Proximity Mapping of CCP6 Reveals Its Association with Centrosome Organization and Cilium Assembly.

The cytosolic carboxypeptidase 6 (CCP6) catalyzes the deglutamylation of polyglutamate side chains, a post-translational modification that affects proteins such as tubulins or nucleosome assembly proteins. CCP6 is involved in several cell processes, such as spermatogenesis, antiviral activity, embryonic development, and pathologies like renal adenocarcinoma. In the present work, the cellular role of CCP6 has been assessed by BioID, a proximity labeling approach for mapping physiologically relevant protein-protein interactions (PPIs) and bait proximal proteins by mass spectrometry. We used HEK 293 cells stably expressing CCP6-BirA* to identify 37 putative interactors of this enzyme. This list of CCP6 proximal proteins displayed enrichment of proteins associated with the centrosome and centriolar satellites, indicating that CCP6 could be present in the pericentriolar material. In addition, we identified cilium assembly-related proteins as putative interactors of CCP6. In addition, the CCP6 proximal partner list included five proteins associated with the Joubert syndrome, a ciliopathy linked to defects in polyglutamylation. Using the proximity ligation assay (PLA), we show that PCM1, PIBF1, and NudC are true CCP6 physical interactors. Therefore, the BioID methodology confirms the location and possible functional role of CCP6 in centrosomes and centrioles, as well as in the formation and maintenance of primary cilia.

Correlation of MR-Based Metabolomics and Molecular Profiling in the Tumor Microenvironment of Temozolomide-Treated Orthotopic GL261 Glioblastoma in Mice.

The tumor microenvironment in glioblastoma (GB) is considered to be "cold", i.e., the fraction of cytotoxic T cells, for instance, is low. Instead, macrophages are the major immune cell population in GB, which stem either from tissue response (resident microglia) or recruitment of macrophages from the periphery, thereby undergoing tumor-dependent "imprinting" mechanisms by which macrophages can adapt a tumor-supportive phenotype. In this regard, it is important to describe the nature of macrophages associated with GB, in particular under therapy conditions using the gold standard chemotherapy drug temozolomide (TMZ). Here, we explored the suitability of combining information from in vivo magnetic resonance spectroscopic (MRS) approaches (metabolomics) with in vitro molecular analyses to assess therapy response and characterize macrophage populations in mouse GB using an isogenic GL261 model. For macrophage profiling, expression levels of matrix metalloproteinases (MMPs) and A disintegrin and metalloproteinases (ADAMs) were determined, since their gene products affect macrophage-tumor cell communication by extensive cleavage of immunomodulatory membrane proteins, such as PD-L1. In tumor mice with an overall therapy response, expression of genes encoding the proteases ADAM8, ADAM10, and ADAM17 was increased and might contribute to the immunosuppressive phenotype of GB and immune cells. In tumors responding to therapy, expression levels of ADAM8 were upregulated by TMZ, and higher levels of PD-L1 were correlated significantly. Using a CRISPR/Cas9 knockout of ADAM8 in GL261 cells, we demonstrated that soluble PD-L1 (sPD-L1) is only generated in the presence of ADAM8. Moreover, primary macrophages from WT and ADAM8-deficient mice showed ADAM8-dependent release of sPD-L1, independent of the macrophage polarization state. Since ADAM8 expression is induced in responding tumors and PD-L1 shedding is likely to decrease the anti-tumor activities of T-cells, we conclude that immunotherapy resistance is caused, at least in part, by the increased presence of proteases, such as ADAM8.

Conservation of Aging and Cancer Epigenetic Signatures across Human and Mouse.

Aging and cancer are two interrelated processes, with aging being a major risk factor for the development of cancer. Parallel epigenetic alterations have been described for both, although differences, especially within the DNA hypomethylation scenario, have also been recently reported. Although many of these observations arise from the use of mouse models, there is a lack of systematic comparisons of human and mouse epigenetic patterns in the context of disease. However, such comparisons are significant as they allow to establish the extent to which some of the observed similarities or differences arise from pre-existing species-specific epigenetic traits. Here, we have used reduced representation bisulfite sequencing to profile the brain methylomes of young and old, tumoral and nontumoral brain samples from human and mouse. We first characterized the baseline epigenomic patterns of the species and subsequently focused on the DNA methylation alterations associated with cancer and aging. Next, we described the functional genomic and epigenomic context associated with the alterations, and finally, we integrated our data to study interspecies DNA methylation levels at orthologous CpG sites. Globally, we found considerable differences between the characteristics of DNA methylation alterations in cancer and aging in both species. Moreover, we describe robust evidence for the conservation of the specific cancer and aging epigenomic signatures in human and mouse. Our observations point toward the preservation of the functional consequences of these alterations at multiple levels of genomic regulation. Finally, our analyses reveal a role for the genomic context in explaining disease- and species-specific epigenetic traits.

Metal-Free Radical Dendrimers as MRI Contrast Agents for Glioblastoma Diagnosis: Ex Vivo and In Vivo Approaches.

Simultaneously being a nonradiative and noninvasive technique makes magnetic resonance imaging (MRI) one of the highly required imaging approaches for the early diagnosis and follow-up of tumors, specifically for brain cancer. Paramagnetic gadolinium (Gd)-based contrast agents (CAs) are the most widely used ones in brain MRI acquisitions with special interest when assessing blood-brain barrier (BBB) integrity, a characteristic of high-grade tumors. However, alternatives to Gd-based contrast agents (CAs) are highly required to overcome their established toxicity. Organic radicals anchored on a dendrimer macromolecule surface (radical dendrimers) are promising alternatives since they also exhibit paramagnetic properties and can act as T1 CAs like Gd-based CAs while being organic species (mitigating concerns about toxic metal accumulation). Here, we studied the third generation of a water-soluble family of poly(phosphorhydrazone) radical dendrimers, with 48 PROXYL radical units anchored on their branches, exploring their potential of ex vivo and in vivo contrast enhancement in brain tumors (in particular, of immunocompetent, orthotopic GL261 murine glioblastoma (GB)). Remarkably, this radical species provides suitable contrast enhancement on murine GL261 GB tumors, which was comparable to that of commercial Gd-based CAs (at standard dose 0.1 mmol/kg), even at its 4 times lower administered dose (0.025 mmol/kg). Importantly, no signs of toxicity were detected in vivo. In addition, it showed a selective accumulation in brain tumor tissues, exhibiting longer retention within the tumor, which allows performing imaging acquisition over longer time frames (≥2.5 h) as opposed to Gd chelates. Finally, we observed high stability of the radicals in biological media, on the order of hours instead of minutes, characteristic of the isolated radicals. All of these features allow us to suggest that the G3-Tyr-PROXYL-ONa radical dendrimer could be a viable alternative to metal-based MRI contrast agents, particularly on MRI analysis of GB, representing, to the best of our knowledge, the first case of organic radical species used for this purpose and one of the very few examples of these types of radical species working as MRI CAs in vivo.

Anti-tumour immune response in GL261 glioblastoma generated by Temozolomide Immune-Enhancing Metronomic Schedule monitored with MRSI-based nosological images.

Glioblastomas (GB) are brain tumours with poor prognosis even after aggressive therapy. Improvements in both therapeutic and follow-up strategies are urgently needed. In previous work we described an oscillatory pattern of response to Temozolomide (TMZ) using a standard administration protocol, detected through MRSI-based machine learning approaches. In the present work, we have introduced the Immune-Enhancing Metronomic Schedule (IMS) with an every 6-d TMZ administration at 60 mg/kg and investigated the consistence of such oscillatory behaviour. A total of n = 17 GL261 GB tumour-bearing C57BL/6j mice were studied with MRI/MRSI every 2 d, and the oscillatory behaviour (6.2 ± 1.5 d period from the TMZ administration day) was confirmed during response. Furthermore, IMS-TMZ produced significant improvement in mice survival (22.5 ± 3.0 d for controls vs 135.8 ± 78.2 for TMZ-treated), outperforming standard TMZ treatment. Histopathological correlation was investigated in selected tumour samples (n = 6) analyzing control and responding fields. Significant differences were found for CD3+ cells (lymphocytes, 3.3 ± 2.5 vs 4.8 ± 2.9, respectively) and Iba-1 immunostained area (microglia/macrophages, 16.8% ± 9.7% and 21.9% ± 11.4%, respectively). Unexpectedly, during IMS-TMZ treatment, tumours from some mice (n = 6) fully regressed and remained undetectable without further treatment for 1 mo. These animals were considered "cured" and a GL261 re-challenge experiment performed, with no tumour reappearance in five out of six cases. Heterogeneous therapy response outcomes were detected in tumour-bearing mice, and a selected group was investigated (n = 3 non-responders, n = 6 relapsing tumours, n = 3 controls). PD-L1 content was found ca. 3-fold increased in the relapsing group when comparing with control and non-responding groups, suggesting that increased lymphocyte inhibition could be associated to IMS-TMZ failure. Overall, data suggest that host immune response has a relevant role in therapy response/escape in GL261 tumours under IMS-TMZ therapy. This is associated to changes in the metabolomics pattern, oscillating every 6 d, in agreement with immune cycle length, which is being sampled by MRSI-derived nosological images.

Anti-PD-1 Immunotherapy in Preclinical GL261 Glioblastoma: Influence of Therapeutic Parameters and Non-Invasive Response Biomarker Assessment with MRSI-Based Approaches.

Glioblastomas (GBs) are malignant brain tumours with poor prognosis even after aggressive therapy. Programmed cell death-1 (PD-1) immune checkpoint blockade is a promising strategy in many types of cancer, but its therapeutic effects in GB remain low and associated with immune infiltration. Previous work suggests that oscillations of magnetic resonance spectroscopic imaging (MRSI)-based response pattern with chemotherapy could act as a biomarker of efficient immune system attack onto GBs. The presence of such oscillations with other monotherapies such as anti-PD-1 would reinforce its monitoring potential. Here, we confirm that the oscillatory behaviour of the response biomarker is also detected in mice treated with anti PD-1 immunotherapy both in combination with temozolomide and as monotherapy. This indicates that the spectral pattern changes observed during therapy response are shared by different therapeutic strategies, provided the host immune system is elicited and able to productively attack tumour cells. Moreover, the participation of the immune system in response is also supported by the rate of cured animals observed with different therapeutic strategies (in the range of 50-100% depending on the treatment), which also held long-term immune memory against tumour cells re-challenge. Taken together, our findings open the way for a translational use of the MRSI-based biomarker in patient-tailored GB therapy, including immunotherapy, for which reliable non-invasive biomarkers are still missing.

Cancer metabolism in a snapshot: MRS(I).

The contribution of MRS(I) to the in vivo evaluation of cancer-metabolism-derived metrics, mostly since 2016, is reviewed here. Increased carbon consumption by tumour cells, which are highly glycolytic, is now being sampled by 13 C magnetic resonance spectroscopic imaging (MRSI) following the injection of hyperpolarized [1-13 C] pyruvate (Pyr). Hot-spots of, mostly, increased lactate dehydrogenase activity or flow between Pyr and lactate (Lac) have been seen with cancer progression in prostate (preclinical and in humans), brain and pancreas (both preclinical) tumours. Therapy response is usually signalled by decreased Lac/Pyr 13 C-labelled ratio with respect to untreated or non-responding tumour. For therapeutic agents inducing tumour hypoxia, the 13 C-labelled Lac/bicarbonate ratio may be a better metric than the Lac/Pyr ratio. 31 P MRSI may sample intracellular pH changes from brain tumours (acidification upon antiangiogenic treatment, basification at fast proliferation and relapse). The steady state tumour metabolome pattern is still in use for cancer evaluation. Metrics used for this range from quantification of single oncometabolites (such as 2-hydroxyglutarate in mutant IDH1 glial brain tumours) to selected metabolite ratios (such as total choline to N-acetylaspartate (plain ratio or CNI index)) or the whole 1 H MRSI(I) pattern through pattern recognition analysis. These approaches have been applied to address different questions such as tumour subtype definition, following/predicting the response to therapy or defining better resection or radiosurgery limits.

Brain metabolic pattern analysis using a magnetic resonance spectra classification software in experimental stroke.

BACKGROUND: Magnetic resonance spectroscopy (MRS) provides non-invasive information about the metabolic pattern of the brain parenchyma in vivo. The SpectraClassifier software performs MRS pattern-recognition by determining the spectral features (metabolites) which can be used objectively to classify spectra. Our aim was to develop an Infarct Evolution Classifier and a Brain Regions Classifier in a rat model of focal ischemic stroke using SpectraClassifier. RESULTS: A total of 164 single-voxel proton spectra obtained with a 7 Tesla magnet at an echo time of 12 ms from non-infarcted parenchyma, subventricular zones and infarcted parenchyma were analyzed with SpectraClassifier ( http://gabrmn.uab.es/?q=sc ). The spectra corresponded to Sprague-Dawley rats (healthy rats, n = 7) and stroke rats at day 1 post-stroke (acute phase, n = 6 rats) and at days 7 ± 1 post-stroke (subacute phase, n = 14). In the Infarct Evolution Classifier, spectral features contributed by lactate + mobile lipids (1.33 ppm), total creatine (3.05 ppm) and mobile lipids (0.85 ppm) distinguished among non-infarcted parenchyma (100% sensitivity and 100% specificity), acute phase of infarct (100% sensitivity and 95% specificity) and subacute phase of infarct (78% sensitivity and 100% specificity). In the Brain Regions Classifier, spectral features contributed by myoinositol (3.62 ppm) and total creatine (3.04/3.05 ppm) distinguished among infarcted parenchyma (100% sensitivity and 98% specificity), non-infarcted parenchyma (84% sensitivity and 84% specificity) and subventricular zones (76% sensitivity and 93% specificity). CONCLUSION: SpectraClassifier identified candidate biomarkers for infarct evolution (mobile lipids accumulation) and different brain regions (myoinositol content).

Metronomic treatment in immunocompetent preclinical GL261 glioblastoma: effects of cyclophosphamide and temozolomide.

Glioblastoma (GBM) causes poor survival in patients even when applying aggressive treatment. Temozolomide (TMZ) is the standard chemotherapeutic choice for GBM treatment, but resistance always ensues. In previous years, efforts have focused on new therapeutic regimens with conventional drugs to activate immune responses that may enhance tumor regression and prevent regrowth, for example the "metronomic" approaches. In metronomic scheduling studies, cyclophosphamide (CPA) in GL261 GBM growing subcutaneously in C57BL/6 mice was shown not only to activate antitumor CD8+ T-cell response, but also to induce long-term specific T-cell tumor memory. Accordingly, we have evaluated whether metronomic CPA or TMZ administration could increase survival in orthotopic GL261 in C57BL/6 mice, an immunocompetent model. Longitudinal in vivo studies with CPA (140 mg/kg) or TMZ (range 140-240 mg/kg) metronomic administration (every 6 days) were performed in tumor-bearing mice. Tumor evolution was monitored at 7 T with MRI (T2 -weighted, diffusion-weighted imaging) and MRSI-based nosological images of response to therapy. Obtained results demonstrated that both treatments resulted in increased survival (38.6 ± 21.0 days, n = 30) compared with control (19.4 ± 2.4 days, n = 18). Best results were obtained with 140 mg/kg TMZ (treated, 44.9 ± 29.0 days, n = 12, versus control, 19.3 ± 2.3 days, n = 12), achieving a longer survival rate than previous group work using three cycles of TMZ therapy at 60 mg/kg (33.9 ± 11.7 days, n = 38). Additional interesting findings were, first, clear edema appearance during chemotherapeutic treatment, second, the ability to apply the semi-supervised source analysis previously developed in our group for non-invasive TMZ therapy response monitoring to detect CPA-induced response, and third, the necropsy findings in mice cured from GBM after high TMZ cumulative dosage (980-1400 mg/kg), which demonstrated lymphoma incidence. In summary, every 6 day administration schedule of TMZ or CPA improves survival in orthotopic GL261 GBM with respect to controls or non-metronomic therapy, in partial agreement with previous work on subcutaneous GL261.

Development of a transplantable glioma tumour model from genetically engineered mice: MRI/MRS/MRSI characterisation.

The initial aim of this study was to generate a transplantable glial tumour model of low-intermediate grade by disaggregation of a spontaneous tumour mass from genetically engineered models (GEM). This should result in an increased tumour incidence in comparison to GEM animals. An anaplastic oligoastrocytoma (OA) tumour of World Health Organization (WHO) grade III was obtained from a female GEM mouse with the S100ß-v-erbB/inK4a-Arf (+/-) genotype maintained in the C57BL/6 background. The tumour tissue was disaggregated; tumour cells from it were grown in aggregates and stereotactically injected into C57BL/6 mice. Tumour development was followed using Magnetic Resonance Imaging (MRI), while changes in the metabolomics pattern of the masses were evaluated by Magnetic Resonance Spectroscopy/Spectroscopic Imaging (MRS/MRSI). Final tumour grade was evaluated by histopathological analysis. The total number of tumours generated from GEM cells from disaggregated tumour (CDT) was 67 with up to 100 % penetrance, as compared to 16 % in the local GEM model, with an average survival time of 66 ± 55 days, up to 4.3-fold significantly higher than the standard GL261 glioblastoma (GBM) tumour model. Tumours produced by transplantation of cells freshly obtained from disaggregated GEM tumour were diagnosed as WHO grade III anaplastic oligodendroglioma (ODG) and OA, while tumours produced from a previously frozen sample were diagnosed as WHO grade IV GBM. We successfully grew CDT and generated tumours from a grade III GEM glial tumour. Freezing and cell culture protocols produced progression to grade IV GBM, which makes the developed transplantable model qualify as potential secondary GBM model in mice.

Molecular imaging coupled to pattern recognition distinguishes response to temozolomide in preclinical glioblastoma.

Non-invasive monitoring of response to treatment of glioblastoma (GB) is nowadays carried out using MRI. MRS and MR spectroscopic imaging (MRSI) constitute promising tools for this undertaking. A temozolomide (TMZ) protocol was optimized for GL261 GB. Sixty-three mice were studied by MRI/MRS/MRSI. The spectroscopic information was used for the classification of control brain and untreated and responding GB, and validated against post-mortem immunostainings in selected animals. A classification system was developed, based on the MRSI-sampled metabolome of normal brain parenchyma, untreated and responding GB, with a 93% accuracy. Classification of an independent test set yielded a balanced error rate of 6% or less. Classifications correlated well both with tumor volume changes detected by MRI after two TMZ cycles and with the histopathological data: a significant decrease (p < 0.05) in the proliferation and mitotic rates and a 4.6-fold increase in the apoptotic rate. A surrogate response biomarker based on the linear combination of 12 spectral features has been found in the MRS/MRSI pattern of treated tumors, allowing the non-invasive classification of growing and responding GL261 GB. The methodology described can be applied to preclinical treatment efficacy studies to test new antitumoral drugs, and begets translational potential for early response detection in clinical studies.

A new ex vivo method to evaluate the performance of candidate MRI contrast agents: a proof-of-concept study.

BACKGROUND: Magnetic resonance imaging (MRI) plays an important role in tumor detection/diagnosis. The use of exogenous contrast agents (CAs) helps to improve the discrimination between lesion and neighbouring tissue, but most of the currently available CAs are non-specific. Assessing the performance of new, selective CAs requires exhaustive assays and large amounts of material. Accordingly, in a preliminary screening of new CAs, it is important to choose candidate compounds with good potential for in vivo efficiency. This screening method should reproduce as close as possible the in vivo environment. In this sense, a fast and reliable method to select the best candidate CAs for in vivo studies would minimize time and investment cost, and would benefit the development of better CAs. RESULTS: The post-mortem ex vivo relative contrast enhancement (RCE) was evaluated as a method to screen different types of CAs, including paramagnetic and superparamagnetic agents. In detail, sugar/gadolinium-loaded gold nanoparticles (Gd-GNPs) and iron nanoparticles (SPIONs) were tested. Our results indicate that the post-mortem ex vivo RCE of evaluated CAs, did not correlate well with their respective in vitro relaxivities. The results obtained with different Gd-GNPs suggest that the linker length of the sugar conjugate could modulate the interactions with cellular receptors and therefore the relaxivity value. A paramagnetic CA (GNP (E_2)), which performed best among a series of Gd-GNPs, was evaluated both ex vivo and in vivo. The ex vivo RCE was slightly worst than gadoterate meglumine (201.9 ± 9.3% versus 237 ± 14%, respectively), while the in vivo RCE, measured at the time-to-maximum enhancement for both compounds, pointed to GNP E_2 being a better CA in vivo than gadoterate meglumine. This is suggested to be related to the nanoparticule characteristics of the evaluated GNP. CONCLUSION: We have developed a simple, cost-effective relatively high-throughput method for selecting CAs for in vivo experiments. This method requires approximately 800 times less quantity of material than the amount used for in vivo administrations.

Platinum-Based Nanoformulations for Glioblastoma Treatment: The Resurgence of Platinum Drugs?

Current therapies for treating Glioblastoma (GB), and brain tumours in general, are inefficient and represent numerous challenges. In addition to surgical resection, chemotherapy and radiotherapy are presently used as standards of care. However, treated patients still face a dismal prognosis with a median survival below 15-18 months. Temozolomide (TMZ) is the main chemotherapeutic agent administered; however, intrinsic or acquired resistance to TMZ contributes to the limited efficacy of this drug. To circumvent the current drawbacks in GB treatment, a large number of classical and non-classical platinum complexes have been prepared and tested for anticancer activity, especially platinum (IV)-based prodrugs. Platinum complexes, used as alkylating agents in the anticancer chemotherapy of some malignancies, are though often associated with severe systemic toxicity (i.e., neurotoxicity), especially after long-term treatments. The objective of the current developments is to produce novel nanoformulations with improved lipophilicity and passive diffusion, promoting intracellular accumulation, while reducing toxicity and optimizing the concomitant treatment of chemo-/radiotherapy. Moreover, the blood-brain barrier (BBB) prevents the access of the drugs to the brain and accumulation in tumour cells, so it represents a key challenge for GB management. The development of novel nanomedicines with the ability to (i) encapsulate Pt-based drugs and pro-drugs, (ii) cross the BBB, and (iii) specifically target cancer cells represents a promising approach to increase the therapeutic effect of the anticancer drugs and reduce undesired side effects. In this review, a critical discussion is presented concerning different families of nanoparticles able to encapsulate platinum anticancer drugs and their application for GB treatment, emphasizing their potential for increasing the effectiveness of platinum-based drugs.

Tracking Therapy Response in Glioblastoma Using 1D Convolutional Neural Networks.

BACKGROUND: Glioblastoma (GB) is a malignant brain tumour that is challenging to treat, often relapsing even after aggressive therapy. Evaluating therapy response relies on magnetic resonance imaging (MRI) following the Response Assessment in Neuro-Oncology (RANO) criteria. However, early assessment is hindered by phenomena such as pseudoprogression and pseudoresponse. Magnetic resonance spectroscopy (MRS/MRSI) provides metabolomics information but is underutilised due to a lack of familiarity and standardisation. METHODS: This study explores the potential of spectroscopic imaging (MRSI) in combination with several machine learning approaches, including one-dimensional convolutional neural networks (1D-CNNs), to improve therapy response assessment. Preclinical GB (GL261-bearing mice) were studied for method optimisation and validation. RESULTS: The proposed 1D-CNN models successfully identify different regions of tumours sampled by MRSI, i.e., normal brain (N), control/unresponsive tumour (T), and tumour responding to treatment (R). Class activation maps using Grad-CAM enabled the study of the key areas relevant to the models, providing model explainability. The generated colour-coded maps showing the N, T and R regions were highly accurate (according to Dice scores) when compared against ground truth and outperformed our previous method. CONCLUSIONS: The proposed methodology may provide new and better opportunities for therapy response assessment, potentially providing earlier hints of tumour relapsing stages.

Prospective diagnostic performance evaluation of single-voxel 1H MRS for typing and grading of brain tumours.

The purpose of this study was to evaluate whether single-voxel (1)H MRS could add useful information to conventional MRI in the preoperative characterisation of the type and grade of brain tumours. MRI and MRS examinations from a prospective cohort of 40 consecutive patients were analysed double blind by radiologists and spectroscopists before the histological diagnosis was known. The spectroscopists had only the MR spectra, whereas the radiologists had both the MR images and basic clinical details (age, sex and presenting symptoms). Then, the radiologists and spectroscopists exchanged their predictions and re-evaluated their initial opinions, taking into account the new evidence. Spectroscopists used four different systems of analysis for (1)H MRS data, and the efficacy of each of these methods was also evaluated. Information extracted from (1)H MRS significantly improved the radiologists' MRI-based characterisation of grade IV tumours (glioblastomas, metastases, medulloblastomas and lymphomas) in the cohort [area under the curve (AUC) in the MRI re-evaluation 0.93 versus AUC in the MRI evaluation 0.85], and also of the less malignant glial tumours (AUC in the MRI re-evaluation 0.93 versus AUC in the MRI evaluation 0.81). One of the MRS analysis systems used, the INTERPRET (International Network for Pattern Recognition of Tumours Using Magnetic Resonance) decision support system, outperformed the others, as well as being better than the MRI evaluation for the characterisation of grade III astrocytomas. Thus, preoperative MRS data improve the radiologists' performance in diagnosing grade IV tumours and, for those of grade II-III, MRS data help them to recognise the glial lineage. Even in cases in which their diagnoses were not improved, the provision of MRS data to the radiologists had no negative influence on their predictions.

Minimization of spectral pattern changes during HRMAS experiments at 37 degrees celsius by prior focused microwave irradiation.

OBJECT: High-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy provides detailed metabolomic information from intact tissue. However, long acquisition times and high rotation speed may lead to timedependent spectral pattern changes, which may affect proper interpretation of results. We report a strategy to minimize those changes, even at physiological recording temperature. MATERIALS AND METHODS: Glioblastoma(Gbm) tumours were induced in 12 mice by stereotactic injection of GL261 cells. Animals were sacrificed and tumours were removed and stored in liquid N2. Half of the samples were exposed to focused microwave (FMW) irradiation prior to HRMAS while the other half was not. Time-course experiments (374 min at 37°C, 9.4T, 3,000 Hz spinning rate) were carried out to monitor spectral pattern changes. Differences were assessed with Unianova test while post-HRMAS histopathology analysis was performed to assess tissue integrity. RESULTS: Significant changes (up to 1.7 fold) were observed in samples without FMW irradiation in several spectral regions e.g. mobile lipids/lactate (0.90-1.30 ppm), acetate (1.90 ppm), N-acetyl aspartate (2.00 ppm), and Choline-containing compounds (3.19-3.25 ppm). No significant changes in the spectral pattern of FMW-irradiated samples were recorded. CONCLUSION: We describe here a successful strategy to minimize spectral pattern changes in mouse Gbm samples using a FMW irradiation system.

Establishing Imaging Biomarkers of Host Immune System Efficacy during Glioblastoma Therapy Response: Challenges, Obstacles and Future Perspectives.

This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the literature data supporting the claim that the immune system is behind the efficacy of most successful glioblastoma therapies but, unfortunately, there are no current short-term imaging biomarkers of its activity. We also discuss how using an immunocompetent murine model of glioblastoma, allowing the cure of mice and the generation of immune memory, provides a suitable framework for glioblastoma therapy response biomarker studies. Both magnetic resonance imaging and magnetic resonance-based metabolomic data (i.e., magnetic resonance spectroscopic imaging) can provide non-invasive assessments of such a system. A predictor based in nosological images, generated from magnetic resonance spectroscopic imaging analyses and their oscillatory patterns, should be translational to clinics. We also review hurdles that may explain why such an oscillatory biomarker was not reported in previous imaging glioblastoma work. Single shot explorations that neglect short-term oscillatory behavior derived from immune system attack on tumors may mislead actual response extent detection. Finally, we consider improvements required to properly predict immune system-mediated early response (1-2 weeks) to therapy. The sensible use of improved biomarkers may enable translatable evidence-based therapeutic protocols, with the possibility of extending preclinical results to human patients.

Advances in Preclinical/Clinical Glioblastoma Treatment: Can Nanoparticles Be of Help?

Glioblastoma multiforme (GB) is the most aggressive and frequent primary malignant tumor in the central nervous system (CNS), with unsatisfactory and challenging treatment nowadays. Current standard of care includes surgical resection followed by chemotherapy and radiotherapy. However, these treatments do not much improve the overall survival of GB patients, which is still below two years (the 5-year survival rate is below 7%). Despite various approaches having been followed to increase the release of anticancer drugs into the brain, few of them demonstrated a significant success, as the blood brain barrier (BBB) still restricts its uptake, thus limiting the therapeutic options. Therefore, enormous efforts are being devoted to the development of novel nanomedicines with the ability to cross the BBB and specifically target the cancer cells. In this context, the use of nanoparticles represents a promising non-invasive route, allowing to evade BBB and reducing systemic concentration of drugs and, hence, side effects. In this review, we revise with a critical view the different families of nanoparticles and approaches followed so far with this aim.

Intranasal Administration of Catechol-Based Pt(IV) Coordination Polymer Nanoparticles for Glioblastoma Therapy.

Cisplatin has been described as a potent anticancer agent for decades. However, in the case of glioblastomas, it is only considered a rescue treatment applied after the failure of second-line treatments. Herein, based on the versatility offered by coordination chemistry, we engineered nanoparticles by reaction of a platinum (IV) prodrug and iron metal ions showing in vitro dual pH- and redox-sensitivity, controlled release and comparable cytotoxicity to cisplatin against HeLa and GL261 cells. In vivo intranasal administration in orthotopic preclinical GL261 glioblastoma tumor-bearing mice demonstrated increased accumulation of platinum in tumors, leading in some cases to complete cure and prolonged survival of the tested cohort. This was corroborated by a magnetic resonance imaging follow-up, thus opening new opportunities for intranasal glioblastoma therapies while minimizing side effects. The findings derived from this research showed the potentiality of this approach as a novel therapy for glioblastoma treatment.

Incremental Gaussian Discriminant Analysis based on Graybill and Deal weighted combination of estimators for brain tumour diagnosis.

In the last decade, machine learning (ML) techniques have been used for developing classifiers for automatic brain tumour diagnosis. However, the development of these ML models rely on a unique training set and learning stops once this set has been processed. Training these classifiers requires a representative amount of data, but the gathering, preprocess, and validation of samples is expensive and time-consuming. Therefore, for a classical, non-incremental approach to ML, it is necessary to wait long enough to collect all the required data. In contrast, an incremental learning approach may allow us to build an initial classifier with a smaller number of samples and update it incrementally when new data are collected. In this study, an incremental learning algorithm for Gaussian Discriminant Analysis (iGDA) based on the Graybill and Deal weighted combination of estimators is introduced. Each time a new set of data becomes available, a new estimation is carried out and a combination with a previous estimation is performed. iGDA does not require access to the previously used data and is able to include new classes that were not in the original analysis, thus allowing the customization of the models to the distribution of data at a particular clinical center. An evaluation using five benchmark databases has been used to evaluate the behaviour of the iGDA algorithm in terms of stability-plasticity, class inclusion and order effect. Finally, the iGDA algorithm has been applied to automatic brain tumour classification with magnetic resonance spectroscopy, and compared with two state-of-the-art incremental algorithms. The empirical results obtained show the ability of the algorithm to learn in an incremental fashion, improving the performance of the models when new information is available, and converging in the course of time. Furthermore, the algorithm shows a negligible instance and concept order effect, avoiding the bias that such effects could introduce.