Purine metabolism regulates DNA repair and therapy resistance in glioblastoma

Intratumoral genomic heterogeneity in glioblastoma (GBM) is a barrier to overcoming therapy resistance. Treatments that are effective independent of genotype are urgently needed. By correlating intracellular metabolite levels with radiation resistance across dozens of genomically-distinct models of GBM, we find that purine metabolites, especially guanylates, strongly correlate with radiation resistance. Inhibiting GTP synthesis radiosensitizes GBM cells and patient-derived neurospheres by impairing DNA repair. Likewise, administration of exogenous purine nucleosides protects sensitive GBM models from radiation by promoting DNA repair. Neither modulating pyrimidine metabolism nor purine salvage has similar effects. An FDA-approved inhibitor of GTP synthesis potentiates the effects of radiation in flank and orthotopic patient-derived xenograft models of GBM. High expression of the rate-limiting enzyme of de novo GTP synthesis is associated with shorter survival in GBM patients. These findings indicate that inhibiting purine synthesis may be a promising strategy to overcome therapy resistance in this genomically heterogeneous disease.

Targeting genotype-independent abnormalities may overcome therapy resistance in glioblastoma despite intratumoral genomic heterogeneity. Here, the authors show that glioblastoma radiation resistance is promoted by purine metabolism and can be overcome by inhibitors of purine synthesis.

A simple method for detecting oncofetal chondroitin sulfate glycosaminoglycans in bladder cancer urine

Proteoglycans in bladder tumors are modified with a distinct oncofetal chondroitin sulfate (ofCS) glycosaminoglycan that is normally restricted to placental trophoblast cells. This ofCS-modification can be detected in bladder tumors by the malarial VAR2CSA protein, which in malaria pathogenesis mediates adherence of parasite-infected erythrocytes within the placenta. In bladder cancer, proteoglycans are constantly shed into the urine, and therefore have the potential to be used for detection of disease. In this study we investigated whether recombinant VAR2CSA (rVAR2) protein could be used to detect ofCS-modified proteoglycans (ofCSPGs) in the urine of bladder cancer patients as an indication of disease presence. We show that ofCSPGs in bladder cancer urine can be immobilized on cationic nitrocellulose membranes and subsequently probed for ofCS content by rVAR2 protein in a custom-made dot-blot assay. Patients with high-grade bladder tumors displayed a marked increase in urinary ofCSPGs as compared to healthy individuals. Urine ofCSPGs decreased significantly after complete tumor resection compared to matched urine collected preoperatively from patients with bladder cancer. Moreover, ofCSPGs in urine correlated with tumor size of bladder cancer patients. These findings demonstrate that rVAR2 can be utilized in a simple biochemical assay to detect cancer-specific ofCS-modifications in the urine of bladder cancer patients, which may be further developed as a noninvasive approach to detect and monitor the disease.

Applying an immersive tutorial in virtual reality to learning a new technique

OBJECTIVE

The medical world is continuously evolving, with techniques being created or improved almost daily. Immersive virtual reality (VR) is a technology that could be harnessed to develop tools that meet the educational challenges of this changing environment. We previously described the immersive tutorial, a 3D video (filmed from the first-person point of view), displayed on a VR application. This tool offers access to supplementary educational data in addition to the video. Here we attempt to assess improvement in learning a technique using this new educational format.

MATERIAL AND METHODS

We selected a single neurosurgical technique for the study: external ventricular drainage. We wrote a technical note describing this procedure and produced the corresponding immersive tutorial. We conducted a prospective randomized comparative study with students. All participants read the technical note, and one group used the immersive tutorial as a teaching supplement. The students completed a multiple-choice questionnaire immediately after the training and again at six months.

RESULTS

One hundred seventy-six fourth-year medical students participated in the study; 173 were included in assessing the immediate learning outcomes and 72 were included at the six-month follow-up. The VR group demonstrated significantly better short-term results than the control group (P=0.01). The same trend was seen at six months.

CONCLUSION

To our knowledge, this study presents one of the largest cohorts for VR. The use of the immersive tutorial could enable a large number of healthcare professionals to be trained without the need for expensive equipment.

Exercise-Mediated Lowering of Glutamine Availability Suppresses Tumor Growth and Attenuates Muscle Wasting

Glutamine is a central nutrient for many cancers, contributing to the generation of building blocks and energy-promoting signaling necessary for neoplastic proliferation. In this study, we hypothesized that lowering systemic glutamine levels by exercise may starve tumors, thereby contributing to the inhibitory effect of exercise on tumor growth. We demonstrate that limiting glutamine availability, either pharmacologically or physiologically by voluntary wheel running, significantly attenuated the growth of two syngeneic murine tumor models of breast cancer and lung cancer, respectively, and decreased markers of atrophic signaling in muscles from tumor-bearing mice. In continuation, wheel running completely abolished tumor-induced loss of weight and lean body mass, independently of the effect of wheel running on tumor growth. Moreover, wheel running abolished tumor-induced upregulation of muscular glutamine transporters and myostatin signaling. In conclusion, our data suggest that voluntary wheel running preserves muscle mass by counteracting muscular glutamine release and tumor-induced atrophic signaling.

Pan-cancer analysis of the metabolic reaction network

Metabolic reprogramming is considered a hallmark of malignant transformation. However, it is not clear whether the network of metabolic reactions expressed by cancers of different origin differ from each other or from normal human tissues. In this study, we reconstructed functional and connected genome-scale metabolic models for 917 primary tumor samples across 13 types based on the probability of expression for 3765 reference metabolic genes in the sample. This network-centric approach revealed that tumor metabolic networks are largely similar in terms of accounted reactions, despite diversity in the expression of the associated genes. On average, each network contained 4721 reactions, of which 74% were core reactions (present in >95% of all models). Whilst 99.3% of the core reactions were classified as housekeeping also in normal tissues, we identified reactions catalyzed by ARG2, RHAG, SLC6 and SLC16 family gene members, and PTGS1 and PTGS2 as core exclusively in cancer. These findings were subsequently replicated in an independent validation set of 3388 genome-scale metabolic models. The remaining 26% of the reactions were contextual reactions. Their inclusion was dependent in one case (GLS2) on the absence of TP53 mutations and in 94.6% of cases on differences in cancer types. This dependency largely resembled differences in expression patterns in the corresponding normal tissues, with some exceptions like the presence of the NANP-encoded reaction in tumors not from the female reproductive system or of the SLC5A9-encoded reaction in kidney-pancreatic-colorectal tumors. In conclusion, tumors expressed a metabolic network virtually overlapping the matched normal tissues, raising the possibility that metabolic reprogramming simply reflects cancer cell plasticity to adapt to varying conditions thanks to redundancy and complexity of the underlying metabolic networks. At the same time, the here uncovered exceptions represent a resource to identify selective liabilities of tumor metabolism.

Plasma Glycosaminoglycans as Diagnostic and Prognostic Biomarkers in Surgically Treated Renal Cell Carcinoma

BACKGROUND

Plasma glycosaminoglycan (GAG) measurements, when aggregated into diagnostic scores, accurately distinguish metastatic clear-cell renal cell carcinoma (RCC) from healthy samples and correlate with prognosis. However, it is unknown if GAG scores can detect RCC in earlier stages or if they correlate with prognosis after surgery.

OBJECTIVE

To explore the sensitivity and specificity of plasma GAGs for detection of early-stage RCC and prediction of recurrence and death after RCC surgery.

DESIGN, SETTING, AND PARTICIPANTS

This was a retrospective case-control study consisting of a consecutive series of 175 RCC patients surgically treated between May 2011 and February 2014 and 19 healthy controls.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Plasma GAGs in preoperative and postoperative RCC and healthy samples were measured using capillary electrophoresis with laser-induced fluorescence in a single blinded laboratory. A discovery set was first analyzed to update the historical GAG score. The sensitivity of the new GAG score for RCC detection versus healthy subjects was validated using the remaining samples. The correlation of the new GAG score to histopathologic variables, overall survival, and recurrence-free survival was evaluated using nonparametric and log-rank tests and multivariable Cox regression analyses.

RESULTS AND LIMITATIONS

The RCC cohort included 94 stage I, 58 stage II-III, and 22 stage IV cases. In the first discovery set (n=67), the new GAG score distinguished RCC from healthy samples with an area under the receiver operating characteristic curve (AUC) of 0.999. In the validation set (n=108), the GAG score achieved an AUC of 0.991, with 93.5% sensitivity. GAG scores were elevated in RCC compared to healthy samples, irrespective of and uncorrelated to stage, grade, histology, age, or gender. The total chondroitin sulfate concentration was an independent prognostic factor for both overall and recurrence-free survival (hazard ratios 1.51 and 1.25) with high concordance when combined with variables available at pathologic diagnosis (C-index 0.926 and 0.849) or preoperatively (C-index 0.846 and 0.736). Limitations of the study include its retrospective nature and moderate variability in GAG laboratory measurements.

CONCLUSIONS

Plasma GAGs are highly sensitive diagnostic and prognostic biomarkers in surgically treated RCC independent of stage, grade, or histology. Prospective validation studies on GAG scores for early detection, prediction, and surveillance for RCC recurrence are thus warranted.

PATIENT SUMMARY

In this study, we examined if a new molecular blood test can detect renal cell carcinoma in the early stages and predict if the cancer might relapse after surgery. The trial is registered on ClinicalTrial.gov as NCT03471897.

Recon3D enables a three-dimensional view of gene variation in human metabolism

Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism. Recon3D is available at http://vmh.life.

Exploiting off-targeting in guide-RNAs for CRISPR systems for simultaneous editing of multiple genes

Bioinformatics tools to design guide-RNAs (gRNAs) in Clustered Regularly Interspaced Short Palindromic Repeats systems mostly focused on minimizing off-targeting to enhance efficacy of genome editing. However, there are circumstances in which off-targeting might be desirable to target multiple genes simultaneously with a single gRNA. We termed these gRNAs as promiscuous gRNAs. Here, we present a computational workflow to identify promiscuous gRNAs that putatively bind to the region of interest for a defined list of genes in a genome. We experimentally validated two promiscuous gRNA for gene deletion, one targeting FAA1 and FAA4 and one targeting PLB1 and PLB2, thus demonstrating that multiplexed genome editing through design of promiscuous gRNA can be performed in a time and cost-effective manner.

Prognostic Value of Plasma and Urine Glycosaminoglycan Scores in Clear Cell Renal Cell Carcinoma

BACKGROUND

The prognosis of metastatic clear cell renal cell carcinoma (ccRCC) vastly improved since the introduction of antiangiogenic-targeted therapy. However, it is still unclear which biological processes underlie ccRCC aggressiveness and affect prognosis. Here, we checked whether a recently discovered systems biomarker based on plasmatic or urinary measurements of glycosaminoglycans (GAGs) aggregated into diagnostic scores correlated with ccRCC prognosis.

METHODS

Thirty-one patients with a diagnosis of ccRCC (23 metastatic) were prospectively enrolled, and their urine and plasma biomarker scores were correlated to progression-free survival (PFS) and overall survival (OS) as either a dichotomous ("Low" vs. "High") or a continuous variable in a multivariate survival analysis.

RESULTS

The survival difference between "High"- vs. "Low"-scored patients was significant in the case of urine scores (2-year PFS rate = 53.3 vs. 100%, p = 3 × 10-4 and 2-year OS rate = 73.3 vs. 100%, p = 0.0078) and in the case of OS for plasma scores (2-year PFS rate = 60 vs. 84%, p = 0.0591 and 2-year OS rate = 66.7 vs. 90%, p = 0.0206). In multivariate analysis, the urine biomarker score as a continuous variable was an independent predictor of PFS [hazard ratio (HR): 4.62, 95% CI: 1.66-12.83, p = 0.003] and OS (HR: 10.13, 95% CI: 1.80-57.04, p = 0.009).

CONCLUSION

This is the first report on an association between plasma or urine GAG scores and the prognosis of ccRCC patients. Prospective trials validating the prognostic and predictive role of this novel systems biomarker are warranted.

Systematic analysis of overall survival and interactions between tumor mutations and drug treatment

BACKGROUND

Few exceptional responses in cancer treatment were attributed to a genetic predisposition of the tumor.

METHODS

We analyzed a cohort of 3105 patients from 12 different cancer types and systematically sought the existence of a correlation between overall survival and the interaction of 21 antineoplastic treatments with 6 tumor mutations.

RESULTS

We identified a single significant correlation resulting in increased overall survival from temozolomide in lower-grade glioma with IDH1 R132H mutations. The trend could not be attributed to either the treatment or the mutation alone. Univariate and multivariate Cox regression demonstrated that this interaction stood as an independent prognostic predictor of survival.

CONCLUSION

Our results suggest infrequent instances of exceptional responses ascribable to tumor genomics yet corroborate the existence of an interaction of temozolomide with IDH1 mutations in lower-grade glioma.

In search for symmetries in the metabolism of cancer

Even though aerobic glycolysis, or the Warburg effect, is arguably the most common trait of metabolic reprogramming in cancer, it is unobserved in certain tumor types. Systems biology advocates a global view on metabolism to dissect which traits are consistently reprogrammed in cancer, and hence likely to constitute an obligate step for the evolution of cancer cells. We refer to such traits as symmetric. Here, we review early systems biology studies that attempted to reveal symmetric traits in the metabolic reprogramming of cancer, discuss the symmetry of reprogramming of nucleotide metabolism, and outline the current limitations that, if unlocked, could elucidate whether symmetries in cancer metabolism may be claimed.

Flux balance analysis predicts essential genes in clear cell renal cell carcinoma metabolism

Flux balance analysis is the only modelling approach that is capable of producing genome-wide predictions of gene essentiality that may aid to unveil metabolic liabilities in cancer. Nevertheless, a systemic validation of gene essentiality predictions by flux balance analysis is currently missing. Here, we critically evaluated the accuracy of flux balance analysis in two cancer types, clear cell renal cell carcinoma (ccRCC) and prostate adenocarcinoma, by comparison with large-scale experiments of gene essentiality in vitro. We found that in ccRCC, but not in prostate adenocarcinoma, flux balance analysis could predict essential metabolic genes beyond random expectation. Five of the identified metabolic genes, AGPAT6, GALT, GCLC, GSS, and RRM2B, were predicted to be dispensable in normal cell metabolism. Hence, targeting these genes may selectively prevent ccRCC growth. Based on our analysis, we discuss the benefits and limitations of flux balance analysis for gene essentiality predictions in cancer metabolism, and its use for exposing metabolic liabilities in ccRCC, whose emergent metabolic network enforces outstanding anabolic requirements for cellular proliferation.

JRC GMO-Matrix: a web application to support Genetically Modified Organisms detection strategies

Background

The polymerase chain reaction (PCR) is the current state of the art technique for DNA-based detection of Genetically Modified Organisms (GMOs). A typical control strategy starts by analyzing a sample for the presence of target sequences (GM-elements) known to be present in many GMOs. Positive findings from this “screening” are then confirmed with GM (event) specific test methods. A reliable knowledge of which GMOs are detected by combinations of GM-detection methods is thus crucial to minimize the verification efforts.

Description

In this article, we describe a novel platform that links the information of two unique databases built and maintained by the European Union Reference Laboratory for Genetically Modified Food and Feed (EU-RL GMFF) at the Joint Research Centre (JRC) of the European Commission, one containing the sequence information of known GM-events and the other validated PCR-based detection and identification methods. The new platform compiles in silico determinations of the detection of a wide range of GMOs by the available detection methods using existing scripts that simulate PCR amplification and, when present, probe binding. The correctness of the information has been verified by comparing the in silico conclusions to experimental results for a subset of forty-nine GM events and six methods.

Conclusions

The JRC GMO-Matrix is unique for its reliance on DNA sequence data and its flexibility in integrating novel GMOs and new detection methods. Users can mine the database using a set of web interfaces that thus provide a valuable support to GMO control laboratories in planning and evaluating their GMO screening strategies. The platform is accessible at http://gmo-crl.jrc.ec.europa.eu/jrcgmomatrix/.

Kiwi: a tool for integration and visualization of network topology and gene-set analysis

BACKGROUND

The analysis of high-throughput data in biology is aided by integrative approaches such as gene-set analysis. Gene-sets can represent well-defined biological entities (e.g. metabolites) that interact in networks (e.g. metabolic networks), to exert their function within the cell. Data interpretation can benefit from incorporating the underlying network, but there are currently no optimal methods that link gene-set analysis and network structures.

RESULTS

Here we present Kiwi, a new tool that processes output data from gene-set analysis and integrates them with a network structure such that the inherent connectivity between gene-sets, i.e. not simply the gene overlap, becomes apparent. In two case studies, we demonstrate that standard gene-set analysis points at metabolites regulated in the interrogated condition. Nevertheless, only the integration of the interactions between these metabolites provides an extra layer of information that highlights how they are tightly connected in the metabolic network.

CONCLUSIONS

Kiwi is a tool that enhances interpretability of high-throughput data. It allows the users not only to discover a list of significant entities or processes as in gene-set analysis, but also to visualize whether these entities or processes are isolated or connected by means of their biological interaction. Kiwi is available as a Python package at http://www.sysbio.se/kiwi and an online tool in the BioMet Toolbox at http://www.biomet-toolbox.org.

Characterization and sub-cellular localization of SS1R, SS2R, and SS5R in human late-stage prostate cancer cells: effect of mono- and bi-specific somatostatin analogs on cell growth

Somatostatin (SST) and SST receptors (SS1R, SS2R, SS3R, SS4R and SS5R) appear to play a significant role in the progression of human prostate cancer (PCa), which is associated with heterogeneity of SSRs expression and specific cell localization as we already demonstrated in the LNCaP cell line, an in vitro model of human androgen-dependent PCa. In this study, PC-3 and DU-145 human castration-resistant PCa cells were found to express all SSRs, while LNCaP expressed all but SS4R. A 48-h treatment with BIM-23244 (SS2R/SS5R) or BIM-23926 (SS1R) SST analogs was more effective in inhibiting cell proliferation, compared to BIM-23120 (SS2R), BIM-23206 (SS5R) and BIM-23704 (SS1R/SS2R). BIM-23926 (SS1R) treatment increased the amount of p21 and decreased phosphorylated (p) ERK1/2. BIM-23244 (SS2R/SS5R) led to p21 increment only in PC-3 cells, and to pERK1/2 reduction in both cell lines. SS1R/SS2R and SS2R/SS5R receptor dimers were natively present on cell membrane and their amount was increased by BIM-23704 (SS1R/SS2R) or BIM-23244 (SS2R/SS5R) treatment, respectively. SS1R, SS2R and SS5R were differently distributed among nuclear, lysosomal and microsomal compartment, according to their different recycling dynamics. These results show that, in PC-3, DU-145 and LNCaP cells, activation of SS1R and SS2R/SS5R leads to relevant antiproliferative effects.

Preoperative normalization of cortisol levels in Cushing's disease after medical treatment: consequences for somatostatin and dopamine receptor subtype expression and in vitro response to somatostatin analogs and dopamine agonists

CONTEXT

Corticotroph pituitary adenomas often highly express the dopamine 2 receptor (D₂R) and somatostatin receptor subtype 5 (sst₅). The sst₂ expression is relatively low, likely resulting from downregulating effects of high cortisol levels. This may explain why the sst₂-preferring somatostatin analog octreotide, compared with the multi-receptor-targeting somatostatin analog pasireotide, is generally ineffective in Cushing's disease.

OBJECTIVE

Our objective was to compare sst and D₂R expression levels between adenomas from patients with elevated and normalized preoperative urinary free cortisol excretion.

PATIENTS AND DESIGN

Corticotroph adenoma tissue was examined from patients from group 1 (n = 22; elevated preoperative urinary free cortisol) and group 2 (n = 11; mean duration of preoperative normocortisolism 10 weeks). Somatotroph adenoma tissue from 10 acromegalic patients was examined to compare receptor expression profiles.

MAIN OUTCOME MEASURES

We evaluated receptor mRNA and protein expression levels and effects of octreotide, pasireotide, and cabergoline on ACTH secretion by cultured human corticotroph adenoma cells.

RESULTS

The sst₂ mRNA expression in group 2 was 10-fold higher than in group 1 (P < .01), even comparable to that in somatotroph adenomas. There were no statistically significant differences in sst₅ and D₂R mRNA expression or in sst₂, sst₅, and D₂R protein expression between both groups of corticotroph adenomas. In responders, octreotide (n = 2 out of 4; -30.5% ± 10.4%) was less potent than pasireotide (n = 5 out of 6; -47.0% ± 4.2%) and cabergoline (n = 3 out of 4; -41.9% ± 3.1%) with respect to inhibition of ACTH secretion by adenomas from group 2.

CONCLUSIONS

After achieving normocortisolism induced by medical therapy, cortisol-mediated sst₂ downregulation on corticotroph adenomas appears to be a reversible process at the mRNA but not at the protein level. Octreotide remains less potent than pasireotide and cabergoline with respect to in vitro inhibition of ACTH secretion. Whether sustained normocortisolism induced by medical therapy induces re-expression of functional sst₂ protein in corticotroph adenomas and whether this increases the ACTH-lowering potency of octreotide remains to be established.

Genome-scale modeling of human metabolism - a systems biology approach

Altered metabolism is linked to the appearance of various human diseases and a better understanding of disease-associated metabolic changes may lead to the identification of novel prognostic biomarkers and the development of new therapies. Genome-scale metabolic models (GEMs) have been employed for studying human metabolism in a systematic manner, as well as for understanding complex human diseases. In the past decade, such metabolic models - one of the fundamental aspects of systems biology - have started contributing to the understanding of the mechanistic relationship between genotype and phenotype. In this review, we focus on the construction of the Human Metabolic Reaction database, the generation of healthy cell type- and cancer-specific GEMs using different procedures, and the potential applications of these developments in the study of human metabolism and in the identification of metabolic changes associated with various disorders. We further examine how in silico genome-scale reconstructions can be employed to simulate metabolic flux distributions and how high-throughput omics data can be analyzed in a context-dependent fashion. Insights yielded from this mechanistic modeling approach can be used for identifying new therapeutic agents and drug targets as well as for the discovery of novel biomarkers. Finally, recent advancements in genome-scale modeling and the future challenge of developing a model of whole-body metabolism are presented. The emergent contribution of GEMs to personalized and translational medicine is also discussed.

Immunohistochemical localization and quantitative expression of somatostatin receptors in normal human spleen and thymus: Implications for the in vivo visualization during somatostatin receptor scintigraphy

BACKGROUND

[111In-DTPA-D-Phe1]-octreotide scintigraphy allows the visualization of SRIF receptor (SSR)-expressing tumors, including thymic tumors, and normal tissues. While the spleen is clearly visualized, the thymus is not depicted, although both contain SSR.

AIM

We evaluated whether the heterogeneity, the type, and the amount of SSR might explain this contrasting finding.

MATERIALS, METHODS, AND RESULTS

By ligand-binding the number of [125I-Tyr11]-SRIF- 14 binding sites resulted comparable between the two tissues, whereas the number of [125I-Tyr3]-octreotide sites was significantly higher in the spleen (p<0.001). Quantitative RTPCR showed a significantly higher expression of sst2A mRNA in the spleen, whereas a significantly higher expression of SRIF and sst3 in the thymus. The highest density of sst2A in the spleen is in line with the in vivo uptake of [111In-DTPA-D-Phe1]- octreotide, which is considered a sst2-preferring ligand. The specificity is confirmed by the evidence that in vivo [111In-DTPA- D-Phe1]-octreotide uptake can be abolished during chronic administration of "cold" octreotide. Immunohistochemistry confirmed a preferential expression of sst2A on microenvironmental cells and of sst3 on lymphoid cells.

CONCLUSIONS

The heterogeneity of SSR expression and the higher SRIF content explain the lack of thymus visualization during scintigraphy, whereas thymic tumors, which do not express SRIF, are visualized. Apart from the affinity of the radioligand, also the efficacy of the internalization is crucial for the in vivo uptake, and both heterogeneity and SRIF content affect this process. These observations might have an important impact when interpretating in vivo visualization of SSR-positive lesions, and when treatment with novel SRIF analogs is considered.