Integrating RNA sequencing into neuro-oncology practice

Involvement of Fgf2-mediated tau protein phosphorylation in cognitive deficits induced by sevoflurane in aged rats

OBJECTIVE

Anesthetics have been linked to cognitive alterations, particularly in the elderly. The current research delineates how Fibroblast Growth Factor 2 (Fgf2) modulates tau protein phosphorylation, contributing to cognitive impairments in aged rats upon sevoflurane administration.

METHODS

Rats aged 3, 12, and 18 months were subjected to a 2.5% sevoflurane exposure to form a neurotoxicity model. Cognitive performance was gauged, and the GEO database was employed to identify differentially expressed genes (DEGs) in the 18-month-old cohort post sevoflurane exposure. Bioinformatics tools, inclusive of STRING and GeneCards, facilitated detailed analysis. Experimental validations, both in vivo and in vitro, examined Fgf2's effect on tau phosphorylation.

RESULTS

Sevoflurane notably altered cognitive behavior in older rats. Out of 128 DEGs discerned, Fgf2 stood out as instrumental in regulating tau protein phosphorylation. Sevoflurane exposure spiked Fgf2 expression in cortical neurons, intensifying tau phosphorylation via the PI3K/AKT/Gsk3b trajectory. Diminishing Fgf2 expression correspondingly curtailed tau phosphorylation, neurofibrillary tangles, and enhanced cognitive capacities in aged rats.

CONCLUSION

Sevoflurane elicits a surge in Fgf2 expression in aging rats, directing tau protein phosphorylation through the PI3K/AKT/Gsk3b route, instigating cognitive aberrations.

Therapeutic HDAC inhibition in hypermutant diffuse intrinsic pontine glioma

Constitutional mismatch repair deficiency (CMMRD) is a cancer predisposition syndrome associated with the development of hypermutant pediatric high-grade glioma, and confers a poor prognosis. While therapeutic histone deacetylase (HDAC) inhibition of diffuse intrinsic pontine glioma (DIPG) has been reported; here, we use a clinically relevant biopsy-derived hypermutant DIPG model (PBT-24FH) and a CRISPR-Cas9 induced genetic model to evaluate the efficacy of HDAC inhibition against hypermutant DIPG. We screened PBT-24FH cells for sensitivity to a panel of HDAC inhibitors (HDACis) in vitro, identifying two HDACis associated with low nanomolar IC50s, quisinostat (27 nM) and romidepsin (2 nM). In vivo, quisinostat proved more efficacious, inducing near-complete tumor regression in a PBT-24FH flank model. RNA sequencing revealed significant quisinostat-driven changes in gene expression, including upregulation of neural and pro-inflammatory genes. To validate the observed potency of quisinostat in vivo against additional hypermutant DIPG models, we tested quisinostat in genetically-induced mismatch repair (MMR)-deficient DIPG flank tumors, demonstrating that loss of MMR function increases sensitivity to quisinostat in vivo. Here, we establish the preclinical efficacy of quisinostat against hypermutant DIPG, supporting further investigation of epigenetic targeting of hypermutant pediatric cancers with the potential for clinical translation. These findings support further investigation of HDAC inhibitors against pontine high-grade gliomas, beyond only those with histone mutations, as well as against other hypermutant central nervous system tumors.

The coming decade in precision oncology: six riddles

High-throughput methods to investigate tumour omic landscapes have quickly catapulted cancer specialists into the precision oncology era. The singular lesson of precision oncology might be that, for it to be precise, treatment must be personalized, as each cancer's complex molecular and immune landscape differs from patient to patient. Transformative therapies include those that are targeted at the sequelae of molecular abnormalities or at immune mechanisms, and, increasingly, pathways previously thought to be undruggable have become druggable. Critical to applying precision medicine is the concept that the right combination of drugs must be chosen for each patient and used at the right stage of the disease. Multiple puzzles remain that complicate therapy choice, including evidence that deleterious mutations are common in normal tissues and non-malignant conditions. The host's role is also likely to be key in determining treatment response, especially for immunotherapy. Indeed, maximizing the impact of immunotherapy will require omic analyses to match the right immune-targeted drugs to the individualized patient and tumour setting. In this Perspective, we discuss six key riddles that must be solved to optimize the application of precision oncology to otherwise lethal malignancies.

Metabolic modeling-based drug repurposing in Glioblastoma

The manifestation of intra- and inter-tumor heterogeneity hinders the development of ubiquitous cancer treatments, thus requiring a tailored therapy for each cancer type. Specifically, the reprogramming of cellular metabolism has been identified as a source of potential drug targets. Drug discovery is a long and resource-demanding process aiming at identifying and testing compounds early in the drug development pipeline. While drug repurposing efforts (i.e., inspecting readily available approved drugs) can be supported by a mechanistic rationale, strategies to further reduce and prioritize the list of potential candidates are still needed to facilitate feasible studies. Although a variety of ‘omics’ data are widely gathered, a standard integration method with modeling approaches is lacking. For instance, flux balance analysis is a metabolic modeling technique that mainly relies on the stoichiometry of the metabolic network. However, exploring the network’s topology typically neglects biologically relevant information. Here we introduce Transcriptomics-Informed Stoichiometric Modelling And Network analysis (TISMAN) in a recombinant innovation manner, allowing identification and validation of genes as targets for drug repurposing using glioblastoma as an exemplar.

A Toolkit for Profiling the Immune Landscape of Pediatric Central Nervous System Malignancies

The prognosis of pediatric central nervous system (CNS) malignancies remains dismal due to limited treatment options, resulting in high mortality rates and long-term morbidities. Immunotherapies, including checkpoint inhibition, cancer vaccines, engineered T cell therapies, and oncolytic viruses, have promising results in some hematological and solid malignancies, and are being investigated in clinical trials for various high-grade CNS malignancies. However, the role of the tumor immune microenvironment (TIME) in CNS malignancies is mostly unknown for pediatric cases. In order to successfully implement immunotherapies and to eventually predict which patients would benefit from such treatments, in-depth characterization of the TIME at diagnosis and throughout treatment is essential. In this review, we provide an overview of techniques for immune profiling of CNS malignancies, and detail how they can be utilized for different tissue types and studies. These techniques include immunohistochemistry and flow cytometry for quantifying and phenotyping the infiltrating immune cells, bulk and single-cell transcriptomics for describing the implicated immunological pathways, as well as functional assays. Finally, we aim to describe the potential benefits of evaluating other compartments of the immune system implicated by cancer therapies, such as cerebrospinal fluid and blood, and how such liquid biopsies are informative when designing immune monitoring studies. Understanding and uniformly evaluating the TIME and immune landscape of pediatric CNS malignancies will be essential to eventually integrate immunotherapy into clinical practice.

The Practical Application of Emerging Technologies Influencing the Diagnosis and Care of Patients With Primary Brain Tumors

Over the past decade, a variety of new and innovative technologies has led to important advances in the diagnosis and management of patients with primary malignant brain tumors. New approaches to surgical navigation and tumor localization, advanced imaging to define tumor biology and treatment response, and the widespread adoption of a molecularly defined integrated diagnostic paradigm that complements traditional histopathologic diagnosis continue to impact the day-to-day care of these patients. In the neuro-oncology clinic, discussions with patients about the role of tumor treating fields (TTFields) and the incorporation of next-generation sequencing (NGS) data into therapeutic decision-making are now a standard practice. This article summarizes newer applications of technology influencing the pathologic, neuroimaging, neurosurgical, and medical management of patients with malignant primary brain tumors.

Peripheral Blood RNAs and Left Ventricular Dysfunction after Myocardial Infarction: Towards Translation into Clinical Practice

The treatment and early outcome of patients with acute myocardial infarction (MI) have dramatically improved the past decades, but the incidence of left ventricular (LV) dysfunction post-MI remains high. Peripheral blood RNAs reflect pathophysiological changes during acute MI and the inflammatory process. Therefore, these RNAs are promising new markers to molecularly phenotype patients and improve the early identification of patients at risk of subsequent LV dysfunction. We here discuss the coding and long non-coding RNAs that can be measured in peripheral blood of patients with acute MI and list the advantages and limitations for implementation in clinical practice. Although some studies provide preliminary evidence of their diagnostic and prognostic potential, the use of these makers has not yet been implemented in clinical practice. The added value of RNAs to improve treatment and outcome remains to be determined in larger clinical studies. International consortia are now catalyzing renewed efforts to investigate novel RNAs that may improve post-MI outcome in a precision-medicine approach. Graphical Abstract Peripheral blood RNAs reflect the inflammatory changes in acute MI. A number of studies provide preliminary evidence of their prognostic potential, although the use of these makers has not yet been assessed in clinical practice.

Defining housekeeping genes suitable for RNA-seq analysis of the human allograft kidney biopsy tissue

BACKGROUND

RNA-seq is poised to play a major role in the management of kidney transplant patients. Rigorous definition of housekeeping genes (HKG) is essential for further progress in this field. Using single genes or a limited set HKG is inherently problematic since their expression might be altered by specific diseases in the patients being studied.

METHODS

To generate a HKG set specific for kidney transplantation, we performed RNA-sequencing from renal allograft biopsies collected in a variety of clinical settings. Various normalization methods were applied to identify transcripts that had a coefficient of variation of expression that was below the 2nd percentile across all samples, and the corresponding genes were designated as housekeeping genes. Comparison with transcriptomic data from the Gene Expression Omnibus (GEO) database, pathway analysis and molecular biological functions were utilized to validate the housekeeping genes set.

RESULTS

We have developed a bioinformatics solution to this problem by using nine different normalization methods to derive large HKG gene sets from a RNA-seq data set of 47,611 transcripts derived from 30 biopsies. These biopsies were collected in a variety of clinical settings, including normal function, acute rejection, interstitial nephritis, interstitial fibrosis/tubular atrophy and polyomavirus nephropathy. Transcripts with coefficient of variation below the 2nd percentile were designated as HKG, and validated by showing their virtual absence in diseased allograft derived transcriptomic data sets available in the GEO. Pathway analysis indicated a role for these genes in maintenance of cell morphology, pyrimidine metabolism, and intracellular protein signaling.

CONCLUSIONS

Utilization of these objectively defined HKG data sets will guard against errors resulting from focusing on individual genes like 18S RNA, actin & tubulin, which do not maintain constant expression across the known spectrum of renal allograft pathology.

Molecular tools for the pathologic diagnosis of central nervous system tumors

Molecular diagnostics currently has a crucial role in neuro-oncological patient care. (Epi)genetic assays testing for point mutations, copy number variations, gene fusions, translocations, and methylation status are of main diagnostic interest in neuro-oncology. Multiple assays have been developed for this purpose, ranging from single gene tests to high-throughput, integrated techniques enabling detection of multiple genetic aberrations in a single workflow. This review describes the nature of the simpler and more complex assays for molecular diagnostics of tumors of the central nervous system and briefly discusses their strengths and weaknesses.

Therapy of breast cancer brain metastases: challenges, emerging treatments and perspectives

Brain metastases are the most common central nervous system tumors in adults, and incidence of brain metastases is increasing due to both improved diagnostic techniques (e.g. magnetic resonance imaging) and increased cancer patient survival through advanced systemic treatments. Outcomes of patients remain disappointing and treatment options are limited, usually involving multimodality approaches. Brain metastases represent an unmet medical need in solid tumor care, especially in breast cancer, where brain metastases are frequent and result in impaired quality of life and death. Challenges in the management of brain metastases have been highlighted in this review. Innovative research and treatment strategies, including prevention approaches and emerging systemic treatment options for brain metastases of breast cancer, are further discussed.