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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.

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 M

Glioblastoma is the most malignant and frequently occurring type of brain tumors in adults. Its treatment has been greatly hampered by the difficulty to achieve effective therapeutic concentration in the tumor sites due to its location and the blood–brain barrier. Intranasal administration has emerged as an alternative for drug delivery into the brain though mucopenetration, and rapid mucociliary clearance still remains an issue to be solved before its implementation. To address these issues, based on the intriguing properties of proteins secreted by mussels, polyphenol and catechol functionalization has already been used to promote mucopenetration, intranasal delivery and transport across the blood–brain barrier. Thus, herein we report the synthesis and study of complex 1, a Pt(IV) prodrug functionalized with catecholic moieties. This complex considerably augmented solubility in contrast to cisplatin and showed a comparable cytotoxic effect on cisplatin in HeLa, 1Br3G and GL261 cells. Furthermore, preclinical in vivo therapy using the intranasal administration route suggested that it can reach the brain and inhibit the growth of orthotopic GL261 glioblastoma. These results open new opportunities for catechol-bearing anticancer prodrugs in the treatment for brain tumors via intranasal administration.

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.

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.

Aging and cancer are two interrelated biological processes, with aging being one of the most important risk factors for the development of cancer. Parallel epigenetic alterations have been described for both, although differences, especially within the DNA hypomethylation scenario, have also been identified in recent literature. While many of these observations arise from the use of mouse models, there is a lack of systematic and single-base resolution comparisons of human and mouse epigenetic patterns in the context of disease. However, such comparisons are especially significant with respect to the DNA methylation alterations found independently in the two species 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 non-tumoral 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 in order to study interspecies DNA methylation levels at specific CpG sites. Globally, we found robust evidence for the conservation of cancer and aging-associated epigenomic patterns in both species, and our observations point towards the preservation of the functional consequences of these alterations at multiple levels of genomic regulation.

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.

In the last years, extensive attention has been paid on designing and developing functional imaging contrast agents for providing accurate noninvasive evaluation of pathology in vivo. However, the issue of false-positives or ambiguous imaging and the lack of a robust strategy for simultaneous dual-mode imaging remain to be fully addressed. One effective strategy for improving it is to rationally design magnetic resonance imaging (MRI) contrast agents (CAs) with intrinsic T1/ T2 dual-mode imaging features. In this work, the development and characterization of one-pot synthesized nanostructured coordination polymers (NCPs) which exhibit dual mode T1/ T2 MRI contrast behavior is described. The resulting material comprises the combination of different paramagnetic ions (Fe3+, Gd3+, Mn2+) with selected organic ligands able to induce the polymerization process and nanostructure stabilization. Among them, the Fe-based NCPs showed the best features in terms of colloidal stability, low toxicity, and dual T1/ T2 MRI contrast performance overcoming the main drawbacks of reported CAs. The dual-mode CA capability was evaluated by different means: in vitro phantoms, ex vivo and in vivo MRI, using a preclinical model of murine glioblastoma. Interestingly, the in vivo MRI of Fe-NCPs show T1 and T2 high contrast potential, allowing simultaneous recording of positive and negative contrast images in a very short period of time while being safer for the mouse. Moreover, the biodistribution assays reveals the persistence of the nanoparticles in the tumor and subsequent gradual clearance denoting their biodegradability. After a comparative study with commercial CAs, the results suggest these nanoplatforms as promising candidates for the development of dual-mode MRI CAs with clear advantages.

[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.

Background DCE@urLAB is a software application for analysis of dynamic contrast-enhanced magnetic resonance imaging data (DCE-MRI). The tool incorporates a friendly graphical user interface (GUI) to interactively select and analyze a region of interest (ROI) within the image set, taking into account the tissue concentration of the contrast agent (CA) and its effect on pixel intensity. Results Pixel-wise model-based quantitative parameters are estimated by fitting DCE-MRI data to several pharmacokinetic models using the Levenberg-Marquardt algorithm (LMA). DCE@urLAB also includes the semi-quantitative parametric and heuristic analysis approaches commonly used in practice. This software application has been programmed in the Interactive Data Language (IDL) and tested both with publicly available simulated data and preclinical studies from tumor-bearing mouse brains. Conclusions A user-friendly solution for applying pharmacokinetic and non-quantitative analysis DCE-MRI in preclinical studies has been implemented and tested. The proposed tool has been specially designed for easy selection of multi-pixel ROIs. A public release of DCE@urLAB, together with the open source code and sample datasets, is available at http://www.die.upm.es/im/archives/DCEurLAB/ webcite.

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. © 2011 Elsev

Development of molecular diagnostics that can reliably differentiate amongst different subtypes of brain tumors is an important unmet clinical need in postgenomics medicine and clinical oncology. A simple linear formula derived from gene expression values of four genes (GFAP, PTPRZ1, GPM6B, and PRELP) measured from cDNA microarrays (n=35) have distinguished glioblastoma and meningioma cases in a previous study. We herein extend this work further and report that the above predictor formula showed its robustness when applied to Affymetrix microarray data acquired prospectively in our laboratory (n=80) as well as publicly available data (n=98). Importantly, GFAP and GPM6B were both retained as being significant in the predictive model upon using the Affymetrix data obtained in our laboratory, whereas the other two predictor genes were SFRP2 and SLC6A2. These results collectively indicate the importance of the expression values of GFAP and GPM6B genes sampled from the two types of microarray technologies tested. The high prediction accuracy obtained in these instances demonstrates the robustness of the predictors across microarray platforms used. This result would require further validation with a larger population of meningioma and glioblastoma cases. At any rate, this study paves the way for further application of gene signatures to more stringent biopsy discrimination challenges. © 2010, Mary Ann Liebert, Inc.