Landscape of brain myeloid cell transcriptome along the spatiotemporal progression of Alzheimer's disease reveals distinct sequential responses to Aß and tau.

Human microglia are critically involved in Alzheimer's disease (AD) progression, as shown by genetic and molecular studies. However, their role in tau pathology progression in human brain has not been well described. Here, we characterized 32 human donors along progression of AD pathology, both in time-from early to late pathology-and in space-from entorhinal cortex (EC), inferior temporal gyrus (ITG), prefrontal cortex (PFC) to visual cortex (V2 and V1)-with biochemistry, immunohistochemistry, and single nuclei-RNA-sequencing, profiling a total of 337,512 brain myeloid cells, including microglia. While the majority of microglia are similar across brain regions, we identified a specific subset unique to EC which may contribute to the early tau pathology present in this region. We calculated conversion of microglia subtypes to diseased states and compared conversion patterns to those from AD animal models. Targeting genes implicated in this conversion, or their upstream/downstream pathways, could halt gene programs initiated by early tau progression. We used expression patterns of early tau progression to identify genes whose expression is reversed along spreading of spatial tau pathology (EC > ITG > PFC > V2 > V1) and identified their potential involvement in microglia subtype conversion to a diseased state. This study provides a data resource that builds on our knowledge of myeloid cell contribution to AD by defining the heterogeneity of microglia and brain macrophages during both temporal and regional pathology aspects of AD progression at an unprecedented resolution.

Distinct transcriptomic responses to Aß plaques, neurofibrillary tangles, and APOE in Alzheimer's disease.

INTRODUCTION: Omics studies have revealed that various brain cell types undergo profound molecular changes in Alzheimer's disease (AD) but the spatial relationships with plaques and tangles and APOE-linked differences remain unclear. METHODS: We performed laser capture microdissection of amyloid beta (Aß) plaques, the 50 µm halo around them, tangles with the 50 µm halo around them, and areas distant (> 50 µm) from plaques and tangles in the temporal cortex of AD and control donors, followed by RNA-sequencing. RESULTS: Aß plaques exhibited upregulated microglial (neuroinflammation/phagocytosis) and downregulated neuronal (neurotransmission/energy metabolism) genes, whereas tangles had mostly downregulated neuronal genes. Aß plaques had more differentially expressed genes than tangles. We identified a gradient Aß plaque > peri-plaque > tangle > distant for these changes. AD APOE ε4 homozygotes had greater changes than APOE ε3 across locations, especially within Aß plaques. DISCUSSION: Transcriptomic changes in AD consist primarily of neuroinflammation and neuronal dysfunction, are spatially associated mainly with Aß plaques, and are exacerbated by the APOE ε4 allele.

Endothelial Cells Are Heterogeneous in Different Brain Regions and Are Dramatically Altered in Alzheimer's Disease.

Vascular endothelial cells play an important role in maintaining brain health, but their contribution to Alzheimer's disease (AD) is obscured by limited understanding of the cellular heterogeneity in normal aged brain and in disease. To address this, we performed single nucleus RNAseq on tissue from 32 human AD and non-AD donors (19 female, 13 male) each with five cortical regions: entorhinal cortex, inferior temporal gyrus, prefrontal cortex, visual association cortex, and primary visual cortex. Analysis of 51,586 endothelial cells revealed unique gene expression patterns across the five regions in non-AD donors. Alzheimer's brain endothelial cells were characterized by upregulated protein folding genes and distinct transcriptomic differences in response to amyloid ß plaques and cerebral amyloid angiopathy. This dataset demonstrates previously unrecognized regional heterogeneity in the endothelial cell transcriptome in both aged non-AD and AD brain.SIGNIFICANCE STATEMENT In this work, we show that vascular endothelial cells collected from five different brain regions display surprising variability in gene expression. In the presence of Alzheimer's disease pathology, endothelial cell gene expression is dramatically altered with clear differences in regional and temporal changes. These findings help explain why certain brain regions appear to differ in susceptibility to disease-related vascular remodeling events that may impact blood flow.

Distinct Transcriptomic Responses to Aß plaques, Neurofibrillary Tangles, and APOE in Alzheimer's Disease.

INTRODUCTION: Omics studies have revealed that various brain cell types undergo profound molecular changes in Alzheimer's disease (AD) but the spatial relationships with plaques and tangles and APOE -linked differences remain unclear. METHODS: We performed laser capture microdissection of Aß plaques, the 50µm halo around them, tangles with the 50µm halo around them, and areas distant (>50µm) from plaques and tangles in the temporal cortex of AD and control donors, followed by RNA-sequencing. RESULTS: Aß plaques exhibited upregulated microglial (neuroinflammation/phagocytosis) and downregulated neuronal (neurotransmission/energy metabolism) genes, whereas tangles had mostly downregulated neuronal genes. Aß plaques had more differentially expressed genes than tangles. We identified a gradient Aß plaque>peri-plaque>tangle>distant for these changes. AD APOE ε4 homozygotes had greater changes than APOE ε3 across locations, especially within Aß plaques. DISCUSSION: Transcriptomic changes in AD consist primarily of neuroinflammation and neuronal dysfunction, are spatially associated mainly with Aß plaques, and are exacerbated by the APOE ε4 allele.

Endothelial Cells are Heterogeneous in Different Brain Regions and are Dramatically Altered in Alzheimer's Disease.

Vascular endothelial cells play an important role in maintaining brain health, but their contribution to Alzheimer's disease (AD) is obscured by limited understanding of the cellular heterogeneity in normal aged brain and in disease. To address this, we performed single nucleus RNAseq on tissue from 32 AD and non-AD donors each with five cortical regions: entorhinal cortex, inferior temporal gyrus, prefrontal cortex, visual association cortex and primary visual cortex. Analysis of 51,586 endothelial cells revealed unique gene expression patterns across the five regions in non-AD donors. Alzheimer's brain endothelial cells were characterized by upregulated protein folding genes and distinct transcriptomic differences in response to amyloid beta plaques and cerebral amyloid angiopathy (CAA). This dataset demonstrates previously unrecognized regional heterogeneity in the endothelial cell transcriptome in both aged non-AD and AD brain. Significance Statement: In this work, we show that vascular endothelial cells collected from five different brain regions display surprising variability in gene expression. In the presence of Alzheimer's disease pathology, endothelial cell gene expression is dramatically altered with clear differences in regional and temporal changes. These findings help explain why certain brain regions appear to differ in susceptibility to disease-related vascular remodeling events that may impact blood flow.

High-Throughput Profiling of Colorectal Cancer Liver Metastases Reveals Intra- and Inter-Patient Heterogeneity in the EGFR and WNT Pathways Associated with Clinical Outcome.

Seventy percent of patients with colorectal cancer develop liver metastases (CRLM), which are a decisive factor in cancer progression. Therapy outcome is largely influenced by tumor heterogeneity, but the intra- and inter-patient heterogeneity of CRLM has been poorly studied. In particular, the contribution of the WNT and EGFR pathways, which are both frequently deregulated in colorectal cancer, has not yet been addressed in this context. To this end, we comprehensively characterized normal liver tissue and eight CRLM from two patients by standardized histopathological, molecular, and proteomic subtyping. Suitable fresh-frozen tissue samples were profiled by transcriptome sequencing (RNA-Seq) and proteomic profiling with reverse phase protein arrays (RPPA) combined with bioinformatic analyses to assess tumor heterogeneity and identify WNT- and EGFR-related master regulators and metastatic effectors. A standardized data analysis pipeline for integrating RNA-Seq with clinical, proteomic, and genetic data was established. Dimensionality reduction of the transcriptome data revealed a distinct signature for CRLM differing from normal liver tissue and indicated a high degree of tumor heterogeneity. WNT and EGFR signaling were highly active in CRLM and the genes of both pathways were heterogeneously expressed between the two patients as well as between the synchronous metastases of a single patient. An analysis of the master regulators and metastatic effectors implicated in the regulation of these genes revealed a set of four genes (SFN, IGF2BP1, STAT1, PIK3CG) that were differentially expressed in CRLM and were associated with clinical outcome in a large cohort of colorectal cancer patients as well as CRLM samples. In conclusion, high-throughput profiling enabled us to define a CRLM-specific signature and revealed the genes of the WNT and EGFR pathways associated with inter- and intra-patient heterogeneity, which were validated as prognostic biomarkers in CRC primary tumors as well as liver metastases.

Coordinated regulation of WNT/ß-catenin, c-Met, and integrin signalling pathways by miR-193b controls triple negative breast cancer metastatic traits.

BACKGROUND: Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC). Treatment options for TNBC patients are limited and further insights into disease aetiology are needed to develop better therapeutic approaches. microRNAs' ability to regulate multiple targets could hold a promising discovery approach to pathways relevant for TNBC aggressiveness. Thus, we address the role of miRNAs in controlling three signalling pathways relevant to the biology of TNBC, and their downstream phenotypes. METHODS: To identify miRNAs regulating WNT/ß-catenin, c-Met, and integrin signalling pathways, we performed a high-throughput targeted proteomic approach, investigating the effect of 800 miRNAs on the expression of 62 proteins in the MDA-MB-231 TNBC cell line. We then developed a novel network analysis, Pathway Coregulatory (PC) score, to detect miRNAs regulating these three pathways. Using in vitro assays for cell growth, migration, apoptosis, and stem-cell content, we validated the function of candidate miRNAs. Bioinformatic analyses using BC patients' datasets were employed to assess expression of miRNAs as well as their pathological relevance in TNBC patients. RESULTS: We identified six candidate miRNAs coordinately regulating the three signalling pathways. Quantifying cell growth of three TNBC cell lines upon miRNA gain-of-function experiments, we characterised miR-193b as a strong and consistent repressor of proliferation. Importantly, the effects of miR-193b were stronger than chemical inhibition of the individual pathways. We further demonstrated that miR-193b induced apoptosis, repressed migration, and regulated stem-cell markers in MDA-MB-231 cells. Furthermore, miR-193b expression was the lowest in patients classified as TNBC or Basal compared to other subtypes. Gene Set Enrichment Analysis showed that miR-193b expression was significantly associated with reduced activity of WNT/ß-catenin and c-Met signalling pathways in TNBC patients. CONCLUSIONS: Integrating miRNA-mediated effects and protein functions on networks, we show that miRNAs predominantly act in a coordinated fashion to activate or repress connected signalling pathways responsible for metastatic traits in TNBC. We further demonstrate that our top candidate, miR-193b, regulates these phenotypes to an extent stronger than individual pathway inhibition, thus emphasizing that its effect on TNBC aggressiveness is mediated by the coordinated repression of these functionally interconnected pathways.

Profiling Microglia From Alzheimer's Disease Donors and Non-demented Elderly in Acute Human Postmortem Cortical Tissue.

Microglia are the tissue-resident macrophages of the central nervous system (CNS). Recent studies based on bulk and single-cell RNA sequencing in mice indicate high relevance of microglia with respect to risk genes and neuro-inflammation in Alzheimer's disease (AD). Here, we investigated microglia transcriptomes at bulk and single-cell levels in non-demented elderly and AD donors using acute human postmortem cortical brain samples. We identified seven human microglial subpopulations with heterogeneity in gene expression. Notably, gene expression profiles and subcluster composition of microglia did not differ between AD donors and non-demented elderly in bulk RNA sequencing nor in single-cell sequencing.

Reconstruction of Different Modes of WNT Dependent Protein Networks from Time Series Protein Quantification.

Protein signaling networks are crucial cornerstones in cellular responses. Deregulation causes various diseases, including cancer. One pathway that is frequently deregulated in cancer is the WNT signaling pathway. It has been shown that WNT signaling is highly context-dependent and the availability of receptors and ligands determines downstream signaling. In order to reveal which signaling pathways are activated by a specific receptor-ligand combination, we overexpressed the non-canonical WNT receptor ROR2 in the human breast cancer cell line MCF-7 and stimulated it with its putative ligand WNT11. Based on characterization of the cells by Reverse Phase Protein Array (RPPA), we integrated the proteomic data by network reconstruction analysis with prior knowledge from a pathway database. Using this approach, we were able to identify novel edges that differed upon ROR2 overexpression and WNT11 stimulation.

The transcriptional regulator FUBP1 influences disease outcome in murine and human myeloid leukemia.

The transcriptional regulator far upstream element binding protein 1 (FUBP1) acts as an oncoprotein in solid tumor entities and plays a role in the maintenance of hematopoietic stem cells. However, its potential function in leukemia is unknown. In murine models of chronic (CML) and acute myeloid leukemia (AML) induced by BCR-ABL1 and MLL-AF9, respectively, knockdown of Fubp1 resulted in prolonged survival, decreased numbers of CML progenitor cells, decreased cell cycle activity and increased apoptosis. Knockdown of FUBP1 in CML and AML cell lines recapitulated these findings and revealed enhanced DNA damage compared to leukemia cells expressing wild type FUBP1 levels. FUBP1 was more highly expressed in human CML compared to normal bone marrow cells and its expression correlated with disease progression. In AML, higher FUBP1 expression in patient leukemia cells was observed with a trend toward correlation with shorter overall survival. Treatment of mice with AML with irinotecan, known to inhibit topoisomerase I and FUBP1, significantly prolonged survival alone or in combination with cytarabine. In summary, our data suggest that FUBP1 acts as cell cycle regulator and apoptosis inhibitor in leukemia. We demonstrated that FUBP1 might play a role in DNA repair, and its inhibition may improve outcome in leukemia patients.

PI3K: A master regulator of brain metastasis-promoting macrophages/microglia.

Mutations and activation of the PI3K signaling pathway in breast cancer cells have been linked to brain metastases. However, here we describe that in some breast cancer brain metastases samples the protein expression of PI3K signaling components is restricted to the metastatic microenvironment. In contrast to the therapeutic effects of PI3K inhibition on the breast cancer cells, the reaction of the brain microenvironment is less understood. Therefore we aimed to quantify the PI3K pathway activity in breast cancer brain metastasis and investigate the effects of PI3K inhibition on the central nervous system (CNS) microenvironment. First, to systematically quantify the PI3K pathway activity in breast cancer brain metastases, we performed a prospective biomarker study using a reverse phase protein array (RPPA). The majority, namely 30 out of 48 (62.5%) brain metastatic tissues examined, revealed high PI3K signaling activity that was associated with a median overall survival (OS) of 9.41 months, while that of patients, whose brain metastases showed only moderate or low PI3K activity, amounted to only 1.93 and 6.71 months, respectively. Second, we identified PI3K as a master regulator of metastasis-promoting macrophages/microglia during CNS colonization; and treatment with buparlisib (BKM120), a pan-PI3K Class I inhibitor with a good blood-brain-barrier penetrance, reduced their metastasis-promoting features. In conclusion, PI3K signaling is active in the majority of breast cancer brain metastases. Since PI3K inhibition does not only affect the metastatic cells but also re-educates the metastasis-promoting macrophages/microglia, PI3K inhibition may hold considerable promise in the treatment of brain metastasis and the respective microenvironment.

FGFR3 mRNA overexpression defines a subset of oligometastatic colorectal cancers with worse prognosis.

OBJECTIVES: Metastatic colorectal cancer (CRC) remains a leading cause of cancer related deaths. Patients with oligometastatic liver disease represent a clinical subgroup with heterogeneous course. Until now, biomarkers to characterize outcome and therapeutic options have not been fully established. METHODS: We investigated the prevalence of FGFR alterations in a total of 140 primary colorectal tumors and 63 liver metastases of 55 oligometastatic CRC patients. FGF receptors (FGFR1-4) and their ligands (FGF3, 4 and 19) were analyzed for gene amplifications and rearrangements as well as for RNA overexpression in situ. Results were correlated with clinico-pathologic data and molecular subtypes. RESULTS: Primary tumors showed FGFR1 (6.3%) and FGF3,4,19 (2.2%) amplifications as well as FGFR1 (10.1%), FGFR2 (5.5%) and FGFR3 (16.2%) overexpression. In metastases, we observed FGFR1 amplifications (4.8%) as well as FGFR1 (8.5%) and FGFR3 (14.9%) overexpression. Neither FGFR2-4 amplifications nor gene rearrangements were observed. FGFR3 overexpression was significantly associated with shorter overall survival in metastases (mOS 19.9 vs. 47.4 months, HR=3.14, p=0.0152), but not in primary CRC (HR=1.01, p=0.985). Although rare, also FGFR1 amplification was indicative of worse outcome (mOS 12.6 vs. 47.4 months, HR=8.83, p=0.00111). CONCLUSIONS: We provide the so far most comprehensive analysis of FGFR alterations in primary and metastatic CRC. We describe FGFR3 overexpression in 15% of CRC patients with oligometastatic liver disease as a prognosticator for poor outcome. Recently FGFR3 overexpression has been shown to be a potential therapeutic target. Therefore, we suggest focusing on this subgroup in upcoming clinical trials with FGFR-targeted therapies.

TGFß1 regulates HGF-induced cell migration and hepatocyte growth factor receptor MET expression via C-ets-1 and miR-128-3p in basal-like breast cancer.

Breast cancer is the most common cancer in women worldwide. The tumor microenvironment contributes to tumor progression by inducing cell dissemination from the primary tumor and metastasis. TGFß signaling is involved in breast cancer progression and is specifically elevated during metastatic transformation in aggressive breast cancer. In this study, we performed genomewide correlation analysis of TGFBR2 expression in a panel of 51 breast cancer cell lines and identified that MET is coregulated with TGFBR2. This correlation was confirmed at the protein level in breast cancer cell lines and human tumor tissues. Flow cytometric analysis of luminal and basal-like breast cancer cell lines and examination of 801 tumor specimens from a prospective cohort of breast cancer patients using reverse phase protein arrays revealed that expression of TGFBR2 and MET is increased in basal-like breast cancer cell lines, as well as in triple-negative breast cancer tumor tissues, compared to other subtypes. Using real-time cell analysis technology, we demonstrated that TGFß1 triggered hepatocyte growth factor (HGF)-induced and MET-dependent migration in vitro. Bioinformatic analysis predicted that TGFß1 induces expression of C-ets-1 as a candidate transcription factor regulating MET expression. Indeed, TGFß1-induced expression of ETS1 and breast cancer cell migration was blocked by knockdown of ETS1. Further, we identified that MET is a direct target of miR-128-3p and that this miRNA is negatively regulated by TGFß1. Overexpression of miR-128-3p reduced MET expression and abrogated HGF-induced cell migration of invasive breast cancer cells. In conclusion, we have identified that TGFß1 regulates HGF-induced and MET-mediated cell migration, through positive regulation of C-ets-1 and negative regulation of miR-128-3p expression in basal-like breast cancer cell lines and in triple-negative breast cancer tissue.

Proteomic profiling of breast cancer metabolism identifies SHMT2 and ASCT2 as prognostic factors.

BACKGROUND: Breast cancer tumors are known to be highly heterogeneous and differences in their metabolic phenotypes, especially at protein level, are less well-understood. Profiling of metabolism-related proteins harbors the potential to establish new patient stratification regimes and biomarkers promoting individualized therapy. In our study, we aimed to examine the relationship between metabolism-associated protein expression profiles and clinicopathological characteristics in a large cohort of breast cancer patients. METHODS: Breast cancer specimens from 801 consecutive patients, diagnosed between 2009 and 2011, were investigated using reverse phase protein arrays (RPPA). Patients were treated in accordance with national guidelines in five certified German breast centers. To obtain quantitative expression data, 37 antibodies detecting proteins relevant to cancer metabolism, were applied. Hierarchical cluster analysis and individual target characterization were performed. Clustering results and individual protein expression patterns were associated with clinical data. The Kaplan-Meier method was used to estimate survival functions. Univariate and multivariate Cox regression models were applied to assess the impact of protein expression and other clinicopathological features on survival. RESULTS: We identified three metabolic clusters of breast cancer, which do not reflect the receptor-defined subtypes, but are significantly correlated with overall survival (OS, p ≤ 0.03) and recurrence-free survival (RFS, p ≤ 0.01). Furthermore, univariate and multivariate analysis of individual protein expression profiles demonstrated the central role of serine hydroxymethyltransferase 2 (SHMT2) and amino acid transporter ASCT2 (SLC1A5) as independent prognostic factors in breast cancer patients. High SHMT2 protein expression was significantly correlated with poor OS (hazard ratio (HR) = 1.53, 95% confidence interval (CI) = 1.10-2.12, p ≤ 0.01) and RFS (HR = 1.54, 95% CI = 1.16-2.04, p ≤ 0.01). High protein expression of ASCT2 was significantly correlated with poor RFS (HR = 1.31, 95% CI = 1.01-1.71, p ≤ 0.05). CONCLUSIONS: Our data confirm the heterogeneity of breast tumors at a functional proteomic level and dissects the relationship between metabolism-related proteins, pathological features and patient survival. These observations highlight the importance of SHMT2 and ASCT2 as valuable individual prognostic markers and potential targets for personalized breast cancer therapy. TRIAL REGISTRATION: ClinicalTrials.gov, NCT01592825 . Registered on 3 May 2012.

Characterisation of tumour-derived microvesicles in cancer patients' blood and correlation with clinical outcome.

To evaluate whether tumour-derived microvesicles (T-MV), originating from the plasma membrane, represent suitable cancer biomarkers, we isolated MV from peripheral blood samples of cancer patients with locally advanced and/or metastatic solid tumours (n = 330, including 79 head & neck cancers, 74 lung cancers, 41 breast cancers, 28 colorectal cancers and 108 with other cancer forms) and controls (n = 103). Whole MV preparations were characterised using flow cytometry. While MV carrying the tumour-associated proteins MUC1, EGFR and EpCAM were found to be enhanced in a tumour-subtype-specific way in patients' blood, expression of the matrix metalloproteinase inducer EMMPRIN was increased independent of tumour type. Higher levels of EMMPRIN+-MV correlated significantly with poor overall survival, whereas the other markers were prognostic only in specific tumour subgroups. By combining all four tumour-associated antigens, cancer patients were separated from healthy controls with an AUC of up to 0.85. Ex vivo, whole MV preparations from cancer patients, in contrast to those of controls, induced a tumour-supporting phenotype in macrophages and increased tumour cell invasion, which was dependent on the highly glycosylated isoform of EMMPRIN. In conclusion, the detection of T-MV in whole blood, even in minor amounts, is feasible with standard techniques, proves functionally relevant and correlates with clinical outcome.

Hoxa9 and Meis1 Cooperatively Induce Addiction to Syk Signaling by Suppressing miR-146a in Acute Myeloid Leukemia.

The transcription factor Meis1 drives myeloid leukemogenesis in the context of Hox gene overexpression but is currently considered undruggable. We therefore investigated whether myeloid progenitor cells transformed by Hoxa9 and Meis1 become addicted to targetable signaling pathways. A comprehensive (phospho)proteomic analysis revealed that Meis1 increased Syk protein expression and activity. Syk upregulation occurs through a Meis1-dependent feedback loop. By dissecting this loop, we show that Syk is a direct target of miR-146a, whose expression is indirectly regulated by Meis1 through the transcription factor PU.1. In the context of Hoxa9 overexpression, Syk signaling induces Meis1, recapitulating several leukemogenic features of Hoxa9/Meis1-driven leukemia. Finally, Syk inhibition disrupts the identified regulatory loop, prolonging survival of mice with Hoxa9/Meis1-driven leukemia.

Use of the Impella Device for Acute Coronary Syndrome Complicated by Cardiogenic Shock - Experience From a Single Heart Center With Analysis of Long-term Mortality.

AIMS: Impella is a microaxial rotary pump that is placed across the aortic valve to expel aspirated blood from the left ventricle into the ascending aorta; it can be used in cardiogenic shock. While previous studies have evaluated the efficacy and safety of the Impella device, more clinically relevant data are necessary, especially with regard to outcomes. METHODS AND RESULTS: We screened our database of Impella patients in our heart center and found 68 consecutive patients who underwent Impella implantation due to acute coronary syndrome (ACS) complicated by cardiogenic shock. Data were evaluated with regard to baseline and procedural characteristics and also included an assessment of the short-term and long-term outcomes. The majority of patients (74%) suffered from an ST-elevation myocardial infarction, and 59% of patients received the Impella device during the initial coronary angiography. In the remaining cases, Impella implantation was performed at a later time, most commonly after IABP implantation. Patient characteristics were not significantly different between both groups. The predominantly implanted device was an Impella 2.5. Mortality in the severely ill patient population remained high, but univariate/multivariate analyses identified significant risk factors. Interestingly, delayed initiation of Impella support was an independent predictor of higher long-term mortality (hazard ratio, 2.157; P=.04) within the Impella patient cohort. CONCLUSION: This large series of patients with ACS complicated by cardiogenic shock who underwent Impella implantation provides information on the relevant risk factors for mortality. Early (compared with delayed) initiation of Impella support was a predictor of improved survival in this population of patients.

pwOmics: an R package for pathway-based integration of time-series omics data using public database knowledge.

UNLABELLED: Characterization of biological processes is progressively enabled with the increased generation of omics data on different signaling levels. Here we present a straightforward approach for the integrative analysis of data from different high-throughput technologies based on pathway and interaction models from public databases. pwOmics performs pathway-based level-specific data comparison of coupled human proteomic and genomic/transcriptomic datasets based on their log fold changes. Separate downstream and upstream analyses results on the functional levels of pathways, transcription factors and genes/transcripts are performed in the cross-platform consensus analysis. These provide a basis for the combined interpretation of regulatory effects over time. Via network reconstruction and inference methods (Steiner tree, dynamic Bayesian network inference) consensus graphical networks can be generated for further analyses and visualization. AVAILABILITY AND IMPLEMENTATION: The R package pwOmics is freely available on Bioconductor (http://www.bioconductor.org/). CONTACT: astrid.wachter@med.uni-goettingen.de.

Analysis of Reverse Phase Protein Array Data: From Experimental Design towards Targeted Biomarker Discovery.

Mastering the systematic analysis of tumor tissues on a large scale has long been a technical challenge for proteomics. In 2001, reverse phase protein arrays (RPPA) were added to the repertoire of existing immunoassays, which, for the first time, allowed a profiling of minute amounts of tumor lysates even after microdissection. A characteristic feature of RPPA is its outstanding sample capacity permitting the analysis of thousands of samples in parallel as a routine task. Until today, the RPPA approach has matured to a robust and highly sensitive high-throughput platform, which is ideally suited for biomarker discovery. Concomitant with technical advancements, new bioinformatic tools were developed for data normalization and data analysis as outlined in detail in this review. Furthermore, biomarker signatures obtained by different RPPA screens were compared with another or with that obtained by other proteomic formats, if possible. Options for overcoming the downside of RPPA, which is the need to steadily validate new antibody batches, will be discussed. Finally, a debate on using RPPA to advance personalized medicine will conclude this article.

Decoding Cellular Dynamics in Epidermal Growth Factor Signaling Using a New Pathway-Based Integration Approach for Proteomics and Transcriptomics Data.

Identification of dynamic signaling mechanisms on different cellular layers is now facilitated as the increased usage of various high-throughput techniques goes along with decreasing costs for individual experiments. A lot of these signaling mechanisms are known to be coordinated by their dynamics, turning time-course data sets into valuable information sources for inference of regulatory mechanisms. However, the combined analysis of parallel time-course measurements from different high-throughput platforms still constitutes a major challenge requiring sophisticated bioinformatic tools in order to ease biological interpretation. We developed a new pathway-based integration approach for the analysis of coupled omics time-series data, which we implemented in the R package pwOmics. Unlike many other approaches, our approach acknowledges the role of the different cellular layers of measurement and infers consensus profiles and time profile clusters for further biological interpretation. We investigated a time-course data set on epidermal growth factor stimulation of human mammary epithelial cells generated on the two layers of RNA and proteins. The data was analyzed using our new approach with a focus on feedback signaling and pathway crosstalk. We could confirm known regulatory patterns relevant in the physiological cellular response to epidermal growth factor stimulation as well as identify interesting new interactions in this signaling context, such as the regulatory influence of the connective tissue growth factor on transferrin receptor or the influence of growth arrest and DNA-damage-inducible alpha on the connective tissue growth factor. Thus, we show that integrated cross-platform analysis provides a deeper understanding of regulatory signaling mechanisms. Combined with time-course information it enables the characterization of dynamic signaling processes and leads to the identification of important regulatory interactions which might be dysregulated in disease with adverse effects.