Identify Gene Expression Signatures Research Articles

Retrospective study assessing the role of theandrogen receptor in clear cell renal cell cancer patients treated with VEGFR inhibitors in monotherapy.

Despite that incorporating antiangiogenic in combination with immune-checkpoint inhibitors as the standard first-line treatment for advanced clear cell renal cell cancer (ccRCC) yields promising outcomes, these regimens often lead to significant toxicity. However, a subgroup of patients has shown responsiveness to VEGFR tyrosine-kinase inhibitors (TKIs) in monotherapy, leading tothe question ofwhether employing combination therapies can significantly enhance overall survival in all patients over monotherapy. Thus, we aim to identify gene expression signatures that can predict TKI response within subpopulations that might benefit from single-agent therapies, to minimize unnecessary exposure to combination therapies and their associated toxicities, as well as to discover new potential therapeutic targets to improve ccRCC treatment. Based on prior data, the androgen receptor (AR) might meet both conditions. We evaluated the association between AR expression, assessed through NanoString® technology-derived mRNA counts, and the clinical outcomes of 98 ccRCC patients treated with first-line antiangiogenics and determined its association with other genes implicated in ccRCC tumorigenesis. Higher AR-expression correlates significantly with better prognosis and survival based on the MSKCC risk score, and longer PFS. Furthermore, we have identified a gene set signature associated with AR-overexpression and several genes involved in angiogenesis and transcriptional targets of the hypoxia-inducible factor, a cornerstone of ccRCC. AR-overexpression and its association with other genes could favor a transcriptomic signature set to aidin identifying patients suitable for TKI in monotherapy, rather than aggressive combinations, enhancing thus, precision and personalized therapeutic decisions.

Deciphering gene expression signatures in liver metastasized colorectal cancer in stage IV colorectal cancer patients

BackgroundColorectal cancer (CRC) liver metastasis (CRLM) is a clinical challenge, and optimizing treatment strategies is crucial for improving patient outcomes. This study aimed to identify gene expression signatures associated with CRLM for early diagnosis and improved treatment outcomes. MethodsWe obtained RNA-seq data of 34 samples (17 colorectal tumor samples from metastasized liver and 17 samples from normal surrounding colonic epithelia) from the Gene Expression Omnibus (GEO) with accession number GSE50760 and analysed them using next-generation knowledge discovery tools such as GEO2R and web based gene set enrichment analysis (WebGestalt). ResultsA total of 18808 genes were identified in the initial analysis which were further reduced to 2490 differentially expressed genes (DEGs) after applying different parameters using GEO2R tools. Furthermore, in the gene set enrichment analysis (GSEA), we analysed the biological processes, cellular components, and molecular functions. We analysed four pathways: KEGG, panther, reactome, and wikipathway cancer. In each analysis, we ascertained the most important top expressed and downregulated genes. ConclusionsWe identified various gene sets that could be used as important prognostic and therapeutic markers, particularly in patients with advanced CRLM. Future studies in larger cohorts may further our research findings to establish the best prognostic biomarkers for early diagnosis and improved overall survival.

Examination of irAE and treatment discontinuation irAE in patients with RCC with T effector phenotype.

4549 Background: The standard of care for renal cell carcinoma (RCC) is physician-choice of dual immunotherapy with ipilimumab/nivolumab (IO/IO) or a combination a VEGF inhibitor with immunotherapy (VEGF/IO). The IMmotion 151 trial identified gene expression signatures that differentiate likelihood of response to IO/IO (cluster 4 and 5 – T effector) versus VEGF/IO (cluster 1 and 2 - Angiogenic). Given that the T effector RNA-seq signature consists of higher expression of genes associated with inflammation, we hypothesized that patients with the T effector phenotype would have higher rates of immune-related adverse events (irAE) on IO-based therapy. Methods: Patients with metastatic RCC treated with systemic IO-based therapy had RNA sequencing completed on the primary tumor or metastatic site. Charts of patients who had a T effector RNA-seq signature were manually curated to identify development of irAE by reading the most recent clinic note and searching ‘steroids’, ‘irAE’, ‘rash’, ‘thyroid’. Hits from searches were investigated by manual chart review. Results: 118 patients underwent RNA sequencing and 105 passed quality control. Nineteen patients (18%) were assigned the T effector phenotype. Of the 17 metastatic patients, twelve of these patients received at least one dose of IO/IO in the first or second line of therapy, five were treated with VEGF/IO Among patients treated with IO/IO, 8 developed any grade irAE (66%; 41% grade 3+), 5 (41%) required steroid treatment, 5 (41%) required hospitalization, and 4 (33%) discontinued treatment due to irAE. Grade 3 toxicities in this group included colitis, adrenal insufficiency, and hypophysitis. Of the 5 patients treated with VEGF/IO, 3 developed any grade irAE (60%; 20% grade 3+), none were treated with steroids, and none were hospitalized. The grade 3 toxicity in this group was adrenal insufficiency. Conclusions: Patients with a T effector RNA-seq signature had higher rates ofirAE than historic controls when treated with IO/IO leading to high rates of steroid use and treatment discontinuation. VEGF/IO-treated patients with the T effector RNA-seq signature had similar rates of irAE to historic controls. The ongoing OPTIC clinical will expand on these results by studying treatment assignment in a prospective manner.

Association of TRAIL receptor with phosphatase SHP-1 enables repressing T cell receptor signaling and T cell activation through inactivating Lck

BackgroundT cell receptor (TCR) signaling and T cell activation are tightly regulated by gatekeepers to maintain immune tolerance and avoid autoimmunity. The TRAIL receptor (TRAIL-R) is a TNF-family death receptor that transduces apoptotic signals to induce cell death. Recent studies have indicated that TRAIL-R regulates T cell-mediated immune responses by directly inhibiting T cell activation without inducing apoptosis; however, the distinct signaling pathway that regulates T cell activation remains unclear. In this study, we screened for intracellular TRAIL-R-binding proteins within T cells to explore the novel signaling pathway transduced by TRAIL-R that directly inhibits T cell activation.MethodsWhole-transcriptome RNA sequencing was used to identify gene expression signatures associated with TRAIL-R signaling during T cell activation. High-throughput screening with mass spectrometry was used to identify the novel TRAIL-R binding proteins within T cells. Co-immunoprecipitation, lipid raft isolation, and confocal microscopic analyses were conducted to verify the association between TRAIL-R and the identified binding proteins within T cells.ResultsTRAIL engagement downregulated gene signatures in TCR signaling pathways and profoundly suppressed phosphorylation of TCR proximal tyrosine kinases without inducing cell death. The tyrosine phosphatase SHP-1 was identified as the major TRAIL-R binding protein within T cells, using high throughput mass spectrometry-based proteomics analysis. Furthermore, Lck was co-immunoprecipitated with the TRAIL-R/SHP-1 complex in the activated T cells. TRAIL engagement profoundly inhibited phosphorylation of Lck (Y394) and suppressed the recruitment of Lck into lipid rafts in the activated T cells, leading to the interruption of proximal TCR signaling and subsequent T cell activation.ConclusionsTRAIL-R associates with phosphatase SHP-1 and transduces a unique and distinct immune gatekeeper signal to repress TCR signaling and T cell activation via inactivating Lck. Thus, our results define TRAIL-R as a new class of immune checkpoint receptors for restraining T cell activation, and TRAIL-R/SHP-1 axis can serve as a potential therapeutic target for immune-mediated diseases.

Gene expression alterations predict the pathological complete response in triple-negative breast cancer exploratory analysis of the NACATRINE trial

This exploratory analysis of the Neoadjuvant Carboplatin in Triple Negative Breast Cancer (NACATRINE) study aimed to identify the biomarkers of pathological complete response (pCR) in patients with triple-negative breast cancer (TNBC) treated with neoadjuvant chemotherapy (NAC) within the context of a clinical trial. The NACATRINE trial is a phase II, single-center, randomized, open-label clinical trial that investigated the addition of carboplatin to sequential anthracycline- and taxane-based NAC for TNBC. We evaluated the gene expression in untreated samples to investigate its association with pCR, overall survival (OS), and disease-free survival (DFS). RNA was extracted from the tissue biopsy, and the nCounter Breast Cancer panel was used to analyze gene expression. Of the 66 patients included in the gene expression profiling analysis, 24 (36.4%) achieved pCR and 42 (63.6%) had residual disease. In unsupervised hierarchical clustering analyses, differentially expressed genes between patients with and without pCR were identified irrespective of the treatment (24 genes), carboplatin (37 genes), and non-carboplatin (27 genes) arms. In receiver operating characteristic (ROC) curve analysis, 10 genes in the carboplatin arm (area under the ROC curve [AUC], 0.936) and three genes in the non-carboplatin arm (AUC, 0.939) were considered to be potential pCR-associated biomarkers. We identified genes that were associated with improvements in OS and DFS in addition to being related to pCR. We successfully identified gene expression signatures associated with pCR in pretreatment samples of patients with TNBC treated with NAC. Further investigation of these biomarkers is warranted.

Abstract B064: Single-cell RNA sequencing reveals tumorigenic trajectories of mismatch repair deficient cells

Abstract Mismatch repair (MMR) deficiency is commonly found in tumors with high mutational burden. Although the mutational signatures of these deficiencies are determined, the initial trajectories these cells follow to reach a tumorigenic state with high mutational load have not been studied due to lack of isogenic model systems. For this reason, we generated three isogenic MMR deficient cell lines from a normally untransformed cell line with few genomic abnormalities and low mutational burden. After continued culturing of these MMR-deficient cell lines for several months, we profiled them by single cell RNA sequencing using the 10X Chromium platform. Next, we identified different clusters of cells in MMR deficient cell lines that acquire tumorigenic properties. In these clusters, we identified gene expression signatures that are responsible from the tumorigenic properties of these clusters of cells. After isolation of the single clones that bear these gene expression signatures, we characterized how MMR deficiency can give rise to tumors with particular gene expression trajectories. In addition, we performed CRISPR/Cas9-based genome-wide screens to understand the vulnerabilities of these clusters of cells. Altogether, our results shed light on the early steps of tumorigenesis in MMR deficiency. Citation Format: Alexandra Vitor, Salvatore Benfatto, Frank Zenke, Sebastian Waszak, Balca Mardin. Single-cell RNA sequencing reveals tumorigenic trajectories of mismatch repair deficient cells [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr B064.

Personalized drug screening in patient-derived organoids of biliary tract cancer and its clinical application

Patients with biliary tract cancer (BTC) show different responses to chemotherapy, and there is no effective way to predict chemotherapeutic response. We have generated 61 BTC patient-derived organoids (PDOs) from 82 tumors (74.4%) that show similar histological and genetic characteristics to the corresponding primary BTC tissues. BTC tumor tissues with enhanced stemness- and proliferation-related gene expression by RNA sequencing can more easily form organoids. As expected, BTC PDOs show different responses to the chemotherapies of gemcitabine, cisplatin, 5-fluoruracil, oxaliplatin, etc. The drug screening results in PDOs are further validated in PDO-based xenografts and confirmed in 92.3% (12/13) of BTC patients with actual clinical response. Moreover, we have identified gene expression signatures of BTC PDOs with different drug responses and established gene expression panels to predict chemotherapy response in BTC patients. In conclusion, BTC PDO is a promising precision medicine tool for anti-cancer therapy in BTC patients.

Spatial transcriptomics reveal markers of histopathological changes in Duchenne muscular dystrophy mouse models

Duchenne muscular dystrophy is caused by mutations in the DMD gene, leading to lack of dystrophin. Chronic muscle damage eventually leads to histological alterations in skeletal muscles. The identification of genes and cell types driving tissue remodeling is a key step to developing effective therapies. Here we use spatial transcriptomics in two Duchenne muscular dystrophy mouse models differing in disease severity to identify gene expression signatures underlying skeletal muscle pathology and to directly link gene expression to muscle histology. We perform deconvolution analysis to identify cell types contributing to histological alterations. We show increased expression of specific genes in areas of muscle regeneration (Myl4, Sparc, Hspg2), fibrosis (Vim, Fn1, Thbs4) and calcification (Bgn, Ctsk, Spp1). These findings are confirmed by smFISH. Finally, we use differentiation dynamic analysis in the D2-mdx muscle to identify muscle fibers in the present state that are predicted to become affected in the future state.

Immune gene co-expression signatures implicated in occurence and persistence of cognitive dysfunction in depression

Cognitive dysfunction contributes significantly to the burden caused by Major Depressive Disorder (MDD). Yet, while compelling evidence suggests that different biological processes play a part in both MDD aetiology and the development of cognitive decline more generally, we only begin to understand the molecular underpinnings of depression-related cognitive impairment. Developments in psychometric assessments, molecular high-throughput methods and systems biology derived analysis strategies advance this endeavour.Here, we aim to identify gene expression signatures associated with cognitive dysfunction and cognitive improvement following therapy using RNA sequencing to analyze the whole blood-derived transcriptome of altogether 101 MDD patients who enrolled in the CERT-D study. The mRNA(Nova)Seq based transcriptome was analyzed from whole blood taken at baseline assessment, and patients' cognitive performance was measured twice at baseline and following eight weeks of therapy by means of the THINC integrated tool. Thirty-six patients showed comparatively low cognitive performance at baseline assessment, and 32 patients showed comparatively strong cognitive improvement following therapy. Differential gene expression analysis was performed using limma to a significance threshold of 0.05 and a logFC cutoff of |1.2|. Although we observed some indications for expression differences related to low cognitive performance and cognitive therapy response, signals did not withstand adjustment for multiple testing. Applying WGCNA, we retrieved altogether 25 modules of co-expressed genes and we used a combination of correlational and linear analyses to identify modules related to baseline cognitive performance and cognitive improvement following therapy. Three immune modules reflected distinct but interrelated immune processes (the yellow module: neutrophil-mediated immunity, the darkorange module: interferon signaling, the tan module: platelet activation), and higher expression of the yellow (r = −0.21, p < .05), the dark orange (r = 0.2, p < .05), and the tan (r = −0.23, p < .05) module correlated significantly negatively with patients' cognitive baseline performance. Patients' cognitive baseline performance was a significant predictor of the darkorange module (b = −0.039, p < .05) and the tan module's expression (b = 0.02, p < .05) and was close to becoming a significant predictor of the yellow module's expression (b = −0.02, p = .05). Furthermore, patients characterized by comparatively low cognitive performance at baseline showed significantly higher expression of the tan module when compared to all other patients F(1,97) = 4.32, p < .05, η= 0.04. Following eight weeks of treatment, we observed altogether significant improvement in patients' cognitive performance (b = 0.30, p < .001), and patients with comparatively high cognitive gain showed noticeably lower, but not significantly lower F(1,98) = 3.76, p = .058, expression of a dark turquoise module, which reflects complement and B-cell-associated immune processes. Noteworthy, the relation between cognitive performance and module expression remained observable after controlling for symptom severity and BMI, which partly accounted for variance in module expression. As such, our findings provide further evidence for the involvement of immune processes in MDD related cognitive dysfunction and they suggest that different immune processes contribute to the development and long-term persistence of cognitive dysfunction in the context of depression.

Perturbations in fatty acid metabolism and collagen production infer pathogenicity of a novel MBTPS2 variant in Osteogenesis imperfecta.

Osteogenesis imperfecta (OI) is a heritable and chronically debilitating skeletal dysplasia. Patients with OI typically present with reduced bone mass, tendency for recurrent fractures, short stature and bowing deformities of the long bones. Mutations causative of OI have been identified in over 20 genes involved in collagen folding, posttranslational modification and processing, and in bone mineralization and osteoblast development. In 2016, we described the first X-linked recessive form of OI caused by MBTPS2 missense variants in patients with moderate to severe phenotypes. MBTPS2 encodes site-2 protease, a Golgi transmembrane protein that activates membrane-tethered transcription factors. These transcription factors regulate genes involved in lipid metabolism, bone and cartilage development, and ER stress response. The interpretation of genetic variants in MBTPS2 is complicated by the gene's pleiotropic properties; MBTPS2 variants can also cause the dermatological conditions Ichthyosis Follicularis, Atrichia and Photophobia (IFAP), Keratosis Follicularis Spinulosa Decalvans (KFSD) and Olmsted syndrome (OS) without skeletal abnormalities typical of OI. Using control and patient-derived fibroblasts, we previously identified gene expression signatures that distinguish MBTPS2-OI from MBTPS2-IFAP/KFSD and observed stronger suppression of genes involved in fatty acid metabolism in MBTPS2-OI than in MBTPS2-IFAP/KFSD; this was coupled with alterations in the relative abundance of fatty acids in MBTPS2-OI. Furthermore, we observed a reduction in collagen deposition in the extracellular matrix by MBTPS2-OI fibroblasts. Here, we extrapolate our observations in the molecular signature unique to MBTPS2-OI to infer the pathogenicity of a novel MBTPS2 c.516A>C (p.Glu172Asp) variant of unknown significance in a male proband. The pregnancy was terminated at gestational week 21 after ultrasound scans showed bowing of femurs and tibiae and shortening of long bones particularly of the lower extremity; these were further confirmed by autopsy. By performing transcriptional analyses, gas chromatography-tandem mass spectrometry-based quantification of fatty acids and immunocytochemistry on fibroblasts derived from the umbilical cord of the proband, we observed perturbations in fatty acid metabolism and collagen production similar to what we previously described in MBTPS2-OI. These findings support pathogenicity of the MBTPS2 variant p.Glu172Asp as OI-causative and highlights the value of extrapolating molecular signatures identified in multiomics studies to characterize novel genetic variants.

Modeling human skeletal development using human pluripotent stem cells

Chondrocytes and osteoblasts differentiated from induced pluripotent stem cells (iPSCs) will provide insights into skeletal development and genetic skeletal disorders and will generate cells for regenerative medicine applications. Here, we describe a method that directs iPSC-derived sclerotome to chondroprogenitors in 3D pellet culture then to articular chondrocytes or, alternatively, along the growth plate cartilage pathway to become hypertrophic chondrocytes that can transition to osteoblasts. Osteogenic organoids deposit and mineralize a collagen I extracellular matrix (ECM), mirroring invivo endochondral bone formation. We have identified gene expression signatures at key developmental stages including chondrocyte maturation, hypertrophy, and transition to osteoblasts and show that this system can be used to model genetic cartilage and bone disorders.

Methodology to identify a gene expression signature by merging microarray datasets

A vast number of microarray datasets have been produced as a way to identify differentially expressed genes and gene expression signatures. A better understanding of these biological processes can help in the diagnosis and prognosis of diseases, as well as in the therapeutic response to drugs. However, most of the available datasets are composed of a reduced number of samples, leading to low statistical, predictive and generalization power. One way to overcome this problem is by merging several microarray datasets into a single dataset, which is typically a challenging task. Statistical methods or supervised machine learning algorithms are usually used to determine gene expression signatures. Nevertheless, statistical methods require an arbitrary threshold to be defined, and supervised machine learning methods can be ineffective when applied to high-dimensional datasets like microarrays. We propose a methodology to identify gene expression signatures by merging microarray datasets. This methodology uses statistical methods to obtain several sets of differentially expressed genes and uses supervised machine learning algorithms to select the gene expression signature. This methodology was validated using two distinct research applications: one using heart failure and the other using autism spectrum disorder microarray datasets. For the first, we obtained a gene expression signature composed of 117 genes, with a classification accuracy of approximately 98%. For the second use case, we obtained a gene expression signature composed of 79 genes, with a classification accuracy of approximately 82%. This methodology was implemented in R language and is available, under the MIT licence, at https://github.com/bioinformatics-ua/MicroGES.

Transcriptome-wide association study of circulating IgE levels identifies novel targets for asthma and allergic diseases.

Measurement of circulating immunoglobulin E (IgE) concentration is helpful for diagnosing and treating asthma and allergic diseases. Identifying gene expression signatures associated with IgE might elucidate novel pathways for IgE regulation. To this end, we performed a discovery transcriptome-wide association study to identify differentially expressed genes associated with circulating IgE levels in whole-blood derived RNA from 5,345 participants in the Framingham Heart Study across 17,873 mRNA gene-level transcripts. We identified 216 significant transcripts at a false discovery rate <0.05. We conducted replication using the meta-analysis of two independent external studies: the Childhood Asthma Management Program (n=610) and the Genetic Epidemiology of Asthma in Costa Rica Study (n=326); we then reversed the discovery and replication cohorts, which revealed 59 significant genes that replicated in both directions. Gene ontology analysis revealed that many of these genes were implicated in immune function pathways, including defense response, inflammatory response, and cytokine production. Mendelian randomization (MR) analysis revealed four genes (CLC, CCDC21, S100A13, and GCNT1) as putatively causal (p<0.05) regulators of IgE levels. GCNT1 (beta=1.5, p=0.01)-which is a top result in the MR analysis of expression in relation to asthma and allergic diseases-plays a role in regulating T helper type 1 cell homing, lymphocyte trafficking, and B cell differentiation. Our findings build upon prior knowledge of IgE regulation and provide a deeper understanding of underlying molecular mechanisms. The IgE-associated genes that we identified-particularly those implicated in MR analysis-can be explored as promising therapeutic targets for asthma and IgE-related diseases.

Neighbor-specific gene expression revealed from physically interacting cells during mouse embryonic development

Development of multicellular organisms is orchestrated by persistent cell-cell communication between neighboring partners. Direct interaction between different cell types can induce molecular signals that dictate lineage specification and cell fate decisions. Current single-cell RNA-seq technology cannot adequately analyze cell-cell contact-dependent gene expression, mainly due to the loss of spatial information. To overcome this obstacle and resolve cell-cell contact-specific gene expression during embryogenesis, we performed RNA sequencing of physically interacting cells (PIC-seq) and assessed them alongside similar single-cell transcriptomes derived from developing mouse embryos between embryonic day (E) 7.5 and E9.5. Analysis of the PIC-seq data identified gene expression signatures that were dependent on the presence of specific neighboring cell types. Our computational predictions, validated experimentally, demonstrated that neural progenitor (NP) cells upregulate Lhx5 and Nkx2-1 genes, when exclusively interacting with definitive endoderm (DE) cells. Moreover, there was a reciprocal impact on the transcriptome of DE cells, as they tend to upregulate Rax and Gsc when in contact with NP cells. Using individual cell transcriptome data, we formulated a means of computationally predicting the impact of one cell type on the transcriptome of its neighboring cell types. We have further developed a distinctive spatial-t-distributed stochastic neighboring embedding to display the pseudospatial distribution of cells in a 2-dimensional space. In summary, we describe an innovative approach to study contact-specific gene regulation during embryogenesis.

S-22-3: UNCOVERING NEW GENES, TISSUES AND THERAPEUTIC TARGETS FOR BLOOD PRESSURE THROUGH LARGE-SCALE TRANSCRIPTOME-WIDE ASSOCIATION STUDIES

Objective: Transcriptome-wide association study (TWAS) leverages information from reference panels of human tissues to predict the genetically determined component of expression in much larger datasets for thousands of genes and explore their association with a phenotype/disease of interest in thousands of individuals. Using TWAS, we sought to 1) define contributors to blood pressure (BP) regulation across a panel of 49 human cell-types/tissues 2) detect new kidney genes associated with BP in human kidney samples and 3) identify new pharmacological opportunities for hypertension through TWAS-informed drug repurposing. Design and method: We performed TWAS using PrediXcan across 49 human tissues/cell-types from The Genotype-Tissue Expression project and ranked the overall relevance of tissue of BP according to three independent metrics defining the strength of uncovered tissue-trait associations. We then trained predictors of gene expression from 478 samples from the Human Kidney Tissue Resource by applying a new predictive model which utilises epigenetic and three-dimensional genomic information to prioritise essential genetic variants. The subsequent BP kidney TWAS was conducted in up to ∼750k individuals from UK Biobank and International Consortium for Blood Pressure. Finally, we combined the input from BP kidney TWAS with Connectivity Map to identify drugs capable of inducing or reversing the identified gene expression signatures. Results: We found that fibroblasts, kidney cortex, lymphocytes, brain, thyroid, adrenal glands, aorta and spleen showed the overall strongest associations with BP across 49 human tissues/cell-types. Through TWAS of systolic blood pressure/diastolic blood pressure/pulse pressure we identified 997 kidney genes associated with at least one BP trait. Of these, 562 (56%) have not been reported before. Our computational druggability analysis re-affirmed the potential of several known BP inducers (glucocorticoid receptor agonists, calcineurin inhibitors) to increase BP and uncovered adenylate cyclase system activators to reverse the BP-related changes in the transcriptome. We also found purinergic receptor as a potential gene target for drug repurposing in hypertension. Finally, we found that use of topoisomerase inhibitors, cyclin-dependent kinase inhibitors, inosine monophosphate dehydrogenase inhibitors, and histone deacetylase inhibitors may be associated with hypotension. Conclusion: Our data provided evidence for the role of the kidney as an organ of the key relevance to hypertension and highlighted the importance of immune system in BP regulation. We also identified 997 kidney genes robustly associated with BP. Through TWAS-informed drug repurposing analysis, we uncovered novel targets for drug development in hypertension and highlighted BP drop as a potential side effect of several existing therapeutics.

ERR2 and ERR3 promote the development of gamma motor neuron functional properties required for proprioceptive movement control

The ability of terrestrial vertebrates to effectively move on land is integrally linked to the diversification of motor neurons into types that generate muscle force (alpha motor neurons) and types that modulate muscle proprioception, a task that in mammals is chiefly mediated by gamma motor neurons. The diversification of motor neurons into alpha and gamma types and their respective contributions to movement control have been firmly established in the past 7 decades, while recent studies identified gene expression signatures linked to both motor neuron types. However, the mechanisms that promote the specification of gamma motor neurons and/or their unique properties remained unaddressed. Here, we found that upon selective loss of the orphan nuclear receptors ERR2 and ERR3 (also known as ERRβ, ERRγ or NR3B2, NR3B3, respectively) in motor neurons in mice, morphologically distinguishable gamma motor neurons are generated but do not acquire characteristic functional properties necessary for regulating muscle proprioception, thus disrupting gait and precision movements. Complementary gain-of-function experiments in chick suggest that ERR2 and ERR3 could operate via transcriptional activation of neural activity modulators to promote a gamma motor neuron biophysical signature of low firing thresholds and high firing rates. Our work identifies a mechanism specifying gamma motor neuron functional properties essential for the regulation of proprioceptive movement control.

Transcriptome signatures preceding the induction of anti-stalk antibodies elicited after universal influenza vaccination.

A phase 1 clinical trial to test the immunogenicity of a chimeric group 1 HA (cHA) universal influenza virus vaccine targeting the conserved stalk domain of the hemagglutinin of influenza viruses was carried out. Vaccination with adjuvanted-inactivated vaccines induced high anti-stalk antibody titers. We sought to identify gene expression signatures that correlate with such induction. Messenger-RNA sequencing in whole blood was performed on the peripheral blood of 53 vaccinees. We generated longitudinal data on the peripheral blood of 53 volunteers, at early (days 3 and 7) and late (28 days) time points after priming and boosting with cHAs. Differentially expressed gene analysis showed no differences between placebo and live-attenuated vaccine groups. However, an upregulation of genes involved in innate immune responses and type I interferon signaling was found at day 3 after vaccination with inactivated adjuvanted formulations. Cell type deconvolution analysis revealed a significant enrichment for monocyte markers and different subsets of dendritic cells as mediators for optimal B cell responses and significant increase of anti-stalk antibodies in sera. A significant upregulation of immunoglobulin-related genes was only observed after administration of adjuvanted vaccines (either as primer or booster) with specific induction of anti-stalk IGVH1-69. This approach informed of specific immune signatures that correlate with robust anti-stalk antibody responses, while also helping to understand the regulation of gene expression induced by cHA proteins under different vaccine regimens.

Placental Transcriptome Profiling in Subtypes of Diabetic Pregnancies Is Strongly Confounded by Fetal Sex

The placenta is a temporary organ with a unique structure and function to ensure healthy fetal development. Placental dysfunction is involved in pre-eclampsia (PE), fetal growth restriction, preterm birth, and gestational diabetes mellitus (GDM). A diabetic state affects maternal and fetal health and may lead to functional alterations of placental metabolism, inflammation, hypoxia, and weight, amplifying the fetal stress. The placental molecular adaptations to the diabetic environment and the adaptive spatio-temporal consequences to elevated glucose or insulin are largely unknown (2). We aimed to identify gene expression signatures related to the diabetic placental pathology of placentas from women with diabetes mellitus. Human placenta samples (n = 77) consisting of healthy controls, women with either gestational diabetes mellitus (GDM), type 1 or type 2 diabetes, and women with GDM, type 1 or type 2 diabetes and superimposed PE were collected. Interestingly, gene expression differences quantified by total RNA sequencing were mainly driven by fetal sex rather than clinical diagnosis. Association of the principal components with a full set of clinical patient data identified fetal sex as the single main explanatory variable. Accordingly, placentas complicated by type 1 and type 2 diabetes showed only few differentially expressed genes, while possible effects of GDM and diabetic pregnancy complicated by PE were not identifiable in this cohort. We conclude that fetal sex has a prominent effect on the placental transcriptome, dominating and confounding gene expression signatures resulting from diabetes mellitus in settings of well-controlled diabetic disease. Our results support the notion of placenta as a sexual dimorphic organ.

Molecular characterization of renal cell carcinoma tumors from a phase III anti-angiogenic adjuvant therapy trial

Multigene assays can provide insight into key biological processes and prognostic information to guide development and selection of adjuvant cancer therapy. We report a comprehensive genomic and transcriptomic analysis of tumor samples from 171 patients at high risk for recurrent renal cell carcinoma post nephrectomy from the S-TRAC trial (NCT00375674). We identify gene expression signatures, including STRAC11 (derived from the sunitinib-treated population). The overlap in key elements captured in these gene expression signatures, which include genes representative of the tumor stroma microenvironment, regulatory T cell, and myeloid cells, suggests they are likely to be both prognostic and predictive of the anti-angiogenic effect in the adjuvant setting. These signatures also point to the identification of potential therapeutic targets for development in adjuvant renal cell carcinoma, such as MERTK and TDO2. Finally, our findings suggest that while anti-angiogenic adjuvant therapy might be important, it may not be sufficient to prevent recurrence and that other factors such as immune response and tumor environment may be of greater importance.

Insights into H2O2-induced signaling in Jurkat cells from analysis of gene expression

Hydrogen peroxide (H2O2) is a ubiquitous oxidant produced in a regulated manner by various enzymes in mammalian cells. H2O2 reversibly oxidizes thiol groups of cysteine residues to mediate intracellular signaling. While examples of H2O2-dependent signaling have been reported, the exact molecular mechanism(s) of signaling and the pathways affected are not well understood. Here, the transcriptomic response of Jurkat T cells to H2O2 was investigated to determine global effects on gene expression. With a low H2O2 concentration (10 µM) that did not induce an oxidative stress response or cell death, extensive changes in gene expression occurred after 4 h (6803 differentially expressed genes). Of the genes with a greater then 2-fold change in expression, 85% were upregulated suggesting that in a physiological setting H2O2 predominantly activates gene expression. Pathway analysis identified gene expression signatures associated with FOXO and NTRK signaling. These signatures were associated with an overlapping set of transcriptional regulators. Overall, our results provide a snapshot of gene expression changes in response to H2O2, which, along with further studies, will lead to new insights into the specific pathways that are activated in response to endogenous production of H2O2, and the molecular mechanisms of H2O2 signaling.