Summary We leveraged IDH wild-type glioblastomas, derivative neurospheres, and single cell gene expression profiles to define three tumor-intrinsic transcriptional subtypes designated as proneural, mesenchymal, and classical. Transcriptomic subtype multiplicity correlated with increased intratumoral heterogeneity and presence of tumor microenvironment. In silico cell sorting identified macrophages/microglia, CD4+ T lymphocytes, and neutrophils in the glioma microenvironment. NF1 deficiency resulted in increased tumor-associated macrophages/microglia infiltration. Longitudinal transcriptome analysis showed that expression subtype is retained in 55% of cases. Gene signature-based tumor microenvironment inference revealed a decrease in invading monocytes and a subtype-dependent increase in macrophages/microglia cells upon disease recurrence. Hypermutation at diagnosis or at recurrence associated with CD8+ T cell enrichment. Frequency of M2 macrophages detection associated with short-term relapse after radiation therapy.

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Tumor recurrence following treatment is the major cause of mortality for glioblastoma multiforme (GBM) patients. Thus, insights on the evolutionary process at recurrence are critical for improved patient care. Here, we describe our genomic analyses of the initial and recurrent tumor specimens from each of 38 GBM patients. A substantial divergence in the landscape of driver alterations was associated with distant appearance of a recurrent tumor from the initial tumor, suggesting that the genomic profile of the initial tumor can mislead targeted therapies for the distally recurred tumor. In addition, in contrast to IDH1-mutated gliomas, IDH1-wild-type primary GBMs rarely developed hypermutation following temozolomide (TMZ) treatment, indicating low risk for TMZ-induced hypermutation for these tumors under the standard regimen.

Graphical AbstractHighlights d Characterization of the mutational landscape of secondary glioblastoma d Clonal and subclonal METex14 promote glioma progression and mark worse prognosis d PLB-1001 is a highly selective, efficient, and BBB-permeable MET kinase inhibitor d PLB-1001 provides a safe and efficacious therapeutic approach for glioma treatment SUMMARY Low-grade gliomas almost invariably progress into secondary glioblastoma (sGBM) with limited therapeutic option and poorly understood mechanism. By studying the mutational landscape of 188 sGBMs, we find significant enrichment of TP53 mutations, somatic hypermutation, MET-exon-14-skipping (METex14), PTPRZ1-MET (ZM) fusions, and MET amplification. Strikingly, METex14 frequently co-occurs with ZM fusion and is present in $14% of cases with significantly worse prognosis. Subsequent studies show that METex14 promotes glioma progression by prolonging MET activity. Furthermore, we describe a MET kinase inhibitor, PLB-1001, that demonstrates remarkable potency in selectively inhibiting MET-altered tumor cells in preclinical models. Importantly, this compound also shows blood-brain barrier permeability and is subsequently applied in a phase I clinical trial that enrolls MET-altered chemo-resistant glioma patients. Encouragingly, PLB-1001 achieves partial response in at least two advanced sGBM patients with rarely significant side effects, underscoring the clinical potential for precisely treating gliomas using this therapy.

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As a futuristic diagnosis platform, breath analysis is gaining much attention because it is a noninvasive, simple, and low cost diagnostic method. Very promising clinical applications have been demonstrated for diagnostic purposes by correlation analysis between exhaled breath components and specific diseases. In addition, diverse breath molecules, which serve as biomarkers for specific diseases, are precisely identified by statistical pattern recognition studies. To further improve the accuracy of breath analysis as a diagnostic tool, breath sampling, biomarker sensing, and data analysis should be optimized. In particular, development of high performance breath sensors, which can detect biomarkers at the ppb-level in exhaled breath, is one of the most critical challenges. Due to the presence of numerous interfering gas species in exhaled breath, selective detection of specific biomarkers is also important. This Account focuses on chemiresistive type breath sensors with exceptionally high sensitivity and selectivity that were developed by combining hollow protein templated nanocatalysts with electrospun metal oxide nanostructures. Nanostructures with high surface areas are advantageous in achieving high sensitivity because the sensing signal is dominated by the surface reaction between the sensing layers and the target biomarkers. Furthermore, macroscale pores between one-dimensional (1D) nanostructures can facilitate fast gas diffusion into the sensing layers. To further enhance the selectivity, catalytic functionalization of the 1D metal oxide nanostructure is essential. However, the majority of conventional techniques for catalytic functionalization have failed to achieve a high degree of dispersion of nanoscale catalysts due to aggregation on the surface of the metal oxide, which severely deteriorates the sensing properties by lowering catalytic activity. This issue has led to extensive studies on monolithically dispersed nanoscale particles on metal oxides to maximize the catalytic performances. As a pioneering technique, a bioinspired templating route using apoferritin, that is, a hollow protein cage, has been proposed to obtain nanoscale (∼2 nm) catalyst particles with high dispersity. Nanocatalysts encapsulated by a protein shell were first used in chemiresistive type breath sensors for catalyst functionalization on 1D metal oxide structures. We discuss the robustness and versatility of the apoferrtin templating route for creating highly dispersive catalytic NPs including single components (Au, Pt, Pd, Rh, Ag, Ru, Cu, and La) and bimetallic catalysts (PtY and PtCo), as well as the core-shell structure of Au-Pd (Au-core@Pd-shell). The use of these catalysts is essential to establish high performance sensors arrays for the pattern recognition of biomarkers. In addition, novel multicomponent catalysts provide unprecedented sensitivity and selectivity. With this in mind, we discuss diverse synthetic routes for nanocatalysts using apoferritin and the formation of various catalyst-1D metal oxide composite nanos...

Hydrogen (H 2 ) is one of the next-generation energy sources because it is abundant in nature and has a high combustion efficiency that produces environmentally benign products (H 2 O). However, H 2 /air mixtures are explosive at H 2 concentrations above 4%, thus any leakage of H 2 must be rapidly and reliably detected at much lower concentrations to ensure safety. Among the various types of H 2 sensors, chemiresistive sensors are one of the most promising sensing systems due to their simplicity and low cost. This review highlights the advances in H 2 chemiresistors, including metal-, semiconducting metal oxide-, carbon-based materials, and other materials. The underlying sensing mechanisms for different types of materials are discussed, and the correlation of sensing performances with nanostructures, surface chemistry, and electronic properties is presented. In addition, the discussion of each material emphasizes key advances and strategies to develop superior H 2 sensors. Furthermore, recent key advances in other types of H 2 sensors are briefly discussed. Finally, the review concludes with a brief outlook, perspective, and future directions.

Achieving an improved understanding of catalyst properties, with ability to predict new catalytic materials, is key to overcoming the inherent limitations of metal oxide based gas sensors associated with rather low sensitivity and selectivity, particularly under highly humid conditions. This study introduces newly designed bimetallic nanoparticles (NPs) employing bimetallic Pt-based NPs (PtM, where M = Pd, Rh, and Ni) via a protein encapsulating route supported on mesoporous WO nanofibers. These structures demonstrate unprecedented sensing performance for detecting target biomarkers (even at p.p.b. levels) in highly humid exhaled breath. Sensor arrays are further employed to enable pattern recognition capable of discriminating between simulated biomarkers and controlled breath. The results provide a new class of multicomponent catalytic materials, demonstrating potential for achieving reliable breath analysis sensing.