Towards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning

Cancer is one of the leading causes of death worldwide and can be caused by environmental aspects (for example, exposure to asbestos), by human behavior (such as smoking), or by genetic factors. To understand which genes might be involved in patients’ survival, researchers have invented prognostic genetic signatures: lists of genes that can be used in scientific analyses to predict if a patient will survive or not. In this study, we joined together five different prognostic signatures, each of them related to a specific cancer type, to generate a unique pan-cancer prognostic signature, that contains 207 unique probesets related to 187 unique gene symbols, with one particular probeset present in two cancer type-specific signatures (203072_at related to the MYO1E gene). We applied our proposed pan-cancer signature with the Random Forests machine learning method to 57 microarray gene expression datasets of 12 different cancer types, and analyzed the results. We also compared the performance of our pan-cancer signature with the performances of two alternative prognostic signatures, and with the performances of each cancer type-specific signature on their corresponding cancer type-specific datasets. Our results confirmed the effectiveness of our prognostic pan-cancer signature. Moreover, we performed a pathway enrichment analysis, which indicated an association between the signature genes and a protein-protein interaction analysis, that highlighted PIK3R2 and FN1 as key genes having a fundamental relevance in our signature, suggesting an important role in pan-cancer prognosis for both of them.

Cold Spray: Over 30 Years of Development Toward a Hot Future

Cold Spray (CS) is a deposition process, part of the thermal spray family. In this method, powder particles are accelerated at supersonic speed within a nozzle; impacts against a substrate material triggers a complex process, ultimately leading to consolidation and bonding. CS, in its modern form, has been around for approximately 30 years and has undergone through exciting and unprecedented developmental steps. In this article, we have summarized the key inventions and sub-inventions which pioneered the innovation aspect to the process that is known today, and the key breakthroughs related to the processing of materials CS is currently mastering. CS has not followed a liner path since its invention, but an evolution more similar to a hype cycle: high initial growth of expectations, followed by a decrease in interest and a renewed thrust pushed by a number of demonstrated industrial applications. The process interest is expected to continue (gently) to grow, alongside with further development of equipment and feedstock materials specific for CS processing. A number of current applications have been identified the areas that the process is likely to be the most disruptive in the medium-long term future have been laid down.

Defining imaging sub-phenotypes of psoriatic arthritis: integrative analysis of imaging data and gene expression in a PsA patient cohort

OBJECTIVES

To define imaging sub-phenotypes in patients with PsA; determine their association with whole blood gene expression and identify biological pathways characterizing the sub-phenotypes.

METHODS

Fifty-five patients with PsA ready to initiate treatment for active disease were prospectively recruited. We performed musculoskeletal ultrasound assessment of the extent of inflammation in the following domains: synovitis, peritenonitis, tenosynovitis and enthesitis. Peripheral whole blood was profiled with RNAseq, and gene expression data were obtained. First, unsupervised cluster analysis was performed to define imaging sub-phenotypes that reflected the predominant tissue involved. Subsequently, principal component analysis was used to determine the association between imaging-defined sub-phenotypes and peripheral blood gene expression profile. Pathway enrichment analysis was performed to identify underlying mechanisms that characterize individual sub-phenotypes.

RESULTS

Cluster analysis revealed three imaging sub-phenotypes: (i) synovitis predominant [n = 31 (56%)]; (ii) enthesitis predominant [n = 13 (24%)]; (iii) peritenonitis predominant [n = 11 (20%)]. The peritenonitis-predominant sub-phenotype had the most severe clinical joint involvement, whereas the enthesitis-predominant sub-phenotype had the highest tender entheseal count. Unsupervised clustering of gene expression data identified three sub-phenotypes that partially overlapped with the imaging sub-phenotypes suggesting biological and clinical relevance of these sub-phenotypes. We therefore characterized enriched differential pathways, which included: immune system (innate system, B cells and neutrophil degranulation), complement system, platelet activation and coagulation function.

CONCLUSIONS

We identified three sub-phenotypes based on the predominant tissue involved in patients with active PsA. Distinct biological pathways may underlie these imaging sub-phenotypes seen in PsA, suggesting their biological and clinical importance.

miRAnno-network-based functional microRNA annotation

MOTIVATION

Functional annotation is a common part of microRNA (miRNA)-related research, typically carried as pathway enrichment analysis of the selected miRNA targets. Here, we propose miRAnno, a fast and easy-to-use web application for miRNA annotation.

RESULTS

miRAnno uses comprehensive molecular interaction network and random walks with restart to measure the association between miRNAs and individual pathways. Independent validation shows that miRAnno achieves higher signal-to-noise ratio compared to the standard enrichment analysis.

AVAILABILITY AND IMPLEMENTATION

miRAnno is freely available at https://ophid.utoronto.ca/miRAnno/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

HSSAGA: Designation and scheduling of nurses for taking care of COVID-19 patients using novel method of Hybrid Salp Swarm Algorithm and Genetic Algorithm

The COVID-19 pandemic is viewed as the most basic worldwide disaster that humankind has observed since the second World War. There is no report of any clinically endorsed antiviral medications or antibodies that are successful against COVID-19. It has quickly spread everywhere, presenting tremendous well-being, financial, ecological, and social difficulties to the whole human populace. The COVID flare-up is seriously disturbing the worldwide economy. Practically all the countries are battling to hinder the transmission of the malady by testing and treating patients, isolating speculated people through contact following, confining huge social affairs, keeping up total or incomplete lockdown, etc. Proper scheduling of nursing workers and optimal designation of nurses may significantly affect the quality of clinical facilities. It is delivered by eliminating unbalanced workloads or undue stress, which could lead to decreased nurse performance and potential human errors., Nurses are frequently asked to leave while caring for all sick patients. However, regular scheduling formulas are not thought to consider this possibility because they are out of scheduling control in typical scenarios. In this paper, a novel model of the Hybrid Salp Swarm Algorithm and Genetic Algorithm (HSSAGA) is proposed to solve nurses’ scheduling and designation. The findings of the suggested test function algorithm demonstrate that this algorithm has outperformed state-of-the-art approaches.

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.

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.

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

Complexities in Genetics of Psoriatic Arthritis

PURPOSE OF THE REVIEW

To provide a general overview and current challenges regarding the genetics of psoriatic disease. With the use of integrative medicine, multiple candidate loci identified to date in psoriatic disease will be annotated, summarized, and visualized. Recent studies reporting differences in genetic architecture between psoriatic arthritis and cutaneous-only psoriasis will be highlighted.

RECENT FINDINGS

Focusing on functional pathways that connect previously identified genetic variants can increase our understanding of psoriatic diseases. The genetic architecture differs between psoriatic arthritis and cutaneous-only psoriasis with arthritis-specific signals in linkage disequilibrium independent of the published psoriasis signals. Integrative medicine is helpful in understanding cellular mechanisms of psoriatic diseases. Careful selection of the psoriatic disease cohort has translated into mechanistic differences among psoriatic arthritis and cutaneous psoriasis.

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.

A combined panel of circulating microRNA as a diagnostic tool for detection of the non-small cell lung cancer

BACKGROUND

Recently, much attention has been paid to use circulating microRNAs (miRs) as a non-invasive tumor marker. The present study for the first time was designed to evaluate concurrent use of miR-21, miR-638, miR148 and miR-152 as putative diagnostic tool for detection of non-small cell lung carcinoma (NSCLC).

METHODS

Forty-three patients diagnosed as primary NSCLC was included in this study. The level of selected miRs was measured in whole blood specimens of patients and controls. The corresponding values were also obtained in stages I-IV. We also assessed possible correlation between selected miRs and the clinicopathological findings of studied individuals.

RESULTS

miR-21 was increased in patients compared to controls (P = 0.004). In contrast, circulating miR-638, miR-148 and miR-152 was observed to be down-regulated in NSCLC patients than controls (P = 0.001, 0.003, 0.053, respectively). Rise in miR-21-5p expression and decreased blood level of miR-148a-3p was associated with higher stage of NSCLC. The highest sensitivity (90%) was observed for miR-21 while miR-148 had the highest specificity (71%). The corresponding sensitivity and specificity for combined-miRs-panel was 96.4% and 86.67%, respectively.

CONCLUSION

In summary, our data suggested the diagnostic importance of combined-miR-panel including miR-21, miR-638, miR148 and miR-152 for effective discrimination of NSCLC from non-cancerous subjects.

Micro-Residual Stress Measurement in Nanocomposite Reinforced Polymers

In the present study, residual stress is measured in fiber-reinforced SWCNT/epoxy at weight fractions of 0.1% and 0.5% with a cross-ply layup on a micro-scale. The mechanical properties of the SWCNT/epoxy composites were determined by tensile testing and the Young's modulus of the epoxy increased moderately with the addition of CNTs. The micro-residual stress of the cross-ply CF/epoxy and CNF-reinforced CF/epoxy laminates were measured using a new experimental approach. The micro-hole was milled by laser beam and the surface displacement was recorded by SEM after milling. In order to determine the residual stress from the recorded strain, the calibration matrix was calculated using the finite element method. The residual stress was obtained at a certain hole depth of specimens. The reliability of this approach was assessed by comparing the residual stress measurements from this method and from the standard hole-drilling method. The experimental results of the present approach confirmed that laser hole drilling SEM-DIC has excellent potential as a reliable method for measuring residual stress in polymer nanocomposites. Generally, CNT agglomerates, especially in high weight fractions, increased the micro-residual stress. An analytical method based on classical theory was used to calculate the residual stress and was compared with the experimental results. Good agreement was found between the results of the analytical methods and the experimental measurement.

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.

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.

pathDIP: an annotated resource for known and predicted human gene-pathway associations and pathway enrichment analysis

Molecular pathway data are essential in current computational and systems biology research. While there are many primary and integrated pathway databases, several challenges remain, including low proteome coverage (57%), low overlap across different databases, unavailability of direct information about underlying physical connectivity of pathway members, and high fraction of protein-coding genes without any pathway annotations, i.e. ‘pathway orphans’. In order to address all these challenges, we developed pathDIP, which integrates data from 20 source pathway databases, ‘core pathways’, with physical protein–protein interactions to predict biologically relevant protein–pathway associations, referred to as ‘extended pathways’. Cross-validation determined 71% recovery rate of our predictions. Data integration and predictions increase coverage of pathway annotations for protein-coding genes to 86%, and provide novel annotations for 5732 pathway orphans. PathDIP (http://ophid.utoronto.ca/pathdip) annotates 17 070 protein-coding genes with 4678 pathways, and provides multiple query, analysis and output options.

Topoisomerase IV, alone, unknots DNA in E. coli

Knotted DNA has potentially devastating effects on cells. By using two site-specific recombination systems, we tied all biologically significant simple DNA knots in Escherichia coli. When topoisomerase IV activity was blocked, either with a drug or in a temperature-sensitive mutant, the knotted recombination intermediates accumulated whether or not gyrase was active. In contrast to its decatenation activity, which is strongly affected by DNA supercoiling, topoisomerase IV unknotted DNA independently of supercoiling. This differential supercoiling effect held true regardless of the relative sizes of the catenanes and knots. Finally, topoisomerase IV unknotted DNA equally well when DNA replication was blocked with hydroxyurea. We conclude that topoisomerase IV, not gyrase, unknots DNA and that it is able to access DNA in the cell freely. With these results, it is now possible to assign completely the topological roles of the topoisomerases in E. coli. It is clear that the topoisomerases in the cell have distinct and nonoverlapping roles. Consequently, our results suggest limitations in assigning a physiological function to a protein based upon sequence similarity or even upon in vitro biochemical activity.

Isothermic hemodialysis and ultrafiltration

The increase in patient temperature during hemodialysis is explained by hemodynamic compensation during ultrafiltration and hypovolemia that leads to peripheral vasoconstriction and reduced heat losses. We analyzed 51 stable high-efficiency hemodialysis treatments in 27 patients during isothermic dialysis in which body temperature was maintained at a constant level (+/-0.1 degrees C) using the temperature-control option of the Blood Temperature Monitor (BTM; Fresenius Medical Care, Bad Homburg, Germany). Hemodialysis was delivered using ultrapure water (limulus amebocyte lysate test < 0. 06 endotoxin units/mL) at mean blood flows of 410 +/- 40 mL/min. During treatments lasting 178 +/- 23 minutes, 4.8% +/- 1.4% of postdialysis body weight (W%) and 9.5% +/- 2.5% of postdialysis body water were removed using mean ultrafiltration rates of 1.1 +/- 0.3 L/h. Dialysate temperatures significantly decreased from 35.9 degrees C +/- 0.3 degrees C to 35.6 degrees C +/- 0.6 degrees C during hemodialysis. During these treatments, 187 +/- 69 kJ of thermal energy were removed from the patients through the extracorporeal circulation using cool dialysate. Extracorporeal heat flow was 17 +/- 6 W. Energy expenditure (H) estimated from anthropometric data was 65 +/- 12 W. Thus, 28% +/- 10% of estimated energy expenditure (H%) was removed during isothermic dialysis. A highly significant correlation was observed between H% and W% (H% = -5.6 * W%; r(2) = 0.91; P < 0.0001). This result is in support of the volume hypothesis of intradialytic heat accumulation and provides a rule of thumb to estimate extracorporeal cooling requirements for isothermic dialysis. Approximately 6% of H must be removed through the extracorporeal circulation for each percent of ultrafiltration-induced body-weight change. The importance of body temperature control during hemodialysis increases with increased ultrafiltration requirements.

Structure-function analysis of the mammalian DNA polymerase beta active site: role of aspartic acid 256, arginine 254, and arginine 258 in nucleotidyl transfer

The crystal structure of the catalytic domain of rat DNA polymerase beta revealed that Asp256 is located in proximity to the previously identified active site residues Asp190 and Asp192. We have prepared and kinetically characterized the nucleotidyl transfer activity of wild type and several mutant forms of human and rat pol beta. Herein we report steady-state kinetic determinations of KmdTTP, Km(dT)16, and kcat for mutants in residue Asp256 and two neighboring residues, Arg254 and Arg258, all centrally located on strand beta 7 in the pol beta structure. Mutation of Asp256 to alanine abolished the enzymatic activity of pol beta. Conservative replacement with glutamic acid (D256E) led to a 320-fold reduction of kcat compared to wild type. Replacement of Arg254 with an alanine (R254A) resulted in a 50-fold reduction of kcat compared to wild type. The Km(dT)16 of D256E and R254A increased about 18-fold relative to wild type. Replacement of Arg254 with a lysine resulted in a 15-fold decrease in kcat, and a 5-fold increase in the Km(dT)16. These kinetic observations support a role of Asp256 and Arg254 in the positioning of divalent metal ions and substrates in precise geometrical orientation for efficient catalysis. The mutation of Arg258 to alanine (R258A) resulted in a 10-fold increase in KmdTTP and a 65-fold increase in Km(dT)16 but resulted in no change of kcat. These observations are discussed in the context of the three-dimensional structures of the catalytic domain of pol beta and the ternary complex of pol beta, ddCTP, and DNA.

RNase D, a reported new activity associated with HIV-1 reverse transcriptase, displays the same cleavage specificity as Escherichia coli RNase III

RNase D was recently reported as a new enzymatic activity associated with HIV-1 reverse transcriptase (RT), cleaving RNA at two positions within the double-stranded region of the tRNA primer-viral RNA template complex (Ben-Artzi et al., Proc. Natl. Acad. Sci. USA 89 (1992) 927-931). This would make RNase D a fourth distinct activity of HIV-1 RT, in addition to RNA- and DNA-dependent DNA polymerase and RNase H. Using a specific substrate containing tRNA(Lys,3) hybridized to the primer binding site, we were able to detect the reported RNase D activity in our preparations of recombinant HIV-1 RT. This activity was also present in several active-site mutants of RT, suggesting that it is independent of the RNase H and polymerase functionalities of RT. Furthermore, we found that the cleavage specificity of RNase D is the same as that of RNase III isolated from E.coli. A likely explantation of these results--that the observed RNase D activity is attributable to traces of RNase III contamination--was further strengthened by the finding that the recombinant preparations of HIV-1 RT can specifically cleave a phage T7-derived double-stranded RNA processing signal, which has been used as a model substrate for detection of E.coli RNase III. Moreover, RT purified from an RNase III- strain of E.coli displayed no cleavage of the tRNA primer-RNA template complex.