Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes

Integrating Signaling Pathways with Transcription Factor Networks-On the Trail of Sisyphus?

In the context of health and disease research, cells use signaling pathways that transduce stimuli from the extracellular environment to modulate intracellular gene expression via the activity of transcription factors and cofactors (coactivators and/or corepressors) [...].

RAB12-LRRK2 Complex Suppresses Primary Ciliogenesis and Regulates Centrosome Homeostasis in Astrocytes

Leucine-rich repeat kinase 2 (LRRK2) phosphorylates a subset of RAB GTPases, and the phosphorylation levels are elevated by Parkinson's disease (PD)-linked mutations of LRRK2. However, the precise function of the specific RAB GTPase targeted by LRRK2 signaling in the brain remains to be elucidated. Here, we identify RAB12 as a robust LRRK2 substrate in the mouse brains through phosphoproteomics profiling and solve the structure of RAB12-LRRK2 protein complex through Cryo-EM analysis. Mechanistically, RAB12 cooperates with LRRK2 to inhibit primary ciliogenesis and regulate centrosome homeostasis in astrocytes through enhancing the phosphorylation of RAB10 and recruiting Rab interacting lysosomal protein like 1 (RILPL1), while the functions of RAB12 require a direct interaction with LRRK2 and LRRK2 kinase activity. Furthermore, the ciliary deficits and centrosome alteration caused by the PD-linked LRRK2-G2019S mutation are prevented by the deletion of Rab12 in astrocytes. Thus, our study reveals a physiological function of the RAB12-LRRK2 complex in regulating ciliogenesis and centrosome homeostasis. The RAB12-LRRK2 structure offers a guidance in the therapeutic development of PD by targeting the RAB12-LRRK2 interaction.

Engineering CRISPR/Cas9 therapeutics for cancer precision medicine

The discovery of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated protein 9 (Cas9) technology has revolutionized field of cancer treatment. This review explores usage of CRISPR/Cas9 for editing and investigating genes involved in human carcinogenesis. It provides insights into the development of CRISPR as a genetic tool. Also, it explores recent developments and tools available in designing CRISPR/Cas9 systems for targeting oncogenic genes for cancer treatment. Further, we delve into an overview of cancer biology, highlighting key genetic alterations and signaling pathways whose deletion prevents malignancies. This fundamental knowledge enables a deeper understanding of how CRISPR/Cas9 can be tailored to address specific genetic aberrations and offer personalized therapeutic approaches. In this review, we showcase studies and preclinical trials that show the utility of CRISPR/Cas9 in disrupting oncogenic targets, modulating tumor microenvironment and increasing the efficiency of available anti treatments. It also provides insight into the use of CRISPR high throughput screens for cancer biomarker identifications and CRISPR based screening for drug discovery. In conclusion, this review offers an overview of exciting developments in engineering CRISPR/Cas9 therapeutics for cancer treatment and highlights the transformative potential of CRISPR for innovation and effective cancer treatments.

Identifying Sex-Specific Serum Patterns of Alzheimer's Mice through Deep TMT Profiling and a Concentration-Dependent Concatenation Strategy

Alzheimer's disease (AD) is the most prevalent form of dementia, disproportionately affecting women in disease prevalence and progression. Comprehensive analysis of the serum proteome in a common AD mouse model offers potential in identifying possible AD pathology- and gender-associated biomarkers. Here, we introduce a multiplexed, nondepleted mouse serum proteome profiling via tandem mass-tag (TMTpro) labeling. The labeled sample was separated into 475 fractions using basic reversed-phase liquid chromatography (RPLC), which were categorized into low-, medium-, and high-concentration fractions for concatenation. This concentration-dependent concatenation strategy resulted in 128 fractions for acidic RPLC-tandem mass spectrometry (MS/MS) analysis, collecting ∼5 million MS/MS scans and identifying 3972 unique proteins (3413 genes) that cover a dynamic range spanning at least 6 orders of magnitude. The differential expression analysis between wild type and the commonly used AD model (5xFAD) mice exhibited minimal significant protein alterations. However, we detected 60 statistically significant (FDR < 0.05), sex-specific proteins, including complement components, serpins, carboxylesterases, major urinary proteins, cysteine-rich secretory protein 1, pregnancy-associated murine protein 1, prolactin, amyloid P component, epidermal growth factor receptor, fibrinogen-like protein 1, and hepcidin. The results suggest that our platform possesses the sensitivity and reproducibility required to detect sex-specific differentially expressed proteins in mouse serum samples.

ATM inhibition enhances the efficacy of radiation across distinct molecular subgroups of pediatric high-grade glioma

BACKGROUND

Pediatric high-grade glioma (pHGG) is largely incurable and accounts for most brain tumor-related deaths in children. Radiation is a standard therapy, yet the benefit from this treatment modality is transient, and most children succumb to disease within 2 years. Recent large-scale genomic studies suggest that pHGG has alterations in DNA damage response (DDR) pathways that induce resistance to DNA damaging agents. The aim of this study was to evaluate the therapeutic potential and molecular consequences of combining radiation with selective DDR inhibition in pHGG.

METHODS

We conducted an unbiased screen in pHGG cells that combined radiation with clinical candidates targeting the DDR and identified the ATM inhibitor AZD1390. Subsequently, we profiled AZD1390 + radiation in an extensive panel of early passage pHGG cell lines, mechanistically characterized response to the combination in vitro in sensitive and resistant cells and evaluated the combination in vivo using TP53 wild-type and TP53 mutant orthotopic xenografts.

RESULTS

AZD1390 significantly potentiated radiation across molecular subgroups of pHGG by increasing mutagenic nonhomologous end joining and augmenting genomic instability. In contrast to previous reports, ATM inhibition significantly improved the efficacy of radiation in both TP53 wild-type and TP53 mutant isogenic cell lines and distinct orthotopic xenograft models. Furthermore, we identified a novel mechanism of resistance to AZD1390 + radiation that was marked by an attenuated ATM pathway response which dampened sensitivity to ATM inhibition and induced synthetic lethality with ATR inhibition.

CONCLUSIONS

Our study supports the clinical evaluation of AZD1390 in combination with radiation in pediatric patients with HGG.

A proteome-level view of brain tumors for a better understanding of novel diagnosis, prognosis, and therapy

INTRODUCTION

Brain tumors are complex and heterogeneous malignancies with significant challenges in diagnosis, prognosis, and therapy. Proteomics, the large-scale study of proteins and their functions, has emerged as a powerful tool to comprehensively investigate the molecular mechanisms underlying brain tumor regulation.

AREAS COVERED

This review explores brain tumors from a proteomic standpoint, highlighting recent progress and insights gained through proteomic methods. It delves into the proteomic techniques employed and underscores potential biomarkers for early detection, prognosis, and treatment planning. Recent PubMed Central proteomic studies (2017-present) are discussed, summarizing findings on altered protein expression, post-translational changes, and protein interactions. This sheds light on brain tumor signaling pathways and their significance in innovative therapeutic approaches.

EXPERT OPINION

Proteomics offers immense potential for revolutionizing brain tumor diagnosis and therapy. To unlock its full benefits, further translational research is crucial. Combining proteomics with other omics data enhances our grasp of brain tumors. Validating and translating proteomic biomarkers are vital for better patient results. Challenges include tumor complexity, lack of curated proteomic databases, and the need for collaboration between researchers and clinicians. Overcoming these challenges requires investment in technology, data sharing, and translational research.

Proteomic Shotgun and Targeted Mass Spectrometric Datasets of Cerebrospinal Fluid (Liquor) Derived from Patients with Vestibular Schwannoma

Vestibular schwannomas are relatively rare intracranial tumors compared to other brain tumors. Data on the molecular features, especially on schwannoma proteome, are scarce. The 41 cerebrospinal fluid (liquor) samples were obtained during the surgical removal of vestibular schwannoma. Obtained peptide samples were analyzed by shotgun LC-MS/MS high-resolution mass spectrometry. The same peptide samples were spiked with 148 stable isotopically labeled peptide standards (SIS) followed by alkaline fractionation and scheduled multiple reaction monitoring (MRM) for quantitative analysis. The natural counterparts of SIS peptides were mapped onto 111 proteins that were Food and Drug Administration (FDA)-approved for diagnostic use. As a result, 525 proteins were identified by shotgun LC-MS/MS with high confidence (at least two peptides per protein, FDR < 1%) in liquor samples. Absolute quantitative concentrations were obtained for 54 FDA-approved proteins detected in at least five experimental samples. Since there is lack of data on the molecular landscape of vestibular schwannoma, the obtained datasets are unique and one of the first in its field.

Turck C. Delineation of biomarkers and molecular pathways of residual effects of fluoxetine treatment in juvenile rhesus monkeys by proteomic profiling

Fluoxetine (Prozac™) is the only antidepressant approved by the US Food and Drug Administration (FDA) for the treatment of major depressive disorder (MDD) in children. Despite its considerable efficacy as a selective serotonin reuptake inhibitor, the possible long-term effects of fluoxetine on brain development in children are poorly understood. In the current study, we aimed to delineate molecular mechanisms and protein biomarkers in the brains of juvenile rhesus macaques (Macaca mulatta) one year after the discontinuation of fluoxetine treatment using proteomic and phosphoproteomic profiling. We identified several differences in protein expression and phosphorylation in the dorsolateral prefrontal cortex (DLPFC) and cingulate cortex (CC) that correlated with impulsivity in animals, suggesting that the GABAergic synapse pathway may be affected by fluoxetine treatment. Biomarkers in combination with the identified pathways contribute to a better understanding of the mechanisms underlying the chronic effects of fluoxetine after discontinuation in children.

In-Depth Blood Proteome Profiling by Extensive Fractionation and Multiplexed Quantitative Mass Spectrometry

Blood in the circulatory system carries information of physiological and pathological status of the human body, so blood proteins are often used as biomarkers for diagnosis, prognosis, and therapy. Human blood proteome can be explored by the latest technologies in mass spectrometry (MS), creating an opportunity of discovering new disease biomarkers. The extreme dynamic range of protein concentrations in blood, however, poses a challenge to detect proteins of low abundance, namely, tissue leakage proteins. Here, we describe a strategy to directly analyze undepleted blood samples by extensive liquid chromatography (LC) fractionation and 18-plex tandem-mass-tag (TMT) mass spectrometry. The proteins in blood specimens (e.g., plasma or serum) are isolated by acetone precipitation and digested into peptides. The resulting peptides are TMT-labeled, separated by basic pH reverse-phase (RP) LC into at least 40 fractions, and analyzed by acidic pH RPLC and high-resolution MS/MS, leading to the quantification of ~3000 unique proteins. Further increase of basic pH RPLC fractions and adjustment of the fraction concatenation strategy can enhance the proteomic coverage (up to ~5000 proteins). Finally, the combination of multiple batches of TMT experiments allows the profiling of hundreds of blood samples. This TMT-MS-based method provides a powerful platform for deep proteome profiling of human blood samples.

An integrative bioinformatics investigation and experimental validation of critically involved genes in high-grade gliomas

Background

Lack of knowledge around underlying mechanisms of gliomas mandates intense research efforts to improve the disease outcomes. Identification of high-grade gliomas pathogenesis which is known for poor prognosis and low survival is of particular importance. Distinguishing the differentially expressed genes is one of the core approaches to clarify the causative factors.

Methods

Microarray datasets of the treatment-naïve gliomas were provided from the Gene Expression Omnibus considering the similar platform and batch effect removal. Interacting recovery of the top differentially expressed genes was performed on the STRING and Cytoscape platforms. Kaplan–Meier analysis was piloted using RNA sequencing data and the survival rate of glioma patients was checked considering selected genes. To validate the bioinformatics results, the gene expression was elucidated by real-time RT-qPCR in a series of low and high-grade fresh tumor samples.

Results

We identified 323 up-regulated and 253 down-regulated genes. The top 20 network analysis indicated that PTX3, TIMP1, CHI3L1, LTF and IGFBP3 comprise a crucial role in gliomas progression. The survival was inversely linked to the levels of all selected genes. Further analysis of RNA sequencing data indicated a significant increase in all five genes in high-grade tumors. Among them, PTX3, TIMP1 and LTF did not show any change in low-grade versus controls. Real-time RT-qPCR confirmed the in-silico results and revealed significantly higher expression of selected genes in high-grade samples compared to low-grade.

Conclusions

Our results highlighted the role of PTX3 and TIMP1 which were previously considered in glioma tumorigenesis as well as LTF as a new potential biomarker.

A pan-cancer analysis of the oncogenic role of dual-specificity tyrosine (Y)-phosphorylation- regulated kinase 2 (DYRK2) in human tumors

Although there have been studies correlating DYRK2 with a number of human cancers, there has been no pan-cancer analysis. Therefore, through the TCGA database, we conducted a related study on the expression of DYRK2 in cancers.The expression of DYRK2 is obviously increased in some cancers, while the opposite is true in others, and there is a clear association between its expression and the prognosis of cancer patients.The mutation of DYRK2 is also significantly correlated with patients’ prognosis in certain human tumors. In addition, phosphorylation and methylation levels of DYRK2 are different between tumor tissues and adjacent normal tissues in various tumors. In the tumour microenvironment, the expression of DYRK2 correlates with cancer-associated fibroblast infiltration, such as BLCA or HNSC. In order to fully understand the role of DYRK2 in different tumors, we conducted a pan-cancer analysis.

Roles of dual specificity tyrosine-phosphorylation-regulated kinase 2 in nervous system development and disease

Dual specificity tyrosine-phosphorylation-regulated kinases (DYRKs) are a group of conserved eukaryotic kinases phosphorylating tyrosine, serine, and threonine residues. The human DYRK family comprises 5 members (DYRK1A, DYRK1B, DYRK2, DYRK3, and DYRK4). The different DYRKs have been implicated in neurological diseases, cancer, and virus infection. Specifically, DYRK2 has been mainly implicated in cancer progression. However, its role in healthy and pathological nervous system function has been overlooked. In this context, we review current available data on DYRK2 in the nervous system, where the available studies indicate that it has key roles in neuronal development and function. DYRK2 regulates neuronal morphogenesis (e.g., axon growth and branching) by phosphorylating cytoskeletal elements (e.g., doublecortin). Comparative data reveals that it is involved in the development of olfactory and visual systems, the spinal cord and possibly the cortex. DYRK2 also participates in processes such as olfaction, vision and, learning. However, DYRK2 could be involved in other brain functions since available expression data shows that it is expressed across the whole brain. High DYRK2 protein levels have been detected in basal ganglia and cerebellum. In adult nervous system, DYRK2 mRNA expression is highest in the cortex, hippocampus, and retina. Regarding nervous system disease, DYRK2 has been implicated in neuroblastoma, glioma, epilepsy, neuroinflammation, Alzheimer's disease, Parkinson's disease, spinal cord injury and virus infection. DYRK2 upregulation usually has a negative impact in cancer-related conditions and a positive impact in non-malignant conditions. Its role in axon growth makes DYRK2 as a promising target for spinal cord or brain injury and regeneration.

Nano-omics: nanotechnology-based multidimensional harvesting of the blood-circulating cancerome

Over the past decade, the development of 'simple' blood tests that enable cancer screening, diagnosis or monitoring and facilitate the design of personalized therapies without the need for invasive tumour biopsy sampling has been a core ambition in cancer research. Data emerging from ongoing biomarker development efforts indicate that multiple markers, used individually or as part of a multimodal panel, are required to enhance the sensitivity and specificity of assays for early stage cancer detection. The discovery of cancer-associated molecular alterations that are reflected in blood at multiple dimensions (genome, epigenome, transcriptome, proteome and metabolome) and integration of the resultant multi-omics data have the potential to uncover novel biomarkers as well as to further elucidate the underlying molecular pathways. Herein, we review key advances in multi-omics liquid biopsy approaches and introduce the 'nano-omics' paradigm: the development and utilization of nanotechnology tools for the enrichment and subsequent omics analysis of the blood-circulating cancerome.

Potential prognosis index for m6A-related mRNA in cholangiocarcinoma

Background

Cholangiocarcinoma (CHOL) is a malignant tumor that originates in the extrahepatic bile duct and can extend from the hilar region to the lower end of the common bile duct. The prognosis of CHOL patients is particularly poor; therefore, in this study, we screened mRNAs correlated with N6-methyladenosine (m⁶A) to construct a risk model for prognosis in CHOL.

Methods

The TCGA-CHOL dataset was applied to obtain and analyze the coexpression of 1281 m⁶A-related mRNAs, from which 14 were selected for further analysis through univariate proportional hazards (cox) regression analysis. Aryl hydrocarbon receptor interacting protein (AIP), CCAAT/enhancer binding protein beta (CEBPB), syndecan1 (SDC1), vacuolar protein sorting 25 homolog (VPS25) and syntaxin binding protein 2 (STXBP2) were then screened out through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to develop a precise m⁶A-related mRNA prognosis risk model (MRMRPM) with an area under curve (AUC) of 0.908 and 0.923 after 1 and 2 years, respectively. We divided the samples into high-risk and low-risk groups using the m⁶A-related mRNA prognosis risk model.

Results

Kaplan–Meier analysis indicated poor overall survival (OS) for the high-risk group. Two Gene Expression Omnibus (GEO) datasets (GSE89748 and GSE107943) were used to validate the risk model. The results of drug sensitivity and immune cell infiltration analysis showed that the risk model could serve as a prognosis index of potential immunotherapeutic characteristics and drug sensitivity. Furthermore, the proportion of resting dendritic cells and regulatory T cells was positively associated with an increased expression of four m⁶A-related mRNAs — AIP, CEBPB, SDC1, and VPS25 — in the high-risk CHOL group.

Conclusions

Our findings suggest that this model can be a prognostic indicator for CHOL patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09665-3.

Deep Single-Cell-Type Proteome Profiling of Mouse Brain by Nonsurgical AAV-Mediated Proximity Labeling

Proteome profiling is a powerful tool in biological and biomedical studies, starting with samples at bulk, single-cell, or single-cell-type levels. Reliable methods for extracting specific cell-type proteomes are in need, especially for the cells (e.g., neurons) that cannot be readily isolated. Here, we present an innovative proximity labeling (PL) strategy for single-cell-type proteomics of mouse brain, in which TurboID (an engineered biotin ligase) is used to label almost all proteins in a specific cell type. This strategy bypasses the requirement of cell isolation and includes five major steps: (i) constructing recombinant adeno-associated viruses (AAVs) to express TurboID driven by cell-type-specific promoters, (ii) delivering the AAV to mouse brains by direct intravenous injection, (iii) enhancing PL labeling by biotin administration, (iv) purifying biotinylated proteins, followed by on-bead protein digestion, and (v) quantitative tandem-mass-tag (TMT) labeling. We first confirmed that TurboID can label a wide range of cellular proteins in human HEK293 cells and optimized the single-cell-type proteomic pipeline. To analyze specific brain cell types, we generated recombinant AAVs to coexpress TurboID and mCherry proteins, driven by neuron- or astrocyte-specific promoters and validated the expected cell expression by coimmunostaining of mCherry and cellular markers. Subsequent biotin purification and TMT analysis identified ∼10,000 unique proteins from a few micrograms of protein samples with excellent reproducibility. Comparative and statistical analyses indicated that these PL proteomes contain cell-type-specific cellular pathways. Although PL was originally developed for studying protein-protein interactions and subcellular proteomes, we extended it to efficiently tag the entire proteomes of specific cell types in the mouse brain using TurboID biotin ligase. This simple, effective in vivo approach should be broadly applicable to single-cell-type proteomics.

Combining selinexor with alisertib to target the p53 pathway in neuroblastoma

Neuroblastoma accounts for 15% of cancer-related deaths in children, highlighting an unmet need for novel therapies. Selinexor is a small molecule inhibitor of XPO1. XPO1 shuffles cargo proteins with a nuclear export sequence from the nucleus to the cytosol, many of which are essential for cancer growth and cell maintenance. We systematically tested the effect of selinexor against neuroblastoma cells in vitro and in vivo and used an advanced proteomic and phosphoproteomic screening approach to interrogate unknown mechanisms of action. We found that selinexor induced its cytotoxic effects in neuroblastoma through the predominantly nuclear accumulation of p53 and global activation of apoptosis pathways. Selinexor also induced p53 phosphorylation at site S315, which is one initiating step for p53 degradation. Since this phosphorylation step is undertaken mostly by aurora kinase A (AURKA), we used the clinically available AURKA inhibitor, alisertib, and found p53-mediated lethality could be further augmented in three orthotopic xenograft mouse models. These findings suggest a potential therapeutic benefit using selinexor and alisertib to synergistically increase p53-mediated cytotoxicity of high-risk neuroblastoma.

Proteomic Profiling of Cerebrospinal Fluid by 16-Plex TMT-Based Mass Spectrometry

Mass spectrometry (MS) has become a mainstream platform for comprehensive profiling of proteome, especially with the improvement of multiplexed tandem mass tag labeling coupled with two-dimensional liquid chromatography and tandem mass spectrometry (TMT-LC/LC-MS/MS). Recently, we have established a robust method for direct profiling of undepleted cerebrospinal fluid (CSF) proteome with the 16-plex TMTpro method, in which we optimized parameters in experimental steps of sample preparation, TMT labeling, LC/LC fractionation, tandem mass spectrometry, and computational data processing. The extensive LC fractionation not only enhances proteome coverage of the CSF but also alleviates ratio distortion of TMT quantification. The crucial quality control steps and improvements specific for the TMT16 analysis are highlighted. More than 3000 proteins can be quantified in a single experiment from 16 different CSF samples. This multiplexed method offers a powerful tool for profiling a variety of complex biofluids samples such as CSF, serum/plasma, and other clinical specimens.

CRISPR screens unveil signal hubs for nutrient licensing of T cell immunity

Nutrients are emerging regulators of adaptive immunity1. Selective nutrients interplay with immunological signals to activate mechanistic target of rapamycin complex 1 (mTORC1), a key driver of cell metabolism2-4, but how these environmental signals are integrated for immune regulation remains unclear. Here we use genome-wide CRISPR screening combined with protein-protein interaction networks to identify regulatory modules that mediate immune receptor- and nutrient-dependent signalling to mTORC1 in mouse regulatory T (Treg) cells. SEC31A is identified to promote mTORC1 activation by interacting with the GATOR2 component SEC13 to protect it from SKP1-dependent proteasomal degradation. Accordingly, loss of SEC31A impairs T cell priming and Treg suppressive function in mice. In addition, the SWI/SNF complex restricts expression of the amino acid sensor CASTOR1, thereby enhancing mTORC1 activation. Moreover, we reveal that the CCDC101-associated SAGA complex is a potent inhibitor of mTORC1, which limits the expression of glucose and amino acid transporters and maintains T cell quiescence in vivo. Specific deletion of Ccdc101 in mouse Treg cells results in uncontrolled inflammation but improved antitumour immunity. Collectively, our results establish epigenetic and post-translational mechanisms that underpin how nutrient transporters, sensors and transducers interplay with immune signals for three-tiered regulation of mTORC1 activity and identify their pivotal roles in licensing T cell immunity and immune tolerance.

Pharmaco-proteogenomic profiling of pediatric diffuse midline glioma to inform future treatment strategies

Diffuse midline glioma (DMG) is a deadly pediatric and adolescent central nervous system (CNS) tumor localized along the midline structures of the brain atop the spinal cord. With a median overall survival (OS) of just 9–11-months, DMG is characterized by global hypomethylation of histone H3 at lysine 27 (H3K27me3), driven by recurring somatic mutations in H3 genes including, HIST1H3B/C (H3.1K27M) or H3F3A (H3.3K27M), or through overexpression of EZHIP in patients harboring wildtype H3. The recent World Health Organization’s 5th Classification of CNS Tumors now designates DMG as, ‘H3 K27-altered’, suggesting that global H3K27me3 hypomethylation is a ubiquitous feature of DMG and drives devastating transcriptional programs for which there are no treatments. H3-alterations co-segregate with various other somatic driver mutations, highlighting the high-level of intertumoral heterogeneity of DMG. Furthermore, DMG is also characterized by very high-level intratumoral diversity with tumors harboring multiple subclones within each primary tumor. Each subclone contains their own combinations of driver and passenger lesions that continually evolve, making precision-based medicine challenging to successful execute. Whilst the intertumoral heterogeneity of DMG has been extensively investigated, this is yet to translate to an increase in patient survival. Conversely, our understanding of the non-genomic factors that drive the rapid growth and fatal nature of DMG, including endogenous and exogenous microenvironmental influences, neurological cues, and the posttranscriptional and posttranslational architecture of DMG remains enigmatic or at best, immature. However, these factors are likely to play a significant role in the complex biological sequelae that drives the disease. Here we summarize the heterogeneity of DMG and emphasize how analysis of the posttranslational architecture may improve treatment paradigms. We describe factors that contribute to treatment response and disease progression, as well as highlight the potential for pharmaco-proteogenomics (i.e., the integration of genomics, proteomics and pharmacology) in the management of this uniformly fatal cancer.

Genomic and Transcriptomic Profiling of Brain Metastases

Simple Summary

Brain metastases (BM) are the most common brain tumors in adults and are the main cause of cancer-associated death. Omics analysis of BM will allow for a better understanding of metastatic progression, prognosis and therapeutic targeting. In this study, BM samples underwent comprehensive molecular profiling with genomics and transcriptomics. Mutational signatures suggested that most mutations were gained prior to metastasis. A novel copy number event centered around the MCL1 gene was found in 75% of all samples. Transcriptomics revealed that melanoma BM formed a distinct cluster in comparison to other subtypes. Poor survival correlated to self-identified black race and absence of radiation treatment but not molecular profiles. These data identify potential new drivers of brain metastatic progression, implicate that melanoma BM are distinctive and likely responsive to unique therapies, and further investigation of sociodemographic and clinical features are needed in BM cohorts.

Abstract

Brain metastases (BM) are the most common brain tumors in adults occurring in up to 40% of all cancer patients. Multi-omics approaches allow for understanding molecular mechanisms and identification of markers with prognostic significance. In this study, we profile 130 BM using genomics and transcriptomics and correlate molecular characteristics to clinical parameters. The most common tumor origins for BM were lung (40%) followed by melanoma (21%) and breast (15%). Melanoma and lung BMs contained more deleterious mutations than other subtypes (p < 0.001). Mutational signatures suggested that the bulk of the mutations were gained before metastasis. A novel copy number event centered around the MCL1 gene was found in 75% of all samples, suggesting a broader role in promoting metastasis. Unsupervised hierarchical cluster analysis of transcriptional signatures available in 65 samples based on the hallmarks of cancer revealed four distinct clusters. Melanoma samples formed a distinctive cluster in comparison to other BM subtypes. Characteristics of molecular profiles did not correlate with survival. However, patients with self-identified black race or those who did not receive radiation correlated with poor survival. These data identify potential new drivers of brain metastatic progression. Our data also suggest further investigation of sociodemographic and clinical features is needed in BM cohorts.

Profiling of Carnitine Shuttle System Intermediates in Gliomas Using Solid-Phase Microextraction (SPME)

Alterations in the carnitine shuttle system may be an indication of the presence of cancer. As such, in-depth analyses of this pathway in different malignant tumors could be important for the detection and treatment of this disease. The current study aims to assess the profiles of carnitine and acylcarnitines in gliomas with respect to their grade, the presence of isocitrate dehydrogenase (IDH) mutations, and 1p/19q co-deletion. Brain tumors obtained from 19 patients were sampled on-site using solid-phase microextraction (SPME) immediately following excision. Analytes were desorbed and then analyzed via liquid chromatography–high-resolution mass spectrometry. The results showed that SPME enabled the extraction of carnitine and 22 acylcarnitines. An analysis of the correlation factor revealed the presence of two separate clusters: short-chain and long-chain carnitine esters. Slightly higher carnitine and acylcarnitine concentrations were observed in the higher-malignancy tumor samples (high vs. low grade) and in those samples with worse projected clinical outcomes (without vs. with IDH mutation; without vs. with 1p/19q co-deletion). Thus, the proposed chemical biopsy approach offers a simple solution for on-site sampling that enables sample preservation, thus supporting comprehensive multi-method analyses.

Acute depletion of CTCF rewires genome-wide chromatin accessibility

BACKGROUND

The transcription factor CTCF appears indispensable in defining topologically associated domain boundaries and maintaining chromatin loop structures within these domains, supported by numerous functional studies. However, acute depletion of CTCF globally reduces chromatin interactions but does not significantly alter transcription.

RESULTS

Here, we systematically integrate multi-omics data including ATAC-seq, RNA-seq, WGBS, Hi-C, Cut&Run, and CRISPR-Cas9 survival dropout screens, and time-solved deep proteomic and phosphoproteomic analyses in cells carrying auxin-induced degron at endogenous CTCF locus. Acute CTCF protein degradation markedly rewires genome-wide chromatin accessibility. Increased accessible chromatin regions are frequently located adjacent to CTCF-binding sites at promoter regions and insulator sites associated with enhanced transcription of nearby genes. In addition, we use CTCF-associated multi-omics data to establish a combinatorial data analysis pipeline to discover CTCF co-regulatory partners. We successfully identify 40 candidates, including multiple established partners. Interestingly, many CTCF co-regulators that have alterations of their respective downstream gene expression do not show changes of their own expression levels across the multi-omics measurements upon acute CTCF loss, highlighting the strength of our system to discover hidden co-regulatory partners associated with CTCF-mediated transcription.

CONCLUSIONS

This study highlights that CTCF loss rewires genome-wide chromatin accessibility, which plays a critical role in transcriptional regulation.

Targeting Neuroinflammation in Brain Cancer: Uncovering Mechanisms, Pharmacological Targets, and Neuropharmaceutical Developments

Gliomas are one of the most lethal types of cancers accounting for ∼80% of all central nervous system (CNS) primary malignancies. Among gliomas, glioblastomas (GBM) are the most aggressive, characterized by a median patient survival of fewer than 15  months. Recent molecular characterization studies uncovered the genetic signatures and methylation status of gliomas and correlate these with clinical prognosis. The most relevant molecular characteristics for the new glioma classification are IDH mutation, chromosome 1p/19q deletion, histone mutations, and other genetic parameters such as ATRX loss, TP53, and TERT mutations, as well as DNA methylation levels. Similar to other solid tumors, glioma progression is impacted by the complex interactions between the tumor cells and immune cells within the tumor microenvironment. The immune system’s response to cancer can impact the glioma’s survival, proliferation, and invasiveness. Salient characteristics of gliomas include enhanced vascularization, stimulation of a hypoxic tumor microenvironment, increased oxidative stress, and an immune suppressive milieu. These processes promote the neuro-inflammatory tumor microenvironment which can lead to the loss of blood-brain barrier (BBB) integrity. The consequences of a compromised BBB are deleteriously exposing the brain to potentially harmful concentrations of substances from the peripheral circulation, adversely affecting neuronal signaling, and abnormal immune cell infiltration; all of which can lead to disruption of brain homeostasis. In this review, we first describe the unique features of inflammation in CNS tumors. We then discuss the mechanisms of tumor-initiating neuro-inflammatory microenvironment and its impact on tumor invasion and progression. Finally, we also discuss potential pharmacological interventions that can be used to target neuro-inflammation in gliomas.

Network-based systems pharmacology reveals heterogeneity in LCK and BCL2 signaling and therapeutic sensitivity of T-cell acute lymphoblastic leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy, and novel therapeutics are much needed. Profiling patient leukemia' drug sensitivities ex vivo, we discovered that 44.4% of childhood and 16.7% of adult T-ALL cases exquisitely respond to dasatinib. Applying network-based systems pharmacology analyses to examine signal circuitry, we identified preTCR-LCK activation as the driver of dasatinib sensitivity, and T-ALL-specific LCK dependency was confirmed in genome-wide CRISPR-Cas9 screens. Dasatinib-sensitive T-ALLs exhibited high BCL-XL and low BCL2 activity and venetoclax resistance. Discordant sensitivity of T-ALL to dasatinib and venetoclax is strongly correlated with T-cell differentiation, particularly with the dynamic shift in LCK vs. BCL2 activation. Finally, single-cell analysis identified leukemia heterogeneity in LCK and BCL2 signaling and T-cell maturation stage, consistent with dasatinib response. In conclusion, our results indicate that developmental arrest in T-ALL drives differential activation of preTCR-LCK and BCL2 signaling in this leukemia, providing unique opportunities for targeted therapy.

Emerging roles of DYRK2 in cancer

Over the last decade, the CMGC kinase DYRK2 has been reported as a tumor suppressor across various cancers triggering major antitumor and proapoptotic signals in breast, colon, liver, ovary, brain, and lung cancers, with lower DYRK2 expression correlated with poorer prognosis in patients. Contrary to this, various medicinal chemistry studies reported robust antiproliferative properties of DYRK2 inhibitors, whereas unbiased 'omics' and genome-wide association study-based studies identified DYRK2 as a highly overexpressed kinase in various patient tumor samples. A major paradigm shift occurred in the last 4 years when DYRK2 was found to regulate proteostasis in cancer via a two-pronged mechanism. DYRK2 phosphorylated and activated the 26S proteasome to enhance degradation of misfolded/tumor-suppressor proteins while also promoting the nuclear stability and transcriptional activity of its substrate, heat-shock factor 1 triggering protein folding. Together, DYRK2 regulates proteostasis and promotes protumorigenic survival for specific cancers. Indeed, potent and selective small-molecule inhibitors of DYRK2 exhibit in vitro and in vivo anti-tumor activity in triple-negative breast cancer and myeloma models. However, with conflicting and contradictory reports across different cancers, the overarching role of DYRK2 remains enigmatic. Specific cancer (sub)types coupled to spatiotemporal interactions with substrates could decide the procancer or anticancer role of DYRK2. The current review aims to provide a balanced and critical appreciation of the literature to date, highlighting top substrates such as p53, c-Myc, c-Jun, heat-shock factor 1, proteasome, or NOTCH1, to discuss DYRK2 inhibitors available to the scientific community and to shed light on this duality of protumorigenic and antitumorigenic roles of DYRK2.

High-Throughput Profiling of Proteome and Posttranslational Modifications by 16-Plex TMT Labeling and Mass Spectrometry

Mass spectrometry (MS)-based proteomic profiling of whole proteome and protein posttranslational modifications (PTMs) is a powerful technology to measure the dynamics of proteome with high throughput and deep coverage. The reproducibility of quantification benefits not only from the fascinating developments in high-performance liquid chromatography (LC) and high-resolution MS with enhanced scan rates but also from the invention of multiplexed isotopic labeling strategies, such as the tandem mass tags (TMT). In this chapter, we introduce a 16-plex TMT-LC/LC-MS/MS protocol for proteomic profiling of biological and clinical samples. The protocol includes protein extraction, enzymatic digestion, PTM peptide enrichment, TMT labeling, and two-dimensional reverse-phase liquid chromatography fractionation coupled with tandem mass spectrometry (MS/MS) analysis, followed by computational data processing. In general, more than 10,000 proteins and tens of thousands of PTM sites (e.g., phosphorylation and ubiquitination) can be confidently quantified. This protocol provides a general protein measurement tool, enabling the dissection of protein dysregulation in any biological samples and human diseases.

Bioinformatics Analysis of Differentially Expressed Genes and miRNAs in Low-Grade Gliomas

Low-grade glioma is the most common type of primary intracranial tumor. In the last 3 years, new observations of molecular precursors in adults with gliomas have led to a modification in the histopathologic classification of these brain tumors. Among the biomarkers that have been highlighted, we have the micro RNAs (miRNAs) which play a crucial role in the regulation of gene expression and the long noncoding RNAs (lncRNAs) controlling various cellular and metabolic pathways. In our study, large-scale data on sequenced RNA and miRNAs from 516 patients were obtained from the Cancer Genome Atlas database by the TCGAbiolinks package. We identified the differential expression of miRNAs and genes using the Limma package and then we used the ClusterProfiler package for annotations of the biological pathways of the expressed genes, the survival package to estimate the survival analysis, and the GDCRNATools package to determine miRNAs-genes and miRNAs-lncRNAs interactions. We obtained a significant correlation between the miRNAs identified and the overall survival of the patients (log-rank P < .05) and we have theoretically proposed a novel network of miRNAs involved in low-grade gliomas, specifically astrocytomas and oligodendrogliomas, which combine both genes and lncRNAs.

Argonaut: A Web Platform for Collaborative Multi-omic Data Visualization and Exploration

Researchers now generate large multi-omic datasets using increasingly mature mass spectrometry techniques at an astounding pace, facing new challenges of "Big Data" dissemination, visualization, and exploration. Conveniently, web-based data portals accommodate the complexity of multi-omic experiments and the many experts involved. However, developing these tailored companion resources requires programming expertise and knowledge of web server architecture-a substantial burden for most. Here, we describe Argonaut, a simple, code-free, and user-friendly platform for creating customizable, interactive data-hosting websites. Argonaut carries out real-time statistical analyses of the data, which it organizes into easily sharable projects. Collaborating researchers worldwide can explore the results, visualized through popular plots, and modify them to streamline data interpretation. Increasing the pace and ease of access to multi-omic data, Argonaut aims to propel discovery of new biological insights. We showcase the capabilities of this tool using a published multi-omics dataset on the large mitochondrial protease deletion collection.

High-throughput and Deep-proteome Profiling by 16-plex Tandem Mass Tag Labeling Coupled with Two-dimensional Chromatography and Mass Spectrometry

Isobaric tandem mass tag (TMT) labeling is widely used in proteomics because of its high multiplexing capacity and deep proteome coverage. Recently, an expanded 16-plex TMT method has been introduced, which further increases the throughput of proteomic studies. In this manuscript, we present an optimized protocol for 16-plex TMT-based deep-proteome profiling, including protein sample preparation, enzymatic digestion, TMT labeling reaction, two-dimensional reverse-phase liquid chromatography (LC/LC) fractionation, tandem mass spectrometry (MS/MS), and computational data processing. The crucial quality control steps and improvements in the process specific for the 16-plex TMT analysis are highlighted. This multiplexed process offers a powerful tool for profiling a variety of complex samples such as cells, tissues, and clinical specimens. More than 10,000 proteins and posttranslational modifications such as phosphorylation, methylation, acetylation, and ubiquitination in highly complex biological samples from up to 16 different samples can be quantified in a single experiment, providing a potent tool for basic and clinical research.

Integrated analysis of ultra-deep proteomes in cortex, cerebrospinal fluid and serum reveals a mitochondrial signature in Alzheimer's disease

BACKGROUND

Based on amyloid cascade and tau hypotheses, protein biomarkers of different Aβ and tau species in cerebrospinal fluid (CSF) and blood/plasma/serum have been examined to correlate with brain pathology. Recently, unbiased proteomic profiling of these human samples has been initiated to identify a large number of novel AD biomarker candidates, but it is challenging to define reliable candidates for subsequent large-scale validation.

METHODS

We present a comprehensive strategy to identify biomarker candidates of high confidence by integrating multiple proteomes in AD, including cortex, CSF and serum. The proteomes were analyzed by the multiplexed tandem-mass-tag (TMT) method, extensive liquid chromatography (LC) fractionation and high-resolution tandem mass spectrometry (MS/MS) for ultra-deep coverage. A systems biology approach was used to prioritize the most promising AD signature proteins from all proteomic datasets. Finally, candidate biomarkers identified by the MS discovery were validated by the enzyme-linked immunosorbent (ELISA) and TOMAHAQ targeted MS assays.

RESULTS

We quantified 13,833, 5941, and 4826 proteins from human cortex, CSF and serum, respectively. Compared to other studies, we analyzed a total of 10 proteomic datasets, covering 17,541 proteins (13,216 genes) in 365 AD, mild cognitive impairment (MCI) and control cases. Our ultra-deep CSF profiling of 20 cases uncovered the majority of previously reported AD biomarker candidates, most of which, however, displayed no statistical significance except SMOC1 and TGFB2. Interestingly, the AD CSF showed evident decrease of a large number of mitochondria proteins that were only detectable in our ultra-deep analysis. Further integration of 4 cortex and 4 CSF cohort proteomes highlighted 6 CSF biomarkers (SMOC1, C1QTNF5, OLFML3, SLIT2, SPON1, and GPNMB) that were consistently identified in at least 2 independent datasets. We also profiled CSF in the 5xFAD mouse model to validate amyloidosis-induced changes, and found consistent mitochondrial decreases (SOD2, PRDX3, ALDH6A1, ETFB, HADHA, and CYB5R3) in both human and mouse samples. In addition, comparison of cortex and serum led to an AD-correlated protein panel of CTHRC1, GFAP and OLFM3. In summary, 37 proteins emerged as potential AD signatures across cortex, CSF and serum, and strikingly, 59% of these were mitochondria proteins, emphasizing mitochondrial dysfunction in AD. Selected biomarker candidates were further validated by ELISA and TOMAHAQ assays. Finally, we prioritized the most promising AD signature proteins including SMOC1, TAU, GFAP, SUCLG2, PRDX3, and NTN1 by integrating all proteomic datasets.

CONCLUSIONS

Our results demonstrate that novel AD biomarker candidates are identified and confirmed by proteomic studies of brain tissue and biofluids, providing a rich resource for large-scale biomarker validation for the AD community.

Molecular and clinicopathologic features of gliomas harboring NTRK fusions

Fusions involving neurotrophic tyrosine receptor kinase (NTRK) genes are detected in ≤2% of gliomas and can promote gliomagenesis. The remarkable therapeutic efficacy of TRK inhibitors, which are among the first Food and Drug Administration-approved targeted therapies for NTRK-fused gliomas, has generated significant clinical interest in characterizing these tumors. In this multi-institutional retrospective study of 42 gliomas with NTRK fusions, next generation DNA sequencing (n = 41), next generation RNA sequencing (n = 1), RNA-sequencing fusion panel (n = 16), methylation profile analysis (n = 18), and histologic evaluation (n = 42) were performed. All infantile NTRK-fused gliomas (n = 7) had high-grade histology and, with one exception, no other significant genetic alterations. Pediatric NTRK-fused gliomas (n = 13) typically involved NTRK2, ranged from low- to high-histologic grade, and demonstrated histologic overlap with desmoplastic infantile ganglioglioma, pilocytic astrocytoma, ganglioglioma, and glioblastoma, among other entities, but they rarely matched with high confidence to known methylation class families or with each other; alterations involving ATRX, PTEN, and CDKN2A/2B were present in a subset of cases. Adult NTRK-fused gliomas (n = 22) typically involved NTRK1 and had predominantly high-grade histology; genetic alterations involving IDH1, ATRX, TP53, PTEN, TERT promoter, RB1, CDKN2A/2B, NF1, and polysomy 7 were common. Unsupervised principal component analysis of methylation profiles demonstrated no obvious grouping by histologic grade, NTRK gene involved, or age group. KEGG pathway analysis detected methylation differences in genes involved in PI3K/AKT, MAPK, and other pathways. In summary, the study highlights the clinical, histologic, and molecular heterogeneity of NTRK-fused gliomas, particularly when stratified by age group.

Advances in the Knowledge of the Molecular Biology of Glioblastoma and Its Impact in Patient Diagnosis, Stratification, and Treatment

Gliomas are the most common primary brain tumors in adults. They arise in the glial tissue and primarily occur in the brain. Low-grade tumors of World Health Organization (WHO) grade II tend to progress to high-grade gliomas of WHO grade III and, eventually, glioblastoma of WHO grade IV, which is the most common and deadly glioma, with a median survival of 12-15 months after final diagnosis. Knowledge of the molecular biology and genetics of glioblastoma has increased significantly in the past few years, giving rise to classification methods that can help in management and stratification of glioblastoma patients. However, glioblastoma remains an incurable disease. Glioblastoma cells have acquired genetic and metabolic adaptations in order to sustain tumor growth and progression, including changes in energetic metabolism, invasive capacity, migration, and angiogenesis, that make it very difficult to find suitable therapeutic targets and to develop effective drugs. The current standard of care for glioblastoma patients is surgery followed by radiotherapy plus concomitant and adjuvant chemotherapy with temozolomide. Although progress in glioblastoma therapies in recent years has been more limited than in other tumors, numerous drugs and targets are being proposed and many clinical trials are underway to develop effective subtype-specific treatments.

Innovation and strategic orientations for the development of advanced biorefineries

Advanced biorefineries, which aim at valorizing biomass (from agriculture, forestry, aquaculture, among others) into a wide spectrum of products and bioenergy, are seen today as key to implement a sustainable biobased economy. Although different concepts of biorefinery are currently under development, further research and improvement are still required to obtain environmentally friendly and economically feasible commercial scale biorefineries. Valorization of all biomass components and integration of different disciplines are some of the strategies that have been considered to improve the economic and environmental performance. This paper summarizes and discusses the most recent innovations and strategic orientations for the development of advanced biorefineries. Focus is given on the valorization of non-carbohydrate components of biomass (protein, acetic acid and lignin), on-site and tailor-made production of enzymes, big data analytics, and interdisciplinary efforts. The idea is to provide new insights and directions to support the development and large-scale implementation of biorefineries.

Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer's Disease Progression

Alzheimer's disease (AD) displays a long asymptomatic stage before dementia. We characterize AD stage-associated molecular networks by profiling 14,513 proteins and 34,173 phosphosites in the human brain with mass spectrometry, highlighting 173 protein changes in 17 pathways. The altered proteins are validated in two independent cohorts, showing partial RNA dependency. Comparisons of brain tissue and cerebrospinal fluid proteomes reveal biomarker candidates. Combining with 5xFAD mouse analysis, we determine 15 Aβ-correlated proteins (e.g., MDK, NTN1, SMOC1, SLIT2, and HTRA1). 5xFAD shows a proteomic signature similar to symptomatic AD but exhibits activation of autophagy and interferon response and lacks human-specific deleterious events, such as downregulation of neurotrophic factors and synaptic proteins. Multi-omics integration prioritizes AD-related molecules and pathways, including amyloid cascade, inflammation, complement, WNT signaling, TGF-β and BMP signaling, lipid metabolism, iron homeostasis, and membrane transport. Some Aβ-correlated proteins are colocalized with amyloid plaques. Thus, the multilayer omics approach identifies protein networks during AD progression.

How to interpret and integrate multi-omics data at systems level

Current parallel sequencing technologies generate biological sequence data explosively and enable omics studies that analyze collective biological features. The more omics data that is accumulated, the more they show the regulatory complexity of biological phenotypes. This high order regulatory complexity needs systems-level approaches, including network analysis, to understand it. There are a series of layers in the omics field that are closely connected to each other as described in ‘central dogma.’ We, therefore, have to not only interpret each single omics layer but also to integrate multi-omics layers systematically to get a full picture of the regulatory landscape of the biological phenotype. Especially, individual omics data has their own adequate biological network to apply systematic analysis appropriately. A full regulatory landscape can only be obtained when multi-omics data are incorporated within adequate networks. In this review, we discuss how to interpret and integrate multi-omics data systematically using recent studies. We also propose an analysis framework for systematic multi-omics interpretation by centering on the transcriptional core regulator, which can be incorporated in all omics networks.

MicroRNA-346 inhibits the growth of glioma by directly targeting NFIB

Background

Glioma is considered one of the most common tumors and has a poor prognosis. Recently, microRNAs (miRNAs) have been reported to be strongly linked to various human tumors including glioma. In this study, we investigated a new anticancer miRNA, miR-346, to determine the effects and mechanism of miR-346 and its downstream target gene NFIB on tumors.

Methods

Lentivirus transfection, real-time PCR, western blotting, immunohistochemistry, cell proliferation assays, and mouse experiments were used to examine the relationship between miR-346 and its regulation of NFIB in glioma cells.

Results

The expression of miR-346 was downregulated in glioma cells. Overexpression of miR-346 arrested the cell cycle of glioma cells and inhibited their proliferation in vitro and in vivo. NFIB was a direct target of miR-346, whose expression was reduced by the miRNA. Overexpression of NFIB reversed all tested functions of miR-346.

Conclusion

miR-346 inhibited the growth of glioma cells by targeting NFIB and may be a new prognostic and diagnostic biomarker for glioma.