Nanoparticle enrichment mass-spectrometry proteomics identifies protein-altering variants for precise pQTL mapping.

Proteogenomics studies generate hypotheses on protein function and provide genetic evidence for drug target prioritization. Most previous work has been conducted using affinity-based proteomics approaches. These technologies face challenges, such as uncertainty regarding target identity, non-specific binding, and handling of variants that affect epitope affinity binding. Mass spectrometry-based proteomics can overcome some of these challenges. Here we report a pQTL study using the Proteograph™ Product Suite workflow (Seer, Inc.) where we quantify over 18,000 unique peptides from nearly 3000 proteins in more than 320 blood samples from a multi-ethnic cohort in a bottom-up, peptide-centric, mass spectrometry-based proteomics approach. We identify 184 protein-altering variants in 137 genes that are significantly associated with their corresponding variant peptides, confirming target specificity of co-associated affinity binders, identifying putatively causal cis-encoded proteins and providing experimental evidence for their presence in blood, including proteins that may be inaccessible to affinity-based proteomics.

piTracer - Automatic reconstruction of molecular cascades for the identification of synergistic drug targets.

Cancer cells frequently undergo metabolic reprogramming as a mechanism of resistance against chemotherapeutic drugs. Metabolomic profiling provides a direct readout of metabolic changes and can thus be used to identify these tumor escape mechanisms. Here, we introduce piTracer, a computational tool that uses multi-scale molecular networks to identify potential combination therapies from pre- and post-treatment metabolomics data. We first demonstrate piTracer’s core ability to reconstruct cellular cascades by inspecting well-characterized molecular pathways and previously studied associations between genetic variants and metabolite levels. We then apply a new gene ranking algorithm on differential metabolomic profiles from human breast cancer cells after glutaminase inhibition. Four of the automatically identified gene targets were experimentally tested by simultaneous inhibition of the respective targets and glutaminase. Of these combination treatments, two were be confirmed to induce synthetic lethality in the cell line. In summary, piTracer integrates the molecular monitoring of escape mechanisms into comprehensive pathway networks to accelerate drug target identification. The tool is open source and can be accessed at https://github.com/krumsieklab/pitracer .

Advancing Cancer Treatment by Targeting Glutamine Metabolism-A Roadmap.

Tumor growth and metastasis strongly depend on adapted cell metabolism. Cancer cells adjust their metabolic program to their specific energy needs and in response to an often challenging tumor microenvironment. Glutamine metabolism is one of the metabolic pathways that can be successfully targeted in cancer treatment. The dependence of many hematological and solid tumors on glutamine is associated with mitochondrial glutaminase (GLS) activity that enables channeling of glutamine into the tricarboxylic acid (TCA) cycle, generation of ATP and NADPH, and regulation of glutathione homeostasis and reactive oxygen species (ROS). Small molecules that target glutamine metabolism through inhibition of GLS therefore simultaneously limit energy availability and increase oxidative stress. However, some cancers can reprogram their metabolism to evade this metabolic trap. Therefore, the effectiveness of treatment strategies that rely solely on glutamine inhibition is limited. In this review, we discuss the metabolic and molecular pathways that are linked to dysregulated glutamine metabolism in multiple cancer types. We further summarize and review current clinical trials of glutaminolysis inhibition in cancer patients. Finally, we put into perspective strategies that deploy a combined treatment targeting glutamine metabolism along with other molecular or metabolic pathways and discuss their potential for clinical applications.

Defining the landscape of metabolic dysregulations in cancer metastasis.

Metastasis is the primary cause of cancer related deaths due to the limited number of efficient druggable targets. Signatures of dysregulated cancer metabolism could serve as a roadmap for the determination of new treatment strategies. However, the metabolic signatures of metastatic cells remain vastly elusive. Our aim was to determine metabolic dysregulations associated with high metastatic potential in breast cancer cell lines. We have selected 5 triple negative breast cancer (TNBC) cell lines including three with high metastatic potential (HMP) (MDA-MB-231, MDA-MB-436, MDA-MB-468) and two with low metastatic potential (LMP) (BT549, HCC1143). The normal epithelial breast cell line (hTERT-HME1) was also investigated. The untargeted metabolic profiling of cells and growth media was conducted and total of 479 metabolites were quantified. First we characterized metabolic features differentiating TNBC cell lines from normal cells as well as identified cell line specific metabolic fingerprints. Next, we determined 92 metabolites in cells and 22 in growth medium that display significant differences between LMP and HMP. The HMP cell lines had elevated level of molecules involved in glycolysis, TCA cycle and lipid metabolism. We identified metabolic advantages of cell lines with HMP beyond enhanced glycolysis by pinpointing the role of branched chain amino acids (BCAA) catabolism as well as molecules supporting coagulation and platelet activation as important contributors to the metastatic cascade. The landscape of metabolic dysregulations, characterized in our study, could serve as a roadmap for the identification of treatment strategies targeting cancer cells with enhanced metastatic potential.

Deep sequencing of DNA from urine of kidney allograft recipients to estimate donor/recipient-specific DNA fractions.

Kidney transplantation is the treatment of choice for patients with end-stage kidney failure, but transplanted allograft could be affected by viral and bacterial infections and by immune rejection. The standard test for the diagnosis of acute pathologies in kidney transplants is kidney biopsy. However, noninvasive tests would be desirable. Various methods using different techniques have been developed by the transplantation community. But these methods require improvements. We present here a cost-effective method for kidney rejection diagnosis that estimates donor/recipient-specific DNA fraction in recipient urine by sequencing urinary cell DNA. We hypothesized that in the no-pathology stage, the largest tissue types present in recipient urine are donor kidney cells, and in case of rejection, a larger number of recipient immune cells would be observed. Extensive in-silico simulation was used to tune the sequencing parameters: number of variants and depth of coverage. Sequencing of DNA mixture from 2 healthy individuals showed the method is highly predictive (maximum error < 0.04). We then demonstrated the insignificant impact of familial relationship and ethnicity using an in-house and public database. Lastly, we performed deep DNA sequencing of urinary cell pellets from 32 biopsy-matched samples representing two pathology groups: acute rejection (AR, 11 samples) and acute tubular injury (ATI, 12 samples) and 9 samples with no pathology. We found a significant association between the donor/recipient-specific DNA fraction in the two pathology groups compared to no pathology (P = 0.0064 for AR and P = 0.026 for ATI). We conclude that deep DNA sequencing of urinary cells from kidney allograft recipients offers a noninvasive means of diagnosing acute pathologies in the human kidney allograft.

Identification of genetic variants controlling RNA editing and their effect on RNA structure stabilization.

Post-transcriptional modification of RNA (RNA editing, RNAe) results in differences between the RNA transcript and the genomic DNA sequence (RDD). Enzymatic modification of adenosine to inosine (A2I) by ADAR is the most studied type of RNAe. However, few genetic association studies with A2I RNAe events have been conducted. Some studies have analyzed the inter-population RNAe-QTL diversity in humans, but the sample size of these studies was limited. Other types of RNA and DNA differences have been reported but are largely understudied. Here, we report a comprehensive analysis of all types of RDD, based on two independent datasets. We found that A2I was by far the most observed type of RDD. Moreover, manual curation suggests that A2I is likely the only enzymatically driven RNAe type observed in blood derived DNA, all other non-A2I RDD could either be attributed to sequencing and processing artifacts, or are a result of somatic DNA rearrangements. We then conducted an in-cis genetic association study and identified 472 genetic associations (RNAe-QTL), that were replicated in both datasets. We confirm the potential effect of the RNAe-QTL on RNA structure by showing that allele specific RNAe occurs in heterozygotes. Although the generally assumed function of RNAe is to destabilize double stranded RNA structure, we found clear evidence for the potential additional involvement of RNAe in maintaining RNA hairpin that has been altered by the RNAe-QTL. Our study confirms, in two independent datasets, the potential role of RNAe in maintaining RNA structure in the presence of genetic variation.

Metabolic Signatures of Tumor Responses to Doxorubicin Elucidated by Metabolic Profiling in Ovo.

BACKGROUND: Dysregulated cancer metabolism is associated with acquired resistance to chemotherapeutic treatment and contributes to the activation of cancer survival mechanisms. However, which metabolic pathways are activated following treatment often remains elusive. The combination of chicken embryo tumor models (in ovo) with metabolomics phenotyping could offer a robust platform for drug testing. Here, we assess the potential of this approach in the treatment of an in ovo triple negative breast cancer with doxorubicin. METHODS: MB-MDA-231 cells were grafted in ovo. The resulting tumors were then treated with doxorubicin or dimethyl sulfoxide (DMSO) for six days. Tumors were collected and analyzed using a global untargeted metabolomics and comprehensive lipidomics. RESULTS: We observed a significant suppression of tumor growth in the doxorubicin treated group. The metabolic profiles of doxorubicin and DMSO-treated tumors were clearly separated in a principle component analysis. Inhibition of glycolysis, nucleotide synthesis, and glycerophospholipid metabolism appear to be triggered by doxorubicin treatment, which could explain the observed suppressed tumor growth. In addition, metabolic cancer survival mechanisms could be supported by an acceleration of antioxidative pathways. CONCLUSIONS: Metabolomics in combination with in ovo tumor models provide a robust platform for drug testing to reveal tumor specific treatment targets such as the antioxidative tumor capacity.

Metabolic and proteomic signatures of hypoglycaemia in type 2 diabetes.

AIMS: To determine the biochemical changes that underlie hypoglycaemia in a healthy control group and in people with type 2 diabetes (T2D). MATERIALS AND METHODS: We report a hypoglycaemic clamp study in seven healthy controls and 10 people with T2D. Blood was withdrawn at four time points: at baseline after an overnight fast; after clamping to euglycaemia at 5 mmol/L; after clamping to hypoglycaemia at 2.8 mmol/L; and 24 hours later, after overnight fast. Deep molecular phenotyping using non-targeted metabolomics and the SomaLogic aptamer-based proteomics platform was performed on collected samples. RESULTS: A total of 955 metabolites and 1125 proteins were identified, with significant alterations in >90 molecules. A number of metabolites significantly increased during hypoglycaemia, but only cortisol, adenosine-3',5'-cyclic monophosphate (cyclic AMP), and pregnenolone sulphate, were independent of insulin. By contrast, identified protein changes were triggered by hypoglycaemia rather than insulin. The T2D group had significantly higher levels of fatty acids including 10-nonadecenoate, linolenate and dihomo-linoleate during hypoglycaemia compared with the control group. Molecules contributing to cardiovascular complications such as fatty-acid-binding protein-3 and pregnenolone sulphate were altered in the participants with T2D during hypoglycaemia. Almost all molecules returned to baseline at 24 hours. CONCLUSIONS: The present study provides a comprehensive description of molecular events that are triggered by insulin-induced hypoglycaemia. We identified deregulated pathways in T2D that may play a role in the pathophysiology of hypoglycaemia-induced cardiovascular complications.

Accelerated lipid catabolism and autophagy are cancer survival mechanisms under inhibited glutaminolysis.

Suppressing glutaminolysis does not always induce cancer cell death in glutamine dependent tumors because cells may switch to alternative energy sources. To reveal compensatory metabolic pathways, we investigated the metabolome-wide cellular response to inhibited glutaminolysis in cancer cells. Glutaminolysis inhibition with C.968 suppressed cell proliferation but was insufficient to induce cancer cell death. We found that lipid catabolism was activated as a compensation for glutaminolysis inhibition. Accelerated lipid catabolism, together with oxidative stress induced by glutaminolysis inhibition, triggered autophagy. Simultaneously inhibiting glutaminolysis and either beta oxidation with trimetazidine or autophagy with chloroquine both induced cancer cell death. Here we identified metabolic escape mechanisms contributing to cancer cell survival under treatment and we suggest potentially translational strategy for combined cancer therapy, given that chloroquine is an FDA approved drug. Our findings are first to show efficiency of combined inhibition of glutaminolysis and beta oxidation as potential anti-cancer strategy as well as add to the evidence that combined inhibition of glutaminolysis and autophagy may be effective in glutamine-addicted cancers.

Deep molecular phenotypes link complex disorders and physiological insult to CpG methylation.

Epigenetic regulation of cellular function provides a mechanism for rapid organismal adaptation to changes in health, lifestyle and environment. Associations of cytosine-guanine di-nucleotide (CpG) methylation with clinical endpoints that overlap with metabolic phenotypes suggest a regulatory role for these CpG sites in the body's response to disease or environmental stress. We previously identified 20 CpG sites in an epigenome-wide association study (EWAS) with metabolomics that were also associated in recent EWASs with diabetes-, obesity-, and smoking-related endpoints. To elucidate the molecular pathways that connect these potentially regulatory CpG sites to the associated disease or lifestyle factors, we conducted a multi-omics association study including 2474 mass-spectrometry-based metabolites in plasma, urine and saliva, 225 NMR-based lipid and metabolite measures in blood, 1124 blood-circulating proteins using aptamer technology, 113 plasma protein N-glycans and 60 IgG-glyans, using 359 samples from the multi-ethnic Qatar Metabolomics Study on Diabetes (QMDiab). We report 138 multi-omics associations at these CpG sites, including diabetes biomarkers at the diabetes-associated TXNIP locus, and smoking-specific metabolites and proteins at multiple smoking-associated loci, including AHRR. Mendelian randomization suggests a causal effect of metabolite levels on methylation of obesity-associated CpG sites, i.e. of glycerophospholipid PC(O-36: 5), glycine and a very low-density lipoprotein (VLDL-A) on the methylation of the obesity-associated CpG loci DHCR24, MYO5C and CPT1A, respectively. Taken together, our study suggests that multi-omics-associated CpG methylation can provide functional read-outs for the underlying regulatory response mechanisms to disease or environmental insults.

Nesting of colon and ovarian cancer cells in the endothelial niche is associated with alterations in glycan and lipid metabolism.

The metabolic phenotype of a cancer cell is determined by its genetic makeup and microenvironment, which dynamically modulates the tumor landscape. The endothelial cells provide both a promoting and protective microenvironment - a niche for cancer cells. Although metabolic alterations associated with cancer and its progression have been fairly defined, there is a significant gap in our understanding of cancer metabolism in context of its microenvironment. We deployed an in vitro co-culture system based on direct contact of cancer cells with endothelial cells (E4+EC), mimicking the tumor microenvironment. Metabolism of colon (HTC15 and HTC116) and ovarian (OVCAR3 and SKOV3) cancer cell lines was profiled with non-targeted metabolic approaches at different time points in the first 48 hours after co-culture was established. We found significant, coherent and non-cell line specific changes in fatty acids, glycerophospholipids and carbohydrates over time, induced by endothelial cell contact. The metabolic patterns pinpoint alterations in hexosamine biosynthetic pathway, glycosylation and lipid metabolism as crucial for cancer - endothelial cells interaction. We demonstrated that "Warburg effect" is not modulated in the initial stage of nesting of cancer cell in the endothelial niche. Our study provides novel insight into cancer cell metabolism in the context of the endothelial microenvironment.

Metabolic signatures differentiate ovarian from colon cancer cell lines.

BACKGROUND: In this era of precision medicine, the deep and comprehensive characterization of tumor phenotypes will lead to therapeutic strategies beyond classical factors such as primary sites or anatomical staging. Recently, "-omics" approached have enlightened our knowledge of tumor biology. Such approaches have been extensively implemented in order to provide biomarkers for monitoring of the disease as well as to improve readouts of therapeutic impact. The application of metabolomics to the study of cancer is especially beneficial, since it reflects the biochemical consequences of many cancer type-specific pathophysiological processes. Here, we characterize metabolic profiles of colon and ovarian cancer cell lines to provide broader insight into differentiating metabolic processes for prospective drug development and clinical screening. METHODS: We applied non-targeted metabolomics-based mass spectroscopy combined with ultrahigh-performance liquid chromatography and gas chromatography for the metabolic phenotyping of four cancer cell lines: two from colon cancer (HCT15, HCT116) and two from ovarian cancer (OVCAR3, SKOV3). We used the MetaP server for statistical data analysis. RESULTS: A total of 225 metabolites were detected in all four cell lines; 67 of these molecules significantly discriminated colon cancer from ovarian cancer cells. Metabolic signatures revealed in our study suggest elevated tricarboxylic acid cycle and lipid metabolism in ovarian cancer cell lines, as well as increased ß-oxidation and urea cycle metabolism in colon cancer cell lines. CONCLUSIONS: Our study provides a panel of distinct metabolic fingerprints between colon and ovarian cancer cell lines. These may serve as potential drug targets, and now can be evaluated further in primary cells, biofluids, and tissue samples for biomarker purposes.

Metabolomics in cell culture--a strategy to study crucial metabolic pathways in cancer development and the response to treatment.

Metabolomics is a comprehensive tool for monitoring processes within biological systems. Thus, metabolomics may be widely applied to the determination of diagnostic biomarkers for certain diseases or treatment outcomes. There is significant potential for metabolomics to be implemented in cancer research because cancer may modify metabolic pathways in the whole organism. However, not all biological questions can be answered solely by the examination of small molecule composition in biofluids; in particular, the study of cellular processes or preclinical drug testing requires ex vivo models. The major objective of this review was to summarise the current achievement in the field of metabolomics in cancer cell culture-focusing on the metabolic pathways regulated in different cancer cell lines-and progress that has been made in the area of drug screening and development by the implementation of metabolomics in cell lines.

Release of lysophospholipid 'find-me' signals during apoptosis requires the ATP-binding cassette transporter A1.

Efficient engulfment of apoptotic cells is essential in multi-cellular organisms in order to prevent inflammatory responses. Apoptotic cells secure this process by releasing 'find-me' signals for the attraction of phagocytes. A major 'find-me' signal liberated from apoptotic cells is lysophosphatidylcholine (LPC). So far, however, the mechanisms underlying LPC release are poorly understood. In this study, we demonstrate that pharmacological inhibition and RNAi-mediated knock-down of the lipid transporter ABCA1 in apoptotic cells completely abolished phagocyte attraction. Moreover, ectopic expression of ABCA1 significantly enhanced monocyte migration to supernatants of apoptotic cells. Hence, ABCA1 represents a novel regulator of LPC release during apoptosis.

Metabolic signatures in apoptotic human cancer cell lines.

Cancer cells have several specific metabolic features, which have been explored for targeted therapies. Agents that promote apoptosis in tumors are currently considered as a powerful tool for cancer therapeutics. The present study aimed to design a fast, reliable and robust system for metabolite measurements in cells lines to observe impact of apoptosis on the metabolome. For that purpose the NBS (newborn screen) mass spectrometry-based metabolomics assay was adapted for cell culture approach. In HEK 293 and in cancer cell lines HepG2, PC3, and MCF7 we searched for metabolic biomarkers of apoptosis differing from that of necrosis. Already nontreated cell lines revealed distinct concentrations of metabolites. Several metabolites indicative for apoptotic processes in cell culture including aspartate, glutamate, methionine, alanine, glycine, propionyl carnitine (C3-carnitine), and malonyl carnitine (C3DC-carnitine) were observed. In some cell lines metabolite changes were visible as early as 4 h after apoptosis induction and preceeding the detection by caspase 3/7 assay. We demonstrated for the first time that the metabolomic signatures might be used in the tests of efficacy of agents causing apoptosis in cell culture. These signatures could be obtained in fast high-throughput screening.

Improved in vivo gene transfer into tumor tissue by stabilization of pseudodendritic oligoethylenimine-based polyplexes.

BACKGROUND: HD O is a low molecular weight pseudodendrimer containing oligoethylenimine and degradable hexanediol diacrylate diesters. DNA polyplexes display encouraging gene transfer efficiency in vitro and in vivo but also a limited stability under physiological conditions. This limitation must be overcome for further development into more sophisticated formulations. METHODS: HD O polyplexes were laterally stabilized by crosslinking surface amines via bifunctional crosslinkers, bioreducible dithiobis(succimidyl propionate) (DSP) or the nonreducible analog disuccinimidyl suberate (DSS). Optionally, in a subsequent step, the targeting ligand transferrin (Tf) was attached to DSP-linked HD O polyplexes via Schiff base formation between HD O amino groups and Tf aldehyde groups, which were introduced into Tf by periodate oxidation of the glycosylation sites. RESULTS: Crosslinked DNA polyplexes showed an increased stability against exchange reaction by salt or heparin. Disulfide bond containing DSP-linked polyplexes were susceptible to reducing conditions. These polyplexes displayed the highest gene expression levels in vitro and in vivo (upon intratumoral application in mice), and these were significantly elevated and prolonged over standard or DSS-stabilized HD O formulations. DSP-stabilized HD O polyplexes with or without Tf coating were well-tolerated after intravenous application. High gene expression levels were found in tumor tissue, with negligible gene expression in any other organ. CONCLUSIONS: Lateral stabilization of HD O polyplexes with DSP crosslinker enhanced gene transfer efficacy and was essential for the incorporation of a ligand (Tf) into a stable particle formulation.

Polymer-based non-viral gene delivery as a concept for the treatment of cancer.

Gene therapy has become a promising technique for the treatment of cancer. Nevertheless, the success of gene therapy depends on the effectiveness of the vector. The challenge of a gene carrier is to deliver exogenous DNA from the site of administration into the nucleus of the appropriate target cell. Polymer-based vectors are biologically safe, have low production costs and are efficient tools for gene therapy. Although non-degradable polyplexes exhibit high gene expression levels, their application potential is limited due to their inability to be effectively eliminated, which results in cytotoxicity. The development of biodegradable polymers has allowed for high levels of transfection without cytotoxicity. For site-specific targeting of polyplexes, further modifications, such as incorporation of ligands, can be performed. Most expectations have been addressed to polyplexes architecture according it dynamic response with the microenvironment.

Oligoethylenimine-grafted polypropylenimine dendrimers as degradable and biocompatible synthetic vectors for gene delivery.

Several grafted polypropylenimine dendrimers were synthesized by modifying either polypropylenimine (PPI) dendrimer generation 2 (G2) or generation 3 (G3) via 1.6-hexandioldiacrylate with branched oligoethylenimine 800Da (OEI) or PPI dendrimer G2. The resulting derivatives were characterized ((1)H NMR, GPC) and their biophysical properties such as DNA condensing ability, colloidal stability and hydrodynamic diameters were determined. All grafted dendrimers were able to efficiently compact DNA to nanosized polyplexes (100-200 nm) and exhibited an increased colloidal stability as compared to their unmodified counterparts. In vitro, grafted dendrimers resulted in much higher transfection levels as compared to the unmodified ones displaying alongside a clear structure-activity relationship regarding their transfection/toxicity profile. Transfection levels of OEI-grafted dendrimers were the highest, being similar or even higher as compared to standard polyethylenimines (linear and branched), demonstrating that the incorporation of ethylenimine moieties is the key factor contributing to this boosted transfection efficiency. None of the compounds resulted in polymer-induced erythrocyte aggregation. Upon i.v. injection of OEI-grafted dendrimer polyplexes into tumor-bearing mice transgene expression was predominantly found in the (subcutaneous) tumors. Importantly, the tumor gene expression levels significantly increased with the higher dendrimer core generation.