Human Gene Expression Data Research Articles

Time-Resolved Systems Medicine Reveals Viral Infection-Modulating Host Targets.

Introduction: Drug-resistant infections are becoming increasingly frequent worldwide, causing hundreds of thousands of deaths annually. This is partly due to the very limited set of protein drug targets known for human-infecting viral genomes. The eleven influenza virus proteins, for instance, exploit host cell factors for replication and suppression of the antiviral immune responses. A systems medicine approach to identify relevant and druggable host factors would dramatically expand therapeutic options. Therapeutic target identification, however, has hitherto relied on static molecular networks, whereas in reality the interactome, in particular during an infection, is subject to constant change.Methods: We developed time-course network enrichment (TiCoNE), an expert-centered approach for discovering temporal response pathways. In the first stage of TiCoNE, time-series expression data is clustered in a human-augmented manner to identify groups of biological entities with coherent temporal responses. Throughout this process, the expert can add, remove, merge, or split temporal patterns. The resulting groups can then be mapped to an interaction network to identify enriched pathways and to analyze cross-talk enrichments and depletions between groups. Finally, temporal response groups of two experiments can be intersected, to identify condition-variant response patterns that represent promising drug-target candidates.Results: We applied TiCoNE to human gene expression data for influenza A virus infection and rhino virus infection, respectively. We then identified coherent temporal response patterns and employed our cross-talk analysis to establish two potential timelines of systems-level host responses for either infection. Next, we compared the two phenotypes and unraveled condition-variant temporal groups interacting on a networks level. The highest-ranking ones we then validated via literature search and wet-lab experiments. This not only confirmed many of our candidates as previously known, but we also identified phospholipid scramblase 1 (encoded by PLSCR1) as a previously not recognized host factor that is essential for influenza A virus infection.Conclusion: With TiCoNE we developed a novel approach for conjointly analyzing molecular networks with time-series expression data and demonstrated its power by identifying temporal drug-targets. We provide proof-of-concept that not only novel targets can be identified using our approach, but also that anti-infective drug target discovery can be enhanced by investigating temporal molecular networks of the host in response to viral infection.

Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n=35,584 total samples, 11,986 with ASD). Using an enhanced Bayesian framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate ≤ 0.1. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained for severe neurodevelopmental delay, while 53 show higher frequencies in individuals ascertained for ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most of the risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In human cortex single-cell gene expression data, expression of risk genes is enriched in both excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory/inhibitory imbalance underlying ASD.

Learning Differential Module Networks Across Multiple Experimental Conditions.

Module network inference is a statistical method to reconstruct gene regulatory networks, which uses probabilistic graphical models to learn modules of coregulated genes and their upstream regulatory programs from genome-wide gene expression and other omics data. Here, we review the basic theory of module network inference, present protocols for common gene regulatory network reconstruction scenarios based on the Lemon-Tree software, and show, using human gene expression data, how the software can also be applied to learn differential module networks across multiple experimental conditions.

Integrated Genomic and Proteomic Analysis of Murine CLL-like Cells Reveals SF3B1 Mutation to Impact DNA Damage Response and BCR Signaling

Collective large-scale sequencing efforts have unexpectedly revealed the high frequency of mutations in the splicing factor genes (SF3B1, U2AF1, SRSF2, ZRSR2) in various solid and hematological cancers, suggesting the association of splicing dysregulation with tumorigenesis. Mutations in SF3B1 occur in 5-20% of patients with chronic lymphocytic leukemia (CLL) and are associated with poorer overall survival and chemotherapy resistance. These mutations are restricted to hotspots (>50% at K700E site) and strongly co-occur with ATM mutations (loss-of-function) and deletion of 11q (ATM minimal deleted region). Numerous studies including ours have demonstrated that somatic alterations in this gene cause RNA splicing dysregulation, however, how this splicing factor mutation alone and in combination with ATM deletion impacts cellular processes and contributes to CLL remains to be fully defined.To this end, we modeled the effects of these combined alterations by crossing mice with conditional knockout of Atm and mice with a conditional knock-in allele of SF3B1 mutation (Sf3b1-K700E). We achieved B cell-restricted expression of heterozygous Sf3b1 mutation and Atm deletion by breeding these mice with CD19-Cre homozygous transgenic mice. Conditional expression of heterozygous Sf3b1-K700E mutation in mouse B cells disrupts pre-mRNA splicing, alters B-cell development, and induces a state of cellular senescence. Combined with Atm deletion in B cells led to the overcoming of cellular senescence and the development of clonal CLL cells in elderly mice at low penetrance (6%). These malignant cells could be propagated by in vivo passaging, with detectable disease within 4 weeks following transfer, thus making this mouse line amenable to further drug discovery and biologic investigations.To fully understand the underlying mechanisms of how the combined alterations led to CLL, we performed integrated genome, transcriptome, and proteome analysis using mouse CLL (DM-CLL) cells and B cells with either Sf3b1 mutation or Atm deletion, or with double genetic lesions (DM). Whole-genome sequencing of paired DNA from B cells (or DM-CLL) and non-B cell tissue (kidney) revealed the somatic mutation rate in the CLL cells to be ~0.5 mutations/Mb. Few recurrent mutations were identified among the samples. However, copy number variation analysis of DM-CLL cells revealed recurrent amplifications of chromosomes 15 and 17. RNA-seq analysis revealed that these amplifications were associated with overexpression of 835 of 987 Chr15 and Chr17 genes detected in DM-CLL vs. DM cells. Of note, 146 genes were overexpressed in human CLLs with SF3B1 mutations (DFCI cohort), compared to normal B-cells (p<0.05).Integrated transcriptome and proteome analysis of the DM-CLL cells showed coordinated dysregulation of multiple CLL-associated cellular processes with B-cell receptor (BCR) signaling as the most dramatically downregulated compared to DM cells. Since BCR signaling is a therapeutic target in CLL and has critical roles in B cell biology, we asked how SF3B1 mutation contributes to gene expression of BCR signaling. Through RNA-seq data analysis derived from two independent patient cohorts (DFCI and ICGC), we identified downregulation of BCR gene expression in SF3B1 mutant CLL cells. In line with this, human CLLs harboring SF3B1 mutations exhibit greater sensitivity to in vitro treatment with ibrutinib, and altered response kinetics in vivo to ibrutinib, per analysis of patients with SF3B1 mutations treated with ibrutinib. These studies together highlight a role of SF3B1 mutation in BCR signaling.In summary, we have generated a genetically-engineered murine model that recapitulates human CLL genetics, and presents an informative model to functionally dissect the effects of mutant SF3B1 in a B cell context. Starting from computation-based identification of recurrent co-occurring events in CLL, our study employs murine lines that express genetic alterations in an lineage-specific fashion, utilizes integrated genomics and proteomics approaches to dissect pathways that are fundamental to CLL phenotype, and more importantly, links the dysregulated pathways back to human CLL gene expression data and clinical trials to reveal novel mechanisms underlying therapeutic response. DisclosuresWiestner:Pharmacyclics LLC, an AbbVie Company: Research Funding. Wu:Neon Therapeutics: Equity Ownership.

Clinical significance of APOB inactivation in hepatocellular carcinoma

Recent findings from The Cancer Genome Atlas project have provided a comprehensive map of genomic alterations that occur in hepatocellular carcinoma (HCC), including unexpected mutations in apolipoprotein B (APOB). We aimed to determine the clinical significance of this non-oncogenetic mutation in HCC. An Apob gene signature was derived from genes that differed between control mice and mice treated with siRNA specific for Apob (1.5-fold difference; P < 0.005). Human gene expression data were collected from four independent HCC cohorts (n = 941). A prediction model was constructed using Bayesian compound covariate prediction, and the robustness of the APOB gene signature was validated in HCC cohorts. The correlation of the APOB signature with previously validated gene signatures was performed, and network analysis was conducted using ingenuity pathway analysis. APOB inactivation was associated with poor prognosis when the APOB gene signature was applied in all human HCC cohorts. Poor prognosis with APOB inactivation was consistently observed through cross-validation with previously reported gene signatures (NCIP A, HS, high-recurrence SNUR, and high RS subtypes). Knowledge-based gene network analysis using genes that differed between low-APOB and high-APOB groups in all four cohorts revealed that low-APOB activity was associated with upregulation of oncogenic and metastatic regulators, such as HGF, MTIF, ERBB2, FOXM1, and CD44, and inhibition of tumor suppressors, such as TP53 and PTEN. In conclusion, APOB inactivation is associated with poor outcome in patients with HCC, and APOB may play a role in regulating multiple genes involved in HCC development.

Improved Macaca fascicularis gene annotation reveals evolution of gene expression profiles in multiple tissues

BackgroundsMacaca fascicularis (M. fascicularis) is a primate model organism that played important role in studying human health. It is vital to better understand the similarity and differences of gene regulation between M. fascicularis and human. Current comparative study of gene regulation between the two species are limited by low quality of gene annotation and lack of regulatory element data on M. fascicularis genome.ResultsIn this study, we improved the M. fascicularis gene annotation with 57 gene expression data from multiple tissues and, more importantly, a manual curation procedure. The new annotation enabled us to map gene expression and identify gene location more accurately.ConclusionsComparing with human gene expression data from the same cell types, we characterized the evolution of expression patterns of homologous genes.

Transient modification of lin28b expression - Permanent effects on zebrafish growth.

Recent genome-wide association studies and mouse models have identified LIN28B as a gene affecting several pubertal timing-related traits and vertebrate growth. However, the exact biological mechanisms underlying the associations remain unknown. We have explored the mechanisms linking LIN28B with growth regulation by combining human gene expression data with functional models. Specifically, we show that 1) pubertal timing-associated genetic variation correlates with LIN28B expression in the pituitary and hypothalamus, 2) downregulating lin28b in zebrafish embryos associates with aberrant development of kiss2-neurons, and 3) increasing lin28b expression transiently by synthetic mRNA injections during embryogenesis results in sustained enhancement of zebrafish growth. Unexpectedly, the mRNA injections resulted in advanced sexual maturation of female fish, suggesting that lin28b may influence pubertal timing through multiple developmental mechanisms. Overall, these results provide novel insight into LIN28B function in vertebrate growth regulation, emphasizing the importance of the gene and related genetic pathways for embryonic and juvenile development.

Abstract 2050: Tumor stage-dependent transcriptomic signatures of endothelial cells reveal an intense paracrine crosstalk in liver capillarization

Abstract Introduction: The liver blood vessel network, consisting of liver sinusoidal endothelial cells (LSECs) and capillary endothelial cells (CECs), undergoes distinct modifications in the process of liver cancer development. The selective expansion of the CEC compartment is thereby the most prominent modification leading to a change of the predominant endothelial phenotype. An in depth molecular analysis of the dynamic vascular modifications in hepatocellular carcinoma (HCC) is however still missing. Methods: An inducible mouse model with hepatocyte-specific expression of constitutively active yes-associated protein (YAPS127A) was used for stage dependent purification of endothelial cells. Cell sorting allowed the subtyping of liver endothelial cells into LSECs (CD31+, CD146+, Lyve-1+) and CECs (CD31+, CD146+, Lyve-1-) followed by their consecutive transcriptomic analysis. Predicted paracrine interactions were functionally tested in the endothelial cell line SVEC4-10. Gene expression data of 242 HCC patients were used to confirm the findings in human HCC (Roessler et al. 2010). Results Immunofluorescence revealed a progressive replacement of LSECs by CECs in livers, hyperplastic lesions, and HCC derived from YAPS127A mice. FACS analysis confirmed the selective expansion of CECs from 4±2% in healthy livers to 37±16% in hepatomegaly to 61±30% in tumor-bearing livers. Expression profiling of CECs and LSECs revealed dynamic CEC-selective changes in early and late phases of hepatocarcinogenesis including an enrichment of migration specific pathways. Phylogenetic tree analysis of the gene set “cytokine –cytokine receptor interaction” displayed endothelial cell (EC)- and stage-specific secretion patterns suggesting a dynamic crosstalk between the EC populations. The promigratory role of the identified HGF/c-Met axis was confirmed in vitro by single cell tracking and spheroid sprouting. In vivo the inhibition through the c-Met inhibitor Cabozantinib led to a 67% reduction of CEC sprouting, in line with with decreased tumor cell proliferation. Human HCC gene expression data from 242 HCC patients confirmed the prognostic relevance of an identified 19 gene capillarization signature. Conclusions Our results illustrate a dynamic crosstalk between the two major EC populations in the process of liver tumor development, already detectable in early phases of capillarization. The identified HGF/c-Met axis represents an essential signal pathway in the process of arterial branch elongation and its inhibition through clinically relevant c-Met inhibitors may represent a promising approach to perturbate disease-associated capillarization. References Weiler SME, et al., Gastroenterology, 2017. 152(8): p. 2037-2051 e22 Roessler S, et al., Cancer Res. 2010 Dec 15;70(24):10202-12 Citation Format: Stefan Thomann, Sofia Weiler, Martin Dittmer, Daniel Kazdal, Simone Marquard, Stephanie Roessler, Carsten Sticht, Norbert Gretz, Carolin Mogler, Claudia Ball, Hanno Glimm, Eduard Ryschich, Peter Schirmacher, Kai Breuhahn. Tumor stage-dependent transcriptomic signatures of endothelial cells reveal an intense paracrine crosstalk in liver capillarization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2050.

Gene set analysis of post-lactational mammary gland involution gene signatures in inflammatory and triple-negative breast cancer.

BackgroundEpidemiological studies have found that triple-negative breast cancer (TNBC) and TN inflammatory breast cancer (IBC) are associated with lower frequency and duration of breast-feeding compared to non-TNBC and non-TN IBC, respectively. Limited breast-feeding could reflect abrupt or premature involution and contribute to a “primed” stroma that is permissive to the migration of cancer cells typical of IBC. We hypothesized that gene expression related to abrupt mammary gland involution after forced weaning may be enriched in the tissues of IBC patients and, if so, provide a potential correlation between limited breast-feeding and the development of aggressive breast cancer.MethodsWe utilized the Short Time-series Expression Miner (STEM) program to cluster significant signatures from two independent studies that analyzed gene expression at multiple time-points of mouse mammary gland involution. Using 10 significant signatures, we performed gene ontology analysis and gene set enrichment analysis (GSEA) on training and validation sets from human breast cancer gene expression data to identify specific genes that are enriched in IBC compared to non-IBC and in TN compared to non-TN in IBC and non-IBC groups.ResultsExamining the combined data, we identified 10 involution gene clusters (Inv1-10) that share time-dependent regulation after forced weaning. Inv5 was the only cluster significantly enriched in IBC in the training and validation set (nominal p-values <0.05) and only by unadjusted p-values (FDR q-values 0.26 and 0.46 respectively). Eight genes in Inv5 are upregulated in both the training and validation sets in IBC. Combining the training and validation sets, both Inv5 and Inv6 have nominal p-values <0.05 and q-values 0.39 and 0.20, respectively. The time course for both clusters includes genes that change within 12 hours after forced weaning.ConclusionsResults from this in silico study suggest correlation between molecular events during abrupt involution and aggressive breast cancer. Specifically, candidate genes from Inv5 merit functional investigation regarding the role of limited breast-feeding in IBC development.

Prostate Specific Membrane Antigen promotes prostate tumor progression and survival by conferring resistance to hypoxic stress.

Prostate cancer (PC) is the most commonly diagnosed cancer and is the second leading cause of cancer deaths among men in the United States. The ability of tumor cells to survive in the low oxygen (hypoxic) environment created by the expansion of primary tumors is fundamental to their growth in situ as well as metastatic progression that underlies the majority of disease‐related mortality. Prostate Specific Membrane Antigen (PSMA), a type II transmembrane peptidase, is progressively upregulated in ~80% of tumors during PC progression where it correlates negatively with prognosis. We have previously reported that increased PSMA expression on tumor cells alters signal transduction mechanisms downstream of growth factor receptors to promote tumor progression. In addition, we found that expression of PSMA promotes increased survival in hypoxic environments and the current study was designed to determine these PSMA‐dependent survival mechanisms. Using the CRISPR/Cas9 system, we engineered a panel of human and murine PC cell lines (LnCaP, 22rv1, TRAMP‐C1) to lack PSMA expression. Interestingly, loss of PSMA (PSMAKO) in these highly metastatic PC cell lines resulted in a significantly lower proliferation rate than PSMA expressing cells (PSMAWT), formation of smaller anchorage‐independent colonies in soft agar, a shift in the balance of RIPK3/MLKL family of necrosis proteins toward a decreased survival, and a decrease in the migration and intravasation/extravasation potential. Furthermore, in a NOD/SCID xenograft mouse model, LnCaP‐PSMAWT cells formed large, well‐vascularized tumors whereas LnCaP‐PSMAKO showed no evidence of tumor growth, indicating that PSMA is a potent tumor promoter both in vitro and in vivo. Mimicking hypoxic conditions in vitro by treating both PSMAWT and PSMAKO cells with a HiF1 inhibitor, (CoCl2), produced drastic differences in the hypoxia‐induced regulation of the calcineurin A and calpain‐2 calcium‐associated signal‐transduction pathways as well as actin regulated cytoskeletal rearrangement highlighting PSMAs role in resistance to hypoxia as well as its potential contribution to a pro‐tumor phenotype and increased metastatic potential. In support of this notion, in silico meta‐analysis of publicly available human gene expression data sets indicated that changes in PSMA and calcium associated genes correlates significantly with PC metastasis to bone and lymph. Dramatic changes in calcium levels are a primary response of many cells to hypoxia and typically stimulate cell death. These results suggest that PSMA expression on tumor cells confers resistance to hypoxia via changes in the calcium signal‐transduction cascade, thus making the complete disruption of PSMA a promising therapeutic option in management and treatment of PC.Support or Funding InformationResearch reported in this paper was supported by the National Institute of General Medical Sciences of the National Institutes of Health under linked Award Numbers RL5GM118969, TL4GM118971, and UL1GM118970. Support was also received from the National Cancer Institute of the National Institutes of Health K01 Mentored Research Scientist Award to Promote Diversity under linked Award Number K01CA188412. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Abstract B209: Transcriptomic analysis of patient-derived xenografts reveals heterogeneity in human and mouse stroma/immune compartments

Abstract Introduction: Cancers are increasingly recognized as diverse collections of not only genetic diseases but also immune diseases. The heterogeneous tumor microenvironment (TME), including immune components, plays critical roles in tumor growth/progression and response to pharmaceutics, particularly immuno-oncology therapeutics. However, investigating stroma-specific components is rather challenging due to the difficulty in separating stroma from tumor cells, either physically via microdissection or in silico via bioinformatics. Experimental animal models are excellent system to investigate TME1. For example, patient-derived xenograft (PDX), where human and mouse content can readily be separated in silico2, provides a model to study tumor microenvironment, including tumor-stroma interactions. Methods: Whole transcriptome sequencing was performed on subcutaneous PDXs in athymic mice3 and all reads were aligned to human and mouse genomes to discriminate human and mouse content, respectively. Low expressed/less variable genes were removed across the two components. MCP-counter algorithm4 was used to estimate infiltration by various human immune and other stromal cell populations from human gene expression data. The gene expression profiles of 35 cell types from Immunological Genome Consortium (ImmGen)5 were used to create lineage-specific signatures and compute mouse stroma composition by CIBERSORT6. Weighted gene coexpression network analysis (WGCNA)7 was applied on human and mouse gene expression data, respectively, to identify distinct gene modules associated with different biologic functions. Human-mouse gene correlation analysis was performed to construct cross-species expression networks. Results: We have established and profiled ~1800 subcutaneous PDXs, with ~1500 of them whole transcriptome-sequenced (http://crownbio.com/eortc17/stromalposter)8. The average mouse-to-human sequencing read ratio is around 11%, consistent with the previous report2. By deconvolution analysis of human and mouse gene expression data, we identified all types of adaptive and innate immune cells in mouse stroma of these immune-deficient mice. Most surprisingly, a variety of human immune components were also observed in human expression contents. The corresponding fractions vary across cancer subtypes and individual models. The heterogeneity has been also validated by flow cytometry. Distinct coexpressed gene modules from human (50x) and mouse (28x) revealed that human clusters were more correlated to cancer type than mouse clusters, particularly strong in pancreatic, colorectal, and lung cancers. Knowledge-based functional analysis of these gene modules revealed the association of diverse biologic processes. Moreover, cross-species correlation network identified a novel relationship between human and mouse genes over all PDXs and in specific cancers. Conclusions: Both human and mouse stroma/immune composition exists and varies across cancers in subcutaneous PDXs, with each cancer type and each individual model within subtypes, suggesting PDX as a useful experimental model to study TME. Citation Format: Jia Xue, Wubin Qian, Sheng Guo, Jie Cai, Xuesong Ouyang, Henry Qixiang Li. Transcriptomic analysis of patient-derived xenografts reveals heterogeneity in human and mouse stroma/immune compartments [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr B209.

Microarray Gene Expression Statistical Data Analysis of Three Different Clinical Forms of Human Tuberculosis Stimulated Samples in the Bioconductor R Package

The overall aim of this research identified and explores the usage of microarray gene expression statistical tools available in Bioconductor R package for image visualization, data quality control, background correction, summarization, normalization and identification of highly differential gene expression from microarray gene expression data of human tuberculosis infections. The stimulated samples with phosphate buffered saline (PBS) of human tuberculosis microarray gene expression data such include pulmonary TB infection (PTB), meningeal TB infection (TBM) and latent TB infection (LTB) image data were collected from GEO-NCBI (Gene Expression Omnibus-National Centre for Biotechnical information’s) database in a form of CEL file format with Accession number: GSE11199 and all the analyses were performed in the R packages. These analyses identified and explore the use of AffyQCReport tool, affycoretools, PCA, MAS 5.0 and GCRMA for microarray gene expression data pre-processing and for the identification of highly significantly expressed genes, LIMMA was used and explore as a statistical tool for such analysis. The statistical analysis from LIMMA indicates that there was a significant difference between the three different forms of human tuberculosis. Therefore, most of the genes significantly expressed in both groups were genes responsible for cellular immune response. The results of three different comparison groups generated from the LIMMA analysis were further analysed using correlation coefficient=1, when p-value<=0.05 and generated Venn diagram, the results from venn diagram shows that majority of the genes were up-regulated indicating less decrease in the rate of gene expression but increase among the regulated genes of stimulated tuberculosis and more genes were observed with higher expression than those with less expression during the three group’s comparison. It suggested recommendation that the results obtained from this study can be utilize in further analysis for detection and control of human tuberculosis infections.

Identification of Effective Genes from HIV-1 VPR Microarray Datasets after Constructing GA-Optimized Genetic Network

Identification of effective genes from microarray dataset is important for obtaining relationship between that gene and a particular disease. For this, Gene Regulatory Network (GRN) construction is important. In this paper, GA-optimized GRNs are constructed using radial basis neural network (RBN) approach within cluster center matrix of human HIV-1 Vpr mutant microarray time series gene expression data. After this, effective genes from each microarray dataset are found by calculating minimum Euclidean distance between optimized output value and corresponding dataset.

Activated macrophages control human adipocyte mitochondrial bioenergetics via secreted factors

ObjectiveObesity-associated WAT inflammation is characterized by the accumulation and local activation of macrophages (MΦs), and recent data from mouse studies suggest that macrophages are modifiers of adipocyte energy metabolism and mitochondrial function. As mitochondrial dysfunction has been associated with obesity and the metabolic syndrome in humans, herein we aimed to delineate how human macrophages may affect energy metabolism of white adipocytes. MethodsHuman adipose tissue gene expression analysis for markers of macrophage activation and tissue inflammation (CD11c, CD40, CD163, CD206, CD80, MCP1, TNFα) in relationship to mitochondrial complex I (NDUFB8) and complex III (UQCRC2) was performed on subcutaneous WAT of 24 women (BMI 20–61 kg/m2). Guided by these results, the impact of secreted factors of LPS/IFNγ- and IL10/TGFβ-activated human macrophages (THP1, primary blood-derived) on mitochondrial function in human subcutaneous white adipocytes (SGBS, primary) was determined by extracellular flux analysis (Seahorse technology) and gene/protein expression. ResultsStepwise regression analysis of human WAT gene expression data revealed that a linear combination of CD40 and CD163 was the strongest predictor for mitochondrial complex I (NDUFB8) and complex III (UQCRC2) levels, independent of BMI. IL10/TGFβ-activated MΦs displayed high CD163 and low CD40 expression and secreted factors that decreased UQCRC2 gene/protein expression and ATP-linked respiration in human white adipocytes. In contrast, LPS/IFNγ-activated MΦs showed high CD40 and low CD163 expression and secreted factors that enhanced adipocyte mitochondrial activity resulting in a total difference of 37% in ATP-linked respiration of white adipocytes (p = 0.0024) when comparing the effect of LPS/IFNγ- vs IL10/TGFβ-activated MΦs. ConclusionOur data demonstrate that macrophages modulate human adipocyte energy metabolism via an activation-dependent paracrine mechanism.

DIFFERENCES IN INFLAMMATORY SIGNALING BETWEEN MALES AND FEMALES WITH ALZHEIMER’S DISEASE

Studies in human and transgenic mice suggest increased Alzheimer's disease (AD) risk in women is related to two factors: 1) intrinsic hormone differences between sexes, and 2) hormone loss in females due to age or ovary removal. Hormones play many physiologic roles, among which they potently modulate inflammation. Since neuroinflammation is increasingly recognized to promote AD pathogenesis, and since sex hormones modulate inflammation, we hypothesized that females and males would experience differential regulation of one or more inflammatory pathways. We tested our hypothesis by using a multiplexed immunoassay (Bio-Rad) to quantify a panel of 33 cytokines in the hippocampi of 10 month old APPswe/PS1dE9 (APP/PS1) (6 females, 3 males) mice and wild-type littermate controls (3 females, 3 males). We identified differences between groups using a discriminant partial least squares regression. We then corroborated our protein findings from this mouse model against published gene expression data from postmortem human prefrontal cortex using a Gene Set Enrichment Analysis. The human dataset consisted of 129 late onset AD (75 female, 54 male) and 101 control (34 female, 67 male) samples from the prefrontal cortex. We identified a profile of cytokines that were together significantly up-regulated in female APP/PS1 animals compared to controls (p<0.05). The profile included the pro-inflammatory cytokines IL-12p40 and CCL5. A Gene-set Enrichment Analysis of IL-12 and CCL5 pathways in human gene expression data revealed that both of these pathways were enriched in women with AD. Additionally, the same cytokine profile also appeared to distinguish male from female wild-type mice, but the difference was not significant (p=0.1), suggesting that amyloid pathology may exacerbate homeostatic differences in inflammatory signaling between sexes. Our data indicate that males and females experience inflammatory differences in response to Alzheimer's pathology. These differences may be responsible for increased risk and more rapid AD progression in women. Our ongoing work aims to link differences in specific inflammatory pathways to either hormone or chromosomal differences between the sexes.

ASCT2 regulates glutamine uptake and cell growth in endometrial carcinoma

Glutamine commonly becomes a conditionally essential amino acid in cancer. Glutamine is supplied to the cell by transporters such as ASCT2 (SLC1A5), which is frequently upregulated in multiple cancers. Here we investigated the expression of ASCT2 in endometrial carcinoma, and evaluated the contribution of ASCT2 to glutamine uptake and endometrial cancer cell growth. Analysis of human gene expression data showed that ASCT2 was significantly upregulated in both endometrioid and serous subtypes of endometrial carcinoma, compared to normal, age-matched endometrium. Furthermore, immunohistochemical staining of primary human endometrioid adenocarcinomas showed that tumours stain positive for ASCT2 in either a uniform or mosaic expression pattern, while normal adjacent glands appeared predominantly negative for ASCT2 staining. Chemical inhibition of glutamine transport by benzylserine or GPNA led to a significant decrease in endometrial cancer cell growth and spheroid cross-sectional area. ASCT2 knockdown recapitulated the decrease of cell growth and spheroid cross-sectional area in HEC1A cells, suggesting a reliance on ASCT2-mediated glutamine uptake. ASCT2 knockdown in Ishikawa cells led to lower glutamine uptake and cell growth, but did not affect spheroid area. Ishikawa cells express higher levels of the glutamine transporter SNAT1 compared to HEC1A cells, suggesting these cells may rely on both ASCT2 and SNAT1 for glutamine uptake. Since SNAT1 is also significantly upregulated in the endometrioid and serous subtypes, these data indicate that ASCT2 and SNAT1 could be used as markers of malignancy, and/or potential therapeutic targets in patients with endometrial carcinoma.

Quantitative proteomics identify Tenascin-C as a promoter of lung cancer progression and contributor to a signature prognostic of patient survival

The extracellular microenvironment is an integral component of normal and diseased tissues that is poorly understood owing to its complexity. To investigate the contribution of the microenvironment to lung fibrosis and adenocarcinoma progression, two pathologies characterized by excessive stromal expansion, we used mouse models to characterize the extracellular matrix (ECM) composition of normal lung, fibrotic lung, lung tumors, and metastases. Using quantitative proteomics, we identified and assayed the abundance of 113 ECM proteins, which revealed robust ECM protein signatures unique to fibrosis, primary tumors, or metastases. These analyses indicated significantly increased abundance of several S100 proteins, including Fibronectin and Tenascin-C (Tnc), in primary lung tumors and associated lymph node metastases compared with normal tissue. We further showed that Tnc expression is repressed by the transcription factor Nkx2-1, a well-established suppressor of metastatic progression. We found that increasing the levels of Tnc, via CRISPR-mediated transcriptional activation of the endogenous gene, enhanced the metastatic dissemination of lung adenocarcinoma cells. Interrogation of human cancer gene expression data revealed that high TNC expression correlates with worse prognosis for lung adenocarcinoma, and that a three-gene expression signature comprising TNC, S100A10, and S100A11 is a robust predictor of patient survival independent of age, sex, smoking history, and mutational load. Our findings suggest that the poorly understood ECM composition of the fibrotic and tumor microenvironment is an underexplored source of diagnostic markers and potential therapeutic targets for cancer patients.

Interleukin-17A Promotes Lung Tumor Progression through Neutrophil Attraction to Tumor Sites and Mediating Resistance to PD-1 Blockade

IntroductionProinflammatory cytokine interleukin-17A (IL-17A) is overexpressed in a subset of patients with lung cancer. We hypothesized that IL-17A promotes a protumorigenic inflammatory phenotype and inhibits antitumor immune responses. MethodsWe generated bitransgenic mice expressing a conditional IL-17A allele along with conditional KrasG12D and performed immune phenotyping of mouse lungs, a survival analysis, and treatment studies with antibodies either blocking programmed cell death 1 (PD-1) or IL-6 or depleting neutrophils. To support the preclinical findings, we analyzed human gene expression data sets and immune profiled patient lung tumors. ResultsTumors in IL-17:KrasG12D mice grew more rapidly, resulting in a significantly shorter survival as compared with that of KrasG12D mice. IL-6, granulocyte colony-stimulating factor (G-CSF), milk fat globule-EGF factor 8 protein, and C-X-C motif chemokine ligand 1 were increased in the lungs of IL17:Kras mice. Time course analysis revealed that levels of tumor-associated neutrophils were significantly increased, and lymphocyte recruitment was significantly reduced in IL17:KrasG12D mice as compared with in KrasG12D mice. In therapeutic studies PD-1 blockade was not effective in treating IL-17:KrasG12D tumors. In contrast, blocking IL-6 or depleting neutrophils with an anti–Ly-6G antibody in the IL17:KrasG12D tumors resulted in a clinical response associated with T-cell activation. In tumors from patients with lung cancer with KRAS mutation we found a correlation between higher levels of IL-17A and colony- stimulating factor 3 and a significant correlation among high neutrophil and lower T-cell numbers. ConclusionsHere we have shown that an increase in a single cytokine, IL-17A, without additional mutations can promote lung cancer growth by promoting inflammation, which contributes to resistance to PD-1 blockade and sensitizes tumors to cytokine and neutrophil depletion.

Map3K14 signaling attenuates the development of colorectal cancer through activation of the non-canonical NF-κB signaling cascade

Abstract Dysregulation of NF-κB signaling is a common feature in Colorectal Cancer (CRC). While the canonical signaling pathway is well characterized, the non-canonical NF-κB signaling cascade is understudied. Thus, we evaluated the hypothesis that non-canonical NF-κB signaling significantly modulates CRC pathogenesis. To evaluate this hypothesis, we initially conducted a meta-analysis of human gene expression data. Using this approach, we found that non-canonical NF-κB signaling is significantly down-regulated in CRC patients and the extent of pathway attenuation is correlated with disease severity. These findings were confirmed in patient biopsy specimens, where we found significantly reduced expression of ligands, receptors, regulators, and chemokines associated with non-canonical NF-κB signaling. Notably, we observed significantly reduced CCL19, CCL21, CXCL12, and CXCL13 expression in CRC patients compared to healthy controls. To gain mechanistic insight, we utilized genetically modified mice lacking the kinase Map3K14 (NIK), which is essential for non-canonical NF-κB signaling. Nik−/− mice exhibited ablation of non-canonical NF-κB signaling and significantly increased epithelial cell proliferation in the GI tract compared to wild type mice in both in vivo and in vitro studies. Together, our data defines a protective role for non-canonical NF-κB signaling in the gut during CRC and identifies a highly protective role for Map3K14 in attenuating epithelial cell proliferation.

Species translatable blood gene signature as a marker of exposure to smoking: Computational approaches of the top ranked teams in the sbv IMPROVER Systems Toxicology Challenge

Crowdsourcing has been used to address computational challenges in systems biology and assess translation of findings across species. Sub-challenge 2 of the sbv IMPROVER Systems Toxicology Challenge was designed to determine whether a common set of genes can be used to identify exposure to cigarette smoke in both human and mouse. Participating teams used a training set of human and mouse blood gene expression data to derive parsimonious models (up to 40 genes) that classify subjects into exposure groups: smokers, former smokers, and never-smokers. Teams were ranked based on two classification performance metrics evaluated on a blinded test dataset. Prediction of current exposure to cigarette smoke in human and mouse by a common prediction model was achieved by the top ranked team (Team 219) with 89% balanced accuracy (BAC), while past exposure was predicted with only 57% BAC. The prediction model of the top ranked team was a random forest classifier trained on sets of genes that appeared best for each species separately with no overlap between species. By contrast, Team 264, ranked second (tied with Team 250), selected genes that were simultaneously predictive in both species and achieved 80% and 59% BAC when predicting current and past exposure, respectively. These performance values were lower than the 96.5% and 61% BAC estimates for current and past exposure, respectively, obtained by Team 264 (top ranked in sub-challenge 1) when using only human data. Unlike past exposure, current exposure to cigarette smoke can be accurately assessed in both human and mouse with a common prediction model based on blood mRNAs. However, requiring a common gene signature to be predictive in both species resulted in a substantial decrease in balanced accuracy for prediction of current exposure to cigarette smoke (from 96.5% to 80%), suggesting species-specific responses exist.