scholarly journals Paternal Obesity and SGLT2 Inhibition Alter Expression of Placental Regulatory Genes

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A752-A753
Author(s):  
Lei Su ◽  
Soravis Osataphan ◽  
Jessica Desmond ◽  
Rui Fang ◽  
Jeremy Chimene-Weiss ◽  
...  
Keyword(s):  
Sglt2 Inhibitor ◽  
Enrichment Analysis ◽  
Placental Weight ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Metabolic Effects ◽  
Altered Expression ◽  
Gene Sets ◽  
The Impact ◽  
Paternal Obesity

Abstract We previously demonstrated that paternal obesity is associated with offspring metabolic risk during later life, and that paternal SGLT2i treatment improves offspring metabolic phenotypes. Since the placenta is a key determinant of prenatal growth and development, we hypothesized the placenta could mediate the impact of paternal obesity and paternal SGLT2i treatment. Male C57BL/6J mice were fed standard chow (Purina 9F) or 60% high-fat diet (HFD, D12492, Research Diet), or 60% HFD plus the SGLT2 inhibitor canagliflozin (CANA, 25 mg/kg/d) for 4 weeks before mating with chow-fed females. Placenta were collected on E16.5, and RNA-seq was performed on placenta from male offspring (paternal chow, pChow, n=4, pHFD, n=5, and pHFD+CANA, n=4), and differentially expressed genes were identified using Limma. Placenta weight was significantly lower in pHFD (0.089±0.004 g, 7 litters from 6 fathers) vs. both pChow (0.108±0.011 g, 4 litters, 4 fathers) and pHFD+CANA (0.107±0.013 g, 5 litters, 5 fathers)(p<0.05). Litter size, fetal or liver weight, or fetal/placental weight ratio did not differ between groups. No genes were differentially expressed in pHFD vs. pChow (FDR<0.1). Gene set enrichment analysis (GSEA) identified significance (FDR<0.05, NES>1.8) for gene sets in steroid metabolic, drug catabolic, and protein-containing complex remodeling processes. Genes responsible for enrichment included cholesterol biosynthesis (Hmgcs1), transport (Apob, Apoa1/2/4, Apom, Apoc1, Vldlr, Pcsk9) and steroid hormone biosynthesis genes (Hsd3b1, Cyp11b1), all upregulated in pHFD by 1.5-3-fold. These results suggest pHFD could potentially affect maternal and fetal cholesterol homeostasis. pHFD+CANA altered expression of 154 genes vs. pHFD (7 up-, 147 down, FDR <0.1, FC >|1.5|); 18 gene sets were downregulated by pHFD+CANA (GSEA NES<-1.8 and FDR<0.05), including the 3 sets upregulated by pHFD. ChEA3 enrichment analysis (ENCODE library) predicted regulation by transcription factors important for cholesterol and sterol biosynthesis (Srebf1/2), embryonic development (Foxa2), & glucose homeostasis (Hnf4g), suggesting these pathways could mediate the “rescue” effect of pHFD+CANA (FDR<0.05). Expression of Foxa2 was significantly downregulated (4-fold) in pHFD+CANA vs. pHFD. We independently analyzed expression of the 78 detected imprinted genes. None were significantly different in pHFD, but both paternally expressed (Nnat) and maternally expressed genes (H19, Phlda2, Meg3, Meg8) were downregulated in pHFD+CANA vs. pHFD by 1.4 to 3.8 fold in pHFD+CANA (p<0.001,FDR<0.1). In summary, paternal SGLT2i reversed the impact of pHFD on placental weight. Robust impact of both pHFD and pSGLT2i on the transcriptome suggests that the placenta is a key mediator of paternal metabolic effects on offspring development and metabolic disease risk, potentially via modification of lipid transport.

Next Generation Sequencing reveals profound transcriptomic differences between reticulated and non-reticulated platelets from healthy donors, CCS- and STEMI patients

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
L Hille ◽  
T.G Nuehrenberg ◽  
L Hein ◽  
F.J Neumann ◽  
D Trenk
Keyword(s):  
Healthy Subjects ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Gene Set Enrichment ◽  
Reticulated Platelets ◽  
Gene Sets ◽  
Healthy Donors ◽  
Go Terms ◽  
Generation Sequencing

Abstract Background The youngest circulating platelets – so called reticulated platelets (RP) – represent a highly prothrombotic platelet subpopulation. Previous studies showed that patients with chronic coronary syndrome (CCS) as well as patients with ST-elevation myocardial infarction (STEMI) have higher amounts of RP compared to healthy subjects. It has been suggested that intrinsic properties of RP impact on cardiovascular risk. However, it is unknown if transcriptomic alterations contribute to the prothrombotic properties of RP. Purpose This study sought to investigate differences in the transcriptomic landscape of sorted RP versus non-RP, i.e. young and old platelets, in healthy subjects, CCS- and STEMI-patients. Methods Blood samples were obtained from healthy subjects as well as from patients with CCS/STEMI (n=8 each) the day after PCI. After staining with SYTO 13, platelets from each donor were sorted into a RP and a non-RP fraction based on their RNA-content. Next Generation Sequencing (NGS) was applied to generate sequencing reads for sorted RP and non-RP from the 3 cohorts. Data was analyzed by use of the Freiburg bioinformatics platform “Galaxy”. Results Investigation of transcriptomic alterations in non-RP versus RP by differential gene expression analysis revealed a total number of 2,476 transcripts that were differentially expressed in platelets from healthy donors, 2,075 in CCS-patients and 1,852 in STEMI patients, respectively (adj. p<0.05 in all analyses). Comparison of these transcripts revealed a large overlap of 500 mRNAs which were downregulated and 660 mRNAs which were upregulated in RP in all 3 cohorts. However, there are also distinct groups of transcripts that are differentially expressed in only one of the 3 cohorts. Gene ontology (GO)-analysis of the 500 uniformly enriched transcripts in RP yielded 38 overrepresented GO-terms. A large group was related to cytoskeleton and shape change. Furthermore, GO-terms associated to the platelet activation cascade were overrepresented. Upregulated transcripts included well-known examples like GP6 and GP9, P-selectin, integrin β3, integrin a-IIb, and tubulin α4a. GO-analysis of enriched transcripts in non-RP showed a large group associated to mitosis and cell nucleus/DNA which is surprising since platelets neither contain DNA nor a nucleus. Gene set enrichment analysis (GSEA) determined higher normalized enrichment scores for several gene sets associated to platelet degranulation, aggregation and activation in the STEMI-cohort. Gene sets affecting cell adhesion and platelet calcium homeostasis were overexpressed in particular in CCS-patients. Conclusion NGS-results indicate a highly prothrombotic transcriptome of RP from each cohort with high amounts of differentially expressed transcripts overlapping. However, GSEA identified gene sets that are particularly overexpressed in CCS- or STEMI-patients which might contribute to platelet hyperreactivity in these cohorts. Gene set enrichment analysis Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): PharmCompNet Baden-Wuerttemberg: Kompetenznetzwerk Pharmakologie Baden-Wuerttemberg - Wirkstoffnetzwerke als Grundlagen der individualisierten Arzneistofftherapie

scholarly journals Genomic Characterization of Human and Rat Prolactinomas

Endocrinology ◽  
2012 ◽  
Vol 153 (8) ◽  
pp. 3679-3691 ◽  
Author(s):  
Yunguang Tong ◽  
Yun Zheng ◽  
Jin Zhou ◽  
Nelson M. Oyesiku ◽  
H. Phillip Koeffler ◽  
...  
Keyword(s):  
Critical Role ◽  
Enrichment Analysis ◽  
Underlying Disease ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Brown Norway ◽  
Genomic Changes ◽  
Gene Sets ◽  
Pituitary Glands

Although prolactinomas can be effectively treated with dopamine agonists, about 20% of patients develop dopamine resistance or tumor recurrence after surgery, indicating a need for better understanding of underlying disease mechanisms. Although estrogen-induced rat prolactinomas have been widely used to investigate the development of this tumor, the extent that the model recapitulates features of human prolactinomas is unclear. To prioritize candidate genes and gene sets regulating human and rat prolactinomas, microarray results derived from human prolactinomas and pituitaries of estrogen-treated ACI rats were integrated and analyzed. A total of 4545 differentially expressed pituitary genes were identified in estrogen-treated ACI rats [false discovery rate (FDR) < 0.01]. By comparing pituitary microarray results derived from estrogen-treated Brown Norway rats (a strain not sensitive to estrogen), 4073 genes were shown specific to estrogen-treated ACI rats. Human prolactinomas exhibited 1177 differentially expressed genes (FDR < 0.05). Combining microarray data derived from human prolactinoma and pituitaries of estrogen-treated ACI rat, 145 concordantly expressed genes, including E2F1, Myc, Igf1, and CEBPD, were identified. Gene set enrichment analysis revealed that 278 curated pathways and 59 gene sets of transcription factors were enriched (FDR < 25%) in estrogen-treated ACI rats, suggesting a critical role for Myc, E2F1, CEBPD, and Sp1 in this rat prolactinoma. Similarly increased Myc, E2F1, and Sp1 expression was validated using real-time PCR and Western blot in estrogen-treated Fischer rat pituitary glands. In summary, characterization of individual genes and gene sets in human and in estrogen-induced rat prolactinomas validates the model and provides insights into genomic changes associated with this commonly encountered pituitary tumor.

scholarly journals Integrative DNA Methylation and Gene Expression Analysis Reveals Candidate Biomarkers Associated with Dichotomized Response to Chemoimmunotherapy in Diffuse Large B-Cell Lymphoma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 22-22
Author(s):  
Ellen K. Kendall ◽  
Manishkumar S. Patel ◽  
Sarah Ondrejka ◽  
Agrima Mian ◽  
Yazeed Sawalha ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Research Funding ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
B Cell Lymphoma ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Gene Sets

Background: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma. While 60% of DLBCL patients achieve complete remission with frontline therapy, relapsed/refractory (R/R) DLBCL patients have a poor prognosis with median overall survival below one year, necessitating investigation into the biological principles that distinguish cured from R/R DLBCL. Recent analyses have identified unfavorable molecular signatures when accounting for gene expression, copy number alterations and mutational profiles in R/R DLBCL. However, an integrative analysis of the relationship between epigenetic and transcriptomic changes has yet to be described. In this study, we compared baseline methylation and gene expression profiles of DLBCL patients with dichotomized clinical outcomes. Methods: Diagnostic DLBCL biopsies were obtained from two patient cohorts: patients who relapsed or were refractory following chemoimmunotherapy ("R/R"), and patients who entered durable clinical remission following therapy ("cured"). The median age for R/R and cured cohorts were 62 (range 35-86) years vs. 64 (range 28-83) years (P= 0.27). High-intermediate or high IPI scores were present in 14 vs. 6 patients (P= 0.08) in the R/R and cured cohorts, respectively. All patients were treated with frontline R-CHOP or R-EPOCH. DNA and RNA were extracted simultaneously from formalin-fixed, paraffin embedded biopsy samples. An Illumina 850k Methylation Array was used to identify DNA methylation levels in 29 R/R patients and 20 cured patients. RNA sequencing was performed on 9 R/R patients and 7 cured patients at diagnosis using Illumina HiSeq4000. Differentially methylated probes were identified using the DMRcate package, and differentially expressed genes were identified using the DESeq2 package. Gene set enrichment analysis was performed using canonical pathway gene sets from MSigDB. Results: At the time of diagnosis, we found significant epigenetic and transcriptomic differences between cured and R/R patients. Comparing cured to R/R samples, there were 8,159 differentially methylated probes (FDR<0.05). Differentially methylated regions between R/R and cured cohorts overlap with genes previously identified as mutation hotspots in DLBCL. Upon comparing transcriptomic profiles between R/R and cured, 267 genes were found to be differentially expressed (Log2FC>|1| and FDR<0.05). Gene set enrichment analysis revealed gene sets related to cell cycle, membrane trafficking, Rho and Rab family GTPase function, and transcriptional regulation were upregulated in the R/R samples. Gene sets related to innate immune signaling, Type I and II interferon signaling, fatty acid and carbohydrate metabolism were upregulated in the cured samples. To identify genes likely to be regulated by specific changes in methylation, we selected genes that were both differentially expressed and differentially methylated between the R/R and cured cohorts. In the R/R samples, 13 genes (ARMC5, ARRDC1, C12orf57, CCSER1, D2HGDH, DUOX2, FAM189B, FKBP2, KLF5, MFSD10, NEK8, NT5C, and WDR18) were significantly hypermethylated and underexpressed when compared to cured specimens, suggesting that epigenetic silencing of these genes is associated with lack of response to chemoimmunotherapy. In contrast, 12 genes (ATP2B1, C15orf41, FAM102B, FAM3C, FHOD3, FYTTD1, GPR180, KIAA1841, LRMP, MEF2A, RRAS2, and TPD52) were significantly hypermethylated and underexpressed in cured patients, suggesting that epigenetic silencing of these genes is favorable for treatment response. Many of these epigenetically modified genes have been previously implicated in cancer biology, including roles in NOTCH signaling, chromosomal instability, and biomarkers of prognosis. Conclusions: This is the first integrative epigenetic and transcriptomic analysis of diagnostic biopsies from cured and R/R DLBCL patients following chemoimmunotherapy. At the time of diagnosis, both the methylation and gene expression profiles significantly differ between patients that enter durable remission as opposed to those who are R/R to therapy. Soon, the hypomethylating agent CC-486 (i.e. oral azacitidine) will be explored in combination with mini-R-CHOP for older DLBCL patients in whom DNA methylation is likely increased. These data support the use of hypomethylating agents to potentially restore sensitivity of DLBCL to chemoimmunotherapy. Disclosures Hsi: Eli Lilly: Research Funding; Abbvie: Research Funding; Miltenyi: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; CytomX: Consultancy, Honoraria. Hill:Celgene: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Takeda: Research Funding; Beigene: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding.

scholarly journals Higher Acid-Base Imbalance Associated with Respiratory Failure Could Decrease the Survival of Patients with Scrub Typhus during Intensive Care Unit Stay: A Gene Set Enrichment Analysis

2019 ◽  
Vol 8 (10) ◽  
pp. 1580 ◽  
Author(s):  
Kyoung Min Moon ◽  
Kyueng-Whan Min ◽  
Mi-Hye Kim ◽  
Dong-Hoon Kim ◽  
Byoung Kwan Son ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Respiratory Failure ◽  
Scrub Typhus ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Acid Base ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Gene Sets

Ninety percent of patients with scrub typhus (SC) with vasculitis-like syndrome recover after mild symptoms; however, 10% can suffer serious complications, such as acute respiratory failure (ARF) and admission to the intensive care unit (ICU). Predictors for the progression of SC have not yet been established, and conventional scoring systems for ICU patients are insufficient to predict severity. We aimed to identify simple and robust indicators to predict aggressive behaviors of SC. We evaluated 91 patients with SC and 81 non-SC patients who were admitted to the ICU, and 32 cases from the public functional genomics data repository for gene expression analysis. We analyzed the relationships between several predictors and clinicopathological characteristics in patients with SC. We performed gene set enrichment analysis (GSEA) to identify SC-specific gene sets. The acid-base imbalance (ABI), measured 24 h before serious complications, was higher in patients with SC than in non-SC patients. A high ABI was associated with an increased incidence of ARF, leading to mechanical ventilation and worse survival. GSEA revealed that SC correlated to gene sets reflecting inflammation/apoptotic response and airway inflammation. ABI can be used to indicate ARF in patients with SC and assist with early detection.

scholarly journals In Silico Identification of Contradictory Role of ADAMTS5 in Hepatocellular Carcinoma

2021 ◽  
Vol 20 ◽  
pp. 153303382098682
Author(s):  
Zhipeng Zhu ◽  
Jiuhua Xu ◽  
Xiaofang Wu ◽  
Sihao Lin ◽  
Lulu Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Subgroup Analysis ◽  
Prognostic Value ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Clinicopathological Parameters ◽  
Free Survival ◽  
Cox Regression Analysis ◽  
The Impact

Background: ADAMTS5 has different roles in multiple types of cancers and participates in various molecular mechanisms. However, the prognostic value of ADAMTS5 in patients with hepatocellular carcinoma (HCC) still remains unclear. We carried the study to evaluate the prognostic value and identified underlying molecular mechanisms in HCC. Methods: Firstly, the association of ADAMTS5 expression and clinicopathological parameters was evaluated by in GSE14520. Next, ADAMTS5 expression in HCC was performed using GSE14520, GSE36376, GSE76427 and The Cancer Genome Atlas (TCGA) profile. Furthermore, Kaplan-Meier analysis, Univariate and Multivariate Cox regression analysis, subgroup analysis was performed to evaluate the prognostic value of ADAMTS5 in HCC. Finally, GO enrichment analysis, gene set enrichment analysis (GSEA) and weighted gene co-expression network analysis (WGCNA) were performed to revealed underlying molecular mechanisms. Result: The expression of ADAMTS5 was positively correlated with the development of HCC. Next, high ADAMTS5 expression was significantly associated with poorer survival (all P < 0.05) and the impact of ADAMTS5 on all overall survival (OS), disease-free survival (DFS), relapse-free survival (RFS), disease specific survival (DSS) and progression free interval (PFI) was specific for HCC among other 29 cancer types. Subgroup analysis showed that ADAMTS5 overexpression was significantly associated with poorer OS in patients with HCC. Finally, ADAMTS5 might participate in the status conversion from metabolic-dominant to extracellular matrix-dominant, and the activation of ECM-related biological process might contribute to high higher mortality risk for patients with HCC. Conclusion: ADAMTS5 may play an important role in the progression of HCC, and may be considered as a novel and effective biomarker for predicting prognosis for patients with HCC.

scholarly journals Transcriptional survey of alveolar macrophages in a murine model of chronic granulomatous inflammation reveals common themes with human sarcoidosis

2018 ◽  
Vol 314 (4) ◽  
pp. L617-L625 ◽  
Author(s):  
Arjun Mohan ◽  
Anagha Malur ◽  
Matthew McPeek ◽  
Barbara P. Barna ◽  
Lynn M. Schnapp ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Murine Model ◽  
Alveolar Macrophages ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Multiwall Carbon Nanotube ◽  
Gene Set Enrichment ◽  
Integrated Network ◽  
Gene Set ◽  
Gene Sets

To advance our understanding of the pathobiology of sarcoidosis, we developed a multiwall carbon nanotube (MWCNT)-based murine model that shows marked histological and inflammatory signal similarities to this disease. In this study, we compared the alveolar macrophage transcriptional signatures of our animal model with human sarcoidosis to identify overlapping molecular programs. Whole genome microarrays were used to assess gene expression of alveolar macrophages in six MWCNT-exposed and six control animals. The results were compared with the transcriptional profiles of alveolar immune cells in 15 sarcoidosis patients and 12 healthy humans. Rigorous statistical methods were used to identify differentially expressed genes. To better elucidate activated pathways, integrated network and gene set enrichment analysis (GSEA) was performed. We identified over 1,000 differentially expressed between control and MWCNT mice. Gene ontology functional analysis showed overrepresentation of processes primarily involved in immunity and inflammation in MCWNT mice. Applying GSEA to both mouse and human samples revealed upregulation of 92 gene sets in MWCNT mice and 142 gene sets in sarcoidosis patients. Commonly activated pathways in both MWCNT mice and sarcoidosis included adaptive immunity, T-cell signaling, IL-12/IL-17 signaling, and oxidative phosphorylation. Differences in gene set enrichment between MWCNT mice and sarcoidosis patients were also observed. We applied network analysis to differentially expressed genes common between the MWCNT model and sarcoidosis to identify key drivers of disease. In conclusion, an integrated network and transcriptomics approach revealed substantial functional similarities between a murine model and human sarcoidosis particularly with respect to activation of immune-specific pathways.

scholarly journals Drug perturbation gene set enrichment analysis (dpGSEA): a new transcriptomic drug screening approach

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Mike Fang ◽  
Brian Richardson ◽  
Cheryl M. Cameron ◽  
Jean-Eudes Dazard ◽  
Mark J. Cameron
Keyword(s):  
Drug Targets ◽  
T Regulatory Cells ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Regulatory Cells ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Gene Sets ◽  
Gastroenteropancreatic Neuroendocrine Tumor ◽  
Public Datasets

Abstract Background In this study, we demonstrate that our modified Gene Set Enrichment Analysis (GSEA) method, drug perturbation GSEA (dpGSEA), can detect phenotypically relevant drug targets through a unique transcriptomic enrichment that emphasizes biological directionality of drug-derived gene sets. Results We detail our dpGSEA method and show its effectiveness in detecting specific perturbation of drugs in independent public datasets by confirming fluvastatin, paclitaxel, and rosiglitazone perturbation in gastroenteropancreatic neuroendocrine tumor cells. In drug discovery experiments, we found that dpGSEA was able to detect phenotypically relevant drug targets in previously published differentially expressed genes of CD4+T regulatory cells from immune responders and non-responders to antiviral therapy in HIV-infected individuals, such as those involved with virion replication, cell cycle dysfunction, and mitochondrial dysfunction. dpGSEA is publicly available at https://github.com/sxf296/drug_targeting. Conclusions dpGSEA is an approach that uniquely enriches on drug-defined gene sets while considering directionality of gene modulation. We recommend dpGSEA as an exploratory tool to screen for possible drug targeting molecules.

Robust Metabolic Transcriptional Components in 34,494 Patient-Derived Samples and Cell Lines

2021 ◽  
Author(s):  
Vincent Christiaan Leeuwenburgh ◽  
Carlos G. Urzúa-Traslaviña ◽  
Arkajyoti Bhattacharya ◽  
Marthe T.C. Walvoort ◽  
Mathilde Jalving ◽  
...  
Keyword(s):  
Cell Lines ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Metabolic Processes ◽  
Gene Sets ◽  
Transcriptional Changes ◽  
Cancer Tissues ◽  
Tumor Biopsies ◽  
Transcriptional Landscape

Abstract Background: Patient-derived bulk expression profiles of cancers can provide insight into transcriptional changes that underlie reprogrammed metabolism in cancer. These profiles represent the average expression pattern of all heterogeneous tumor and non-tumor cells present in biopsies of tumor lesions. Hence, subtle transcriptional footprints of metabolic processes can be concealed by other biological processes and experimental artifacts. However, consensus Independent Component Analyses (c-ICA) can capture statistically independent transcriptional footprints, of both subtle and more pronounced metabolic processes. Methods: We performed c-ICA with 34,494 bulk expression profiles of patient-derived tumor biopsies, non-cancer tissues, and cell lines. Gene set enrichment analysis with 608 gene sets that describe metabolic processes was performed to identify transcriptional components enriched for metabolic processes (mTCs). The activity of these mTCs were determined in all samples to create a metabolic transcriptional landscape. Results: A set of 555 mTCs were identified of which many were robust across different datasets, platforms, and patient-derived tissues and cell lines. We demonstrate how the metabolic transcriptional landscape defined by the activity of these mTCs in samples can be used to explore associations between the metabolic transcriptome and drug sensitivities, patient outcomes, and the composition of the immune tumor microenvironment. Conclusions: To facilitate the use of our transcriptional metabolic landscape, we have provided access to all data via a web portal ( www.themetaboliclandscapeofcancer.com ). We believe this resource will contribute to the formulation of new hypotheses on how to metabolically engage the tumor or its (immune) microenvironment.

scholarly journals Bioinformatics-based Screening of Key Genes for Saponin Metabolism in Quinoa

2021 ◽  
Author(s):  
Chengang Guo ◽  
Zhimin wei ◽  
Wei Lyu ◽  
Yanlou Geng
Keyword(s):  
Differentially Expressed Genes ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Hierarchical Cluster ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Differential Analysis ◽  
Rna Seq ◽  
Protein Coding ◽  
Key Genes

Abstract Quinoa saponins have complex, diverse and evident physiologic activities. However, the key regulatory genes for quinoa saponin metabolism are not yet well studied. The purpose of this study was to explore genes closely related to quinoa saponin metabolism. In this study, the significantly differentially expressed genes in yellow quinoa were firstly screened based on RNA-seq technology. Then, the key genes for saponin metabolism were selected by gene set enrichment analysis (GSEA) and principal component analysis (PCA) statistical methods. Finally, the specificity of the key genes was verified by hierarchical clustering. The results of differential analysis showed that 1654 differentially expressed genes were achieved after pseudogenes deletion. Therein, there were 142 long non-coding genes and 1512 protein-coding genes. Based on GSEA analysis, 116 key candidate genes were found to be significantly correlated with quinoa saponin metabolism. Through PCA dimension reduction analysis, 57 key genes were finally obtained. Hierarchical cluster analysis further demonstrated that these key genes can clearly separate the four groups of samples. The present results could provide references for the breeding of sweet quinoa and would be helpful for the rational utilization of quinoa saponins.

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