vitro and in silico methods used in cancer research. Common models as cell-lines, xenografts, or genetically modified rodents reflect relevant pathological processes to a different degree, but can not replicate the full spectrum of human disease. There is an increasing importance of computational biology, advancing from the task of assisting biological analysis with network biology approaches as the basis for understanding a cell's functional organization up to model building for predictive systems.

CONCLUSION

Underlining and extending the in silico approach with respect to the 3Rs for replacement, reduction and refinement will lead cancer research towards efficient and effective precision medicine. Therefore, we suggest refined translational models and testing methods based on integrative analyses and the incorporation of computational biology within cancer research.

Encompassing new use cases - level 3.0 of the HUPO-PSI format for molecular interactions

BACKGROUND

Systems biologists study interaction data to understand the behaviour of whole cell systems, and their environment, at a molecular level. In order to effectively achieve this goal, it is critical that researchers have high quality interaction datasets available to them, in a standard data format, and also a suite of tools with which to analyse such data and form experimentally testable hypotheses from them. The PSI-MI XML standard interchange format was initially published in 2004, and expanded in 2007 to enable the download and interchange of molecular interaction data. PSI-XML2.5 was designed to describe experimental data and to date has fulfilled this basic requirement. However, new use cases have arisen that the format cannot properly accommodate. These include data abstracted from more than one publication such as allosteric/cooperative interactions and protein complexes, dynamic interactions and the need to link kinetic and affinity data to specific mutational changes.

RESULTS

The Molecular Interaction workgroup of the HUPO-PSI has extended the existing, well-used XML interchange format for molecular interaction data to meet new use cases and enable the capture of new data types, following extensive community consultation. PSI-MI XML3.0 expands the capabilities of the format beyond simple experimental data, with a concomitant update of the tool suite which serves this format. The format has been implemented by key data producers such as the International Molecular Exchange (IMEx) Consortium of protein interaction databases and the Complex Portal.

CONCLUSIONS

PSI-MI XML3.0 has been developed by the data producers, data users, tool developers and database providers who constitute the PSI-MI workgroup. This group now actively supports PSI-MI XML2.5 as the main interchange format for experimental data, PSI-MI XML3.0 which additionally handles more complex data types, and the simpler, tab-delimited MITAB2.5, 2.6 and 2.7 for rapid parsing and download.

Large-scale discovery of previously undetected microRNAs specific to human liver

MicroRNAs (miRNAs) are crucial regulators of gene expression in normal development and cellular homeostasis. While miRNA repositories contain thousands of unique sequences, they primarily contain molecules that are conserved across several tissues, largely excluding lineage and tissue-specific miRNAs. By analyzing small non-coding RNA sequencing data for abundance and secondary RNA structure, we discovered 103 miRNA candidates previously undescribed in liver tissue. While expression of some of these unannotated sequences is restricted to non-malignant tissue, downregulation of most of the sequences was detected in liver tumors, indicating their importance in the maintenance of liver homeostasis. Furthermore, target prediction revealed the involvement of the unannotated miRNA candidates in fatty-acid metabolism and tissue regeneration, which are key pathways in liver biology. Here, we provide a comprehensive analysis of the undiscovered liver miRNA transcriptome, providing new resources for a deeper exploration of organ-specific biology and disease.

The ablation of the matricellular protein EMILIN2 causes defective vascularization due to impaired EGFR-dependent IL-8 production affecting tumor growth

EMILIN2 is an extracellular matrix constituent playing an important role in angiogenesis; however, the underlying mechanism is unknown. Here we show that EMILIN2 promotes angiogenesis by directly binding epidermal growth factor receptor (EGFR), which enhances interleukin-8 (IL-8) production. In turn, IL-8 stimulates the proliferation and migration of vascular endothelial cells. Emilin2 null mice were generated and exhibited delayed retinal vascular development, which was rescued by the administration of the IL-8 murine ortholog MIP-2. Next, we assessed tumor growth and tumor-associated angiogenesis in these mice. Tumor cell growth in Emilin2 null mice was impaired as well as the expression of MIP-2. The vascular density of the tumors developed in Emilin2 null mice was prejudiced and vessels perfusion, as well as response to chemotherapy, decreased. Accordingly, human tumors expressing high levels of EMILIN2 were more responsive to chemotherapy. These results point at EMILIN2 as a key microenvironmental cue affecting vessel formation and unveil the possibility to develop new prognostic tools to predict chemotherapy efficacy.

Abstract P2-01-05: Comprehensive analysis of genomic alterations in tumor tissue associated with presence of various subpopulations of circulating tumor cells (CTCs) in primary breast cancer

Background: CTCs play a major role in tumor dissemination and progression, and represent one of the key components of the metastatic cascade. The aim of this study was to identify signaling pathways associated with presence of CTCs in primary breast cancer (PBC) patients using a comprehensive genomics approach.

Methods: This translational study included 78 patients with PBC. CTCs were detected before surgery by quantitative RT-PCR assay for expression of epithelial (EP; CK19) or epithelial-mesenchymal transition (EMT) genes (TWIST1, SNAIL1, SLUG, ZEB1). Total DNA and RNA were extracted, in parallel, from fresh frozen primary tumor and the microRNA and mRNA expression profiles were obtained using Human microRNA Microarray v21.0 and SurePrint G3 Human Gene Expression v3 (Agilent Technologies). Next generation sequencing (NGS) was performed by Illumina Multiplex Sequencing using MiSeq Sequencing Reagent Kit V3.

Results:Mutations in BRCA1/2 genes in tumor tissue were more common in patients with epithelial CTCs (CTC_EP) compared to patients without epithelial CTCs in peripheral blood (23.5% vs. 0%, p = 0.02), while there were no mutations in specific genes associated with CTC with EMT phenotype (CTC_EMT).Further, we identified 90 genes and 7 miRs that were expressed at significantly different levels in tumors with presence of CTC_EP and 199 genes and 13 miRs specifically associated with CTC_EMT, compared to tumors with non-detectable CTCs. We also identified 39 overlapping genes and 7 miRs, that were expressed at significantly different levels in tumors with CTC_EP and/or CTC_EMT compared to tumors with non-detectable CTCs. Overlapping genes and miRs with highest different levels in expression were ATAD3A, TMEM201, DCPS, DOCK9-AS2, TRAF2 and miR-5195-3p, miR-188-5p, miR-6780a-5p, miR-6757-5p. Signalling pathways associated with these genomic alterations belong to several critically functional groups, such as immune response, signal transduction, cell proliferation, cell cycle progression, or apoptosis were significantly differentially based on CTCs status.

Conclusions: We identified for the first time various genomic alterations in primary tumor tissue of PBC associated with different CTCs subpopulations in peripheral blood. We hypothesize that these genomic alterations could play a role in tumor dissemination and progression and might lead to identification of new therapeutic targets.

Citation Format: Mego M, Tokar T, Minarik G, Hajduk M, Karaba M, Benca J, Sedlackova T, Repiska G, Krasnicanova L, Macuch J, Sieberova G, Pindak D, Cristofanilli M, Reuben JM, Jurisica I, Mardiak J. Comprehensive analysis of genomic alterations in tumor tissue associated with presence of various subpopulations of circulating tumor cells (CTCs) in primary breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-01-05.

Differentially expressed microRNAs in lung adenocarcinoma invert effects of copy number aberrations of prognostic genes

In many cancers, significantly down- or upregulated genes are found within chromosomal regions with DNA copy number alteration opposite to the expression changes. Generally, this paradox has been overlooked as noise, but can potentially be a consequence of interference of epigenetic regulatory mechanisms, including microRNA-mediated control of mRNA levels.

To explore potential associations between microRNAs and paradoxes in non-small-cell lung cancer (NSCLC) we curated and analyzed lung adenocarcinoma (LUAD) data, comprising gene expressions, copy number aberrations (CNAs) and microRNA expressions. We integrated data from 1,062 tumor samples and 241 normal lung samples, including newly-generated array comparative genomic hybridization (aCGH) data from 63 LUAD samples.

We identified 85 “paradoxical” genes whose differential expression consistently contrasted with aberrations of their copy numbers. Paradoxical status of 70 out of 85 genes was validated on sample-wise basis using The Cancer Genome Atlas (TCGA) LUAD data. Of these, 41 genes are prognostic and form a clinically relevant signature, which we validated on three independent datasets. By meta-analysis of results from 9 LUAD microRNA expression studies we identified 24 consistently-deregulated microRNAs. Using TCGA-LUAD data we showed that deregulation of 19 of these microRNAs explains differential expression of the paradoxical genes.

Our results show that deregulation of paradoxical genes is crucial in LUAD and their expression pattern is maintained epigenetically, defying gene copy number status.

Abstract B01: MicroRNA expression in tumors and liquid biopsy samples from patients with pancreatic ductal adenocarcinoma: Identification of clinically relevant pathways

Background: Pancreatic carcinoma leads to 6.9% and 4% of all cancer-related deaths in the United States and Brazil, respectively. Pancreatic ductal adenocarcinoma (PDAC) comprises ~90% of pancreatic cancer cases and patients have a poor prognosis, mainly due to asymptomatic disease that leads to late diagnosis. Considering that diagnosis of disease in advanced stages is one of the main factors associated with mortality, the identification of circulating biomarkers in tumor and plasma (liquid biopsy) from patients is believed to be a clinically relevant strategy for early disease detection and treatment response monitoring.

Objectives: We aimed to identify global microRNA (miRNA) expression changes in primary untreated tumors and plasma from patients diagnosed with PDAC. Deregulated miRNAs were mapped to miRNA-target genes, and PDAC tumorigenesis pathways were identified.

Patients and Methods: 24 formalin-fixed, paraffin-embedded (FFPE) tumors and their paired normal pancreatic tissues were needle microdissected. In addition, 4 plasma samples from patients diagnosed with PDAC and 10 age-matched controls from individuals without disease were obtained. All samples were profiled using the TaqMan Array Human MicroRNA Cards (TLDA) (card A, v3.0) (Life Technologies). Data analysis was performed using ExpressionSuite Software v1.0.3. Computational miRNA target gene identification was performed using microRNA Data Integration Portal (mirDIP). Comprehensive pathway enrichment analysis based on identified miRNAs and target genes was performed using Pathway Data Integration Portal (pathDIP). Data were considered significant with Bonferroni corrected p-values.

Results and Discussion: 63 miRNAs (33 over- and 30 underexpressed) were significantly deregulated (FC≥2 and p&lt;0.05) in PDAC compared to paired normal pancreatic tissue. In plasma, 25 miRNAs were under- and 16 were overexpressed. Of these, 6 miRNAs were commonly deregulated in both tumor and plasma. Interestingly, 420 genes were identified as targeted by at least 2 of these 6 miRNAs. AKT, Insulin and VEGFR1 signaling pathways were identified as the most significant disease-associated mechanisms affected by miRNA target genes.

Conclusions: A 6-miRNA subset is commonly deregulated in plasma and tumors and associated with important signaling pathways in PDAC. miRNAs are likely valuable diagnostic and predictive biomarkers for patients with PDAC. Our data build on existing knowledge that liquid biopsy samples are a clinically useful and minimally invasive source for the development of molecular testing that should be translated to the clinical setting.

Financial Support: TFF was awarded grant #2014/00367-4, São Paulo Research Foundation (FAPESP); TFF and NB a CAPES-DS Master's Science fellowship. Computational analysis was supported in part by Canada Research Chair Program (#225404), Canada Foundation for Innovation (CFI #225404, #30865), Ontario Research Fund (#34876), IBM (IJ).

Citation Format: Tainara F. Felix,* Natalia Bertoni,* Tomas Tokar, Maria A. M. Rodrigues, Rogerio A. Oliveira, Claudia N. Hasimoto, Juan C. Llanos, Igor Jurisica, Sandra A. Drigo, Robson F. Carvalho, Patricia P. Reis. MicroRNA expression in tumors and liquid biopsy samples from patients with pancreatic ductal adenocarcinoma: Identification of clinically relevant pathways [abstract]. In: Proceedings of the AACR International Conference held in cooperation with the Latin American Cooperative Oncology Group (LACOG) on Translational Cancer Medicine; May 4-6, 2017; São Paulo, Brazil. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(1_Suppl):Abstract nr B01.

Prediction of Protein-Protein Interactions

The authors provide an overview of physical protein-protein interaction prediction, covering the main strategies for predicting interactions, approaches for assessing predictions, and online resources for accessing predictions. This unit focuses on the main advancements in each of these areas over the last decade. The methods and resources that are presented here are not an exhaustive set, but characterize the current state of the field-highlighting key challenges and achievements. © 2017 by John Wiley & Sons, Inc.

RNAi screen identifies essential regulators of human brain metastasis-initiating cells

Brain metastases (BM) are the most common brain tumor in adults and are a leading cause of cancer mortality. Metastatic lesions contain subclones derived from their primary lesion, yet their functional characterization is limited by a paucity of preclinical models accurately recapitulating the metastatic cascade, emphasizing the need for a novel approach to BM and their treatment. We identified a unique subset of stem-like cells from primary human patient brain metastases, termed brain metastasis-initiating cells (BMICs). We now establish a BMIC patient-derived xenotransplantation (PDXT) model as an investigative tool to comprehensively interrogate human BM. Using both in vitro and in vivo RNA interference screens of these BMIC models, we identified SPOCK1 and TWIST2 as essential BMIC regulators. SPOCK1 in particular is a novel regulator of BMIC self-renewal, modulating tumor initiation and metastasis from the lung to the brain. A prospective cohort of primary lung cancer specimens showed that SPOCK1 was overexpressed only in patients who ultimately developed BM. Protein-protein interaction network mapping between SPOCK1 and TWIST2 identified novel pathway interactors with significant prognostic value in lung cancer patients. Of these genes, INHBA, a TGF-β ligand found mutated in lung adenocarcinoma, showed reduced expression in BMICs with knockdown of SPOCK1. In conclusion, we have developed a useful preclinical model of BM, which has served to identify novel putative BMIC regulators, presenting potential therapeutic targets that block the metastatic process, and transform a uniformly fatal systemic disease into a locally controlled and eminently more treatable one.