Multiplexed RNA profiling by regenerative catalysis enables blood-based subtyping of brain tumors.

Current technologies to subtype glioblastoma (GBM), the most lethal brain tumor, require highly invasive brain biopsies. Here, we develop a dedicated analytical platform to achieve direct and multiplexed profiling of circulating RNAs in extracellular vesicles for blood-based GBM characterization. The technology, termed 'enzyme ZIF-8 complexes for regenerative and catalytic digital detection of RNA' (EZ-READ), leverages an RNA-responsive transducer to regeneratively convert and catalytically enhance signals from rare RNA targets. Each transducer comprises hybrid complexes - protein enzymes encapsulated within metal organic frameworks - to configure strong catalytic activity and robust protection. Upon target RNA hybridization, the transducer activates directly to liberate catalytic complexes, in a target-recyclable manner; when partitioned within a microfluidic device, these complexes can individually catalyze strong chemifluorescence reactions for digital RNA quantification. The EZ-READ platform thus enables programmable and reliable RNA detection, across different-sized RNA subtypes (miRNA and mRNA), directly in sample lysates. When clinically evaluated, the EZ-READ platform established composite signatures for accurate blood-based GBM diagnosis and subtyping.

Integrative multi-omics approach to targeted therapy for glioblastoma.

This review describes recent technological advances applied to glioblastoma (GBM), a brain tumor with dismal prognosis. International consortial efforts suggest the presence of molecular subtypes within histologically identical GBM tumors. This emphasizes that future treatment decisions should no longer be made based solely on morphological analyses, but must now take into consideration such molecular and cellular heterogeneity. The use of single-cell technologies has advanced our understanding and assignation of functional subtypes revealing therapeutic vulnerabilities. Our team has developed stratification approaches in the past few years, and we have been able to identify patient cohorts enriched for various signaling pathways. Importantly, our Glioportal brain tumor resource has been established under the National Neuroscience Institute Tissue Bank in 2021. This resource offers preclinical capability to validate working hypotheses established from patient clinical datasets. This review highlights recent developments with the ultimate goal of assigning functional meaning to molecular subtypes, revealing therapeutic vulnerabilities.

Topography of transcriptionally active chromatin in glioblastoma.

Molecular profiling of the most aggressive brain tumor glioblastoma (GBM) on the basis of gene expression, DNA methylation, and genomic variations advances both cancer research and clinical diagnosis. The enhancer architectures and regulatory circuitries governing tumor-intrinsic transcriptional diversity and subtype identity are still elusive. Here, by mapping H3K27ac deposition, we analyze the active regulatory landscapes across 95 GBM biopsies, 12 normal brain tissues, and 38 cell line counterparts. Analyses of differentially regulated enhancers and super-enhancers uncovered previously unrecognized layers of intertumor heterogeneity. Integrative analysis of variant enhancer loci and transcriptome identified topographies of transcriptional enhancers and core regulatory circuitries in four molecular subtypes of primary tumors: AC1-mesenchymal, AC1-classical, AC2-proneural, and AC3-proneural. Moreover, this study reveals core oncogenic dependency on super-enhancer-driven transcriptional factors, long noncoding RNAs, and druggable targets in GBM. Through profiling of transcriptional enhancers, we provide clinically relevant insights into molecular classification, pathogenesis, and therapeutic intervention of GBM.

A STAT3-based gene signature stratifies glioma patients for targeted therapy.

Intratumoral heterogeneity is a hallmark of glioblastoma (GBM) tumors, thought to negatively influence therapeutic outcome. Previous studies showed that mesenchymal tumors have a worse outcome than the proneural subtype. Here we focus on STAT3 as its activation precedes the proneural-mesenchymal transition. We first establish a STAT3 gene signature that stratifies GBM patients into STAT3-high and -low cohorts. STAT3 inhibitor treatment selectively mitigates STAT3-high cell viability and tumorigenicity in orthotopic mouse xenograft models. We show the mechanism underlying resistance in STAT3-low cells by combining STAT3 signature analysis with kinome screen data on STAT3 inhibitor-treated cells. This allows us to draw connections between kinases affected by STAT3 inhibitors, their associated transcription factors and target genes. We demonstrate that dual inhibition of IGF-1R and STAT3 sensitizes STAT3-low cells and improves survival in mice. Our study underscores the importance of serially profiling tumors so as to accurately target individuals who may demonstrate molecular subtype switching.

Epi-Detected Hyperspectral Stimulated Raman Scattering Microscopy for Label-Free Molecular Subtyping of Glioblastomas.

We report the development and implementation of an epi-detected spectral-focusing hyperspectral stimulated Raman scattering (SRS) imaging technique for label-free biomolecular subtyping of glioblastomas (GBMs). The hyperspectral SRS imaging technique developed generates SRS image stacks (from 2800 to 3020 cm-1 at 7 cm-1 intervals) within 30 s through controlling the time delay between the chirped pump and Stokes beams. SRS images at representative Raman shifts (e.g., 2845, 2885, and 2935 cm-1) delineate the biochemical variations and morphological differences between proneural and mesenchymal subtypes of GBMs. Multivariate curve resolution (MCR) analysis on hyperspectral SRS images enables the quantification of major biomolecule distributions in mesenchymal and proneural GBMs. Further principal component analysis (PCA) and linear discriminant analysis (LDA) together with leave-one SRS spectrum-out, cross-validation (LOOCV) yields a diagnostic sensitivity of 96.7% (29/30) and specificity of 88.9% (28/36) for differentiation between mesenchymal and proneural subtypes of GBMs. This study shows great potential of applying hyperspectral SRS imaging technique developed for rapid, label-free molecular subtyping of GBMs in neurosurgery.

Targetable BET proteins- and E2F1-dependent transcriptional program maintains the malignancy of glioblastoma.

Competitive BET bromodomain inhibitors (BBIs) targeting BET proteins (BRD2, BRD3, BRD4, and BRDT) show promising preclinical activities against brain cancers. However, the BET protein-dependent glioblastoma (GBM)-promoting transcriptional network remains elusive. Here, with mechanistic exploration of a next-generation chemical degrader of BET proteins (dBET6), we reveal a profound and consistent impact of BET proteins on E2F1- dependent transcriptional program in both differentiated GBM cells and brain tumor-initiating cells. dBET6 treatment drastically reduces BET protein genomic occupancy, RNA-Pol2 activity, and permissive chromatin marks. Subsequently, dBET6 represses the proliferation, self-renewal, and tumorigenic ability of GBM cells. Moreover, dBET6-induced degradation of BET proteins exerts superior antiproliferation effects compared to conventional BBIs and overcomes both intrinsic and acquired resistance to BBIs in GBM cells. Our study reveals crucial functions of BET proteins and provides the rationale and therapeutic merits of targeted degradation of BET proteins in GBM.

DEAD-box helicase DP103 defines metastatic potential of human breast cancers.

Despite advancement in breast cancer treatment, 30% of patients with early breast cancers experience relapse with distant metastasis. It is a challenge to identify patients at risk for relapse; therefore, the identification of markers and therapeutic targets for metastatic breast cancers is imperative. Here, we identified DP103 as a biomarker and metastasis-driving oncogene in human breast cancers and determined that DP103 elevates matrix metallopeptidase 9 (MMP9) levels, which are associated with metastasis and invasion through activation of NF-κB. In turn, NF-κB signaling positively activated DP103 expression. Furthermore, DP103 enhanced TGF-ß-activated kinase-1 (TAK1) phosphorylation of NF-κB-activating IκB kinase 2 (IKK2), leading to increased NF-κB activity. Reduction of DP103 expression in invasive breast cancer cells reduced phosphorylation of IKK2, abrogated NF-κB-mediated MMP9 expression, and impeded metastasis in a murine xenograft model. In breast cancer patient tissues, elevated levels of DP103 correlated with enhanced MMP9, reduced overall survival, and reduced survival after relapse. Together, these data indicate that a positive DP103/NF-κB feedback loop promotes constitutive NF-κB activation in invasive breast cancers and activation of this pathway is linked to cancer progression and the acquisition of chemotherapy resistance. Furthermore, our results suggest that DP103 has potential as a therapeutic target for breast cancer treatment.