Deleterious Genetic Variation Across the NOD Signaling Pathway Is Associated With Reduced NFKB Signaling Transcription and Upregulation of Alternative Inflammatory Transcripts in Pediatric Inflammatory Bowel Disease

Background Inflammatory bowel disease may arise with inadequate immune response to intestinal bacteria. NOD2 is an established gene in Crohn’s disease pathogenesis, with deleterious variation associated with reduced NFKB signaling. We hypothesized that deleterious variation across the NOD2 signaling pathway impacts on transcription. Methods Treatment-naïve pediatric inflammatory bowel disease patients had ileal biopsies for targeted autoimmune RNA-sequencing and blood for whole exome sequencing collected at diagnostic endoscopy. Utilizing GenePy, a per-individual, per-gene score, genes within the NOD signaling pathway were assigned a quantitative score representing total variant burden. Where multiple genes formed complexes, GenePy scores were summed to create a “complex” score. Normalized transcript expression of 95 genes within this pathway was retrieved. Regression analysis was performed to determine the impact of genomic variation on gene transcription. Results Thirty-nine patients were included. Limited clustering of patients based on NOD signaling transcripts was related to underlying genomic variation. Patients harboring deleterious variation in NOD2 had reduced NOD2 (β = -0.702, P = 4.3 × 10-5) and increased NFKBIA (β = 0.486, P = .001), reflecting reduced NFKB signal activation. Deleterious variation in the NOD2-RIPK2 complex was associated with increased NLRP3 (β = 0.8, P = 3.1475 × 10-8) and TXN (β = -0.417, P = 8.4 × 10-5) transcription, components of the NLRP3 inflammasome. Deleterious variation in the TAK1-TAB complex resulted in reduced MAPK14 transcription (β = -0.677, P = 1.7 × 10-5), a key signal transduction protein in the NOD2 signaling cascade and increased IFNA1 (β = 0.479, P = .001), indicating reduced transcription of NFKB activators and alternative interferon transcription in these patients. Conclusions Data integration identified perturbation of NOD2 signaling transcription correlated with genomic variation. A hypoimmune NFKB signaling transcription response was observed. Alternative inflammatory pathways were activated and may represent therapeutic targets in specific patients.

Construction and Clinical Translation of Causal Pan-Cancer Gene Score Across Cancer Types

Pan-cancer strategy, an integrative analysis of different cancer types, can be used to explain oncogenesis and identify biomarkers using a larger statistical power and robustness. Fine-mapping defines the casual loci, whereas genome-wide association studies (GWASs) typically identify thousands of cancer-related loci and not necessarily have a fine-mapping component. In this study, we develop a novel strategy to identify the causal loci using a pan-cancer and fine-mapping assumption, constructing the CAusal Pan-cancER gene (CAPER) score and validating its performance using internal and external validation on 1,287 individuals and 985 cell lines. Summary statistics of 15 cancer types were used to define 54 causal loci in 15 potential genes. Using the Cancer Genome Atlas (TCGA) training set, we constructed the CAPER score and divided cancer patients into two groups. Using the three validation sets, we found that 19 cancer-related variables were statistically significant between the two CAPER score groups and that 81 drugs had significantly different drug sensitivity between the two CAPER score groups. We hope that our strategies for selecting causal genes and for constructing CAPER score would provide valuable clues for guiding the management of different types of cancers.

Application of Age, Body Mass Index, Chronic Kidney Disease, Diabetes, and Genotyping Score for Efficacy of Clopidogrel: Secondary Analysis of the CHANCE Trial

Background and Purpose: The age, body mass index, chronic kidney disease, diabetes, and genotyping (ABCD-GENE) score is a validated risk score integrating CYP2C19 genotypes with clinical risk factors influencing clopidogrel response that would allow the more precise identification of subjects at risk for high platelet reactivity and adverse clinical outcomes. Our objective was to further verify application of the ABCD-GENE score and investigate appropriate cutoff value in patients with minor stroke or transient ischemic attack. Methods: In this post-analysis of the CHANCE trial (Clopidogrel in High-Risk Patients With Acute Nondisabling Cerebrovascular Events), the ABCD-GENE score was calculated for all patients enrolled in this study. By using the proposed cutoff of 10, patients were stratified as being at high risk for high platelet reactivity or not. We further categorized the ABCD-GENE score to 0 to 5, 6 to 24, and >24 to investigate the cutoff value of this scale in clinical application. Stroke recurrence at 3 months was considered as the primary outcome. Results: Among a total of 2923 patients with minor stroke/transient ischemic attack, there were 2273 (77.76%) with ABCD-GENE score <10 and 650 (22.24%) patients with ABCD-GENE score ≥10. Compared with the aspirin alone, hazard ratios (95% CIs) of the clopidogrel-aspirin therapy for stroke recurrence were 0.70 (0.54–0.91) and 0.76 (0.46–1.24), among patients of ABCD-GENE scores <10 and ABCD-GENE scores ≥10, respectively. Stratified analyses by ABCD-GENE score 0 to 5, 6 to 24, and >24, hazard ratios of the clopidogrel-aspirin therapy for stroke recurrence were 0.57 (95% CI, 0.38–0.85), 0.78 (0.58–1.06), and 1.20 (0.44–3.28) ( P value for trend=0.0052). Conclusions: Among Chinese minor stroke/transient ischemic attack population, the efficacy of clopidogrel-aspirin therapy was decreased in patients with higher ABCD-GENE score. Our study suggests that CYP2C19 genotypes and clinical risk factors can be integrated by ABCD-GENE score to estimate the efficacy of clopidogrel-aspirin therapy.

Identification of a Prognosis-Related Risk Signature for Bladder Cancer to Predict Survival and Immune Landscapes

Background. Bladder cancer is the tenth most common cancer worldwide. Valuable biomarkers in the field of diagnostic bladder cancer are urgently required. Method. Here, the gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA), GSE13507, GSE32894, and Mariathasan et al. Five prognostic genes were identified by the univariate, robust, and multivariate Cox’s regression and were used to develop a prognosis-related model. The Kaplan–Meier survival curves and receiver operating characteristics were used to evaluate the model’s effectiveness. The potential biological functions of the selected genes were analyzed using CIBERSORT and ESTIMATE algorithms. Cancer Therapeutics Response Portal (CTRP) and PRISM datasets were used to identify drugs with high sensitivity. Subsequently, using the bladder cancer (BLCA) cell lines, the role of TNFRSF14 was determined by Western blotting, cell proliferation assay, and 5-ethynyl-20-deoxyuridine assay. Results. GSDMB, CLEC2D, APOL2, TNFRSF14, and GBP2 were selected as prognostic genes in bladder cancer patients. The model’s irreplaceable reliability was validated by the training and validation cohorts. CD8+ T cells were highly infiltrated in the high-TNFRSF14-expression group, and M2 macrophages were the opposite. Higher expression of TNFRSF14 was associated with higher expression levels of LCK, interferon, MHC-I, and MHC-II, while risk score was the opposite. Many compounds with higher sensitivity for treating bladder cancer patients in the low-TNFRSF14-expression group were identified, with obatoclax being a potential drug most likely to treat patients in the low-TNFRSF14-expression group. Finally, the proliferation of BLCA cell lines was increased in the TNFRSF14-reduced group, and the differential expression was identified. TNFRSF14 plays a role in bladder cancer progression through the Wnt/β-catenin-dependent pathway. TNFRSF14 is a potential protective biomarker involved in cell proliferation in BLCA. Conclusion. We conducted a study to establish a 5-gene score model, providing reliable prediction for the outcome of bladder cancer patients and therapeutic drugs to individualize therapy. Our findings provide a signature that might help determine the optimal treatment for individual patients with bladder cancer.

Multi-modal single-cell sequencing identifies cellular immunophenotypes associated with juvenile dermatomyositis disease activity

Juvenile dermatomyositis (JDM) is a rare autoimmune condition with insufficient biomarkers and treatments, in part, due to incomplete knowledge of the cell types mediating disease. We investigated immunophenotypes and cell-specific genes associated with disease activity using multiplexed RNA and protein single-cell sequencing applied to PBMCs from 4 treatment-naive JDM (TN-JDM) subjects at baseline, 2, 4, and 6 months and 4 subjects with inactive disease. Analysis of 55,564 cells revealed separate clustering of TN-JDM cells within monocyte, NK, CD8+ effector T and naive B populations. The proportion of CD16+ monocytes was reduced in TN-JDM, and naive B cells were expanded. Cell-type differential gene expression analysis and hierarchical clustering identified a pan-cell-type IFN gene signature over-expressed in TN-JDM in all cell types and correlated with disease activity. TN-JDM monocytes displayed an inflammatory state: CD16+ monocytes expressed the highest IFN gene score and differential protein expression of adhesion molecules, CD49d and CD56, compared to CD14+ inflammatory monocytes. A transitional B cell population expressing higher CD24 and CD5 proteins and an IFN-hi naive B population were associated with TN-JDM and exhibited less CD39, an immunoregulatory protein. This data provides new insights into JDM immune dysregulation at cellular resolution and novel resource for myositis investigators.

Identification and Validation of a Novel 16-Gene Prognostic Signature for Patients with Breast Cancer

Background: Despite increased early diagnosis and improved treatment in breast cancer (BRCA) patients, prognosis prediction is still a challenging task due to the disease heterogeneity. This study was to identify a novel gene signature that can accurately evaluate BRCA patient survival. Methods: The gene expression and clinical data of BRCA patients were collected from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of BRCA International Consortium (METABRIC) databases. Genes associated with prognosis were determined by Kaplan–Meier survival analysis and multivariate Cox regression analysis. A prognostic 16-gene score was established with linear combination of 16 genes. The prognostic value of the signature was validated in the METABRIC dataset. Gene expression analysis was performed to investigate the diagnostic values of 16 genes. Results: The 16-gene score was associated with shortened overall survival in BRCA patients independently of clinicopathological characteristics. The signalling pathways of cell cycle, oocyte meiosis, RNA degradation, progesterone mediated oocyte maturation and DNA replication were the top five most enriched pathways in the high 16-gene score group. The 16-gene nomogram incorporating the survival‐related clinical factors showed improved prediction accuracies for 1-year, 3-year and 5‐year survival (area under curve [AUC] = 0.91, 0.79 and 0.77 respectively). MORN3, IGJ, DERL1 exhibited high accuracy in differentiating BRCA tissues from normal breast tissues (AUC > 0.80 for all cases). Conclusions: The 16-gene profile provides novel insights into the identification of BRCA with a high risk of death, which eventually guides treatment decision making.

The Development and Validation of a Novel 71-Gene Signature for Risk Stratification and Prognosis in Lower Grade Glioma

Background: Lower-grade gliomas (LGG) are a diverse group of primary brain tumors with relatively poor overall survival in young adults. In this study, we aimed to establish novel method that are effectively predictive of prognosis of LGG patients. Methods: We detected and validated prognosis-associated genes using gene expression and c`Clinical data of LGG patients from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. We then established a novel prognostic 71-gene score and 17-gene nomograms and analyzed their relationship with overall survival (OS) and relapse-free survival (RFS) in LGG patients. We also performed Gene Set Enrichment Analysis to investigate the altered signalling pathways associated with the 71-gene score phenotype and hierarchical clustering analysis of 71 genes to detect subgroups of LGG patients with distinct clinical characteristics. Results: We identified 1489 genes significantly correlated with patients’ prognosis in LGG. The 71-gene score was predictive of favourable OS and RFS in LGG patients independently of clinicopathological characteristics. The wnt signalling pathway, glutathione metabolism, primary immunodeficiency, galactose metabolism were the potential pathways involved in the prognostication of the 71-gene score. Hierarchical clustering analysis of the 71 genes revealed three subgroups of LGG patients in the TCGA dataset. The cluster2 LGG tumours were associated with higher grade, more frequent radiation therapy, poorer OS and RFS than cluster1 and cluster3 tumours. The 71-gene nomogram incorporating the survival‐related clinical factors showed good prediction accuracies for overall survival, 3-year and 5‐year survival (area under curve [AUC] = 0.79, 0.67 and 0.75 respectively). Conclusions: The 71-gene nomogram may turn out to be a useful and robust method to remarkably ameliorate the prognostic prediction in LGG.

Complex analysis of the personalized pharmacotherapy in the management of COVID-19 patients and suggestions for applications of predictive, preventive, and personalized medicine attitude

Aims Coronavirus disease 2019 (COVID-19) is rapidly spreading worldwide. Drug therapy is one of the major treatments, but contradictory results of clinical trials have been reported among different individuals. Furthermore, comprehensive analysis of personalized pharmacotherapy is still lacking. In this study, analyses were performed on 47 well-characterized COVID-19 drugs used in the personalized treatment of COVID-19. Methods Clinical trials with published results of drugs use for COVID-19 treatment were collected to evaluate drug efficacy. Drug-to-Drug Interactions (DDIs) were summarized and classified. Functional variations in actionable pharmacogenes were collected and systematically analysed. “Gene Score” and “Drug Score” were defined and calculated to systematically analyse ethnicity-based genetic differences, which are important for the safer use of COVID-19 drugs. Results Our results indicated that four antiviral agents (ritonavir, darunavir, daclatasvir and sofosbuvir) and three immune regulators (budesonide, colchicine and prednisone) as well as heparin and enalapril could generate the highest number of DDIs with common concomitantly utilized drugs. Eight drugs (ritonavir, daclatasvir, sofosbuvir, ribavirin, interferon alpha-2b, chloroquine, hydroxychloroquine (HCQ) and ceftriaxone had actionable pharmacogenomics (PGx) biomarkers among all ethnic groups. Fourteen drugs (ritonavir, daclatasvir, prednisone, dexamethasone, ribavirin, HCQ, ceftriaxone, zinc, interferon beta-1a, remdesivir, levofloxacin, lopinavir, human immunoglobulin G and losartan) showed significantly different pharmacogenomic characteristics in relation to the ethnic origin of the patient. Conclusion We recommend that particularly for patients with comorbidities to avoid serious DDIs, the predictive, preventive, and personalized medicine (PPPM, 3 PM) strategies have to be applied for COVID-19 treatment, and genetic tests should be performed for drugs with actionable pharmacogenes, especially in some ethnic groups with a higher frequency of functional variations, as our analysis showed. We also suggest that drugs associated with higher ethnic genetic differences should be given priority in future pharmacogenetic studies for COVID-19 management. To facilitate translation of our results into clinical practice, an approach conform with PPPM/3 PM principles was suggested. In summary, the proposed PPPM/3 PM attitude should be obligatory considered for the overall COVID-19 management.