Integrative multi-omics networks identify PKCδ and DNA-PK as master kinases of glioblastoma subtypes and guide targeted cancer therapy

Development and therapeutic potential of DNA-dependent protein kinase inhibitors

The deployment of DNA damage response (DDR) combats various forms of DNA damage, ensuring genomic stability. Cancer cells' propensity for genomic instability offers therapeutic opportunities to selectively kill cancer cells by suppressing the DDR pathway. DNA-dependent protein kinase (DNA-PK), a nuclear serine/threonine kinase, is crucial for the non-homologous end joining (NHEJ) pathway in the repair of DNA double-strand breaks (DSBs). Therefore, targeting DNA-PK is a promising cancer treatment strategy. This review elaborates on the structures of DNA-PK and its related large protein, as well as the development process of DNA-PK inhibitors, and recent advancements in their clinical application. We emphasize our analysis of the development process and structure-activity relationships (SARs) of DNA-PK inhibitors based on different scaffolds. We hope this review will provide practical information for researchers seeking to develop novel DNA-PK inhibitors in the future.

Current status of precision oncology in adult glioblastoma

The concept of precision oncology, the application of targeted drugs based on comprehensive molecular profiling, has revolutionized treatment strategies in oncology. This review summarizes the current status of precision oncology in glioblastoma (GBM), the most common and aggressive primary brain tumor in adults with a median survival below 2 years. Targeted treatments without prior target verification have consistently failed. Patients with BRAF V600E-mutated GBM benefit from BRAF/MEK-inhibition, whereas targeting EGFR alterations was unsuccessful due to poor tumor penetration, tumor cell heterogeneity, and pathway redundancies. Systematic screening for actionable molecular alterations resulted in low rates (< 10%) of targeted treatments. Efficacy was observed in one-third and currently appears to be limited to BRAF-, VEGFR-, and mTOR-directed treatments. Advancing precision oncology for GBM requires consideration of pathways instead of single alterations, new trial concepts enabling rapid and adaptive drug evaluation, a focus on drugs with sufficient bioavailability in the CNS, and the extension of target discovery and validation to the tumor microenvironment, tumor cell networks, and their interaction with immune cells and neurons.

Triggering receptor expressed on myeloid cells 2 (TREM2) regulates phagocytosis in glioblastoma

BACKGROUND

Glioblastomas (GBMs) are central nervous system tumors that resist standard-of-care interventions and even immune checkpoint blockade. Myeloid cells in the tumor microenvironment can contribute to GBM progression; therefore, emerging immunotherapeutic approaches include reprogramming these cells to achieve desirable antitumor activity. Triggering receptor expressed on myeloid cells 2 (TREM2) is a myeloid signaling regulator that has been implicated in a variety of cancers and neurological diseases with contrasting functions, but its role in GBM immunopathology and progression is still under investigation.

METHODS

Our reverse translational investigations leveraged single-cell RNA sequencing and cytometry of human gliomas to characterize TREM2 expression across myeloid subpopulations. Using 2 distinct murine glioma models, we examined the role of Trem2 on tumor progression and immune modulation of myeloid cells. Furthermore, we designed a method of tracking phagocytosis of glioma cells in vivo and employed in vitro assays to mechanistically understand the influence of TREM2 signaling on tumor uptake.

RESULTS

We discovered that TREM2 expression does not correlate with immunosuppressive pathways, but rather showed strong a positive association with the canonical phagocytosis markers lysozyme (LYZ) and macrophage scavenger receptor (CD163) in gliomas. While Trem2 deficiency was found to be dispensable for gliomagenesis, Trem2+ myeloid cells display enhanced tumor uptake compared to Trem2- cells. Mechanistically, we demonstrate that TREM2 mediates phagocytosis via Syk signaling.

CONCLUSIONS

These results indicate that TREM2 is not associated with immunosuppression in gliomas. Instead, TREM2 is an important regulator of phagocytosis that may be exploited as a potential therapeutic strategy for brain tumors.

Artificial intelligence in neurology: opportunities, challenges, and policy implications

Neurological conditions are the leading cause of disability and mortality combined, demanding innovative, scalable, and sustainable solutions. Brain health has become a global priority with adoption of the World Health Organization's Intersectoral Global Action Plan in 2022. Simultaneously, rapid advancements in artificial intelligence (AI) are revolutionizing neurological research and practice. This scoping review of 66 original articles explores the value of AI in neurology and brain health, systematizing the landscape for emergent clinical opportunities and future trends across the care trajectory: prevention, risk stratification, early detection, diagnosis, management, and rehabilitation. AI's potential to advance personalized precision neurology and global brain health directives hinges on resolving core challenges across four pillars-models, data, feasibility/equity, and regulation/innovation-through concerted pursuit of targeted recommendations. Paramount actions include swift, ethical, equity-focused integration of novel technologies into clinical workflows, mitigating data-related issues, counteracting digital inequity gaps, and establishing robust governance frameworks balancing safety and innovation.

VC-resist glioblastoma cell state: vessel co-option as a key driver of chemoradiation resistance

Glioblastoma (GBM) is a highly lethal type of cancer. GBM recurrence following chemoradiation is typically attributed to the regrowth of invasive and resistant cells. Therefore, there is a pressing need to gain a deeper understanding of the mechanisms underlying GBM resistance to chemoradiation and its ability to infiltrate. Using a combination of transcriptomic, proteomic, and phosphoproteomic analyses, longitudinal imaging, organotypic cultures, functional assays, animal studies, and clinical data analyses, we demonstrate that chemoradiation and brain vasculature induce cell transition to a functional state named VC-Resist (vessel co-opting and resistant cell state). This cell state is midway along the transcriptomic axis between proneural and mesenchymal GBM cells and is closer to the AC/MES1-like state. VC-Resist GBM cells are highly vessel co-opting, allowing significant infiltration into the surrounding brain tissue and homing to the perivascular niche, which in turn induces even more VC-Resist transition. The molecular and functional characteristics of this FGFR1-YAP1-dependent GBM cell state, including resistance to DNA damage, enrichment in the G2M phase, and induction of senescence/stemness pathways, contribute to its enhanced resistance to chemoradiation. These findings demonstrate how vessel co-option, perivascular niche, and GBM cell plasticity jointly drive resistance to therapy during GBM recurrence.

Pachyonychia Congenita: A Research Agenda Leading to New Therapeutic Approaches

Pachyonychia congenita (PC) is a dominantly inherited genetic disorder of cornification. PC stands out among other genodermatoses because despite its rarity, it has been the focus of a very large number of pioneering translational research efforts over the past 2 decades, mostly driven by a patient support organization, the Pachyonychia Congenita Project. These efforts have laid the ground for innovative strategies that may broadly impact approaches to the management of other inherited cutaneous and noncutaneous diseases. This article outlines current avenues of research in PC, expected outcomes, and potential hurdles.

Integration of polygenic and gut metagenomic risk prediction for common diseases

Multiomics has shown promise in noninvasive risk profiling and early detection of various common diseases. In the present study, in a prospective population-based cohort with ~18 years of e-health record follow-up, we investigated the incremental and combined value of genomic and gut metagenomic risk assessment compared with conventional risk factors for predicting incident coronary artery disease (CAD), type 2 diabetes (T2D), Alzheimer disease and prostate cancer. We found that polygenic risk scores (PRSs) improved prediction over conventional risk factors for all diseases. Gut microbiome scores improved predictive capacity over baseline age for CAD, T2D and prostate cancer. Integrated risk models of PRSs, gut microbiome scores and conventional risk factors achieved the highest predictive performance for all diseases studied compared with models based on conventional risk factors alone. The present study demonstrates that integrated PRSs and gut metagenomic risk models improve the predictive value over conventional risk factors for common chronic diseases.

Advanced Imaging in the Diagnosis and Response Assessment of High-Grade Glioma: AJR Expert Panel Narrative Review

This AJR Expert Panel Narrative explores the current status of advanced MRI and PET techniques for the post-therapeutic response assessment of high-grade adult-type gliomas, focusing on ongoing clinical controversies in current practice. Discussed techniques that complement conventional MRI and aid the differentiation of recurrent tumor from post-treatment effects include DWI and diffusion tensor imaging; perfusion MRI techniques including dynamic susceptibility contrast (DSC), dynamic contrast-enhanced MRI, and arterial spin labeling; MR spectroscopy including assessment of 2-hydroxyglutarate (2HG) concentration; glucose- and amino acid (AA)-based PET; and amide proton transfer imaging. Updated criteria for Response Assessment in Neuro-Oncology are presented. Given the abundant supporting clinical evidence, the panel supports a recommendation that routine response assessment after HGG treatment should include perfusion MRI, particularly given the development of a consensus recommended DSC-MRI protocol. Although published studies support 2HG MRS and AA PET, these techniques' widespread adoption will likely require increased availability (for 2HG MRS) or increased insurance funding in the United States (for AA PET). The article concludes with a series of consensus opinions from the author panel, centered on the clinical integration of the advanced imaging techniques into posttreatment surveillance protocols.

Integrated proteogenomic characterization of glioblastoma evolution

The evolutionary trajectory of glioblastoma (GBM) is a multifaceted biological process that extends beyond genetic alterations alone. Here, we perform an integrative proteogenomic analysis of 123 longitudinal glioblastoma pairs and identify a highly proliferative cellular state at diagnosis and replacement by activation of neuronal transition and synaptogenic pathways in recurrent tumors. Proteomic and phosphoproteomic analyses reveal that the molecular transition to neuronal state at recurrence is marked by post-translational activation of the wingless-related integration site (WNT)/ planar cell polarity (PCP) signaling pathway and BRAF protein kinase. Consistently, multi-omic analysis of patient-derived xenograft (PDX) models mirror similar patterns of evolutionary trajectory. Inhibition of B-raf proto-oncogene (BRAF) kinase impairs both neuronal transition and migration capability of recurrent tumor cells, phenotypic hallmarks of post-therapy progression. Combinatorial treatment of temozolomide (TMZ) with BRAF inhibitor, vemurafenib, significantly extends the survival of PDX models. This study provides comprehensive insights into the biological mechanisms of glioblastoma evolution and treatment resistance, highlighting promising therapeutic strategies for clinical intervention.

Integrative deep learning framework predicts lipidomics-based investigation of preservatives on meat nutritional biomarkers and metabolic pathways

Preservatives are added as antimicrobial agents to extend the shelf life of meat. Adding preservatives to meat products can affect their flavor and nutrition. This review clarifies the effects of preservatives on metabolic pathways and network molecular transformations in meat products based on lipidomics, metabolomics and proteomics analyses. Preservatives change the nutrient content of meat products via altering ionic strength and pH to influence enzyme activity. Ionic strength in salt triggers muscle triglyceride hydrolysis by causing phosphorylation and lipid droplet splitting in adipose tissue hormone-sensitive lipase and triglyceride lipase. DisoLipPred exploiting deep recurrent networks and transfer learning can predict the lipid binding trend of each amino acid in the disordered region of input protein sequences, which could provide omics analyses of biomarkers metabolic pathways in meat products. While conventional meat quality assessment tools are unable to elucidate the intrinsic mechanisms and pathways of variables in the influences of preservatives on the quality of meat products, the promising application of omics techniques in food analysis and discovery through multimodal learning prediction algorithms of neural networks (e.g., deep neural network, convolutional neural network, artificial neural network) will drive the meat industry to develop new strategies for food spoilage prevention and control.

Molecular signature to predict quality of life and survival with glioblastoma using Multiview omics model

Glioblastoma multiforme (GBM) patients show a variety of signs and symptoms that affect their quality of life (QOL) and self-dependence. Since most existing studies have examined prognostic factors based only on clinical factors, there is a need to consider the value of integrating multi-omics data including gene expression and proteomics with clinical data in identifying significant biomarkers for GBM prognosis. Our research aimed to isolate significant features that differentiate between short-term (≤ 6 months) and long-term (≥ 2 years) GBM survival, and between high Karnofsky performance scores (KPS ≥ 80) and low (KPS ≤ 60), using the iterative random forest (iRF) algorithm. Using the Cancer Genomic Atlas (TCGA) database, we identified 35 molecular features composed of 19 genes and 16 proteins. Our findings propose molecular signatures for predicting GBM prognosis and will improve clinical decisions, GBM management, and drug development.

The latent HIV reservoir: current advances in genetic sequencing approaches

Multiple cellular HIV reservoirs in diverse anatomical sites can undergo clonal expansion and persist for years despite suppressive antiretroviral therapy, posing a major barrier toward an HIV cure. Commonly adopted assays to assess HIV reservoir size mainly consist of PCR-based measures of cell-associated total proviral DNA, intact proviruses and transcriptionally competent provirus (viral RNA), flow cytometry and microscopy-based methods to measure translationally competent provirus (viral protein), and quantitative viral outgrowth assay, the gold standard to measure replication-competent provirus; yet no assay alone can provide a comprehensive view of the total HIV reservoir or its dynamics. Furthermore, the detection of extant provirus by these measures does not preclude defects affecting replication competence. An accurate measure of the latent reservoir is essential for evaluating the efficacy of HIV cure strategies. Recent approaches have been developed, which generate proviral sequence data to create a more detailed profile of the latent reservoir. These sequencing approaches are valuable tools to understand the complex multicellular processes in a diverse range of tissues and cell types and have provided insights into the mechanisms of HIV establishment and persistence. These advancements over previous sequencing methods have allowed multiplexing and new assays have emerged, which can document transcriptional activity, chromosome accessibility, and in-depth cellular phenotypes harboring latent HIV, enabling the characterization of rare infected cells across restrictive sites such as the brain. In this manuscript, we provide a review of HIV sequencing-based assays adopted to address challenges in quantifying and characterizing the latent HIV reservoir.

Molecular classification of hormone receptor-positive HER2-negative breast cancer

Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most prevalent type of breast cancer, in which endocrine therapy resistance and distant relapse remain unmet challenges. Accurate molecular classification is urgently required for guiding precision treatment. We established a large-scale multi-omics cohort of 579 patients with HR+/HER2- breast cancer and identified the following four molecular subtypes: canonical luminal, immunogenic, proliferative and receptor tyrosine kinase (RTK)-driven. Tumors of these four subtypes showed distinct biological and clinical features, suggesting subtype-specific therapeutic strategies. The RTK-driven subtype was characterized by the activation of the RTK pathways and associated with poor outcomes. The immunogenic subtype had enriched immune cells and could benefit from immune checkpoint therapy. In addition, we developed convolutional neural network models to discriminate these subtypes based on digital pathology for potential clinical translation. The molecular classification provides insights into molecular heterogeneity and highlights the potential for precision treatment of HR+/HER2- breast cancer.

Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures

Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution. Infiltrative NE tumor is alternatively enriched with tumor cells exhibiting neuronal or glycolytic/plurimetabolic cellular states, two principal transcriptomic pathway-based glioma subtypes, which respectively demonstrate abundant private mutations or enrichment in immune cell signatures. These NE phenotypes are non-invasively identified through normalized K2 imaging signatures, which discern cell size heterogeneity on dynamic susceptibility contrast (DSC)-MRI. NE tumor populations predicted to display increased cellular proliferation by mean diffusivity (MD) MRI metrics are uniquely associated with EGFR amplification and CDKN2A homozygous deletion. The biophysical mapping of infiltrative HGG potentially enables the clinical recognition of tumor subpopulations with aggressive molecular signatures driving tumor progression, thereby informing precision medicine targeting.

Applications of multi-omics analysis in human diseases

Multi-omics usually refers to the crossover application of multiple high-throughput screening technologies represented by genomics, transcriptomics, single-cell transcriptomics, proteomics and metabolomics, spatial transcriptomics, and so on, which play a great role in promoting the study of human diseases. Most of the current reviews focus on describing the development of multi-omics technologies, data integration, and application to a particular disease; however, few of them provide a comprehensive and systematic introduction of multi-omics. This review outlines the existing technical categories of multi-omics, cautions for experimental design, focuses on the integrated analysis methods of multi-omics, especially the approach of machine learning and deep learning in multi-omics data integration and the corresponding tools, and the application of multi-omics in medical researches (e.g., cancer, neurodegenerative diseases, aging, and drug target discovery) as well as the corresponding open-source analysis tools and databases, and finally, discusses the challenges and future directions of multi-omics integration and application in precision medicine. With the development of high-throughput technologies and data integration algorithms, as important directions of multi-omics for future disease research, single-cell multi-omics and spatial multi-omics also provided a detailed introduction. This review will provide important guidance for researchers, especially who are just entering into multi-omics medical research.