RNA-seq Expression Data Research Articles

Identification of four gastric cancer subtypes based on genetic analysis of cholesterogenic and glycolytic pathways

ABSTRACT Warburg phenomenon refers to the development of unique metabolic patterns during the growth of tumor cells. This study stratified gastric cancer into prognostic metabolic subgroups according to changes in gene expressions related to glycolysis and cholesterol synthesis. The RNA-seq expression data, single nucleotide variants (SNV), short insertions and deletions (InDel) mutation data, copy number variation (CNV) data and clinical follow-up information data of gastric cancer tissues were downloaded from The Cancer Genome Atlas (TCGA) database. ConsensusClusterPlus was used to stratify the metabolic subtypes of gastric cancer. Four metabolic subtypes (Cholesterogenic, Glycolytic, Mixed and Quiescent) of gastric cancer were identified, and patients with cholesterogenic tumors had the longest disease-specific survival (DSS). Genome-wide analysis showed that aberrant amplification of TP53 and MYC in gastric cancer was associated with abnormal cholesterol anabolic metabolism. The mRNA levels of mitochondrial pyruvate carriers 1 and 2 (MPC1/2) differed among the four subtypes. Tumors in the glycolytic group showed a higher PDCD1. A genomic signature based on tumor metabolism of different cancer types was established. This study showed that genes related to glucose and lipid metabolism play an important role in gastric cancer and facilitate a personalized treatment of gastric cancer.

Integrated Analysis of Immunity- and Ferroptosis-Related Biomarker Signatures to Improve the Prognosis Prediction of Hepatocellular Carcinoma.

BackgroundHepatocellular carcinoma (HCC) is a common malignant tumor with high mortality and poor prognoses around the world. Ferroptosis is a new form of cell death, and some studies have found that it is related to cancer immunotherapy. The aim of our research was to find immunity- and ferroptosis-related biomarkers to improve the treatment and prognosis of HCC by bioinformatics analysis.MethodsFirst, we obtained the original RNA sequencing (RNA-seq) expression data and corresponding clinical data of HCC from The Cancer Genome Atlas (TGCA) database and performed differential analysis. Second, we used immunity- and ferroptosis-related differentially expressed genes (DEGs) to perform a computational difference algorithm and Cox regression analysis. Third, we explored the potential molecular mechanisms and properties of immunity- and ferroptosis-related DEGs by computational biology and performed a new prognostic index based on immunity- and ferroptosis-related DEGs by multivariable Cox analysis. Finally, we used HCC data from International Cancer Genome Consortium (ICGC) data to perform validation.ResultsWe obtained 31 immunity (p < 0.001)- and 14 ferroptosis (p < 0.05)-related DEGs correlated with overall survival (OS) in the univariate Cox regression analysis. Then, we screened five immunity- and two ferroptosis-related DEGs (HSPA4, ISG20L2, NRAS, IL17D, NDRG1, ACSL4, and G6PD) to establish a predictive model by multivariate Cox regression analysis. Receiver operating characteristic (ROC) and Kaplan–Meier (K–M) analyses demonstrated a good performance of the seven-biomarker signature. Functional enrichment analysis including Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that the seven-biomarker signature was mainly associated with HCC-related biological processes such as nuclear division and the cell cycle, and the immune status was different between the two risk groups.ConclusionOur results suggest that this specific seven-biomarker signature may be clinically useful in the prediction of HCC prognoses beyond conventional clinicopathological factors. Moreover, it also brings us new insights into the molecular mechanisms of HCC.

Ideal: an R/Bioconductor package for interactive differential expression analysis

BackgroundRNA sequencing (RNA-seq) is an ever increasingly popular tool for transcriptome profiling. A key point to make the best use of the available data is to provide software tools that are easy to use but still provide flexibility and transparency in the adopted methods. Despite the availability of many packages focused on detecting differential expression, a method to streamline this type of bioinformatics analysis in a comprehensive, accessible, and reproducible way is lacking.ResultsWe developed the ideal software package, which serves as a web application for interactive and reproducible RNA-seq analysis, while producing a wealth of visualizations to facilitate data interpretation. ideal is implemented in R using the Shiny framework, and is fully integrated with the existing core structures of the Bioconductor project. Users can perform the essential steps of the differential expression analysis workflow in an assisted way, and generate a broad spectrum of publication-ready outputs, including diagnostic and summary visualizations in each module, all the way down to functional analysis. ideal also offers the possibility to seamlessly generate a full HTML report for storing and sharing results together with code for reproducibility.Conclusionideal is distributed as an R package in the Bioconductor project (http://bioconductor.org/packages/ideal/), and provides a solution for performing interactive and reproducible analyses of summarized RNA-seq expression data, empowering researchers with many different profiles (life scientists, clinicians, but also experienced bioinformaticians) to make the ideal use of the data at hand.

Screening of T Cell-Related Long Noncoding RNA-MicroRNA-mRNA Regulatory Networks in Non-Small-Cell Lung Cancer.

Background Lung cancer (LC) has the highest mortality rate among all the other types of cancer in the world. T cells are known to be the key factor in inducing the immune response during LC. Objective In this study, we aimed to screen and analyze RNAs associated with CD8(+) T cells and activated memory CD4(+) T cells in lung adenocarcinomas, a subtype of non-small-cell lung cancer (NSCLC-LUAD). Methods Gene expression RNA-seq data and clinical data of NSCLC-LUAD were downloaded from the XENA database. The data were divided into low scores and high scores based on the Stromal and Immune scores. Then, all the genes were screened for identifying those specifically associated with CD8(+) T cells and activated memory CD4(+) T cells. The screened genes were used for the construction of the protein-protein interaction (PPI) network and for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis along with prognosis analysis. Based on the results of the prognostic analysis, the prognostic-related genes were used to analyze long noncoding (lnc)RNA-micro(mi)RNA-mRNA networks and to predict small chemical molecules. Results According to the Immune and Stromal scores, a total of 885 upregulated and 29 downregulated RNAs were identified. A total of 90 differentially expressed genes (DEGs) were found to be related to CD8(+) T immune cells, and 48 DEGs were related to activated memory CD4(+) T cells. GPR174 and CD226 suggested a favorable prognosis. For CD8(+) and activated memory CD4(+) T cells, 112 and 113 PPI edges were obtained, respectively. GPR174 was found to be regulated by hsa-miR-19b-5p and hsa-miR-19b-2-5p, and both of these two miRNAs were regulated by lncRNA PCED1B-AS1. CD226 was regulated by hsa-miR-379-5p, which was in turn regulated by lncRNA RP11-81H14.2. Conclusion Our findings provide a deeper understanding of the T cell-related ceRNA regulatory mechanism in NSCLC-LUAD pathogenesis.

BIOM-60. BIOMARKER EVALUATION FOR IMIPRIDONE ONC206 REVEALS ClpP, ATF4, MYC, EGFR and HIF1 AS KEY PREDICTORS OF ANTI-CANCER EFFICACY

Abstract ONC206 is a DRD2 antagonist and ClpP agonist that is a chemical derivative of ONC201, which is in Phase II clinical trials for H3 K27M-mutant glioma. We have previously reported that dopamine receptor expression correlates with ONC201 and ONC206 efficacy. Here, we evaluated additional predictive biomarkers for both agents in the GDSC panel using RNA-seq expression data. ClpP emerged as a strong predictor of efficacy for ONC206 (IC50: p = 1.83E-4, AUC: 9.92E-13). ClpP activation enhances degradation of its substrates, including electron transport chain members responsible for oxidative phosphorylation (OXPHOS). Imipridones activate the integrated stress response involving ATF4 and cause proteasomal degradation of c-myc, which also reduces OXPHOS. Accordingly, high ATF4 (IC50: p = 4.92E-5, AUC: p=2.84E-9) and elevated c-myc correlated with ONC206 efficacy (IC50: p = 6.42E-6, AUC: 3.31E-12). EGFR expression is inversely correlate with DRD2 expression in glioma and its activation is associated with glycolysis. Low EGFR expression correlated with increased ONC206 efficacy (IC50: p = 4.32E-7, AUC: p = 6.44E-20). Loss of HIF1 shunts cellular metabolism toward OXPHOS. Low HIF1 expression correlated with increased anticancer efficacy for ONC206 (IC50: p = 1.96E-3, AUC: p = 1.56E-11). Expression of each of the five markers was significantly different in cell lines that achieved an IC90 with ONC206 (~10%) versus those that did not. A similar analysis for ONC201 revealed that ClpP, MYC and EGFR are more predictive of efficacy relative to ATF4 and HIF1. Combinatorial biomarker analyses revealed MYC/EGFR as the most significant predictor of IC50 for both agents. ClpP/MYC and ClpP/HIF1 were the most significant predictors of AUC for ONC201 and ONC206, respectively. Ongoing studies are further investigating tumor type enrichment of biomarkers. Prediction of innate imipridone sensitivity using biomarkers identified in this study may guide patient and tumor type selection in clinical trials.

KPNA2-Associated Immune Analyses Highlight the Dysregulation and Prognostic Effects of GRB2, NRAS, and Their RNA-Binding Proteins in Hepatocellular Carcinoma.

Karyopherin α2 (KPNA2) was reported to be overexpressed and have unfavorable prognostic effects in many malignancies including hepatocellular carcinoma (HCC). Although its contributions to inflammatory response were reported in many studies, its specific associations with immune infiltrations and immune pathways during cancer progression were unclear. Here, we aimed to identify new markers for HCC diagnosis and prognosis through KPNA2-associated immune analyses. RNA-seq expression data of HCC datasets were downloaded from The Cancer Genome Atlas and International Cancer Genome Consortium. The gene expressions were counts per million normalized. The infiltrations of 24 kinds of immune cells in the samples were evaluated with ImmuCellAI (Immune Cell Abundance Identifier). The Spearman correlations of the immune infiltrations with KPNA2 expression were investigated, and the specific positive correlation of B-cell infiltration with KPNA2 expression in HCC tumors was identified. Fifteen genes in KEGG (Kyoto Encyclopedia of Genes and Genomes) B-cell receptor signaling pathway presented significant correlations with KPNA2 expression in HCC. Among them, GRB2 and NRAS were indicated to be independent unfavorable prognostic factors for HCC overall survival. Clinical Proteomic Tumor Analysis Consortium HCC dataset was investigated to validate the results at protein level. The upregulation and unfavorable prognostic effects of KPNA2 and GRB2 were confirmed, whereas, unlike its mRNA form, NRAS protein was presented to be downregulated and have favorable prognostic effects. Through receiver operating characteristic curve analysis, the diagnostic potential of the three proteins was shown. The RNA-binding proteins (RBPs) of KPNA2, NRAS, and GRB2, downloaded via The Encyclopedia of RNA Interactomes, were investigated for their clinical significance in HCC at protein level. An eight-RBP signature with independent prognostic value and dysregulations in HCC was identified. All the RBPs were significantly correlated with MKI67 expression and at least one of KPNA2, GRB2, and NRAS at protein level in HCC, indicating their roles in HCC progression and the regulation of the three proteins. We concluded that KPNA2, GRB2, NRAS, and their RBPs might have coordinating roles in HCC immunoregulation and progression. They might be new markers for HCC diagnosis and prognosis predication and new targets for HCC immunotherapy.

OATargets: a knowledge base of genes associated with osteoarthritis joint damage in animals

ObjectivesTo collate the genes experimentally modulated in animal models of osteoarthritis (OA) and compare these data with OA transcriptomics data to identify potential therapeutic targets.MethodsPubMed searches were conducted to identify...

EXPath 2.0: An Updated Database for Integrating High-Throughput Gene Expression Data with Biological Pathways.

Co-expressed genes tend to have regulatory relationships and participate in similar biological processes. Construction of gene correlation networks from microarray or RNA-seq expression data has been widely applied to study transcriptional regulatory mechanisms and metabolic pathways under specific conditions. Furthermore, since transcription factors (TFs) are critical regulators of gene expression, it is worth investigating TFs on the promoters of co-expressed genes. Although co-expressed genes and their related metabolic pathways can be easily identified from previous resources, such as EXPath and EXPath Tool, this information is not simultaneously available to identify their regulatory TFs. EXPath 2.0 is an updated database for the investigation of regulatory mechanisms in various plant metabolic pathways with 1,881 microarray and 978 RNA-seq samples. There are six significant improvements in EXPath 2.0: (i) the number of species has been extended from three to six to include Arabidopsis, rice, maize, Medicago, soybean and tomato; (ii) gene expression at various developmental stages have been added; (iii) construction of correlation networks according to a group of genes is available; (iv) hierarchical figures of the enriched Gene Ontology (GO) terms are accessible; (v) promoter analysis of genes in a metabolic pathway or correlation network is provided; and (vi) user's gene expression data can be uploaded and analyzed. Thus, EXPath 2.0 is an updated platform for investigating gene expression profiles and metabolic pathways under specific conditions. It facilitates users to access the regulatory mechanisms of plant biological processes. The new version is available at http://EXPath.itps.ncku.edu.tw.

Read trimming is not required for mapping and quantification of RNA-seq reads at the gene level.

RNA sequencing (RNA-seq) is currently the standard method for genome-wide expression profiling. RNA-seq reads often need to be mapped to a reference genome before read counts can be produced for genes. Read trimming methods have been developed to assist read mapping by removing adapter sequences and low-sequencing-quality bases. It is however unclear what is the impact of read trimming on the quantification of RNA-seq data, an important task in RNA-seq data analysis. In this study, we used a benchmark RNA-seq dataset and simulation data to assess the impact of read trimming on mapping and quantification of RNA-seq reads. We found that adapter sequences can be effectively removed by read aligner via ’soft-clipping’ and that many low-sequencing-quality bases, which would be removed by read trimming tools, were rescued by the aligner. Accuracy of gene expression quantification from using untrimmed reads was found to be comparable to or slightly better than that from using trimmed reads, based on Pearson correlation with reverse transcriptase-polymerase chain reaction data and simulation truth. Total data analysis time was reduced by up to an order of magnitude when read trimming was not performed. Our study suggests that read trimming is a redundant process in the quantification of RNA-seq expression data.

High expression of PLAC1 in colon cancer as a predictor of poor prognosis: A study based on TCGA data.

Colon cancer is one of the most common diseases in the world with both a high incidence and high mortality. PLAC1 is activated and expressed in many cancers. We aim to explore the relationship between PLAC1 expression and prognosis in colon cancer patient. The RNA-Seq expression data and clinical information of colon cancer were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed PLAC1 was obtained by the Wilcoxon signed-rank test; the significance difference being that PLAC1 was more highly expressed in tumor rather than normal tissue (p<0.01). Then patients were classified into high and low risk groups by different risk scores, and the Kaplan-Meier survival analysis showed that colon cancer patients with a high PLAC1 expression had a poorer prognosis than low PLAC1 expression patients (p=0.0031). Next, in analyzing the clinical pathology associated with PLAC1 expression, logistic regression showed that PLAC1 was expressed high in stage (OR=4.11 for I vs. IV), lymph nodes (OR=1.73 for N0 vs. N1+), distant metastasis (OR=2.8 for M0 vs. M1), and status (OR=22.81 for normal vs. tumor). Univariate and multivariate cox analyses were employed to identify that PLAC1 could be regarded as an independent prognostic factor. Univariate cox analysis showed PLAC1 had a correlation to overall survival (OS) (HR: 0.46, 95% CI: 0.28-0.77, p=0.003). Multivariate cox analysis revealed that PLAC1 (HR: 0.51, 95% CI: 0.30-0.86, p=0.012) could be regarded as an Independent prognostic factor. We also used quantitative real-time polymerase chain reaction (qRT-PCR) to test if PLAC1 was differently expressed in cell lines. The qRT-PCR obtained the significant results that PLAC1 expressed high in colon cancer cell lines (p<0.05). Finally, Gene Set Enrichment Analysis (GSEA) was utilized to show 14 enriched signaling pathways. Our study discovered that high expression of PLAC1 predicts poor prognosis in colon cancer patients, providing a new biomarker, which can assist physicians in finding new diagnostic and therapy methods for colon cancer.

Abstract 35: Construction of ce-RNA networks and comprehensive analysis with tumor infiltrating immune cells in hepatocellular carcinoma

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide with a high recurrence rate. Although immune-checkpoint treatment provides survival benefits for patients with HCC, the mortality of HCC is still high. Therefore, it is necessary to understand the molecular mechanism, immune microenvironment and related prognostic factors of HCC. Methods: HCC patients with both RNAseq and miRNA expression data and their clinical information were downloaded from the NCI's Genomic Data Commons. Gene expression data were analyzed to identify differentially expressed genes (DEGs). The results were further used to construct the competing endogenous RNA (ceRNA) networks related to HCC. Meanwhile, the proportions of 22 immune cell types in HCC were estimated by using CIBERSORT (https://cibersort.stanford.edu). Subsequently, two nomograms based on the expression value of ceRNAs and the percentage of immune cells were constructed to predict the prognosis of HCC patients, respectively. The calibration and time series ROC curves were used to evaluate these models. Finally, the correlation between ceRNAs and immune cells were explored to reveal the underlying molecular mechanism. Results: Gene expression data and clinical information of 367 primary HCC and 50 adjacent normal samples were downloaded from the TCGA database. These data were used to identify DEGs. A total of 12 lncRNAs, 71 mRNAs and 39 miRNAs were identified to be in ceRNA networks according to starBase v2.0 database. The results showed that stages of cancer, the expression values of CBX2, MAFG, DNM3, BUB1, ARL5B and other 23 genes were important predictors. The AUCs of the constructed nomogram in predicting the 3- and 5-year OS were 0.79 and 0.81 respectively. Stages of cancer, proportions of resting memory CD4+ T cell, M0 macrophages and resting mast cells constructed another nomogram with AUC of 0.79 and 0.81 in predicting the 3- and 5-year OS. CIBERSORT results showed that the proportions of regulatory T cells, CD8+ T cells, follicular helper T cells and M0 macrophages were slightly higher while the proportions of M2 macrophages, monocytes and activated mast cells were slightly lower in HCC than in adjacent normal samples. Integration analysis of CIBERSORT results, ceRNAs and gene set enrichment analysis of immunologic signatures identified BUB1, E2F8, H2AFZ, JPT1, LPCAT1, MAFG and PSMC3IP to be positively related with regulatory T cells, follicular helper T cells, activated memory CD4+ T cells and M0 macrophages. This is consistent with current knowledge that immune activity is suppressed in certain types of cancers. However, the underlying mechanism warrant further exploration. Conclusions: In this study, two nomograms were constructed to predict the prognosis of HCC patients, which might be useful in predicting the prognosis of HCC patients. The results suggest that the immune suppress effect of HCC may be related to BUB1, E2F8, H2AFZ, JPT1, LPCAT1, MAFG and PSMC3IP genes. These genes may serve as potential therapeutic targets. Acknowledgments: This work was supported by the National Science and Technology Major Project of China (2018ZX10302205). Citation Format: Jianxiang Shi, Chi Cui, Yaru Duan, Hua Ye, Peng Wang, Jitian Li, Shuiling Jin, Liping Dai, Jianying Zhang. Construction of ce-RNA networks and comprehensive analysis with tumor infiltrating immune cells in hepatocellular carcinoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 35.

Abstract 2156: IL-18 pathway agonism expands intratumoral PD1+ Tcf1+ stem-like CD8+ cells and their polyfunctional effector progeny to promote anti-tumor immunity

Abstract Recombinant cytokines were the first modern immunotherapies to produce durable cures in metastatic cancer, but their application has been hampered by only modest efficacy and limited tolerability. A major limitation to cytokine therapies is their lack of selectivity for the small fraction of lymphocytes that specifically recognize tumors. To identify cytokine pathways with greater selectively for anti-tumor lymphocytes, we analyzed single-cell RNA-seq expression data and flow cytometric profiles of tumor-infiltrating lymphocytes (TILs). Among detectable cytokine pathways, Interleukin-18 (IL-18) and its receptors IL-18R1 and IL-18RAP were markedly upregulated in activated and dysfunctional TILs, suggesting the potential of IL-18R agonism to promote anti-tumor immunity. However, recombinant IL-18 therapy has consistently failed to demonstrate anti-tumor efficacy in clinical trials. We hypothesized this may be due to the upregulation of an ultra-high affinity inhibitory decoy receptor of IL-18, IL-18BP. Indeed, IL-18BP is highly expressed in the tumor microenvironment, which we found by immunohistochemical staining and qPCR analysis of IL-18BP levels in several human cancers and syngeneic murine tumor models. Using directed evolution with yeast-surface display, we engineered “decoy-resistant” IL-18 (DR-18), a variant of IL-18 that maintains signaling potential but is impervious to binding and inhibition by IL-18BP. In multiple syngeneic tumor models including YUMMER1.7, MC38, and CT26, we found that recombinant WT IL-18 was ineffective by itself or in combination with anti-PD-1 treatment, similar to the clinical experience of rIL-18 in patients. However, in the same models, DR-18 showed robust monoagent activity that was commensurate or superior to anti-PD-1 antibodies, and it produced added therapeutic synergism when combined with anti-PD-1. Single-cell RNA-seq profiling and flow cytometry analysis of DR-18 treated tumors indicated that DR-18 treatment drives the development of poly-functional effector CD8+ T cells and NK cells. Importantly, DR-18 expands the pool of intratumoral Tcf1+ memory precursor PD1+ CD8+ T cells and decreases the prevalence of exhausted CD8+ T cells that express TOX. Mechanistically, we demonstrate that tumor antigen specific CD8+ T cells were sufficient to mediate tumor regression using LCMV epitope GP33 specific P14 CD8+ T cells in a B16-GP33 model. Together, these results highlight DR-18 is able to remodel the tumor-immune landscape to bias immune cells towards potent anti-tumor effector cells and away from the T exhausted lineage. Therefore, we conclude that the IL-18 pathway is a powerful target for immunotherapeutic intervention and implicate the secreted checkpoint IL-18BP as an obstacle to effective IL-18 immunotherapy. Citation Format: Ting Zhou, Orr-El Weizman, William Damsky, Meaghan McGeary, Marcus W. Bosenberg, Aaron M. Ring. IL-18 pathway agonism expands intratumoral PD1+ Tcf1+ stem-like CD8+ cells and their polyfunctional effector progeny to promote anti-tumor immunity [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2156.

Abstract 4735: Oncogenic involvement of NF-kB signaling pathway in glioma

Abstract Introduction: Aberrant activity of NF-kB has been observed across several cancer types. The current understanding is that the constitutive activation of NF-kB enhances the expression of genes that promote cell proliferation as well as prevent cells from apoptosis. Previous studies have shown that, compared with other cancer types, glioma appears with much significant over-expression of NF-kB. This implies that glioma may be a better subject to elucidate the activity of NF-kB during tumorigenesis. Here we present an analysis aiming to characterize the oncogenic involvement of NF-kB in glioma. Method: We retrieved RNA-Seq expression data of glioblastoma (GBM), low-grade glioma (LGG) as well as other seven major cancer types from TCGA repository. In addition, we collected a total number of 120 tumor samples comprising of 80 GBM and 40 LGG. RNA-Seq experiment was carried out according to standard protocol. Data quality was assessed at multiple steps. In correlation analysis, a number of oncogenic and immune genes / pathways were empirically pre-defined. Pearson coefficient was measured. Expression enrichment analysis was performed using either GSEA or ssGSEA. Immune cell infiltration was assessed using ESTIMATE. Results and conclusion: Pan-cancer analysis shown that, compared with peripheral non-tumor tissue, all five NF-kB member genes, NFKB1, NFKB2, REL, RELA and RELB, are significantly up-regulated in tumor tissue of GBM and LGG, but not in other cancer types. Except previously reported association with EGFR mutation, we also observed that TP53 mutation significantly correlates with over-expression of NF-kB in LGG. CDKN2A and CDKN2B deletion moderately correlate with over-expression of NFKB1,RELB and REL. In addition, RAS and ERBB signaling pathway positively correlates with NF-kB pathway in both GBM and LGG. This is consistent with established cross-talk between these genes. WNT signaling pathway positively correlates with NF-kB in GBM while negatively correlates with NF-kB in LGG. NF-kB regulates WNT signaling through LZTS2 under specific physiological conditions. Our results shown that LZTS2 is up-regulated in LGG while down-regulated in GBM suggesting that NF-kB regulates WNT through LZTS2 in a bidirectional manner. In regulating immune environment, NF-kB expression positively correlates with major immune infiltrates as well as cytokines responsible for modulating the penetrance of blood-brain barrier (BBB), indicating that NF-kB recruit immune cells in response to stimuli in brain despite the existence of BBB. In sum, NF-kB seems to impose rather similar impact on glioma as on other non-CNS solid tumor, i.e. recruitment of immune infiltrates. On the other hand, NF-kB behaves differently in regulating WNT signaling pathway in GBM and LGG. How differential activation of WNT signaling eventually contributes to phenotypical difference between GBM and LGG is to be investigated in further studies Citation Format: Cheng Yan, Lan Su, Xin Qi, Yufei Yang, Jun Wu. Oncogenic involvement of NF-kB signaling pathway in glioma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4735.

Expression Profile of SARS-CoV-2 Host Receptors in Human Pancreatic Islets Revealed Upregulation of ACE2 in Diabetic Donors.

Cellular entry of SARS-CoV-2 is thought to occur through the binding of viral spike S1 protein to ACE2. The entry process involves priming of the S protein by TMPRSS2 and ADAM17, which collectively mediate the binding and promote ACE2 shedding. In this study, microarray and RNA-sequencing (RNA-seq) expression data were utilized to profile the expression pattern of ACE2, ADAM17, and TMPRSS2 in type 2 diabetic (T2D) and non-diabetic human pancreatic islets. Our data show that pancreatic islets express all three receptors irrespective of diabetes status. The expression of ACE2 was significantly increased in diabetic/hyperglycemic islets compared to non-diabetic/normoglycemic. Islets from female donors showed higher ACE2 expression compared to males; the expression of ADAM17 and TMPRSS2 was not affected by gender. The expression of the three receptors was statistically similar in young (≤40 years old) versus old (≥60 years old) donors. Obese (BMI > 30) donors have significantly higher expression levels of ADAM17 and TMPRSS2 relative to those from non-obese donors (BMI < 25). TMPRSS2 expression correlated positively with HbA1c and negatively with age, while ADAM17 and TMPRSS2 correlated positively with BMI. The expression of the three receptors was statistically similar in muscle and subcutaneous adipose tissues obtained from diabetic and nondiabetic donors. Lastly, ACE2 expression was higher in sorted pancreatic β-cell relative to other endocrine cells. In conclusion, ACE2 expression is increased in diabetic human islets. More studies are required to investigate whether variations of ACE2 expression could explain the severity of COVID-19 infection-related symptoms between diabetics and non-diabetic patients.

HN1 as a diagnostic and prognostic biomarker for liver cancer.

Background: The present study aimed to examine the diagnostic and prognostic value of HN1 in terms of overall survival (OS) and recurrence-free survival (RFS) in liver cancer and its potential regulatory signaling pathway.Methods: We obtained clinical data and HN1 RNA-seq expression data of liver cancer patients from The Cancer Genome Atlas database, and analyzed the differences and clinical association of HN1 expression in different clinical features. We uesd receiver-operating characteristic curve to evaluate the diagnosis capability of HN1. We analyzed and evaluated the prognostic significance of HN1 by Kaplan–Meier curves and Cox analysis. Gene Set Enrichment Analysis (GSEA) was used to identify signaling pathways related to HN1 expression.Results: HN1 mRNA was up-regulated in liver cancer, and was associated with age, histologic grade, stage, T classification, M classification, and vital status. HN1 mRNA had ideal specificity and sensitivity for the diagnosis (AUC = 0.855). Besides, the analysis of Kaplan–Meier curves and Cox model showed that HN1 mRNA was strongly associated with the overall survival and could be well-predicted liver cancer prognosis, as an independent prognostic variable. GSEA analysis identified three signaling pathways that were enriched in the presence of high HN1 expression.Conclusion: HN1 serves as a biomarker of diagnosis and prognosis in liver cancer.

Computational Analysis of the Global Effects of Ly6E in the Immune Response to Coronavirus Infection Using Gene Networks.

Gene networks have arisen as a promising tool in the comprehensive modeling and analysis of complex diseases. Particularly in viral infections, the understanding of the host-pathogen mechanisms, and the immune response to these, is considered a major goal for the rational design of appropriate therapies. For this reason, the use of gene networks may well encourage therapy-associated research in the context of the coronavirus pandemic, orchestrating experimental scrutiny and reducing costs. In this work, gene co-expression networks were reconstructed from RNA-Seq expression data with the aim of analyzing the time-resolved effects of gene Ly6E in the immune response against the coronavirus responsible for murine hepatitis (MHV). Through the integration of differential expression analyses and reconstructed networks exploration, significant differences in the immune response to virus were observed in Ly6E compared to wild type animals. Results show that Ly6E ablation at hematopoietic stem cells (HSCs) leads to a progressive impaired immune response in both liver and spleen. Specifically, depletion of the normal leukocyte mediated immunity and chemokine signaling is observed in the liver of Ly6E mice. On the other hand, the immune response in the spleen, which seemed to be mediated by an intense chromatin activity in the normal situation, is replaced by ECM remodeling in Ly6E mice. These findings, which require further experimental characterization, could be extrapolated to other coronaviruses and motivate the efforts towards novel antiviral approaches.

Comparative transcriptome analysis between a resistant and a susceptible Chinese cabbage in response to Hyaloperonospora brassicae

ABSTRACT Downy mildew caused by Hyaloperonosporabrassicae (H. brassicae) leads to up to 90% of the crop yield loss in Chinese cabbage in China. A transcriptome analysis was carried out between a resistant line (13-13, R) and a susceptible line (15-14, S) of Chinese cabbage in response to H. brassicae. The NOISeq method was used to find differentially expressed genes (DEGs) between these two groups and GO and KEGG were carried out to find R genes related to downy mildew response of Chinese cabbage. qRT-PCR was carried out to verify the reliability of RNA-seq expression data. A total of 3,055 DEGs were screened out from 41,020 genes and clustered into 6 groups with distinct expression patterns. A total of 87 candidate DEGs were identified by functional annotation based on GO and KEGG analysis. These candidate genes are involved in plant-pathogen interaction pathway, among which 54 and 33 DEGs were categorized into plant-pathogen interaction proteins and transcription factors, respectively. Proteins encoded by these genes have been reported to play an important role in the pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) processes of disease responses in some model plants, such as Arabidopsis, rice, tobacco, and tomato. However, little is known about the mechanisms of these genes in resistance to downy mildew in Chinese cabbage. Our findings are useful for further characterization of these candidate genes and helpful in breeding resistant strains.

THU0329 SAFETY, TARGET ENGAGEMENT, AND INITIAL EFFICACY OF AVID200, A FIRST-IN-CLASS POTENT AND ISOFORM-SELECTIVE INHIBITOR OF TGF-BETA 1 AND 3, IN PATIENTS WITH DIFFUSE CUTANEOUS SYSTEMIC SCLEROSIS (DCSSC): A PHASE 1 DOSE ESCALATION STUDY

Background:AVID200 is a novel, potent TGF-beta receptor ectodomain-based trap designed to selectively neutralize TGF-beta 1 and 3. These two isoforms have been implicated as central mediators of the pathogenesis of systemic sclerosis (SSc). AVID200 avoids inhibition of TGF-beta 2, the isoform that supports normal cardiac function and hematopoiesis.Objectives:This first-in-human study (AVID200-01;NCT03831438) is a Phase 1, open label, multicenter, cohort dose-escalation trial designed to evaluate safety, tolerability, pharmacokinetic (PK) profile, pharmacodynamic (PD) effects, target engagement, and preliminary efficacy in patients with diffuse cutaneous SSc (dcSSc).Methods:Eligible patients must have dcSSc of &lt;5 years (y) duration and a modified Rodnan Skin Score (MRSS) ≥15. AVID200 at dose levels of 1, 3, 9, or 15 mg/kg IV is administered every 2 weeks (Q2W) for 6 weeks (3 doses). Patients tolerating dosing and who have not experienced disease worsening during the initial Treatment Period may receive up to 6 additional doses Q2W (Extension Period). The ability of AVID200 to selectively sequester its target is assessed in plasma by TGF-beta quantification per ELISA and a cell-based functional readout. Expression of biomarkers of TGF-beta inhibition and genes correlating with MRSS are assessed.Results:The first 2 dose cohorts have completed treatment: male/female 3 each, median age 61y (range 45-70), median MRSS at baseline 31 (range 23-39). Recruitment into cohort 3 is complete. AVID200 was well tolerated with no dose limiting toxicities or serious adverse events (SAEs). AEs, all considered possibly related, included single cases of Grade 1 dizziness and CPK elevation, and Grade 2 anemia. All patients demonstrated a decline in MRSS at 6 weeks by 3, 4, and 9 points in Cohort 1, and 2, 8, and 9 points in Cohort 2. Four of 6 patients demonstrated continued decrease in MRSS 12 weeks after the last dose, with all patients showing a decline in MRSS relative to baseline at this timepoint by 7, 6, and 7 points in Cohort 1 and 4, 8, and 13 points in Cohort 2. AVID200 in plasma engaged endogenous activated TGF-beta and potently neutralized signaling from exogenous TGF-beta 1 and 3, but not TGF-beta 2, across the treatment period. PD effects in skin biopsies, including expression of markers of SSc activity, TGF-beta activity, and myofibroblast-associated genes were assessed. Five of 6 patients showed decreased expression of PD biomarker genes, THBS1 and MS4A4A, comparing end of treatment biopsies to baseline, and all patients showed a decline in SERPINE1 expression, a marker gene for TGF-beta activity. Clustering of RNA-seq expression data showed close coregulation of COMP, THBS1, SERPINE1, LOXL, COL10A1, COL11A1, COL12A1, CTGF, and CDH11, suggesting that blocking TGF-beta inhibits this group of profibrotic genes. Single-cell sequencing data show that expression of these genes is upregulated by subsets of SSc fibroblasts.Conclusion:AVID200 at doses of 1 and 3 mg/kg was well-tolerated in this first study in dcSSc patients. Evidence of anti-fibrotic effects as indicated by rapid, persistent and clinically meaningful declines in MRSS was observed in all patients, as well as AVID200 target engagement and modulation. Recruitment into additional dose and extension cohorts is ongoing. Together, these clinical data support selective TGF-beta 1 and 3 inhibition by AVID200 as a promising therapeutic approach for dcSSc.Disclosure of Interests:Robert Lafyatis Grant/research support from: Forbius, Consultant of: Certa Therapeutics, Forbius, FBM Therapeutics, Robert Spiera Grant/research support from: Roche-Genetech, GSK, Boehringer Ingelheim, Chemocentryx, Corbus, Forbius, Sanofi, Inflarx, Consultant of: Roche-Genetech, GSK, CSL Behring, Sanofi, Janssen, Chemocentryx, Forbius, Mistubishi Tanabe, Robyn Domsic Consultant of: Forbius, Anna Papazoglou: None declared, Colin Ligon Grant/research support from: Forbius, Christina Mae Zinger Morse: None declared, Jean-François Denis Employee of: Forbius, Margaret Davis Employee of: Forbius, Tina Gruosso Employee of: Forbius, Gilles Tremblay Employee of: Forbius, Maureen O’Connor McCourt Employee of: Forbius, Sandra Sinclair Employee of: Forbius, Jonathan Delara Employee of: Forbius, Krista Alvarado Employee of: Forbius, Debra Wood Consultant of: Forbius, Symphogen, Paul Nadler Consultant of: Forbius, Symphogen, Karyopharm, Elizabeth Volkmann Grant/research support from: Forbius, Corbus Pharmaceuticals, Consultant of: Boehringer Ingelheim, Forbius, Speakers bureau: Boehringer Ingelheim

Oncogenic roles of CEACAM6 in pancreatic ductal adenocarcinoma.

e16744 Background: Carcinoembryonic cell adhesion molecule 6 (CEACAM6) is a cell adhesion receptor of the Ig-superfamily overexpressed in human Pancreatic Ductal Adenocarcinoma (PDA), enriching to the classical activated stroma subtype. CEACAM6 has multifaceted roles in PDA and is a poor prognostic maker (Pandey et al. Sci Rep 2019). We report functional correlative studies across PDA cell lines with high vs KO vs low of CEACAM6 and a PDX model with a therapeutic Mab. Methods: RNA-Seq and microarray expression data of PDA cell lines were downloaded from GEO using R (4.3), normalized and log transformed for analysis: CEACAM6 high vs. low were assessed for differential gene expression changes. Correlation of CEACAM6 levels with genes of interest was studied and compared with the CEACAM6 KO proteomic profile of HPAF-II cells. CEACAM6 WT vs. KO cells were profiled for protein kinase (PK) activity (PAMChip) and gene expression changes by RNA-Seq. NSG-CD34+ mice bearing PDX were evaluated with a humanized anti-CEACAM6 Mab for anti-tumor activity. Results: Differential expression analyses between PDA cell lines with low vs KO vs high CEACAM6 resulted in identifying similar markers changing in quantitative proteomics. KRT20, SYTL1, SKIL, CES1P1, MAN1A1 were down-regulated and HMOX1, CPNE2, ABCD1 were up-regulated in CEACAM6 low or KO cell lines. Specific PKs are upregulated in CEACAM6 KO enriching to the TK family (EPH A1, 3, 4, 8 and HCK), AGC family (e.g. AKT, PKA) and cellular apoptosis (e.g. BAD). RNA-Seq of CEACAM6 WT vs KO cells reconfirmed the up-regulation of MMP1, IL2RG, ATP6V0D2 and low expression of KRT20, AGK and MAN1A1 in CEACAM6 KO cells. Pharmacologic inhibition with a humanized anti-CEACAM6 scFv-Fc (IgG4) in PDA PDX of NSG CD34+ mice demonstrated ~55% tumor growth inhibition (TGI) with enhanced survival of &gt; 14 days vs. control. Conclusions: CEACAM6 is expressed exclusively in primates and humans and plays multifaceted oncogenic roles in PDA pathogenesis. When CEACAM6 is disrupted, ECM proteins are altered reshaping the stroma, activating specific PKs and priming apoptosis. The therapeutic anti-CEACAM6 Mab possesses anti-tumor activity with associated cellular apoptosis and increased mouse survival.

RNA pathway enrichment in serum-based mass spectroscopy prognostic analyses.

e15197 Background: Veristrat(VS) good and poor labels were found to be prognostic in the front-line NSCLC setting with or without immune checkpoint inhibitors. Little is known about RNA expression data corresponding to these good and poor prognostic labels. Methods: Raw RNA seq expression data was obtained from TEMPUS XP RNA analysis. Sequences were filtered for allowing only genes that had an overall count of at least 20 across all samples. Samples were then processed through the EdgeR analysis in the R programming environment. Along with a Z-scored heatmap, PCA plot was also generated. Differential abundance analysis was done further filter out the genes. Benjamini-Hochberg correction was done and only genes with corrected p-value of &lt; 0.05 were selected for further pathway analysis. 242 genes with corrected p-value &lt; 0.05 were used. Pathway analysis was performed using the Broad Institute GSEA (Gene Set Enrichment Analysis) and DAVID (Database for Annotation, Visualization and Integrated Discovery). The gene list was ran using KEGG database in GSEA and using KEGG, BioCarta and Reactome pathway databases. Functional analyses against the KEGG and REACTOME database were reported out to determine the enriched pathways in the VS poor and VS good groups. Kaplan-Meier and Logrank were used to compare overall survival in the poor vs. good label cohorts of patients. Results: 26 patients had VS label and RNA expression data available. Nine patients had VS poor label and 17 had veristrat good label. 6(66%) VS poor 13(76%) VS good patients received anti PD1 agents during the course of their therapy. Overall survival was not significantly different between good and poor label groups in this small series. 242 genes had significantly different abundance in the VS poor vs good patients with the majority (211) over expressed in the poor label patients. Significant pathways enriched in the VS poor group included the intrinsic pathway of fibrin clot formation, platelet degranulation (DAVID), steroid hormone biosynthesis and dilated cardiomyopathy (KEGG). Systemic lupus erythematous pathway was enriched in the VS good group (KEGG). Conclusions: In this small set of front-line patients with RNA pathway analyses and known VS poor or good labels, differential expression of acute phase reactants was found in VS poor patients. DAVID and KEGG pathways were differentially enriched and may reveal potential targets to mitigate prognosis in poor risk NSCLC.