Gene Set Analysis Research Articles

Global transcriptome analysis of allopolyploidization reveals large-scale repression of the D-subgenome in synthetic hexaploid wheat

Synthetic hexaploid wheat (SHW) lines are created as pre-breeding germplasm to diversify the D subgenome of hexaploid wheat and capitalize upon the untapped genetic diversity of the Aegilops tauschii gene pool. However, the phenotypes observed in the Ae. tauschii parents are not always recovered in the SHW lines, possibly due to inter-subgenome interactions. To elucidate this post-polyploidization genome reprogramming phenomenon, we performed RNA-seq of four SHW lines and their corresponding tetraploid and diploid parents, across ten tissues and three biological replicates. Homoeologue expression bias (HEB) analysis using more than 18,000 triads suggests massive suppression of homoeoalleles of the D subgenome in SHWs. Comparative transcriptome analysis of the whole-genome gene set further corroborated this finding. Alternative splicing analysis of the high-confidence genes indicates an additional layer of complexity where all five splice events are identified, and retained intron is predominant. Homoeologue expression upon resynthesis of hexaploid wheat has implications to the usage and handling of this germplasm in breeding as it relates to capturing the effects of epistatic interaction across subgenomes upon polyploidization. Special considerations must be given to this germplasm in pre-breeding activities to consider the extent of the inter-subgenome interactions on gene expression and their impact on traits for crop improvement.

Exploring the genetic and genomic connection underlying neurodegeneration with brain iron accumulation and the risk for Parkinson’s disease

Neurodegeneration with brain iron accumulation (NBIA) represents a group of neurodegenerative disorders characterized by abnormal iron accumulation in the brain. In Parkinson’s Disease (PD), iron accumulation is a cardinal feature of degenerating regions in the brain and seems to be a key player in mechanisms that precipitate cell death. The aim of this study was to explore the genetic and genomic connection between NBIA and PD. We screened for known and rare pathogenic mutations in autosomal dominant and recessive genes linked to NBIA in a total of 4481 PD cases and 10,253 controls from the Accelerating Medicines Partnership Parkinsons’ Disease Program and the UKBiobank. We examined whether a genetic burden of NBIA variants contributes to PD risk through single-gene, gene-set, and single-variant association analyses. In addition, we assessed publicly available expression quantitative trait loci (eQTL) data through Summary-based Mendelian Randomization and conducted transcriptomic analyses in blood of 1886 PD cases and 1285 controls. Out of 29 previously reported NBIA screened coding variants, four were associated with PD risk at a nominal p value < 0.05. No enrichment of heterozygous variants in NBIA-related genes risk was identified in PD cases versus controls. Burden analyses did not reveal a cumulative effect of rare NBIA genetic variation on PD risk. Transcriptomic analyses suggested that DCAF17 is differentially expressed in blood from PD cases and controls. Due to low mutation occurrence in the datasets and lack of replication, our analyses suggest that NBIA and PD may be separate molecular entities.

A deep transcriptome meta-analysis reveals sex differences in multiple sclerosis

BackgroundMultiple sclerosis (MS), a chronic auto-immune, inflammatory, and degenerative disease of the central nervous system, affects both males and females; however, females suffer from a higher risk of developing MS (2–3:1 ratio relative to males). The precise sex-based factors influencing risk of MS are currently unknown. Here, we explore the role of sex in MS to identify molecular mechanisms underlying observed MS sex differences that may guide novel therapeutic approaches tailored for males or females. MethodsWe performed a rigorous and systematic review of genome-wide transcriptome studies of MS that included patient sex data in the Gene Expression Omnibus and ArrayExpress databases following PRISMA statement guidelines. For each selected study, we analyzed differential gene expression to explore the impact of the disease in females (IDF), in males (IDM) and our main goal: the sex differential impact of the disease (SDID). Then, for each scenario (IDF, IDM and SDID) we performed 2 meta-analyses in the main tissues involved in the disease (brain and blood). Finally, we performed a gene set analysis in brain tissue, in which a higher number of genes were dysregulated, to characterize sex differences in biological pathways. ResultsAfter screening 122 publications, the systematic review provided a selection of 9 studies (5 in blood and 4 in brain tissue) with a total of 474 samples (189 females with MS and 109 control females; 82 males with MS and 94 control males). Blood and brain tissue meta-analyses identified, respectively, 1 (KIR2DL3) and 13 (ARL17B, CECR7, CEP78, IFFO2, LOC401127, NUDT18, RNF10, SLC17A5, STMP1, TRAF3IP2-AS1, UBXN2B, ZNF117, ZNF488) MS-associated genes that differed between males and females (SDID comparison). Functional analyses in the brain revealed different altered immune patterns in females and males (IDF and IDM comparisons). The pro-inflammatory environment and innate immune responses related to myeloid lineage appear to be more affected in females, while adaptive responses associated with the lymphocyte lineage in males. Additionally, females with MS displayed alterations in mitochondrial respiratory chain complexes, purine, and glutamate metabolism, while MS males displayed alterations in stress response to metal ion, amine, and amino acid transport. ConclusionWe found transcriptomic and functional differences between MS males and MS females (especially in the immune system), which may support the development of new sex-based research of this disease. Our study highlights the importance of understanding the role of biological sex in MS to guide a more personalized medicine.

Abstract 6074: Germline and somatic genomic profiling of urothelial carcinoma

Abstract Urothelial carcinoma (UC) presents most frequently as bladder cancer and is the most common cancer of the urinary system in the United States. UC relapse and progression are common and impose a significant negative impact on the lives of patients and healthcare resources. To elucidate the biological mechanisms of UC and find novel biomarkers, we analyzed the clinical and genomic data in the Oncology Research Information Exchange Network (ORIEN). We conducted gene-based and gene-set based association tests on rare germline variants comparing the exome sequencing of 336 UC patients and genome sequencing of 366 healthy controls (42 unrelated individuals from the Centre d'Etudes du Polymorphisme Humain [CEPH] families and 324 from the University of Utah Heritage 1000 [H1K] Projects). The analysis of loss-of-function (LoF) variants revealed that the forkhead box (FOX) J2 gene set was significantly associated with UC at the genome-wide level (Bonferroni-corrected p-value=0.01). Genes in this gene set contain a motif that matches the FOXJ2 transcription factor binding site. Firth-penalized Cox proportional hazard regression on overall survival identified LoF variants in genes down-regulated in naive CD8 T cells to be associated with worse prognosis (Bonferroni-corrected p-value=0.032, hazard ratio=28.2, and 95% confidence interval 6.66 to 119.0). In exome sequencing of tumor tissues, we searched for driver genes and pathways by testing for higher variant allelic fractions than the genome average. The tests yielded eleven genes with genome-wide significance (Table 1). By gene set analysis using the MSigDB Hallmark database, significant pathways included the P53 pathway (p&amp;lt;2 × 10−16), Wnt beta-catenin signaling (p&amp;lt;2 × 10−16), E2F targets (p=8 × 10−13), PI3K/AKT/mTOR signaling (4 × 10−7), and apoptosis (p=9 × 10−7). These results reveal the germline predisposition variants and somatic oncogenic drivers in UC and suggest immune evasion as a contributing factor for poor clinical outcomes in UC patients. Table 1. Genes with high allelic fractions Gene P-value Number of Variants TP53 &amp;lt;2 × 10−16 203 RB1 2.42 × 10−16 67 ELF3 2.06 × 10−7 38 TSC1 4.05 × 10−7 32 KMT2D 7.59 × 10−7 91 ZFP36L1 8.80 × 10−7 33 CDKN1A 2.47 × 10−6 40 FGFR3 1.11 × 10−5 37 ARID1A 1.28 × 10−5 62 SMARCA4 1.53 × 10−5 17 PIK3CA 2.00 × 10−5 53 Citation Format: Bing-Jian Feng, Wendy Kohlmann, David A. Nix, Aaron Atkinson, Kenneth M. Boucher, Courtney Carroll, Jill Kolesar, Eric A. Singer, Stephen B. Edge, Kamal Sahu, Alejandro Sanchez, Mikaela Larson, Michelle L. Churchman, Laura Graham, John D. Carpten, Yousef Zakharia, Lindsey Byrne, Rohit K. Jain, Kenneth G. Nepple, Ahmad Shabsigh, Jad Chahoud, Sumati Gupta. Germline and somatic genomic profiling of urothelial carcinoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6074.

Abstract 5963: Germline variant positive melanoma patients exhibit an enhanced inflammatory microenvironment

Abstract Germline pathogenic variants (gPV) in cancer susceptibility genes are present in roughly 15% of all melanoma diagnoses. Prior studies note improvements in checkpoint immunotherapy responsiveness in patients with a gPV, which is associated with an increased neo-antigen load in gPV patients. We have also previously reported improvements in melanoma specific survival (MSS) in gPV patients vs non-gPV. No studies to date have examined the immune environment in gPV patients which may account for improvements in survival. In our study, melanoma patients with a personal or family history of multiple cancers were offered germline testing utilizing a commercial germline cancer sequencing panel. Enrolled patients also received a blood draw with subsequent flow cytometry to analyze the immune phenotype. In a cohort of 540 melanoma patients, 80 had a gPV. Multivariable linear regression indicated that significantly fewer polymorphonuclear myeloid derived suppressor cells (PMN-MDSC’s) were noted relative to non-gPV patients when adjusting for melanoma stage at germline testing [β = -.45, 95% CI (-.76, -.15), p = .0036]. This difference was most significant in cutaneous, later stage (IIB-IV) patients, primarily stage III. We also interrogated patterns in gene signature between gPV and non-gPV patients in the TCGA PanCancer cutaneous melanoma cohort. We identified reductions in CCL27 (p = .007) and CCL1 (p = .06), genes associated with MDSC recruitment, across all stages in gPV patients, as well as reductions in ARG1 (p= .05) and S100A7 (p = .08), genes associated with PMN-MDSC’s, in later stage gPV patients. Pathway differences were analyzed using gene set enrichment analysis (GSEA). Analysis of Hallmark gene sets identified significantly upregulated signatures in inflammatory response, TNF-α signaling, IFN-γ signaling, and IL-2 STAT5 signaling in late stage gPV patients. KEGG pathway analysis further identified NK cell mediated cytotoxicity and TCR signaling as significantly upregulated in late stage gPV patients. Notably, fatty acid metabolism pathways, which have been implicated in immunosuppression through MDSC suppressive function, were downregulated in gPV patients. These results suggest that gPV melanoma is associated with both a depletion of PMN-MDSC’s and an upregulation of inflammatory microenvironmental genes in later stages which may explain improved outcomes. Citation Format: Alan Shen, Roshan Lodha, Brandon Bungo, Michelle Arbesman, Nikhil Pramod, Jennifer Ko, Brian Gastman, C. Marcela Diaz, Timothy Chan, Joshua Arbesman, Pauline Funchain. Germline variant positive melanoma patients exhibit an enhanced inflammatory microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5963.

Abstract 2090: Comprehensive interrogation of gene lists from genome-scale cancer screens with oncoEnrichR

Abstract Genome-scale screening experiments in cancer produce long lists of candidate genes that require extensive interpretation for biological insight and prioritization for follow-up studies. Interrogation of gene lists frequently represents a significant and time-consuming undertaking, in which experimental biologists typically combine results from a variety of bioinformatics resources in an attempt to portray and understand cancer relevance. As a means to simplify and strengthen the support for this endeavor, we have developed oncoEnrichR, a flexible bioinformatics tool that allows cancer researchers to comprehensively interrogate a given gene list along multiple facets of cancer relevance. oncoEnrichR differs from general gene set analysis frameworks through the integration of an extensive set of prior knowledge specifically relevant for cancer, including ranked gene-tumor type associations, literature-supported proto-oncogene and tumor suppressor gene annotations, target druggability data, regulatory interactions, synthetic lethality predictions, as well as prognostic associations, gene aberrations, and co-expression patterns across tumor types. The software produces a structured and user-friendly analysis report as its main output, where versions of all underlying data resources are explicitly logged, the latter being a critical component for reproducible science. We demonstrate the usefulness of oncoEnrichR through interrogation of two candidate lists from proteomic and CRISPR screens. oncoEnrichR is freely available as a web-based workflow hosted by the Galaxy platform (https://oncotools.elixir.no), and can also be accessed as a stand-alone R package (https://github.com/sigven/oncoEnrichR). Citation Format: Sigve Nakken, Sveinung Gundersen, Fabian L. Bernal, Dimitris Polychronopoulos, Eivind Hovig, Jørgen Wesche. Comprehensive interrogation of gene lists from genome-scale cancer screens with oncoEnrichR [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2090.

Abstract 3007: Psychosocial stressors and breast cancer gene expression in the Black Women's Health Study

Abstract Introduction: Chronic sympathetic nervous system (SNS) activation following exposure to psychosocial stressors may influence cancer risk through dysregulation of immune function or adrenergic signaling pathways. Prior research out of the Black Women’s Health Study (BWHS) reported associations between psychosocial stressors and breast cancer risk. We hypothesized that women with greater exposure to psychosocial stressors before their breast cancer diagnosis have higher tumor gene expression of immune-related and adrenergic signaling pathways. Methods: The BWHS is a large, prospective cohort study that has collected health and lifestyle information biennially since 1995. We included data from 417 BWHS breast cancer cases with RNA sequencing data and information on early-life trauma and neighborhood disadvantage. We used the R package DESeq2 to conduct age-adjusted differential gene expression analyses by levels of each stress exposure and described the top differentially expressed pathways using the Molecular Signature Database REACTOME subset of canonical pathways. Targeted analyses of immune-related pathways used CIBERSORT to quantify the proportions of infiltrating immune cells and the R package GSVA for single-sample gene set enrichment analysis (ssGSEA) of genes comprising a T cell exhaustion signature. We also used ssGSEA to evaluate a set of genes involved in adrenergic signaling. Given the variability in gene expression for ER+ versus ER- breast cancers, all analyses were run separately for ER+ (n=299) and ER- (n=118) tumors. Results: Pathways related to nervous system development and the metabolism of RNA were differentially expressed by levels of stress exposures among ER+ and ER- cases, while pathways related to immune function and adrenergic signaling were differentially expressed only among ER- cases, and only when evaluating differential gene expression by levels of neighborhood disadvantage. Targeted analyses of tumor immune infiltration showed significantly higher B cell fractions among ER+ cases without exposure to early trauma compared to those with early trauma. The relative fractions of other immune cells did not differ by stress exposure for ER+ or ER- tumors. Findings from ssGSEA gene set analyses indicated similar expression of genes involved in T cell exhaustion and adrenergic signaling pathways by stress exposure levels for both ER+ and ER- breast cancers. Conclusions: Our findings provide evidence of differential gene expression by levels of stress exposure; however, the differential expression may be driven by multiple pathways and not just the hypothesized immune-related and adrenergic signaling pathways. Additional studies are needed to describe mechanisms by which psychosocial stressors may influence breast cancer risk, both overall and by gene expression profile. Citation Format: Mollie E. Barnard, Xutao Wang, Jessica L. Petrick, W. Evan Johnson, Julie R. Palmer. Psychosocial stressors and breast cancer gene expression in the Black Women's Health Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3007.

Development of a cuproptosis-related signature for prognosis prediction in lung adenocarcinoma based on WGCNA.

Cuproptosis is a novel mitochondrial respiration-dependent cell death mechanism induced by copper that can kill cancer cells via copper carriers in cancer therapy. However, the clinical significance and prognostic value of cuproptosis in lung adenocarcinoma (LUAD) remains unclear. We performed a comprehensive bioinformatics analysis of the cuproptosis gene set, including copy number aberration, single-nucleotide variation, clinical characteristics, survival analysis, etc. Cuproptosis-related gene set enrichment scores (cuproptosis Z-scores) were calculated in The Cancer Genome Atlas (TCGA)-LUAD cohort using single-sample gene set enrichment analysis (ssGSEA). Modules significantly associated with cuproptosis Z-scores were screened by weighted gene co-expression network analysis (WGCNA). The hub genes of the module were then further screened by survival analysis and least absolute shrinkage and selection operator (LASSO) analysis, in which TCGA-LUAD (497 samples) and GSE72094 (442 samples) were used as the training and validation cohorts, respectively. Finally, we analyzed the tumor characteristics, immune cell infiltration levels, and potential therapeutic agents. Missense mutation and copy number variant (CNV) events were general in the cuproptosis gene set. We identified 32 modules, of which the MEpurple (107 genes) and MEpink (131 genes) modules significantly positively and negatively correlated with cuproptosis Z-scores, respectively. We identified 35 hub genes significantly related to overall survival and constructed a prognostic model consisting of 7 cuproptosis-related genes in patients with LUAD. Compared with the low-risk group, patients in the high-risk group had a worse overall survival and gene mutation frequency, as well as significantly higher tumor purity. In addition, infiltration of immune cells was also significantly different between the 2 groups. Furthermore, the correlation between the risk scores and half-maximum inhibitory concentration (IC50) of antitumor drugs in the Genomics of Drug Sensitivity in Cancer (GDSC) v. 2 database was explored, revealing differences in drug sensitivity across the 2 risk groups. Our study provided a valid prognostic risk model for LUAD and improved understanding of its heterogeneity, which may aid in the development of personalized treatment strategies.

MP50-11 INTEGRATIVE MULTI-OMICS PROFILING IN PENILE SQUAMOUS CELL CARCINOMA

You have accessJournal of UrologyCME1 Apr 2023MP50-11 INTEGRATIVE MULTI-OMICS PROFILING IN PENILE SQUAMOUS CELL CARCINOMA Timothy Shaw, Alyssa Obermayer, Dalia Ercan, Paul Stewart, Jad Chahoud, Peter Johnstone, Philippe Spiess, Steven Eschrich, and Daniel Grass Timothy ShawTimothy Shaw More articles by this author , Alyssa ObermayerAlyssa Obermayer More articles by this author , Dalia ErcanDalia Ercan More articles by this author , Paul StewartPaul Stewart More articles by this author , Jad ChahoudJad Chahoud More articles by this author , Peter JohnstonePeter Johnstone More articles by this author , Philippe SpiessPhilippe Spiess More articles by this author , Steven EschrichSteven Eschrich More articles by this author , and Daniel GrassDaniel Grass More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003298.11AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Penile squamous cell carcinoma (PSCC) is rare and about 50% of cases are related to HPV. Relapse after definitive therapy or first-line chemotherapy portends poor survival, thus we hypothesized novel targeting strategies in PSCC may be revealed by relating molecular pathways and patient survival. METHODS: We performed RNA-Seq on 37 PSCC tumors (HPV+=16, HPV-=16, unknown=5) from patients at our institution; 16 samples also underwent bulk proteomics with mass spectrometry. PATH-SURVEIOR is a framework for analyzing and visualizing “on-the-fly” associations of pathways with clinical endpoints. We applied PATH-SURVEIOR to perform single sample gene set enrichment (ssGSEA) on the PSCC RNA and protein expression data. Pathway scores and gene expression were dichotomized by the median to group samples as above/below for each pathway or individual gene expression. Multi-omics integration of pathways related to HPV status was assessed with DRPPM-EASY. TCGA data was downloaded from cBioportal. Uniform manifold projection (UMAP) was performed with the umap R package. RESULTS: We first performed an unsupervised analysis on PSCC and TCGA RNA data and UMAP found similarities with PSCC and other SCCs. Next, we associated pathways/genes and overall survival (OS) through univariable Cox regression and filtered results by hazard ratio (HR>1) and p-value<0.05, followed by HR ranking to define pathways/genes related with high-risk patients. Genes related to OS risk in PSCC included higher levels of DLL4, MET, and MSLN. Also, a cisplatin resistance gene set was linked to poor OS in a subset of PSCC patients. Systematic analysis of gene sets found expression associated with HPV as one prognostic feature based on an unsupervised pathway-level survival analysis; projection of this gene-set feature in the TCGA manifold space revealed an HPV-related cluster that included PSCC and other HPV-related cancers. By integrative GSEA of RNA and proteomics data, we found E2F and DNA damage repair pathways were enriched in HPV+ tumors, whereas HPV-tumors had features of EMT and inflammation. Whereas most RNAs and proteins aligned in direction of expression, several genes (e.g., TP53, MAGI3) were discordant to protein expression in HPV+ tumors, which may imply HPV-mediated translational regulation of protein subsets. CONCLUSIONS: Integrative analysis relating multi-omics data to patient survival from PSCC and TCGA samples identified features consistent with other HPV-related cancers, as well as potential novel targets to consider in PSCC. Source of Funding: Congressionally Directed Medical Research Programs: Rare Cancer Research Programs © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e689 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Timothy Shaw More articles by this author Alyssa Obermayer More articles by this author Dalia Ercan More articles by this author Paul Stewart More articles by this author Jad Chahoud More articles by this author Peter Johnstone More articles by this author Philippe Spiess More articles by this author Steven Eschrich More articles by this author Daniel Grass More articles by this author Expand All Advertisement PDF downloadLoading ...

Single-cell protein activity analysis reveals a novel subpopulation of chondrocytes and the corresponding key master regulator proteins associated with anti-senescence and OA progression.

Osteoarthritis (OA) is a prevalent senescence-related disease with substantial joint pain, loss of joint function, and cartilage degeneration. Because of the paucity of single-cell studies of OA and the gene dropout problem of single-cell RNA sequencing, it is difficult to acquire an in-depth understanding of the molecular characteristics of various chondrocyte clusters. Here, we aimed to provide new insights into chondrocyte senescence and a rationale for the development of effective intervention strategies for OA by using published single-cell RNA-sequencing data sets and the metaVIPER algorithm (Virtual Inference of Protein activity by Enriched Regulon). This algorithm was employed to present a proteome catalog of 62,449 chondrocytes from the cartilage of healthy individuals and OA patients at single-cell resolution. Furthermore, histopathologic analysis was carried out in cartilage samples from clinical patients and experimental mouse models of OA to validate above results. We identified 16 protein-activity-based chondrocyte clusters as well as the underlying master regulators in each cluster. By assessing the enrichment score of each cluster in bulk RNA-sequencing data, followed by gene-set variation analysis, we preliminarily identified a novel subpopulation of chondrocytes (cluster 3). This clinically relevant cluster was predicted to be the main chondrocyte cluster responsible for maintaining cellular homeostasis and anti-senescence. Specifically, we uncovered a set of the key leading-edge proteins of cluster 3 by validating the robustness of the above results using another human chondrocyte single-cell RNA-sequencing data set, consisting of 24,675 chondrocytes. Furthermore, cartilage samples from clinical patients and experimental mouse models of OA were used to evaluate the expression patterns of these leading-edge proteins, and the results indicated that NDRG2, TSPYL2, JMJD6 and HMGB2 are closely associated with OA pathogenesis and might play critical roles in modulating cellular homeostasis and anti-senescence in chondrocytes. Our study revealed a novel subpopulation of chondrocytes that are critical for anti-progression of OA and the corresponding master regulator proteins, which might serve as therapeutic targets in OA.

Predicting outcome in dogs with diffuse large B-cell lymphoma with a novel immune landscape signature.

Canine diffuse large B-cell lymphoma (cDLBCL) is characterized by high mortality and clinical heterogeneity. Although chemo-immunotherapy improves outcome, treatment response remains mainly unpredictable. To identify a set of immune-related genes aberrantly regulated and impacting the prognosis, we explored the immune landscape of cDLBCL by NanoString. The immune gene expression profile of 48 fully clinically characterized cDLBCLs treated with chemo-immunotherapy was analyzed with the NanoString nCounter Canine IO Panel using RNA extracted from tumor tissue paraffin blocks. A Cox proportional-hazards model was used to design a prognostic gene signature. The Cox model identified a 6-gene signature (IL2RB, BCL6, TXK, C2, CDKN2B, ITK) strongly associated with lymphoma-specific survival, from which a risk score was calculated. Dogs were assigned to high-risk or low-risk groups according to the median score. Thirty-nine genes were differentially expressed between the 2 groups. Gene set analysis highlighted an upregulation of genes involved in complement activation, cytotoxicity, and antigen processing in low-risk dogs compared with high-risk dogs, whereas genes associated with cell cycle were downregulated in dogs with a lower risk. In line with these results, cell type profiling suggested the abundance of natural killer and CD8+ cells in low-risk dogs compared with high-risk dogs. Furthermore, the prognostic power of the risk score was validated in an independent cohort of cDLBCL. In conclusion, the 6-gene-derived risk score represents a robust biomarker in predicting the prognosis in cDLBCL. Moreover, our results suggest that enhanced tumor antigen recognition and cytotoxic activity are crucial in achieving a more effective response to chemo-immunotherapy.

Integrated phenotyping of the anti-cancer immune response in HIV-associated hepatocellular carcinoma

HIV-seropositivity shortens survival in patients with hepatocellular carcinoma (HCC). Although risk factors for HCC including HCV infection can influence T cell phenotype, it is unknown whether HIV can influence functional characteristics of the T cell infiltrate. From the Liver Cancer in HIV biorepository, we derived 129 samples of transplanted (76%) or resected (20%) HCC in eight European and North American centres. We profiled intra- and peritumoural tissue to evaluate regulatory CD4+/FOXP3+ and immune-exhausted CD8+/PD1+ T cells in HIV+ (n= 66) and HIV- (n= 63) samples. We performed targeted transcriptomics and T-cell receptor sequencing in a restricted subset of samples evaluated in relationship with HIV status. We correlated immunopathologic features with patients' characteristics including markers of HIV infection. Of the 66 HIV+ patients, 83% were HCV coinfected with an undetectable HIV viral load (51%) and a median blood CD4+ cell count of 430 cells/mm3 (range 15-908). Patients who were HIV+ were compared with HIV- controls with similar staging characteristics including Barcelona Clinic Liver Cancer (BCLC) stage A-B (86% vs. 83%, p= 0.16), <3 nodules (90% vs. 83%, p= 0.3) and median alpha-foetoprotein values (10.9 vs. 12.8ng/ml, p= 0.72). HIV+ samples had higher PD-L1 expression rates in tumour tissue (51% vs. 8% p <0.0001) and displayed denser intratumoural CD4+/FOXP3+ (p <0.0001), CD8+/PD1+ (p<0.0001), with lower total peritumoural CD4+ (p <0.0001) and higher peritumoural CD8+/PD1+ (p <0.0001). Gene set analysis revealed HIV+ cases to have evidence of dysregulated adaptive and innate immunity. Tumour-infiltrating lymphocyte clonality was not influenced by HIV status. HIV-associated HCC harbours a profoundly immune-exhausted tumour microenvironment, warranting prospective testing of immunotherapy in this treatment-deprived patient population. Hepatocellular carcinoma is a non-AIDS defining malignancy characterised by poor survival. The programmed cell death (PD-1) pathway governs antiviral and anticancer immune exhaustion and is a therapeutic target in HCC. This study highlights how HIV infection is associated with significantly higher PD-L1 expression in HCC cells and in the surrounding microenvironment, leading to changes in cytotoxic and regulatory T cell function and dysregulation of proinflammatory pathways. Taken together, our results suggest dysfunctional T cell immunity as a mechanism of worse outcome in these patients and suggest clinical testing of checkpoint inhibitors in HIV-associated HCC.

A genome-wide association study identifies a possible role for cannabinoid signalling in the pathogenesis of diabetic kidney disease

Diabetic kidney disease (DKD), also known as diabetic nephropathy, is the leading cause of renal impairment and end-stage renal disease. Patients with diabetes are at risk for DKD because of poor control of their blood glucose, as well as nonmodifiable risk factors including age, ethnicity, and genetics. This genome-wide association study (GWAS) was conducted for the first time in the Emirati population to investigate possible genetic factors associated with the development and progression of DKD. We included data on 7,921,925 single nucleotide polymorphism (SNPs) in 258 cases of type 2 diabetes mellitus (T2DM) who developed DKD and 938 control subjects with T2DM who did not develop DKD. GWAS suggestive results (P < 1 × 10–5) were further replicated using summary statistics from three cohorts with T2DM-induced DKD (Bio Bank Japan data, UK Biobank, and FinnGen Project data) and T1DM-induced DKD (UK-ROI cohort data from Belfast, UK). When conducting a multiple linear regression model for gene-set analyses, the CNR2 gene demonstrated genome-wide significance at 1.46 × 10–6. SNPs in CNR2 gene, encodes cannabinoid receptor 2 or CB2, were replicated in Japanese samples with the leading SNP rs2501391 showing a Pcombined = 9.3 × 10–7, and odds ratio = 0.67 in association with DKD associated with T2DM, but not with T1DM, without any significant association with T2DM itself. The allele frequencies of our cohort and those of the replication cohorts were in most cases markedly different. In addition, we replicated the association between rs1564939 in the GLRA3 gene and DKD in T2DM (P = 0.016, odds ratio = 0.54 per allele C). Our findings suggest evidence that cannabinoid signalling may be involved in the development of DKD through CB2, which is expressed in different kidney regions and known to be involved in insulin resistance, inflammation, and the development of kidney fibrosis.

NaRnEA: An Information Theoretic Framework for Gene Set Analysis

Gene sets are being increasingly leveraged to make high-level biological inferences from transcriptomic data; however, existing gene set analysis methods rely on overly conservative, heuristic approaches for quantifying the statistical significance of gene set enrichment. We created Nonparametric analytical-Rank-based Enrichment Analysis (NaRnEA) to facilitate accurate and robust gene set analysis with an optimal null model derived using the information theoretic Principle of Maximum Entropy. By measuring the differential activity of ~2500 transcriptional regulatory proteins based on the differential expression of each protein's transcriptional targets between primary tumors and normal tissue samples in three cohorts from The Cancer Genome Atlas (TCGA), we demonstrate that NaRnEA critically improves in two widely used gene set analysis methods: Gene Set Enrichment Analysis (GSEA) and analytical-Rank-based Enrichment Analysis (aREA). We show that the NaRnEA-inferred differential protein activity is significantly correlated with differential protein abundance inferred from independent, phenotype-matched mass spectrometry data in the Clinical Proteomic Tumor Analysis Consortium (CPTAC), confirming the statistical and biological accuracy of our approach. Additionally, our analysis crucially demonstrates that the sample-shuffling empirical null models leveraged by GSEA and aREA for gene set analysis are overly conservative, a shortcoming that is avoided by the newly developed Maximum Entropy analytical null model employed by NaRnEA.

Genome-wide association study identifies four pan-ancestry loci for suicidal ideation in the Million Veteran Program.

Suicidal ideation (SI) often precedes and predicts suicide attempt and death, is the most common suicidal phenotype and is over-represented in veterans. The genetic architecture of SI in the absence of suicide attempt (SA) is unknown, yet believed to have distinct and overlapping risk with other suicidal behaviors. We performed the first GWAS of SI without SA in the Million Veteran Program (MVP), identifying 99,814 SI cases from electronic health records without a history of SA or suicide death (SD) and 512,567 controls without SI, SA or SD. GWAS was performed separately in the four largest ancestry groups, controlling for sex, age and genetic substructure. Ancestry-specific results were combined via meta-analysis to identify pan-ancestry loci. Four genome-wide significant (GWS) loci were identified in the pan-ancestry meta-analysis with loci on chromosomes 6 and 9 associated with suicide attempt in an independent sample. Pan-ancestry gene-based analysis identified GWS associations with DRD2, DCC, FBXL19, BCL7C, CTF1, ANNK1, and EXD3. Gene-set analysis implicated synaptic and startle response pathways (q's<0.05). European ancestry (EA) analysis identified GWS loci on chromosomes 6 and 9, as well as GWS gene associations in EXD3, DRD2, and DCC. No other ancestry-specific GWS results were identified, underscoring the need to increase representation of diverse individuals. The genetic correlation of SI and SA within MVP was high (rG = 0.87; p = 1.09e-50), as well as with post-traumatic stress disorder (PTSD; rG = 0.78; p = 1.98e-95) and major depressive disorder (MDD; rG = 0.78; p = 8.33e-83). Conditional analysis on PTSD and MDD attenuated most pan-ancestry and EA GWS signals for SI without SA to nominal significance, with the exception of EXD3 which remained GWS. Our novel findings support a polygenic and complex architecture for SI without SA which is largely shared with SA and overlaps with psychiatric conditions frequently comorbid with suicidal behaviors.

Geographically weighted linear combination test for gene-set analysis of a continuous spatial phenotype as applied to intratumor heterogeneity.

Background: The impact of gene-sets on a spatial phenotype is not necessarily uniform across different locations of cancer tissue. This study introduces a computational platform, GWLCT, for combining gene set analysis with spatial data modeling to provide a new statistical test for location-specific association of phenotypes and molecular pathways in spatial single-cell RNA-seq data collected from an input tumor sample. Methods: The main advantage of GWLCT consists of an analysis beyond global significance, allowing the association between the gene-set and the phenotype to vary across the tumor space. At each location, the most significant linear combination is found using a geographically weighted shrunken covariance matrix and kernel function. Whether a fixed or adaptive bandwidth is determined based on a cross-validation cross procedure. Our proposed method is compared to the global version of linear combination test (LCT), bulk and random-forest based gene-set enrichment analyses using data created by the Visium Spatial Gene Expression technique on an invasive breast cancer tissue sample, as well as 144 different simulation scenarios. Results: In an illustrative example, the new geographically weighted linear combination test, GWLCT, identifies the cancer hallmark gene-sets that are significantly associated at each location with the five spatially continuous phenotypic contexts in the tumors defined by different well-known markers of cancer-associated fibroblasts. Scan statistics revealed clustering in the number of significant gene-sets. A spatial heatmap of combined significance over all selected gene-sets is also produced. Extensive simulation studies demonstrate that our proposed approach outperforms other methods in the considered scenarios, especially when the spatial association increases. Conclusion: Our proposed approach considers the spatial covariance of gene expression to detect the most significant gene-sets affecting a continuous phenotype. It reveals spatially detailed information in tissue space and can thus play a key role in understanding the contextual heterogeneity of cancer cells.

Network biology of lapatinib resistance in different types of HER2-positive breast cancers informs the prioritization of the combination anticancer treatments as anti-resistance interventions

Background: With widespread therapeutic advancement, targeted anticancer therapeutics are taking over traditional treatment protocols. Nevertheless, the resistance to targeted therapeutics has halted the enthusiastic treatment response. An example of targeted therapy is Lapatinib. Lapatinib is a tyrosine kinase inhibitor used in HER2-positive breast cancer. It is widely used in HER2-positive metastatic breast cancer in combination with other drugs. Methods: This study's main objective was to provide a plausible mechanistic insight into lapatinib’s resistance in two HER2 positive breast cancer cell lines, SKBR3 and BT-474. We performed gene set analysis to identify the differentially expressed genes (DEG) in response to treatment with lapatinib from the gene expression profiles obtained from GSE38376 and GSE16179. The DEG was then analyzed by Ingenuity Pathway Analysis (IPA). Results: The IPA analysis showed that the increased expression of Hypoxia-inducible factor-1 alpha (HIF-1α) and Wnt/β-catenin and their related networks were associated with resistance and poor prognosis in SKBR3 and BT-474 cell lines, respectively. Although both cell lines are categorized as HER2 positive cell lines and in some reports were used interchangeably, in our hands, the two cell lines exhibited different biological pathways underlying resistance to lapatinib. In addition, among the other top canonical pathways, TNF was identified as the top upstream regulator in SKBR3 cell lines, whereas the Microphthalmia-associated transcription factor (MITF) was predicted as a top regulator in BT-474 cell lines. Conclusions: This study highlights the relevance of HIF-1α and Wnt/β-catenin compensatory networks in resistance toward lapatinib. Our findings outline the activation of angiogenesis and invasion processes in resistant cells with differential underlining gene networks in two different HER2 positive cell lines. The two cell lines reflect two different types of breast cancer, and hence the treatment strategy to avoid resistance should be planned differently.

Germline variation in RASAL2 may predict survival in patients with RAS-activated colorectal cancer.

Therapeutic agents that specifically target patients with RAS mutant colorectal cancer (CRC) are needed. We sought potential drug targets by relating genome-wide association study and survival data in patients with advanced CRC profiled for mitogen-activated protein kinase (MAPK) pathway mutations. In total, 694 patients from the clinical trials COIN and COIN-B had MAPK-activated CRCs (assigned as KRAS, NRAS, or BRAF mutant). Genome-wide single nucleotide polymorphism (SNP), gene, and gene-set analyses were performed to identify determinants of survival. For rs12028023 in RAS protein activator-like 2 (RASAL2), we studied its effect by MAPK pathway activation status (by comparing to 760 patients without MAPK-activated CRCs), MAPK gene mutation status, surface area of the primary tumor (as a marker of proliferation), and expression on RASAL2. In MAGMA genome-wide analyses, RASAL2 was the most significant gene associated with survival (p=2.0× 10-5 ). Patients carrying the minor (A) allele in the lead SNP, rs12028023 in intron 1 of RASAL2, had a median increase in survival of 167 days as compared with patients carrying the major allele. rs12028023 was predictive for survival by MAPK-activation status (pZ-test = 2.1× 10-3 ). Furthermore, rs12028023 improved survival in patients with RAS mutant (hazard ratio [HR]=0.62, 95% confidence intervals [CI]=0.5-0.8, p= 3.4× 10-5 ) but not BRAF mutant (p= 0.87) CRCs. The rs12028023 A-allele was associated with reduced surface area of the primary tumor (Beta=-0.037, standard error [SE]=0.017, p= 3.2× 10-2 ) and reduced RASAL2 expression in cultured fibroblasts (p= 1.6× 10-11 ). Our data demonstrate a prognostic role for RASAL2 in patients with MAPK-activated CRCs, with potential as a therapeutic target.

Integrated whole-genome gene expression analysis reveals an atlas of dynamic immune landscapes after myocardial infarction.

Myocardial infarction (MI) is a deadly medical condition leading to irreversible damage to the inflicted cardiac tissue. Elevated inflammatory response marks the severity of MI and is associated with the development of heart failure (HF), a long-term adverse outcome of MI. However, the efficacy of anti-inflammatory therapies for MI remains controversial. Deciphering the dynamic transcriptional signatures in peripheral blood mononuclear cells (PBMCs) is a viable and translatable route to better understand post-MI inflammation, which may help guide post-MI anti-inflammatory treatments. In this work, integrated whole-genome gene expression analysis was performed to explore dynamic immune landscapes associated with MI. GSEA and GSVA showed that pathways involved in the inflammatory response and metabolic reprogramming were significantly enriched in PBMCs from MI patients. Based on leukocyte profiles generated by xCell algorithm, the relative abundance of monocytes and neutrophils was significantly increased in PBMCs from MI patients and had positive correlations with typical inflammation-associated transcripts. Mfuzz clustering revealed temporal gene expression profiles of PBMCs during the 6-month post-MI follow-up. Analysis of DEGs and gene sets indicated that PBMCs from HF group were characterized by elevated and lasting expression of genes implicated in inflammation and coagulation. Consensus clustering generated 4 metabolic subtypes of PBMCs with molecular heterogeneity in HF patients. In summary, integrated whole-genome gene expression analysis here outlines a transcriptomic framework that may improve the understanding of dynamic signatures present in PBMCs, as well as the heterogeneity of PBMCs in MI patients with or without long-term clinical outcome of HF. Moreover, the work here uncovers the diversity and heterogeneity of PBMCs from HF patients, providing novel bioinformatic evidence supporting the mechanistic implications of metabolic reprogramming and mitochondrial dysfunction in the post-MI inflammation and HF. Therefore, our work here supports the notion that individualized anti-inflammatory therapies are needed to improve the clinical management of post-MI patients.

NDEx IQuery: a multi-method network gene set analysis leveraging the Network Data Exchange.

The investigation of sets of genes using biological pathways is a common task for researchers and is supported by a wide variety of software tools. This type of analysis generates hypotheses about the biological processes that are active or modulated in a specific experimental context. The Network Data Exchange Integrated Query (NDEx IQuery) is a new tool for network and pathway-based gene set interpretation that complements or extends existing resources. It combines novel sources of pathways, integration with Cytoscape, and the ability to store and share analysis results. The NDEx IQuery web application performs multiple gene set analyses based on diverse pathways and networks stored in NDEx. These include curated pathways from WikiPathways and SIGNOR, published pathway figures from the last 27 years, machine-assembled networks using the INDRA system, and the new NCI-PID v2.0, an updated version of the popular NCI Pathway Interaction Database. NDEx IQuery's integration with MSigDB and cBioPortal now provides pathway analysis in the context of these two resources. NDEx IQuery is available at https://www.ndexbio.org/iquery and is implemented in Javascript and Java.