Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm.

BACKGROUND AND OBJECTIVE: Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learning (ML) models to quantify intra-tumoral genetic heterogeneity for each patient. This capability holds great promise for enabling better therapeutic selection to improve patient outcome. METHODS: We proposed a novel Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) to predict regional genetic alteration status within each GBM tumor using MRI. WSO-SVM was applied to a unique dataset of 318 image-localized biopsies with spatially matched multiparametric MRI from 74 GBM patients. The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA and PTEN) based on features extracted from the corresponding region of five MRI contrast images. For comparison, a variety of existing ML algorithms were also applied. Classification accuracy of each gene were compared between the different algorithms. The SHapley Additive exPlanations (SHAP) method was further applied to compute contribution scores of different contrast images. Finally, the trained WSO-SVM was used to generate prediction maps within the tumoral area of each patient to help visualize the intra-tumoral genetic heterogeneity. RESULTS: WSO-SVM achieved 0.80 accuracy, 0.79 sensitivity, and 0.81 specificity for classifying EGFR; 0.71 accuracy, 0.70 sensitivity, and 0.72 specificity for classifying PDGFRA; 0.80 accuracy, 0.78 sensitivity, and 0.83 specificity for classifying PTEN; these results significantly outperformed the existing ML algorithms. Using SHAP, we found that the relative contributions of the five contrast images differ between genes, which are consistent with findings in the literature. The prediction maps revealed extensive intra-tumoral region-to-region heterogeneity within each individual tumor in terms of the alteration status of the three genes. CONCLUSIONS: This study demonstrated the feasibility of using MRI and WSO-SVM to enable non-invasive prediction of intra-tumoral regional genetic alteration for each GBM patient, which can inform future adaptive therapies for individualized oncology.

RT-PCR assay to detect FGFR3::TACC3 fusions in formalin-fixed, paraffin-embedded glioblastoma samples.

Background: One targeted treatment option for isocitrate dehydrogenase (IDH)-wild-type glioblastoma focuses on tumors with fibroblast growth factor receptor 3::transforming acidic coiled-coil-containing protein 3 (FGFR3::TACC3) fusions. FGFR3::TACC3 fusion detection can be challenging, as targeted RNA next-generation sequencing (NGS) is not routinely performed, and immunohistochemistry is an imperfect surrogate marker. Fusion status can be determined using reverse transcription polymerase chain reaction (RT-PCR) on fresh frozen (FF) material, but sometimes only formalin-fixed, paraffin-embedded (FFPE) tissue is available. Aim: To develop an RT-PCR assay to determine FGFR3::TACC3 status in FFPE glioblastoma samples. Methods: Twelve tissue microarrays with 353 historical glioblastoma samples were immunohistochemically stained for FGFR3. Samples with overexpression of FGFR3 (n = 13) were subjected to FGFR3::TACC3 RT-PCR on FFPE, using 5 primer sets for the detection of 5 common fusion variants. Fusion-negative samples were additionally analyzed with NGS (n = 6), FGFR3 Fluorescence In Situ Hybridization (n = 6), and RNA sequencing (n = 5). Results: Using RT-PCR on FFPE material of the 13 samples with FGFR3 overexpression, we detected an FGFR3::TACC3 fusion in 7 samples, covering 3 different fusion variants. For 5 of these FF was available, and the presence of the fusion was confirmed through RT-PCR on FF. With RNA sequencing, 1 additional sample was found to harbor an FGFR3::TACC3 fusion (variant not covered by current RT-PCR for FFPE). The frequency of FGFR3::TACC3 fusion in this cohort was 9/353 (2.5%). Conclusions: RT-PCR for FGFR3::TACC3 fusions can successfully be performed on FFPE material, with a specificity of 100% and (due to limited primer sets) a sensitivity of 83.3%. This assay allows for the identification of potential targeted treatment options when only formalin-fixed tissue is available.

Pan-cancer proteogenomics characterization of tumor immunity.

Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%-20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.

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.

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.

The Epigenetic Evolution of Glioma Is Determined by the IDH1 Mutation Status and Treatment Regimen.

Tumor adaptation or selection is thought to underlie therapy resistance in glioma. To investigate longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 132 matched initial and recurrent tumors from patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) glioma. IDHwt gliomas showed a stable epigenome over time with relatively low levels of global methylation. The epigenome of IDHmut gliomas showed initial high levels of genome-wide DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. Integration of epigenomics, gene expression, and functional genomics identified HOXD13 as a master regulator of IDHmut astrocytoma evolution. Furthermore, relapse of IDHmut tumors was accompanied by histologic progression that was associated with survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment varied between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neoangiogenesis and T-cell infiltration upon treatment of IDHmut gliomas. This study provides one of the largest cohorts of paired longitudinal glioma samples with epigenomic, transcriptomic, and genomic profiling and suggests that treatment of IDHmut glioma is associated with epigenomic evolution toward an IDHwt-like phenotype. SIGNIFICANCE: Standard treatments are related to loss of DNA methylation in IDHmut glioma, resulting in epigenetic activation of genes associated with tumor progression and alterations in the microenvironment that resemble treatment-naïve IDHwt glioma.

Identifying predictors of glioma evolution from longitudinal sequencing.

Clonal evolution drives cancer progression and therapeutic resistance. Recent studies have revealed divergent longitudinal trajectories in gliomas, but early molecular features steering posttreatment cancer evolution remain unclear. Here, we collected sequencing and clinical data of initial-recurrent tumor pairs from 544 adult diffuse gliomas and performed multivariate analysis to identify early molecular predictors of tumor evolution in three diffuse glioma subtypes. We found that CDKN2A deletion at initial diagnosis preceded tumor necrosis and microvascular proliferation that occur at later stages of IDH-mutant glioma. Ki67 expression at diagnosis was positively correlated with acquiring hypermutation at recurrence in the IDH-wild-type glioma. In all glioma subtypes, MYC gain or MYC-target activation at diagnosis was associated with treatment-induced hypermutation at recurrence. To predict glioma evolution, we constructed CELLO2 (Cancer EvoLution for LOngitudinal data version 2), a machine learning model integrating features at diagnosis to forecast hypermutation and progression after treatment. CELLO2 successfully stratified patients into subgroups with distinct prognoses and identified a high-risk patient group featured by MYC gain with worse post-progression survival, from the low-grade IDH-mutant-noncodel subtype. We then performed chronic temozolomide-induction experiments in glioma cell lines and isogenic patient-derived gliomaspheres and demonstrated that MYC drives temozolomide resistance by promoting hypermutation. Mechanistically, we demonstrated that, by binding to open chromatin and transcriptionally active genomic regions, c-MYC increases the vulnerability of key mismatch repair genes to treatment-induced mutagenesis, thus triggering hypermutation. This study reveals early predictors of cancer evolution under therapy and provides a resource for precision oncology targeting cancer dynamics in diffuse gliomas.

Pan-cancer proteogenomics connects oncogenic drivers to functional states.

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.

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

Despite producing a panoply of potential cancer-specific targets, the proteogenomic characterization of human tumors has yet to demonstrate value for precision cancer medicine. Integrative multi-omics using a machine-learning network identified master kinases responsible for effecting phenotypic hallmarks of functional glioblastoma subtypes. In subtype-matched patient-derived models, we validated PKCδ and DNA-PK as master kinases of glycolytic/plurimetabolic and proliferative/progenitor subtypes, respectively, and qualified the kinases as potent and actionable glioblastoma subtype-specific therapeutic targets. Glioblastoma subtypes were associated with clinical and radiomics features, orthogonally validated by proteomics, phospho-proteomics, metabolomics, lipidomics and acetylomics analyses, and recapitulated in pediatric glioma, breast and lung squamous cell carcinoma, including subtype specificity of PKCδ and DNA-PK activity. We developed a probabilistic classification tool that performs optimally with RNA from frozen and paraffin-embedded tissues, which can be used to evaluate the association of therapeutic response with glioblastoma subtypes and to inform patient selection in prospective clinical trials.

A variational algorithm to detect the clonal copy number substructure of tumors from scRNA-seq data.

Single-cell RNA sequencing is the reference technology to characterize the composition of the tumor microenvironment and to study tumor heterogeneity at high resolution. Here we report Single CEll Variational ANeuploidy analysis (SCEVAN), a fast variational algorithm for the deconvolution of the clonal substructure of tumors from single-cell RNA-seq data. It uses a multichannel segmentation algorithm exploiting the assumption that all the cells in a given copy number clone share the same breakpoints. Thus, the smoothed expression profile of every individual cell constitutes part of the evidence of the copy number profile in each subclone. SCEVAN can automatically and accurately discriminate between malignant and non-malignant cells, resulting in a practical framework to analyze tumors and their microenvironment. We apply SCEVAN to datasets encompassing 106 samples and 93,322 cells from different tumor types and technologies. We demonstrate its application to characterize the intratumor heterogeneity and geographic evolution of malignant brain tumors.

LZTR1 Mutation Mediates Oncogenesis through Stabilization of EGFR and AXL.

LZTR1 is the substrate-specific adaptor of a CUL3-dependent ubiquitin ligase frequently mutated in sporadic and syndromic cancer. We combined biochemical and genetic studies to identify LZTR1 substrates and interrogated their tumor-driving function in the context of LZTR1 loss-of-function mutations. Unbiased screens converged on EGFR and AXL receptor tyrosine kinases as LZTR1 interactors targeted for ubiquitin-dependent degradation in the lysosome. Pathogenic cancer-associated mutations of LZTR1 failed to promote EGFR and AXL degradation, resulting in dysregulated growth factor signaling. Conditional inactivation of Lztr1 and Cdkn2a in the mouse nervous system caused tumors in the peripheral nervous system including schwannoma-like tumors, thus recapitulating aspects of schwannomatosis, the prototype tumor predisposition syndrome sustained by LZTR1 germline mutations. Lztr1- and Cdkn2a-deleted tumors aberrantly accumulated EGFR and AXL and exhibited specific vulnerability to EGFR and AXL coinhibition. These findings explain tumorigenesis by LZTR1 inactivation and offer therapeutic opportunities to patients with LZTR1-mutant cancer. SIGNIFICANCE: EGFR and AXL are substrates of LZTR1-CUL3 ubiquitin ligase. The frequent somatic and germline mutations of LZTR1 in human cancer cause EGFR and AXL accumulation and deregulated signaling. LZTR1-mutant tumors show vulnerability to concurrent inhibition of EGFR and AXL, thus providing precision targeting to patients affected by LZTR1-mutant cancer. This article is highlighted in the In This Issue feature, p. 517.

Tissue-specific modifier alleles determine Mertk loss-of-function traits.

Knockout (KO) mouse models play critical roles in elucidating biological processes behind disease-associated or disease-resistant traits. As a presumed consequence of gene KO, mice display certain phenotypes. Based on insight into the molecular role of said gene in a biological process, it is inferred that the particular biological process causally underlies the trait. This approach has been crucial towards understanding the basis of pathological and/or advantageous traits associated with Mertk KO mice. Mertk KO mice suffer from severe, early-onset retinal degeneration. MERTK, expressed in retinal pigment epithelia, is a receptor tyrosine kinase with a critical role in phagocytosis of apoptotic cells or cellular debris. Therefore, early-onset, severe retinal degeneration was described to be a direct consequence of failed MERTK-mediated phagocytosis of photoreceptor outer segments by retinal pigment epithelia. Here, we report that the loss of Mertk alone is not sufficient for retinal degeneration. The widely used Mertk KO mouse carries multiple coincidental changes in its genome that affect the expression of a number of genes, including the Mertk paralog Tyro3. Retinal degeneration manifests only when the function of Tyro3 is concomitantly lost. Furthermore, Mertk KO mice display improved anti-tumor immunity. MERTK is expressed in macrophages. Therefore, enhanced anti-tumor immunity was inferred to result from the failure of macrophages to dispose of cancer cell corpses, resulting in a pro-inflammatory tumor microenvironment. The resistance against two syngeneic mouse tumor models observed in Mertk KO mice is not, however, phenocopied by the loss of Mertk alone. Neither Tyro3 nor macrophage phagocytosis by alternate genetic redundancy accounts for the absence of anti-tumor immunity. Collectively, our results indicate that context-dependent epistasis of independent modifier alleles determines Mertk KO traits.

Glioblastoma hijacks neuronal mechanisms for brain invasion.

Glioblastomas are incurable tumors infiltrating the brain. A subpopulation of glioblastoma cells forms a functional and therapy-resistant tumor cell network interconnected by tumor microtubes (TMs). Other subpopulations appear unconnected, and their biological role remains unclear. Here, we demonstrate that whole-brain colonization is fueled by glioblastoma cells that lack connections with other tumor cells and astrocytes yet receive synaptic input from neurons. This subpopulation corresponds to neuronal and neural-progenitor-like tumor cell states, as defined by single-cell transcriptomics, both in mouse models and in the human disease. Tumor cell invasion resembled neuronal migration mechanisms and adopted a Lévy-like movement pattern of probing the environment. Neuronal activity induced complex calcium signals in glioblastoma cells followed by the de novo formation of TMs and increased invasion speed. Collectively, superimposing molecular and functional single-cell data revealed that neuronal mechanisms govern glioblastoma cell invasion on multiple levels. This explains how glioblastoma's dissemination and cellular heterogeneity are closely interlinked.

Glioma progression is shaped by genetic evolution and microenvironment interactions.

The factors driving therapy resistance in diffuse glioma remain poorly understood. To identify treatment-associated cellular and genetic changes, we analyzed RNA and/or DNA sequencing data from the temporally separated tumor pairs of 304 adult patients with isocitrate dehydrogenase (IDH)-wild-type and IDH-mutant glioma. Tumors recurred in distinct manners that were dependent on IDH mutation status and attributable to changes in histological feature composition, somatic alterations, and microenvironment interactions. Hypermutation and acquired CDKN2A deletions were associated with an increase in proliferating neoplastic cells at recurrence in both glioma subtypes, reflecting active tumor growth. IDH-wild-type tumors were more invasive at recurrence, and their neoplastic cells exhibited increased expression of neuronal signaling programs that reflected a possible role for neuronal interactions in promoting glioma progression. Mesenchymal transition was associated with the presence of a myeloid cell state defined by specific ligand-receptor interactions with neoplastic cells. Collectively, these recurrence-associated phenotypes represent potential targets to alter disease progression.

Regulated interaction of ID2 with the anaphase-promoting complex links progression through mitosis with reactivation of cell-type-specific transcription.

Tissue-specific transcriptional activity is silenced in mitotic cells but it remains unclear whether the mitotic regulatory machinery interacts with tissue-specific transcriptional programs. We show that such cross-talk involves the controlled interaction between core subunits of the anaphase-promoting complex (APC) and the ID2 substrate. The N-terminus of ID2 is independently and structurally compatible with a pocket composed of core APC/C subunits that may optimally orient ID2 onto the APCCDH1 complex. Phosphorylation of serine-5 by CDK1 prevented the association of ID2 with core APC, impaired ubiquitylation and stabilized ID2 protein at the mitosis-G1 transition leading to inhibition of basic Helix-Loop-Helix (bHLH)-mediated transcription. The serine-5 phospho-mimetic mutant of ID2 that inefficiently bound core APC remained stable during mitosis, delayed exit from mitosis and reloading of bHLH transcription factors on chromatin. It also locked cells into a "mitotic stem cell" transcriptional state resembling the pluripotent program of embryonic stem cells. The substrates of APCCDH1 SKP2 and Cyclin B1 share with ID2 the phosphorylation-dependent, D-box-independent interaction with core APC. These results reveal a new layer of control of the mechanism by which substrates are recognized by APC.

Anti-tumor effects of an ID antagonist with no observed acquired resistance.

ID proteins are helix-loop-helix (HLH) transcriptional regulators frequently overexpressed in cancer. ID proteins inhibit basic-HLH transcription factors often blocking differentiation and sustaining proliferation. A small-molecule, AGX51, targets ID proteins for degradation and impairs ocular neovascularization in mouse models. Here we show that AGX51 treatment of cancer cell lines impairs cell growth and viability that results from an increase in reactive oxygen species (ROS) production upon ID degradation. In mouse models, AGX51 treatment suppresses breast cancer colonization in the lung, regresses the growth of paclitaxel-resistant breast tumors when combined with paclitaxel and reduces tumor burden in sporadic colorectal neoplasia. Furthermore, in cells and mice, we fail to observe acquired resistance to AGX51 likely the result of the inability to mutate the binding pocket without loss of ID function and efficient degradation of the ID proteins. Thus, AGX51 is a first-in-class compound that antagonizes ID proteins, shows strong anti-tumor effects and may be further developed for the management of multiple cancers.

Single-cell characterization of macrophages in glioblastoma reveals MARCO as a mesenchymal pro-tumor marker.

BACKGROUND: Macrophages are the most common infiltrating immune cells in gliomas and play a wide variety of pro-tumor and anti-tumor roles. However, the different subpopulations of macrophages and their effects on the tumor microenvironment remain poorly understood. METHODS: We combined new and previously published single-cell RNA-seq data from 98,015 single cells from a total of 66 gliomas to profile 19,331 individual macrophages. RESULTS: Unsupervised clustering revealed a pro-tumor subpopulation of bone marrow-derived macrophages characterized by the scavenger receptor MARCO, which is almost exclusively found in IDH1-wild-type glioblastomas. Previous studies have implicated MARCO as an unfavorable marker in melanoma and non-small cell lung cancer; here, we find that bulk MARCO expression is associated with worse prognosis and mesenchymal subtype. Furthermore, MARCO expression is significantly altered over the course of treatment with anti-PD1 checkpoint inhibitors in a response-dependent manner, which we validate with immunofluorescence imaging. CONCLUSIONS: These findings illustrate a novel macrophage subpopulation that drives tumor progression in glioblastomas and suggest potential therapeutic targets to prevent their recruitment.

Structural Model for Recruitment of RIT1 to the LZTR1 E3 Ligase: Evidences from an Integrated Computational Approach.

Leucine-zipper transcription regulator 1 (LZTR1) is a highly mutated tumor suppressor gene, involved in the pathogenesis of several cancer types and developmental disorders. In proteasomal degradation, it acts as an adaptor protein responsible for the recognition and recruitment of substrates to be ubiquitinated in Cullin3-RING ligase E3 (CRL3) machinery. LZTR1 belongs to the BTB-Kelch family, a multi-domain protein where the Kelch propeller plays as the substrate recognition region and for which no experimental structure has been solved. Recently, large effort mutational analyses pointed to the role of disease-associated LZTR1 mutations in the RAS/MAPK signaling pathway and RIT1, a small Ras-related GTPase protein, has been identified by mass spectroscopy to interact with LZTR1. Hence, a better understanding of native structure, molecular mechanism, and substrate specificity would help clarifying the role of LZTR1 in pathological diseases, thus promoting advancement in the development of novel therapeutic strategies. Here, we address the interaction model between adaptor LZTR1 and substrate RIT1 by applying an integrated computational approach, including molecular modeling and docking techniques. We observe that the interaction model LZTR1-RIT1 is stabilized by an electrostatic bond network established between the two protein surfaces, which is reminiscent of homologous ubiquitin ligases complexes. Then, running MD simulations, we characterize differential conformational dynamics of the multi-domain LZTR1, offering interesting implications on the mechanistic role of specific point mutations. We identify G248R and R283Q as damaging mutations involved in the recognition process of the substrate RIT1 and R412C as a possible allosteric mutation from the Kelch to the C-term BTB-domain. Our findings provide important structural insights on targeting CRL3s for drug discovery.

The making of the glioblastoma classification.

Classification of cancer should lead to informative patients' stratification and selective therapeutic vulnerabilities. A pathway-based classification of glioblastoma uncovered a mitochondrial subtype with a unique sensitivity to inhibitors of oxidative phosphorylation. Precision targeting of cancer metabolism could provide therapeutic opportunities to a lethal neoplasm and be translated to other tumour types.

Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities.

The transcriptomic classification of glioblastoma (GBM) has failed to predict survival and therapeutic vulnerabilities. A computational approach for unbiased identification of core biological traits of single cells and bulk tumors uncovered four tumor cell states and GBM subtypes distributed along neurodevelopmental and metabolic axes, classified as proliferative/progenitor, neuronal, mitochondrial and glycolytic/plurimetabolic. Each subtype was enriched with biologically coherent multiomic features. Mitochondrial GBM was associated with the most favorable clinical outcome. It relied exclusively on oxidative phosphorylation for energy production, whereas the glycolytic/plurimetabolic subtype was sustained by aerobic glycolysis and amino acid and lipid metabolism. Deletion of the glucose-proton symporter SLC45A1 was the truncal alteration most significantly associated with mitochondrial GBM, and the reintroduction of SLC45A1 in mitochondrial glioma cells induced acidification and loss of fitness. Mitochondrial, but not glycolytic/plurimetabolic, GBM exhibited marked vulnerability to inhibitors of oxidative phosphorylation. The pathway-based classification of GBM informs survival and enables precision targeting of cancer metabolism.