Annotating cancer variants and anti-cancer therapeutics in reactome

A reference set of curated biomedical data and metadata from clinical case reports

Clinical case reports (CCRs) provide an important means of sharing clinical experiences about atypical disease phenotypes and new therapies. However, published case reports contain largely unstructured and heterogeneous clinical data, posing a challenge to mining relevant information. Current indexing approaches generally concern document-level features and have not been specifically designed for CCRs. To address this disparity, we developed a standardized metadata template and identified text corresponding to medical concepts within 3,100 curated CCRs spanning 15 disease groups and more than 750 reports of rare diseases. We also prepared a subset of metadata on reports on selected mitochondrial diseases and assigned ICD-10 diagnostic codes to each. The resulting resource, Metadata Acquired from Clinical Case Reports (MACCRs), contains text associated with high-level clinical concepts, including demographics, disease presentation, treatments, and outcomes for each report. Our template and MACCR set render CCRs more findable, accessible, interoperable, and reusable (FAIR) while serving as valuable resources for key user groups, including researchers, physician investigators, clinicians, data scientists, and those shaping government policies for clinical trials.

Phase I clinical trial of an intranodally administered mRNA-based therapeutic vaccine against HIV-1 infection

Objective:

The efficacy of therapeutic vaccines against HIV-1 infection has been modest. New inerts to redirect responses to vulnerable sites are urgently needed to improve these results.

Design:

We performed the first-in-human clinical trial with naked mRNA (iHIVARNA) combining a dendritic cell activation strategy (TriMix:CD40L+CD70+caTLR4 RNA) with a novel HIV immunogen sequences (HTI immunogen).

Methods:

A dose escalation, phase I clinical trial was performed in 21 chronic HIV-1-infected patients under ART who received three intranodal doses of mRNA (weeks 0, 2 and 4) as follow: TriMix-100 g, TriMix-300 g, TriMix-300 g with HTI-300 g, TriMix-300 g with HTI-600 g, TriMix-300 g with HTI-900 g. Primary end-point was safety and secondary-exploratory end-points were immunogenicity, changes in viral reservoir and transcriptome.

Results:

Overall, the vaccine was secure and well tolerated. There were 31 grade 1/2 and 1 grade 3 adverse events, mostly unrelated to the vaccination. Patients who received the highest dose showed a moderate increase in T-cell responses spanning HTI sequence at week 8. In addition, the proportion of responders receiving any dose of HTI increased from 31% at w0 to 80% postvaccination. The intervention had no impact on caHIV-DNA levels, however, caHIV-RNA expression and usVL were transiently increased at weeks 5 and 6 in the highest dose of iHIVARNA, and these changes were positively correlated with HIV-1-specific-induced immune responses.

Conclusion:

This phase I dose-escalating trial showed that iHIVARNA administration was safe and well tolerated, induced moderate HIV-specific T-cell responses and transiently increased different viral replication readouts. These data support further exploration of iHIVARNA in a phase II study.

ClinicalTrials.gov Identifier:

NCT02413645

More than fishing for a cure: The promises and pitfalls of high throughput cancer cell line screens

High-throughput screens in cancer cell lines (CCLs) have been used for decades to help researchers identify compounds with the potential to improve the treatment of cancer and, more recently, to identify genomic susceptibilities in cancer via genome-wide shRNA and CRISPR/Cas9 screens. Additionally, rich genomic and transcriptomic data of these CCLs has allowed researchers to pair this screening data with biological features, enabling efforts to identify biomarkers of treatment response and gene dependencies. In this paper, we review the major CCL screening efforts and the large datasets these screens have made available. We also assess the CCL screens collectively and include a resource with harmonized CCL and compound identifiers to facilitate comparisons across screens. The CCLs in these screens were found to represent a wide range of cancer types, with a strong correlation between the representation of a cancer type and its associated mortality. Patient ages and gender distributions of CCLs were generally as expected, with some notable exceptions of female underrepresentation in certain disease types. Also, ethnicity information, while largely incomplete, suggests that African American and Hispanic patients may be severely underrepresented in these screens. Nearly all genes were targeted in the genetic perturbations screens, but the compounds used for the drug screens target less than half of known cancer drivers, likely reflecting known limitations in our drug design capabilities. Finally, we discuss recent developments in the field and the promise they hold for enabling future screens to overcome previous limitations and lead to new breakthroughs in cancer treatment.

Analyzing the Structure of Pathways and Its Influence on the Interpretation of Biomedical Proteomics Data Sets

Biochemical pathways are commonly used as a reference to conduct functional analysis on biomedical omics data sets, where experimental results are mapped to knowledgebases comprising known molecular interactions collected from the literature. Due to their central role, the content of the functional knowledgebases directly influences the outcome of pathway analyses. In this study, we investigate the structure of the current pathway knowledge, as exemplified by Reactome, discuss the consequences for biological interpretation, and outline possible improvements in the use of pathway knowledgebases. By providing a view of the underlying protein interaction network, we aim to help pathway analysis users manage their expectations and better identify possible artifacts in the results.

HSP90-incorporating chaperome networks as biosensor for disease-related pathways in patient-specific midbrain dopamine neurons

Environmental and genetic risk factors contribute to Parkinson’s Disease (PD) pathogenesis and the associated midbrain dopamine (mDA) neuron loss. Here, we identify early PD pathogenic events by developing methodology that utilizes recent innovations in human pluripotent stem cells (hPSC) and chemical sensors of HSP90-incorporating chaperome networks. We show that events triggered by PD-related genetic or toxic stimuli alter the neuronal proteome, thereby altering the stress-specific chaperome networks, which produce changes detected by chemical sensors. Through this method we identify STAT3 and NF-κB signaling activation as examples of genetic stress, and phospho-tyrosine hydroxylase (TH) activation as an example of toxic stress-induced pathways in PD neurons. Importantly, pharmacological inhibition of the stress chaperome network reversed abnormal phospho-STAT3 signaling and phospho-TH-related dopamine levels and rescued PD neuron viability. The use of chemical sensors of chaperome networks on hPSC-derived lineages may present a general strategy to identify molecular events associated with neurodegenerative diseases.

The early molecular events that ultimately lead to neuronal cell death in pathologies such as Parkinson’s disease are poorly understood. Here the authors use pluripotent stem-cell-derived human midbrain neurons and chemical biology tools to gain molecular level insight into the events induced by toxic and genetic stresses that mimic those occurring during neurodegeneration.

A genome-wide association study for natural antibodies measured in blood of Canadian Holstein cows

BACKGROUND

Natural antibodies (NAb) are an important component of the innate immune system, and fight infections as a part of the first line defence. NAb are poly-reactive and can respond non-specifically to antigens. Therefore, NAb may be a key trait when evaluating an animal's potential natural disease resistance. Variation in NAb is caused by both genetic and environmental factors. In this study genetic parameters of NAb were estimated and a genome-wide association study (GWAS) was performed to gain further understanding on the genes that are responsible for the observed genetic variation of NAb in Canadian Holsteins.

RESULTS

In total, blood samples of 1327 cows from 64 farms were studied. NAb binding to keyhole limpet hemocyanin (KLH) were determined via indirect ELISA. Immunoglobulin (Ig) isotypes, IgG and IgM, were evaluated. From the sample population, 925 cows were genotyped for 45,187 markers and each individual marker was tested to detect genetic variation in NAb levels. The relationships among animals was accounted for with genomic relationship. Results show heritabilities of 0.27 ± 0.064 (IgG) and 0.31 ± 0.065 (IgM). In total, 23 SNPs were found to be associated with IgG, but no SNPs were associated with IgM (FDR p-value < 0.05). The significant SNPs were located on autosomal chromosomes 1, 20 and 21 of the cow genome. Functional annotation analysis of the positional candidate genes revealed two sets of genes with biologically relevant functions related to NAb. In one set, seven genes with crucial roles in the production of antibody in B cells were associated with the trafficking of vesicles inside the cells between organelles. In the second set, two genes among positional candidate genes were associated with isotype class-switching and somatic hypermutation of B cells.

CONCLUSIONS

This study demonstrated the possibility of increasing NAb through selective breeding. In addition, the effects of two candidate pathways are proposed for further investigation of NAb production in Holsteins.

FGFR1/FOXM1 pathway: a key regulator of glioblastoma stem cells radioresistance and a prognosis biomarker

Glioblastoma are known to be aggressive and therapy-resistant tumors, due to the presence of glioblastoma stem cells inside this heterogeneous tumor. We investigate here the involvement of FGFR1 in glioblastoma stem-like cells (GSLC) radioresistance mechanisms. We first demonstrated that the survival after irradiation was significantly diminished in FGFR1-silenced (FGFR1-) GSLC compared to control GSLC. The transcriptome analysis of GSLCs FGFR1(-) showed that FOX family members are differentially regulated by FGFR1 inhibition, particularly with an upregulation of FOXN3 and a downregulation of FOXM1. GSLC survival after irradiation was significantly increased after FOXN3 silencing and decreased after FOXM1 inhibition, showing opposite effects of FGFR1/FOX family members on cell response to ionizing radiation. Silencing FGFR1 or FOXM1 downregulated genes involved in mesenchymal transition such as GLI2, TWIST1, and ZEB1 in glioblastoma stem-like cells. It also dramatically reduced GSLC migration. Databases analysis confirmed that the combined expression of FGFR1/FOXM1/MELK/GLI2/ZEB1/TWIST1 is significantly associated with patients overall survival after chemo-radiotherapy treatment. All these results, associated with our previous conduced ones with differentiated cells, clearly established that FGFR1-FOXM1 dependent glioblastoma stem-like cells radioresistance pathway is a central actor of GBM treatment resistance and a key target to inhibit in the aim to increase the sensitivity of GBM to the radiotherapy.

Characterization of an activating R1353H insulin-like growth factor 1 receptor variant in a male with extreme tall height

OBJECTIVE

The insulin-like growth factor1 receptor (IGF1R) is important in growth and development, and inactivating IGF1R mutations cause short stature and relatively high levels of serum IGF-I. We identified an unclassified IGF1R^R1353H variant in a male with extreme tall height, very low levels of serum IGF-I and delayed and prolonged growth spurt. The index case's mother and three sons all carried the variant, but so far only the eldest son (age 18 years) presented with tall height. We hypothesized that the variant could constitute an activating mutation.

DESIGN

The IGF1R^R1353H variant was investigated in Igf1r^-/- mouse embryonic fibroblasts (R-cells) by cell cycle, colony formation and transcriptome analyses.

RESULTS

The IGF1R^R1353H (R-1353) exhibited significantly increased cell proliferation, G1-S progression and colony formation in soft agar. RNA sequencing identified 195 differentially expressed genes between R-WT and R-1353 (adjusted P < 1E-100). Most genes were upregulated in R-1353, including the gene encoding the androgen receptor (AR). Gene expression profiling showed the most significant enrichment in extracellular matrix organization (P = 2.76E-7), collagen biosynthesis (P = 1.21E-5) and cell adhesion (P = 7.38E-5). Retrospective biochemical analysis of the index case revealed decreased testosterone and sex hormone-binding globulin levels, whereas LH and FSH were within normal ranges. This profile suggests an increased sensitivity to androgen, which is compatible with the enhanced expression of Ar in R-1353 cells.

CONCLUSIONS

Our findings suggest that R1353H constitutes an activating IGF1R variant. The possible deregulation of collagen turnover and increased androgen sensitivity implicates an association to tall phenotype in male carriers.

Semantic Analysis of Posttranslational Modification of Proteins Accumulated in Thyroid Cancer Cells Exposed to Simulated Microgravity

When monolayers of tissue cancer cells of various origins are exposed to real or simulated microgravity, many cells leave the monolayer and assemble to three-dimensional (3D) aggregates (spheroids). In order to define the cellular machinery leading to this change in growth behavior of FTC-133 human thyroid cancer cells and MCF-7 breast cancer cells, we recently performed proteome analyses on these cell lines and determined the proteins’ accumulation in monolayer cells grown under 1g-conditions as well as in the cells of spheroids assembled under simulated microgravity during three and 14 days, respectively. At that time, an influence of the increment or decrement of some of the more than 5000 proteins detected in each cell line was investigated. In this study, we focused on posttranslational modifications (PTMs) of proteins. For this purpose, we selected candidates from the list of the proteins detected in the two preceding proteome analyses, which showed significant accumulation in spheroid cells as compared to 1g monolayer cells. Then we searched for those PTMs of the selected proteins, which according to the literature have already been determined experimentally. Using the Semantic Protocol and RDF Query Language (SPARQL), various databases were examined. Most efficient was the search in the latest version of the dbPTM database. In total, we found 72 different classes of PTMs comprising mainly phosphorylation, glycosylation, ubiquitination and acetylation. Most interestingly, in 35 of the 69 proteins, N6 residues of lysine are modifiable.

Age Alters Chromatin Structure and Expression of SUMO Proteins under Stress Conditions in Human Adipose-Derived Stem Cells

Adult stem cells play a critical role in tissue homeostasis and repair. Aging leads to a decline in stem cells’ regenerative capacity that contributes significantly to the maintenance of organ and tissue functions. Age-dependent genomic and epigenetic modifications together play a role in the disruption of critical cellular pathways. However, the epigenetic mechanisms responsible for the decline of adult stem cell functions remain to be well established. Here, we investigated age-dependent, genome-wide alterations in the chromatin accessibility of primary human adipose-derived stem cells (ASCs) in comparison to age-matched fibroblasts via ATAC-seq technology. Our results demonstrate that aging ASCs possess globally more stable chromatin accessibility profiles as compared to aging fibroblasts, suggesting that robust regulatory mechanisms maintain adult stem cell chromatin structure against aging. Furthermore, we observed age-dependent subtle changes in promoter nucleosome positioning in selective pathways during aging, concurrent with altered small ubiquitin-related modifier (SUMO) protein expression under stress conditions. Together, our data suggest a significant role for nucleosome positioning in sumoylation pathway regulation in stress response during adult stem cell aging. The differences described here between the chromatin structure of human ASCs and fibroblasts will further elucidate the mechanisms regulating gene expression during aging in both stem cells and differentiated cells.

Novel Myopia Genes and Pathways Identified From Syndromic Forms of Myopia

Purpose

To test the hypothesis that genes known to cause clinical syndromes featuring myopia also harbor polymorphisms contributing to nonsyndromic refractive errors.

Methods

Clinical phenotypes and syndromes that have refractive errors as a recognized feature were identified using the Online Mendelian Inheritance in Man (OMIM) database. One hundred fifty-four unique causative genes were identified, of which 119 were specifically linked with myopia and 114 represented syndromic myopia (i.e., myopia and at least one other clinical feature). Myopia was the only refractive error listed for 98 genes and hyperopia and the only refractive error noted for 28 genes, with the remaining 28 genes linked to phenotypes with multiple forms of refractive error. Pathway analysis was carried out to find biological processes overrepresented within these sets of genes. Genetic variants located within 50 kb of the 119 myopia-related genes were evaluated for involvement in refractive error by analysis of summary statistics from genome-wide association studies (GWAS) conducted by the CREAM Consortium and 23andMe, using both single-marker and gene-based tests.

Results

Pathway analysis identified several biological processes already implicated in refractive error development through prior GWAS analyses and animal studies, including extracellular matrix remodeling, focal adhesion, and axon guidance, supporting the research hypothesis. Novel pathways also implicated in myopia development included mannosylation, glycosylation, lens development, gliogenesis, and Schwann cell differentiation. Hyperopia was found to be linked to a different pattern of biological processes, mostly related to organogenesis. Comparison with GWAS findings further confirmed that syndromic myopia genes were enriched for genetic variants that influence refractive errors in the general population. Gene-based analyses implicated 21 novel candidate myopia genes (ADAMTS18, ADAMTS2, ADAMTSL4, AGK, ALDH18A1, ASXL1, COL4A1, COL9A2, ERBB3, FBN1, GJA1, GNPTG, IFIH1, KIF11, LTBP2, OCA2, POLR3B, POMT1, PTPN11, TFAP2A, ZNF469).

Conclusions

Common genetic variants within or nearby genes that cause syndromic myopia are enriched for variants that cause nonsyndromic, common myopia. Analysis of syndromic forms of refractive errors can provide new insights into the etiology of myopia and additional potential targets for therapeutic interventions.

Immune signatures correlate with L1 retrotransposition in gastrointestinal cancers

Long interspersed nuclear element-1 (LINE-1 or L1) retrotransposons are normally suppressed in somatic tissues mainly due to DNA methylation and antiviral defense. However, the mechanism to suppress L1s may be disrupted in cancers, thus allowing L1s to act as insertional mutagens and cause genomic rearrangement and instability. Whereas the frequency of somatic L1 insertions varies greatly among individual tumors, much remains to be learned about underlying genetic, cellular, or environmental factors. Here, we report multiple correlates of L1 activity in stomach, colorectal, and esophageal tumors through an integrative analysis of cancer whole-genome and matched RNA-sequencing profiles. Clinical indicators of tumor progression, such as tumor grade and patient age, showed positive association. A potential L1 expression suppressor, TP53, was mutated in tumors with frequent L1 insertions. We characterized the effects of somatic L1 insertions on mRNA splicing and expression, and demonstrated an increased risk of gene disruption in retrotransposition-prone cancers. In particular, we found that a cancer-specific L1 insertion in an exon of MOV10, a key L1 suppressor, caused exon skipping and decreased expression of the affected allele due to nonsense-mediated decay in a tumor with a high L1 insertion load. Importantly, tumors with high immune activity, for example, those associated with Epstein–Barr virus infection or microsatellite instability, tended to carry a low number of L1 insertions in genomes with high expression levels of L1 suppressors such as APOBEC3s and SAMHD1. Our results indicate that cancer immunity may contribute to genome stability by suppressing L1 retrotransposition in gastrointestinal cancers.

Pirfenidone decreases mesothelioma cell proliferation and migration via inhibition of ERK and AKT and regulates mesothelioma tumor microenvironment in vivo

Malignant mesothelioma is an aggressive cancer with poor prognosis. It is characterized by prominent extracellular matrix, mesenchymal tumor cell phenotypes and chemoresistance. In this study, the ability of pirfenidone to alter mesothelioma cell proliferation and migration as well as mesothelioma tumor microenvironment was evaluated. Pirfenidone is an anti-fibrotic drug used in the treatment of idiopathic pulmonary fibrosis and has also anti-proliferative activities. Mesothelioma cell proliferation was decreased by pirfenidone alone or in combination with cisplatin. Pirfenidone also decreased significantly Transwell migration/invasion and 3D collagen invasion. This was associated with increased BMP pathway activity, decreased GREM1 expression and downregulation of MAPK/ERK and AKT/mTOR signaling. The canonical Smad-mediated TGF-β signaling was not affected by pirfenidone. However, pirfenidone blocked TGF-β induced upregulation of ERK and AKT pathways. Treatment of mice harboring mesothelioma xenografts with pirfenidone alone did not reduce tumor proliferation in vivo. However, pirfenidone modified the tumor microenvironment by reducing the expression of extracellular matrix associated genes. In addition, GREM1 expression was downregulated by pirfenidone in vivo. By reducing two major upregulated pathways in mesothelioma and by targeting tumor cells and the microenvironment pirfenidone may present a novel anti-fibrotic and anti-cancer adjuvant therapy for mesothelioma.

Decreased E-Cadherin in MCF7 Human Breast Cancer Cells Forming Multicellular Spheroids Exposed to Simulated Microgravity

MCF7 human breast cancer cells were cultured under normal gravity (1 g) and on a random positioning machine (RPM) preventing sedimentation. After 2 weeks, adherent 1 g-control and adherent RPM cells (AD) as well as multicellular spheroids (MCS) were harvested. AD and MCS had been exposed to the RPM in the same culture flask. In a subsequent proteome analysis, the majority of the proteins detected showed similar label-free quantification (LFQ) scores in each of the respective subpopulations, but in both AD or MCS cultures, proteins were also found whose LFQs deviated at least twofold from their counterparts in the 1 g-control cells. They included the cell junction protein E-cadherin, which was diminished in MCS cells, where proteins of the E-cadherin autodegradation pathway were enhanced and c-Src (proto-oncogene tyrosine-protein kinase c-Src) was detected. Spheroid formation was prevented by inhibition of c-Src but promoted by antibodies blocking E-cadherin activity. An interaction analysis of the detected proteins that are involved in forming and regulating junctions or adhesion complexes and in E-cadherin autodegradation indicated connections between the two protein groups. This suggests that the balance of proteins that up- or downregulate E-cadherin mediates the tendency of MCF7 cells to form MCS during RPM exposure.

Linking transcriptional and genetic tumor heterogeneity through allele analysis of single-cell RNA-seq data

Characterization of intratumoral heterogeneity is critical to cancer therapy, as the presence of phenotypically diverse cell populations commonly fuels relapse and resistance to treatment. Although genetic variation is a well-studied source of intratumoral heterogeneity, the functional impact of most genetic alterations remains unclear. Even less understood is the relative importance of other factors influencing heterogeneity, such as epigenetic state or tumor microenvironment. To investigate the relationship between genetic and transcriptional heterogeneity in a context of cancer progression, we devised a computational approach called HoneyBADGER to identify copy number variation and loss of heterozygosity in individual cells from single-cell RNA-sequencing data. By integrating allele and normalized expression information, HoneyBADGER is able to identify and infer the presence of subclone-specific alterations in individual cells and reconstruct the underlying subclonal architecture. By examining several tumor types, we show that HoneyBADGER is effective at identifying deletions, amplifications, and copy-neutral loss-of-heterozygosity events and is capable of robustly identifying subclonal focal alterations as small as 10 megabases. We further apply HoneyBADGER to analyze single cells from a progressive multiple myeloma patient to identify major genetic subclones that exhibit distinct transcriptional signatures relevant to cancer progression. Other prominent transcriptional subpopulations within these tumors did not line up with the genetic subclonal structure and were likely driven by alternative, nonclonal mechanisms. These results highlight the need for integrative analysis to understand the molecular and phenotypic heterogeneity in cancer.

Computer Simulation of TSP1 Inhibition of VEGF-Akt-eNOS: An Angiogenesis Triple Threat

The matricellular protein thrombospondin-1 (TSP1) is a potent inhibitor of angiogenesis. Specifically, TSP1 has been experimentally shown to inhibit signaling downstream of vascular endothelial growth factor (VEGF). The molecular mechanism of this inhibition is not entirely clear. We developed a detailed computational model of VEGF signaling to Akt-endothelial nitric oxide synthase (eNOS) to investigate the quantitative molecular mechanism of TSP1 inhibition. The model demonstrated that TSP1 acceleration of VEGFR2 degradation is sufficient to explain the inhibition of VEGFR2 and eNOS phosphorylation. However, Akt inhibition requires TSP1-induced phosphatase recruitment to VEGFR2. The model was then utilized to test various strategies for the rescue of VEGF signaling to Akt and eNOS. Inhibiting TSP1 was predicted to be not as effective as CD47 depletion in rescuing signaling to Akt. The model further predicts that combination strategy involving depletion of CD47 and inhibition of TSP1 binding to CD47 is necessary for effective recovery of signaling to eNOS. In all, computational modeling offers insight to molecular mechanisms involving TSP1 interaction with VEGF signaling and provides strategies for rescuing angiogenesis by targeting TSP1-CD47 axis.

A computational framework for complex disease stratification from multiple large-scale datasets

BACKGROUND

Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states.

METHODS

The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification.

RESULTS

We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes.

CONCLUSIONS

This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine.

Mistimed food intake and sleep alters 24-hour time-of-day patterns of the human plasma proteome

Proteomics holds great promise for understanding human physiology, developing health biomarkers, and precision medicine. However, how much the plasma proteome varies with time of day and is regulated by the master circadian suprachiasmatic nucleus brain clock, assessed here by the melatonin rhythm, is largely unknown. Here, we assessed 24-h time-of-day patterns of human plasma proteins in six healthy men during daytime food intake and nighttime sleep in phase with the endogenous circadian clock (i.e., circadian alignment) versus daytime sleep and nighttime food intake out of phase with the endogenous circadian clock (i.e., circadian misalignment induced by simulated nightshift work). We identified 24-h time-of-day patterns in 573 of 1,129 proteins analyzed, with 30 proteins showing strong regulation by the circadian cycle. Relative to circadian alignment, the average abundance and/or 24-h time-of-day patterns of 127 proteins were altered during circadian misalignment. Altered proteins were associated with biological pathways involved in immune function, metabolism, and cancer. Of the 30 circadian-regulated proteins, the majority peaked between 1400 hours and 2100 hours, and these 30 proteins were associated with basic pathways involved in extracellular matrix organization, tyrosine kinase signaling, and signaling by receptor tyrosine-protein kinase erbB-2. Furthermore, circadian misalignment altered multiple proteins known to regulate glucose homeostasis and/or energy metabolism, with implications for altered metabolic physiology. Our findings demonstrate the circadian clock, the behavioral wake-sleep/food intake-fasting cycle, and interactions between these processes regulate 24-h time-of-day patterns of human plasma proteins and help identify mechanisms of circadian misalignment that may contribute to metabolic dysregulation.

Phrase mining of textual data to analyze extracellular matrix protein patterns across cardiovascular disease

Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biological processes in an array of organ systems, including the cardiovascular system. Using a novel bioinformatics text-mining tool, we studied six categories of cardiovascular disease (CVD), namely, ischemic heart disease, cardiomyopathies, cerebrovascular accident, congenital heart disease, arrhythmias, and valve disease, anticipating novel ECM protein-disease and protein-protein relationships hidden within vast quantities of textual data. We conducted a phrase-mining analysis, delineating the relationships of 709 ECM proteins with the 6 groups of CVDs reported in 1,099,254 abstracts. The technology pipeline known as Context-Aware Semantic Online Analytical Processing was applied to semantically rank the association of proteins to each CVD and all six CVDs, performing analyses to quantify each protein-disease relationship. We performed principal component analysis and hierarchical clustering of the data, where each protein was visualized as a six-dimensional vector. We found that ECM proteins display variable degrees of association with the six CVDs; certain CVDs share groups of associated proteins, whereas others have divergent protein associations. We identified 82 ECM proteins sharing associations with all 6 CVDs. Our bioinformatics analysis ascribed distinct ECM pathways (via Reactome) from this subset of proteins, namely, insulin-like growth factor regulation and interleukin-4 and interleukin-13 signaling, suggesting their contribution to the pathogenesis of all six CVDs. Finally, we performed hierarchical clustering analysis and identified protein clusters predominantly associated with a targeted CVD; analyses of these proteins revealed unexpected insights underlying the key ECM-related molecular pathogenesis of each CVD, including virus assembly and release in arrhythmias. NEW & NOTEWORTHY The present study is the first application of a text-mining algorithm to characterize the relationships of 709 extracellular matrix-related proteins with 6 categories of cardiovascular disease described in 1,099,254 abstracts. Our analysis informed unexpected extracellular matrix functions, pathways, and molecular relationships implicated in the six cardiovascular diseases.

A kinome-wide high-content siRNA screen identifies MEK5-ERK5 signaling as critical for breast cancer cell EMT and metastasis

An epithelial to mesenchymal transition (EMT) has been correlated to malignant tumor progression and metastasis by promoting cancer cell migration and invasion and chemoresistance. Hence, finding druggable EMT effectors is critical to efficiently interfere with metastasis formation and to overcome therapy resistance. We have employed a high-content microscopy screen in combination with a kinome and phosphatome-wide siRNA library to identify signaling pathways underlying an EMT of murine mammary epithelial cells and breast cancer cells. This screen identified the MEK5-ERK5 axis as a critical player in TGFβ-mediated EMT. Suppression of MEK5-ERK5 signaling completely prevented the morphological and molecular changes occurring during a TGFβ-induced EMT and, conversely, forced highly metastatic breast cancer cells into a differentiated epithelial state. Inhibition of MEK5-ERK5 signaling also repressed breast cancer cell migration and invasion and substantially reduced lung metastasis without affecting primary tumor growth. The results suggest that the MEK5-ERK5 signaling axis via activation of MEF2B and other transcription factors plays an important role in the induction and maintenance of breast cancer cell migration and invasion and thus represents an exploitable target for the pharmacological inhibition of cancer cell metastasis.

Aging and sarcopenia associate with specific interactions between gut microbes, serum biomarkers and host physiology in rats

The microbiome has been demonstrated to play an integral role in the maintenance of many aspects of health that are also associated with aging. In order to identify areas of potential exploration and intervention, we simultaneously characterized age-related alterations in gut microbiome, muscle physiology and serum proteomic and lipidomic profiles in aged rats to define an integrated signature of the aging phenotype. We demonstrate that aging skews the composition of the gut microbiome, in particular by altering the Sutterella to Barneseilla ratio, and alters the metabolic potential of intestinal bacteria. Age-related changes of the gut microbiome were associated with the physiological decline of musculoskeletal function, and with molecular markers of nutrient processing/availability, and inflammatory/immune status in aged versus adult rats. Altogether, our study highlights that aging leads to a complex interplay between the microbiome and host physiology, and provides candidate microbial species to target physical and metabolic decline during aging by modulating gut microbial ecology.

Identification of Novel Response and Predictive Biomarkers to Hsp90 Inhibitors Through Proteomic Profiling of Patient-derived Prostate Tumor Explants

Inhibition of the heat shock protein 90 (Hsp90) chaperone is a promising therapeutic strategy to target expression of the androgen receptor (AR) and other oncogenic drivers in prostate cancer cells. However, identification of clinically-relevant responses and predictive biomarkers is essential to maximize efficacy and treatment personalization. Here, we combined mass spectrometry (MS)-based proteomic analyses with a unique patient-derived explant (PDE) model that retains the complex microenvironment of primary prostate tumors. Independent discovery and validation cohorts of PDEs (n = 16 and 30, respectively) were cultured in the absence or presence of Hsp90 inhibitors AUY922 or 17-AAG. PDEs were analyzed by LC-MS/MS with a hyper-reaction monitoring data independent acquisition (HRM-DIA) workflow, and differentially expressed proteins identified using repeated measure analysis of variance (ANOVA; raw p value <0.01). Using gene set enrichment, we found striking conservation of the most significantly AUY922-altered gene pathways between the discovery and validation cohorts, indicating that our experimental and analysis workflows were robust. Eight proteins were selectively altered across both cohorts by the most potent inhibitor, AUY922, including TIMP1, SERPINA3 and CYP51A (adjusted p < 0.01). The AUY922-mediated decrease in secretory TIMP1 was validated by ELISA of the PDE culture medium. We next exploited the heterogeneous response of PDEs to 17-AAG in order to detect predictive biomarkers of response and identified PCBP3 as a marker with increased expression in PDEs that had no response or increased in proliferation. Also, 17-AAG treatment led to increased expression of DNAJA1 in PDEs that exhibited a cytostatic response, revealing potential drug resistance mechanisms. This selective regulation of DNAJA1 was validated by Western blot analysis. Our study establishes "proof-of-principle" that proteomic profiling of drug-treated PDEs represents an effective and clinically-relevant strategy for identification of biomarkers that associate with certain tumor-specific responses.

Profound Tissue Specificity in Proliferation Control Underlies Cancer Drivers and Aneuploidy Patterns

Genomics has provided a detailed structural description of the cancer genome. Identifying oncogenic drivers that work primarily through dosage changes is a current challenge. Unrestrained proliferation is a critical hallmark of cancer. We constructed modular, barcoded libraries of human open reading frames (ORFs) and performed screens for proliferation regulators in multiple cell types. Approximately 10% of genes regulate proliferation, with most performing in an unexpectedly highly tissue-specific manner. Proliferation drivers in a given cell type showed specific enrichment in somatic copy number changes (SCNAs) from cognate tumors and helped predict aneuploidy patterns in those tumors, implying that tissue-type-specific genetic network architectures underlie SCNA and driver selection in different cancers. In vivo screening confirmed these results. We report a substantial contribution to the catalog of SCNA-associated cancer drivers, identifying 147 amplified and 107 deleted genes as potential drivers, and derive insights about the genetic network architecture of aneuploidy in tumors.

Analysis of time-course microarray data: Comparison of common tools

High-throughput time-series data have a special value for studying the dynamism of biological systems. However, the interpretation of such complex data can be challenging. The aim of this study was to compare common algorithms recently developed for the detection of differentially expressed genes in time-course microarray data. Using different measures such as sensitivity, specificity, predictive values, and related signaling pathways, we found that limma, timecourse, and gprege have reasonably good performance for the analysis of datasets in which only test group is followed over time. However, limma has the additional advantage of being able to report significance cut off, making it a more practical tool. In addition, limma and TTCA can be satisfactorily used for datasets with time-series data for all experimental groups. These findings may assist investigators to select appropriate tools for the detection of differentially expressed genes as an initial step in the interpretation of time-course big data.

Association Between Serotonin Syndrome and Second-Generation Antipsychotics via Pharmacological Target-Adverse Event Analysis

Case reports suggest an association between second‐generation antipsychotics (SGAs) and serotonin syndrome (SS). The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) was analyzed to generate hypotheses about how SGAs may interact with pharmacological targets associated with SS. FAERS was integrated with additional sources to link information about adverse events with drugs and targets. Using Proportional Reporting Ratios, we identified signals that were further investigated with the literature to evaluate mechanistic hypotheses formed from the integrated FAERS data. Analysis revealed common pharmacological targets perturbed in both SGA and SS cases, indicating that SGAs may induce SS. The literature also supported 5‐HT_2A antagonism and 5‐HT_1A agonism as common mechanisms that may explain the SGA‐SS association. Additionally, integrated FAERS data mining and case studies suggest that interactions between SGAs and other serotonergic agents may increase the risk for SS. Computational analysis can provide additional insights into the mechanisms underlying the relationship between SGAs and SS.

Gene microarray analysis of lncRNA and mRNA expression profiles in patients with high‑grade ovarian serous cancer

High-grade ovarian serous cancer is known for its high rates of invasion and metastasis, and resultant high mortality rate. Therefore, research concerning biomarkers and underlying molecular mechanisms of high-grade ovarian serous cancer progression and prognosis are urgently required. Long non-coding RNAs (lncRNAs) have been the subject of an increasing number of studies, and certain lncRNAs have been demonstrated to serve an important function in the development and progression of various cancers, including HOX transcript antisense RNA, competing endogenous lncRNA 2 for microRNA let-7b, urothelial cancer associated 1, and H19, imprinted maternally expressed transcript (non-protein coding). However, few studies have investigated the differential expression of lncRNAs in high-grade ovarian serous cancer. In the present study, differences in lncRNA and mRNA expression profiles between high-grade ovarian serous cancer tissue samples and healthy fallopian tube tissue samples were investigated using microarray analysis, and the differential expression of lncRNAs and mRNAs was confirmed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Then, five abnormally expressed lncRNAs were selected, and the associations between these lncRNAs and ovarian cancer clinicopathological parameters were examined using RT-qPCR. The expression profiles of certain lncRNAs and mRNAs were confirmed to be altered between high-grade ovarian serous cancer tissues and healthy fallopian tube tissues. Furthermore, the expression levels of selected lncRNAs were associated with International Federation of Gynecology and Obstetrics stage and lymph node metastasis. These lncRNAs and mRNAs may therefore be involved in the pathogenesis of high-grade ovarian serous cancer. The results of the present study provide an experimental foundation for further exploration of the value of these lncRNAs and mRNAs in the early diagnosis and treatment of high-grade ovarian serous cancer.

Transcriptome response of human skeletal muscle to divergent exercise stimuli

Aerobic (AE) and resistance exercise (RE) elicit unique adaptations in skeletal muscle that have distinct implications for health and performance. The purpose of this study was to identify the unique transcriptome response of skeletal muscle to acute AE and RE. In a counterbalanced, crossover design, six healthy, recreationally active young men (27 ± 3 yr) completed acute AE (40 min of cycling, ∼70% maximal HR) and RE [8 sets, 10 reps, ∼65% 1-repetition maximum (1RM)], separated by ∼1 wk. Muscle biopsies (vastus lateralis) were obtained before and at 1 and 4 h postexercise. Whole transcriptome RNA sequencing (HiSeq2500; Illumina) was performed on cDNA synthesized from skeletal muscle RNA. Sequencing data were analyzed using HTSeq, and differential gene expression was identified using DESeq2 [adjusted P value (FDR) <0.05, >1.5-fold change from preexercise]. RE resulted in a greater number of differentially expressed genes at 1 (67 vs. 48) and 4 h (523 vs. 221) compared with AE. We identified 348 genes that were differentially expressed only following RE, whereas 48 genes were differentially expressed only following AE. Gene clustering indicated that AE targeted functions related to zinc interaction, angiogenesis, and ubiquitination, whereas RE targeted functions related to transcription regulation, cytokine activity, cell adhesion, kinase activity, and the phosphatidylinositol 3-kinase (PI3K)/Akt pathway. ESRRG and TNFSRF12A were identified as potential targets related to the specific response of skeletal muscle to AE and RE, respectively. These data describe the early postexercise transcriptome response of skeletal muscle to acute AE and RE and further highlight that different forms of exercise stimulate unique molecular activity in skeletal muscle. NEW & NOTEWORTHY Whole transcriptome RNA sequencing was used to determine the early postexercise transcriptome response of skeletal muscle to acute aerobic (AE) and resistance exercise (RE) in untrained individuals. Although a number of shared genes were stimulated following both AE and RE, several genes were uniquely responsive to each exercise mode. These findings support the need for future research focused to better identify the role of exercise mode as it relates to targeting specific cellular skeletal muscle abnormalities.

Sensitive and frequent identification of high avidity neo-epitope specific CD8 + T cells in immunotherapy-naive ovarian cancer

Immunotherapy directed against private tumor neo-antigens derived from non-synonymous somatic mutations is a promising strategy of personalized cancer immunotherapy. However, feasibility in low mutational load tumor types remains unknown. Comprehensive and deep analysis of circulating and tumor-infiltrating lymphocytes (TILs) for neo-epitope specific CD8+ T cells has allowed prompt identification of oligoclonal and polyfunctional such cells from most immunotherapy-naive patients with advanced epithelial ovarian cancer studied. Neo-epitope recognition is discordant between circulating T cells and TILs, and is more likely to be found among TILs, which display higher functional avidity and unique TCRs with higher predicted affinity than their blood counterparts. Our results imply that identification of neo-epitope specific CD8+ T cells is achievable even in tumors with relatively low number of somatic mutations, and neo-epitope validation in TILs extends opportunities for mutanome-based personalized immunotherapies to such tumors.

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly.

Ex vivo miRNome analysis in Ptch1+/- cerebellum granule cells reveals a subset of miRNAs involved in radiation-induced medulloblastoma

It has historically been accepted that incorrectly repaired DNA double strand breaks (DSBs) are the principal lesions of importance regarding mutagenesis, and long-term biological effects associated with ionizing radiation. However, radiation may also cause dysregulation of epigenetic processes that can lead to altered gene function and malignant transformation, and epigenetic alterations are important causes of miRNAs dysregulation in cancer.

Patched1 heterozygous (Ptch1^+/−) mice, characterized by aberrant activation of the Sonic hedgehog (Shh) signaling pathway, are a well-known murine model of spontaneous and radiation-induced medulloblastoma (MB), a common pediatric brain tumor originating from neural granule cell progenitors (GCPs). The high sensitivity of neonatal Ptch1^+/− mice to radiogenic MB is dependent on deregulation of the Ptch1 gene function. Ptch1 activates a growth and differentiation programme that is a strong candidate for regulation through the non-coding genome. Therefore we carried out miRNA next generation sequencing in ex vivo irradiated and control GCPs, isolated and purified from cerebella of neonatal WT and Ptch1^+/− mice. We identified a subset of miRNAs, namely let-7 family and miR-17∼92 cluster members, whose expression is altered in GCPs by radiation alone, or by synergistic interaction of radiation with Shh-deregulation. The same miRNAs were further validated in spontaneous and radiation-induced MBs from Ptch1^+/− mice, confirming persistent deregulation of these miRNAs in the pathogenesis of MB.

Our results support the hypothesis that miRNAs dysregulation is associated with radiosensitivity of GCPs and their neoplastic transformation in vivo.

Differential gene expression induced by anti-cancer agent plumbagin is mediated by androgen receptor in prostate cancer cells

Treatment of mice harboring PTEN-P2 tumors in the prostate or on prostate tissue in vivo with 5-hydroxy-2-methyl-1,4-naphthoquinone, also known as plumbagin, results in tumor regression in castrated mice, but not in intact mice. This suggested that dihydrotestosterone (DHT) production in the testes may prevent cell death due to plumbagin treatment, but the underlying mechanism is not understood. We performed RNA-seq analysis on cells treated with combinations of plumbagin and DHT, and analyzed differential gene expression, to gain insight into the interactions between androgen and plumbgin. DHT and plumbagin synergize to alter the expression of many genes that are not differentially regulated by either single agent when used alone. These experiments revealed that, for many genes, increases in mRNAs caused by DHT are sharply down-regulated by plumbagin, and that many transcripts change in response to plumbagin in a DHT-dependent manner. This suggests that androgen receptor mediates some of the effects of plumbagin on gene expression.

CD99 is a therapeutic target on disease stem cells in myeloid malignancies

Acute myeloid leukemia (AML) and the myelodysplastic syndromes (MDS) are initiated and sustained by self-renewing malignant stem cells; thus, eradication of AML and MDS stem cells is required for cure. We identified CD99 as a cell surface protein frequently overexpressed on AML and MDS stem cells. Expression of CD99 allows for prospective separation of leukemic stem cells (LSCs) from functionally normal hematopoietic stem cells in AML, and high CD99 expression on AML blasts enriches for functional LSCs as demonstrated by limiting dilution xenotransplant studies. Monoclonal antibodies (mAbs) targeting CD99 induce the death of AML and MDS cells in a SARC family kinase-dependent manner in the absence of immune effector cells or complement, and anti-CD99 mAbs exhibit antileukemic activity in AML xenografts. These data establish CD99 as a marker of AML and MDS stem cells, as well as a promising therapeutic target in these disorders.

Epigenome-wide association study reveals differential DNA methylation in individuals with a history of myocardial infarction

Cardiovascular diseases (CVDs) are the leading causes of death worldwide and represent a substantial economic burden on public health care systems. Epigenetic markers have potential as diagnostic markers before clinical symptoms have emerged, and as prognostic markers to inform the choice of clinical intervention. In this study, we performed an epigenome-wide association study (EWAS) for CVDs, to identify disease-specific alterations in DNA methylation. CpG methylation in blood samples from the northern Sweden population health study (NSPHS) (n = 729) was assayed on the Illumina Infinium HumanMethylation450 BeadChip. Individuals with a history of a CVD were identified in the cohort. It included individuals with hypertension (N = 147), myocardial infarction (MI) (N = 48), stroke (N = 27), thrombosis (N = 22) and cardiac arrhythmia (N = 5). Differential DNA methylation was observed at 211 CpG-sites in individuals with a history of MI (q <0.05). These sites represent 196 genes, of which 42 have been described in the scientific literature to be related to cardiac function, cardiovascular disease, cardiogenesis and recovery after ischemic injury. We have shown that individuals with a history of MI have a deviating pattern of DNA methylation at many genomic loci of which a large fraction has previously been linked to CVD. Our results highlight genes that might be important in the pathogenesis of MI or in recovery. In addition, the sites pointed out in this study can serve as candidates for further evaluation as potential biomarkers for MI.

Human Placental-Derived Adherent Stromal Cells Co-Induced with TNF-α and IFN-γ Inhibit Triple-Negative Breast Cancer in Nude Mouse Xenograft Models

Culturing 3D-expanded human placental-derived adherent stromal cells (ASCs) in the presence of tumor necrosis factor-alpha (TNF-α) and interferon-gamma (IFN-γ) transiently upregulated the secretion of numerous anti-proliferative, anti-angiogenic and pro-inflammatory cytokines. In a 3D-spheroid screening assay, conditioned medium from these induced-ASCs inhibited proliferation of cancer cell lines, including triple-negative breast cancer (TNBC) lines. In vitro co-culture studies of induced-ASCs with MDA-MB-231 human breast carcinoma cells, a model representing TNBC, supports a mechanism involving immunomodulation and angiogenesis inhibition. In vivo studies in nude mice showed that intramuscular administration of induced-ASCs halted MDA-MB-231 cell proliferation, and inhibited tumor progression and vascularization. Thirty percent of treated mice experienced complete tumor remission. Murine serum concentrations of the tumor-supporting cytokines Interleukin-6 (IL-6), Vascular endothelial growth factor (VEGF) and Granulocyte-colony stimulating factor (G-CSF) were lowered to naïve levels. A somatic mutation analysis identified numerous genes which could be screened in patients to increase a positive therapeutic outcome. Taken together, these results show that targeted changes in the secretion profile of ASCs may improve their therapeutic potential.

Blood plasma/IgG N-glycome biosignatures associated with major depressive disorder symptom severity and the antidepressant response

While N-linked glycosylation has been extensively studied in the context of inflammatory and metabolic disorders, its relationship with major depressive disorder (MDD) and antidepressant treatment response has not been investigated. In our exploratory study, we analysed N-glycan profiles in blood plasma samples collected from MDD patients (n = 18) and found gender-dependent correlations with severity of depressive symptoms prior to initiating antidepressant treatment. In addition, several N-glycosylation traits showed gender-dependent associations with clinical antidepressant response. Follow up proteomics analysis in peripheral blood mononuclear cells (PBMCs) collected from MDD patients (n = 20) identified baseline and post-antidepressant treatment pathway differences between responder and non-responder patients. Reactome data analysis further delineated potential biological reaction differences between responder and non-responder patients. Our preliminary results suggest that specific glycosylation traits are associated with depressive symptom severity and antidepressant response and may be of use as biomarkers.

Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis

BACKGROUND

Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network.

RESULTS

We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study.

CONCLUSIONS

Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

Human glioblastoma-associated microglia/monocytes express a distinct RNA profile compared to human control and murine samples

Glioblastoma (GBM) is the most aggressive brain tumor in adults. It is strongly infiltrated by microglia and peripheral monocytes that support tumor growth. In the present study we used RNA sequencing to compare the expression profile of CD11b(+) human glioblastoma-associated microglia/monocytes (hGAMs) to CD11b(+) microglia isolated from non-tumor samples. Hierarchical clustering and principal component analysis showed a clear separation of the two sample groups and we identified 334 significantly regulated genes in hGAMs. In comparison to human control microglia hGAMs upregulated genes associated with mitotic cell cycle, cell migration, cell adhesion, and extracellular matrix organization. We validated the expression of several genes associated with extracellular matrix organization in samples of human control microglia, hGAMs, and the hGAMs-depleted fraction via qPCR. The comparison to murine GAMs (mGAMs) showed that both cell populations share a significant fraction of upregulated transcripts compared with their respective controls. These genes were mostly related to mitotic cell cycle. However, in contrast to murine cells, human GAMs did not upregulate genes associated to immune activation. Comparison of human and murine GAMs expression data to several data sets of in vitro-activated human macrophages and murine microglia showed that, in contrast to mGAMs, hGAMs share a smaller overlap to these data sets in general and in particular to cells activated by proinflammatory stimulation with LPS + INFγ or TNFα. Our findings provide new insights into the biology of human glioblastoma-associated microglia/monocytes and give detailed information about the validity of murine experimental models. GLIA 2016 GLIA 2016;64:1416-1436.

The Notch Interactome: Complexity in Signaling Circuitry

The Notch pathway controls a very broad spectrum of cell fates in metazoans during development, influencing proliferation, differentiation and cell death. Given its central role in normal development and homeostasis, misregulation of Notch signals can lead to various disorders including cancer. How the Notch pathway mediates such pleiotropic and differential effects is of fundamental importance. It is becoming increasingly clear through a number of large-scale genetic and proteomic studies that Notch interacts with a staggeringly large number of other genes and pathways in a context-dependent, complex, and highly regulated network, which determines the ultimate biological outcome. How best to interpret and analyze the continuously increasing wealth of data on Notch interactors remains a challenge. Here we review the current state of genetic and proteomic data related to the Notch interactome.

Genomics-Driven Precision Medicine for Advanced Pancreatic Cancer: Early Results from the COMPASS Trial

Purpose: To perform real-time whole genome sequencing (WGS) and RNA sequencing (RNASeq) of advanced pancreatic ductal adenocarcinoma (PDAC) to identify predictive mutational and transcriptional features for better treatment selection.Experimental Design: Patients with advanced PDAC were prospectively recruited prior to first-line combination chemotherapy. Fresh tumor tissue was acquired by image-guided percutaneous core biopsy for WGS and RNASeq. Laser capture microdissection was performed for all cases. Primary endpoint was feasibility to report WGS results prior to first disease assessment CT scan at 8 weeks. The main secondary endpoint was discovery of patient subsets with predictive mutational and transcriptional signatures.Results: Sixty-three patients underwent a tumor biopsy between December 2015 and June 2017. WGS and RNASeq were successful in 62 (98%) and 60 (95%), respectively. Genomic results were reported at a median of 35 days (range, 19-52 days) from biopsy, meeting the primary feasibility endpoint. Objective responses to first-line chemotherapy were significantly better in patients with the classical PDAC RNA subtype compared with those with the basal-like subtype (P = 0.004). The best progression-free survival was observed in those with classical subtype treated with m-FOLFIRINOX. GATA6 expression in tumor measured by RNA in situ hybridization was found to be a robust surrogate biomarker for differentiating classical and basal-like PDAC subtypes. Potentially actionable genetic alterations were found in 30% of patients.Conclusions: Prospective genomic profiling of advanced PDAC is feasible, and our early data indicate that chemotherapy response differs among patients with different genomic/transcriptomic subtypes. Clin Cancer Res; 24(6); 1344-54. ©2017 AACR.

Association of Rare Predicted Loss-of-Function Variants in Cellular Pathways with Sub-Phenotypes in Age-Related Macular Degeneration

PURPOSE

To investigate the association of rare predicted loss-of-function (pLoF) variants within age-related macular degeneration (AMD) risk loci and AMD sub-phenotypes.

DESIGN

Case-control study.

PARTICIPANTS

Participants of AREDS, AREDS2, and Michigan Genomics Initiative.

METHODS

Whole genome sequencing data were analyzed for rare pLoF variants (frequency <0.1%) in the regions of previously identified 52 independent risk variants known to be associated with AMD. Frequency of the rare pLoF variants in cases with intermediate or advanced AMD was compared with controls. Variants were assigned to the complement, extracellular matrix (ECM), lipid, cell survival, immune system, metabolism, or unknown/other pathway. Associations of rare pLoF variant pathways with AMD sub-phenotypes were analyzed using logistic and linear regression, and Cox proportional hazards models.

MAIN OUTCOME MEASURES

Differences in rare pLoF variant pathway burden and association of rare pLoF variant pathways with sub-phenotypes within the population with AMD were evaluated.

RESULTS

Rare pLoF variants were found in 298 of 1689 cases (17.6%) and 237 of 1518 controls (15.6%) (odds ratio [OR], 1.11; 95% confidence interval [CI], 0.91-1.36; P = 0.310). An enrichment of rare pLoF variants in the complement pathway in cases versus controls (OR, 2.94; 95% CI, 1.49-5.79; P = 0.002) was observed. Within cases, associations between all rare pLoF variants and choroidal neovascularization (CNV) (OR, 1.34; 95% CI, 1.04-1.73; P = 0.023), calcified drusen (OR, 1.33; 95% CI, 1.04-1.72; P = 0.025), higher scores on the AREDS Extended AMD Severity Scale (Standardized Coefficient Beta (β)=0.346 [0.086-0.605], P = 0.009), and progression to advanced disease (hazard ratio, 1.25; 95% CI, 1.01-1.55; P = 0.042) were observed. At the pathway level, there were associations between the complement pathway and geographic atrophy (GA) (OR, 2.17; 95% CI, 1.12-4.24; P = 0.023), the complement pathway and calcified drusen (OR, 3.75; 95% CI, 1.79-7.86; P < 0.001), and the ECM pathway and more severe levels in the AREDS Extended AMD Severity Scale (β = 0.62; 95% CI, 0.04-1.20; P = 0.035).

CONCLUSIONS

Rare pLoF variants are associated with disease progression. Variants in the complement pathway modify the clinical course of AMD and increase the risk of developing specific sub-phenotypes.

Predicting cancer type from tumour DNA signatures

Background

Establishing the cancer type and site of origin is important in determining the most appropriate course of treatment for cancer patients. Patients with cancer of unknown primary, where the site of origin cannot be established from an examination of the metastatic cancer cells, typically have poor survival. Here, we evaluate the potential and limitations of utilising gene alteration data from tumour DNA to identify cancer types.

Methods

Using sequenced tumour DNA downloaded via the cBioPortal for Cancer Genomics, we collected the presence or absence of calls for gene alterations for 6640 tumour samples spanning 28 cancer types, as predictive features. We employed three machine-learning techniques, namely linear support vector machines with recursive feature selection, L₁-regularised logistic regression and random forest, to select a small subset of gene alterations that are most informative for cancer-type prediction. We then evaluated the predictive performance of the models in a comparative manner.

Results

We found the linear support vector machine to be the most predictive model of cancer type from gene alterations. Using only 100 somatic point-mutated genes for prediction, we achieved an overall accuracy of 49.4±0.4 % (95 % confidence interval). We observed a marked increase in the accuracy when copy number alterations are included as predictors. With a combination of somatic point mutations and copy number alterations, a mere 50 genes are enough to yield an overall accuracy of 77.7±0.3 %.

Conclusions

A general cancer diagnostic tool that utilises either only somatic point mutations or only copy number alterations is not sufficient for distinguishing a broad range of cancer types. The combination of both gene alteration types can dramatically improve the performance.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0493-2) contains supplementary material, which is available to authorized users.

The Gene Ontology of eukaryotic cilia and flagella

BACKGROUND

Recent research into ciliary structure and function provides important insights into inherited diseases termed ciliopathies and other cilia-related disorders. This wealth of knowledge needs to be translated into a computational representation to be fully exploitable by the research community. To this end, members of the Gene Ontology (GO) and SYSCILIA Consortia have worked together to improve representation of ciliary substructures and processes in GO.

METHODS

Members of the SYSCILIA and Gene Ontology Consortia suggested additions and changes to GO, to reflect new knowledge in the field. The project initially aimed to improve coverage of ciliary parts, and was then broadened to cilia-related biological processes. Discussions were documented in a public tracker. We engaged the broader cilia community via direct consultation and by referring to the literature. Ontology updates were implemented via ontology editing tools.

RESULTS

So far, we have created or modified 127 GO terms representing parts and processes related to eukaryotic cilia/flagella or prokaryotic flagella. A growing number of biological pathways are known to involve cilia, and we continue to incorporate this knowledge in GO. The resulting expansion in GO allows more precise representation of experimentally derived knowledge, and SYSCILIA and GO biocurators have created 199 annotations to 50 human ciliary proteins. The revised ontology was also used to curate mouse proteins in a collaborative project. The revised GO and annotations, used in comparative 'before and after' analyses of representative ciliary datasets, improve enrichment results significantly.

CONCLUSIONS

Our work has resulted in a broader and deeper coverage of ciliary composition and function. These improvements in ontology and protein annotation will benefit all users of GO enrichment analysis tools, as well as the ciliary research community, in areas ranging from microscopy image annotation to interpretation of high-throughput studies. We welcome feedback to further enhance the representation of cilia biology in GO.

Combining membrane proteomics and computational three-way pathway analysis revealed signalling pathways preferentially regulated in human iPSCs and human ESCs

Owing to the clinical potential of human induced pluripotent stem cells (hiPSCs) in regenerative medicine, a thorough examination of the similarities and differences between hiPSCs and human embryonic stem cells (hESCs) has become indispensable. Moreover, as the important roles of membrane proteins in biological signalling, functional analyses of membrane proteome are therefore promising. In this study, a pathway analysis by the bioinformatics tool GSEA was first performed to identify significant pathways associated with the three comparative membrane proteomics experiments: hiPSCs versus precursor human foreskin fibroblasts (HFF), hESCs versus precursor HFF, and hiPSCs versus hESCs. A following three-way pathway comparison was conducted to identify the differentially regulated pathways that may contribute to the differences between hiPSCs and hESCs. Our results revealed that pathways related to oxidative phosphorylation and focal adhesion may undergo incomplete regulations during the reprogramming process. This hypothesis was supported by another public proteomics dataset to a certain degree. The identified pathways and their core enriched proteins could serve as the starting point to explore the possible ways to make hiPSCs closer to hESCs.

Transcriptomics-driven lipidomics (TDL) identifies the microbiome-regulated targets of ileal lipid metabolism

The gut microbiome and lipid metabolism are both recognized as essential components in the maintenance of metabolic health. The mechanisms involved are multifactorial and (especially for microbiome) poorly defined. A strategic approach to investigate the complexity of the microbial influence on lipid metabolism would facilitate determination of relevant molecular mechanisms for microbiome-targeted therapeutics. E. coli is associated with obesity and metabolic syndrome and we used this association in conjunction with gnotobiotic models to investigate the impact of E. coli on lipid metabolism. To address the complexities of the integration of the microbiome and lipid metabolism, we developed transcriptomics-driven lipidomics (TDL) to predict the impact of E. coli colonization on lipid metabolism and established mediators of inflammation and insulin resistance including arachidonic acid metabolism, alterations in bile acids and dietary lipid absorption. A microbiome-related therapeutic approach targeting these mechanisms may therefore provide a therapeutic avenue supporting maintenance of metabolic health.

Microbes multifactorially impact host lipid metabolism bearing a significant impact in health and disease. A team led by Mojgan Masoodi and Scott Parkinson at Nestlé Institute of Health Sciences (NIHS) developed an integrative data driven approach for predictive lipidomics investigations of host-microbial impacts on lipid metabolism. Results of in-vivo studies with germ-free mice inoculated with E. coli and in-vitro studies demonstrated the multifactorial nature of the impact of E. coli on arachidonic acid metabolism in the ileum and altered host inflammation and lipid absorption. The findings provide insights into understanding the host-microbiome interactions and identifying microbiome-related solutions for maintaining health and tackling disease. The systems approach presented is applicable to investigate broad range of microbiome dependent and independent alterations in host lipid metabolism.

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

Single-Base Resolution Mapping of 5-Hydroxymethylcytosine Modifications in Hippocampus of Alzheimer's Disease Subjects

Epigenetic modifications to cytosine have been shown to regulate transcription in cancer, embryonic development, and recently neurodegeneration. While cytosine methylation studies are now common in neurodegenerative research, hydroxymethylation studies are rare, particularly genome-wide mapping studies. As an initial study to analyze 5-hydroxymethylcytosine (5-hmC) in the Alzheimer's disease (AD) genome, reduced representation hydroxymethylation profiling (RRHP) was used to analyze more than 2 million sites of possible modification in hippocampal DNA of sporadic AD and normal control subjects. Genes with differentially hydroxymethylated regions were filtered based on previously published microarray data for altered gene expression in hippocampal DNA of AD subjects. Our data show significant pathways for altered levels of 5-hmC in the hippocampus of AD subjects compared to age-matched normal controls involved in signaling, energy metabolism, cell function, gene expression, protein degradation, and cell structure and stabilization. Overall, our data suggest a possible role for the dysregulation of epigenetic modifications to cytosine in late stage AD.