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Microglia and complement can mediate neurodegeneration in Alzheimer’s disease (AD). By integrative multi-omics analysis, here we show that astrocytic and microglial proteins are increased in TauP301S synapse fractions with age and in a C1q-dependent manner. In addition to microglia, we identified that astrocytes contribute substantially to synapse elimination in TauP301S hippocampi. Notably, we found relatively more excitatory synapse marker proteins in astrocytic lysosomes, whereas microglial lysosomes contained more inhibitory synapse material. C1q deletion reduced astrocyte–synapse association and decreased astrocytic and microglial synapses engulfment in TauP301S mice and rescued synapse density. Finally, in an AD mouse model that combines β-amyloid and Tau pathologies, deletion of the AD risk gene Trem2 impaired microglial phagocytosis of synapses, whereas astrocytes engulfed more inhibitory synapses around plaques. Together, our data reveal that astrocytes contact and eliminate synapses in a C1q-dependent manner and thereby contribute to pathological synapse loss and that astrocytic phagocytosis can compensate for microglial dysfunction.

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The composition of the tumor immune microenvironment (TIME) is considered a key determinant of patients’ response to immunotherapy. The mechanisms underlying TIME formation and development over time are poorly understood. Glioblastoma (GBM) is a lethal primary brain cancer for which there are no curative treatments. GBMs are immunologically heterogeneous and impervious to checkpoint blockade immunotherapies. Utilizing clinically relevant genetic mouse models of GBM, we identified distinct immune landscapes associated with expression of EGFR wild-type and mutant EGFRvIII cancer driver mutations. Over time, accumulation of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC) was more pronounced in EGFRvIII-driven GBMs and was correlated with resistance to PD-1 and CTLA-4 combination checkpoint blockade immunotherapy. We determined that GBM-secreted CXCL1/2/3 and PMN-MDSC–expressed CXCR2 formed an axis regulating output of PMN-MDSCs from the bone marrow leading to systemic increase in these cells in the spleen and GBM tumor-draining lymph nodes. Pharmacologic targeting of this axis induced a systemic decrease in the numbers of PMN-MDSC, facilitated responses to PD-1 and CTLA-4 combination checkpoint blocking immunotherapy, and prolonged survival in mice bearing EGFRvIII-driven GBM. Our results uncover a relationship between cancer driver mutations, TIME composition, and sensitivity to checkpoint blockade in GBM and support the stratification of patients with GBM for checkpoint blockade therapy based on integrated genotypic and immunologic profiles.

Supplementary Table 1

The composition of the tumor immune microenvironment (TIME) is considered a key determinant of patients’ response to immunotherapy. The mechanisms underlying TIME formation and development over time are poorly understood. Glioblastoma (GBM) is a lethal primary brain cancer for which there are no curative treatments. GBMs are immunologically heterogeneous and impervious to checkpoint blockade immunotherapies. Utilizing clinically relevant genetic mouse models of GBM, we identified distinct immune landscapes associated with expression of EGFR wild-type and mutant EGFRvIII cancer driver mutations. Over time, accumulation of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC) was more pronounced in EGFRvIII-driven GBMs and was correlated with resistance to PD-1 and CTLA-4 combination checkpoint blockade immunotherapy. We determined that GBM-secreted CXCL1/2/3 and PMN-MDSC–expressed CXCR2 formed an axis regulating output of PMN-MDSCs from the bone marrow leading to systemic increase in these cells in the spleen and GBM tumor-draining lymph nodes. Pharmacologic targeting of this axis induced a systemic decrease in the numbers of PMN-MDSC, facilitated responses to PD-1 and CTLA-4 combination checkpoint blocking immunotherapy, and prolonged survival in mice bearing EGFRvIII-driven GBM. Our results uncover a relationship between cancer driver mutations, TIME composition, and sensitivity to checkpoint blockade in GBM and support the stratification of patients with GBM for checkpoint blockade therapy based on integrated genotypic and immunologic profiles.

5-fluorouracil (5-FU) is a successful and broadly used anti-cancer therapeutic. A major mechanism of action of 5-FU is thought to be through thymidylate synthase (TYMS) inhibition resulting in dTTP depletion and activation of the DNA damage response. This suggests that 5-FU should synergize with other DNA damaging agents. However, we found that combinations of 5-FU and oxaliplatin or irinotecan failed to display any evidence of synergy in clinical trials, and resulted in sub-additive killing in a panel of colorectal cancer (CRC) cell lines. In seeking to understand this antagonism, we unexpectedly found that an RNA damage response during ribosome biogenesis dominates the drug’s efficacy in tumor types for which 5-FU shows clinical benefit. 5-FU has an inherent bias for RNA incorporation, and blocking this greatly reduced drug-induced lethality, indicating that accumulation of damaged RNA is more deleterious than the lack of new RNA synthesis. Using 5-FU metabolites that specifically incorporate into either RNA or DNA revealed that CRC cell lines and patient-derived colorectal cancer organoids are inherently more sensitive to RNA damage. This difference held true in cell lines from other tissues in which 5-FU has shown clinical utility, whereas cell lines from tumor tissues that lack clinical 5-FU responsiveness typically showed greater sensitivity to the drug’s DNA damage effects. Analysis of changes in the phosphoproteome and ubiquitinome shows RNA damage triggers the selective ubiquitination of multiple ribosomal proteins leading to autophagy-dependent rRNA catabolism and proteasome-dependent degradation of ubiquitinated ribosome proteins. Further, RNA damage response to 5-FU is selectively enhanced by compounds that promote ribosome biogenesis, such as KDM2A inhibitors. These results demonstrate the presence of a strong RNA damage response linked to apoptotic cell death, with clear utility of combinatorially targeting this response in cancer therapy.

Gene signature correlations with clusters 1-4

Supplementary Figure 4

Hippo pathway dysregulation occurs in multiple cancers through genetic and nongenetic alterations, resulting in translocation of YAP to the nucleus and activation of the TEAD family of transcription factors. Unlike other oncogenic pathways such as RAS, defining tumors that are Hippo pathway–dependent is far more complex due to the lack of hotspot genetic alterations. Here, we developed a machine-learning framework to identify a robust, cancer type–agnostic gene expression signature to quantitate Hippo pathway activity and cross-talk as well as predict YAP/TEAD dependency across cancers. Further, through chemical genetic interaction screens and multiomics analyses, we discover a direct interaction between MAPK signaling and TEAD stability such that knockdown of YAP combined with MEK inhibition results in robust inhibition of tumor cell growth in Hippo dysregulated tumors. This multifaceted approach underscores how computational models combined with experimental studies can inform precision medicine approaches including predictive diagnostics and combination strategies.Significance:An integrated chemicogenomics strategy was developed to identify a lineage-independent signature for the Hippo pathway in cancers. Evaluating transcriptional profiles using a machine-learning method led to identification of a relationship between YAP/TAZ dependency and MAPK pathway activity. The results help to nominate potential combination therapies with Hippo pathway inhibition.This article is highlighted in the In This Issue feature, p. 521

Analyzing proteins from single cells by tandem mass spectrometry (MS) has become technically feasible. While such analysis has the potential to accurately quantify thousands of proteins across thousands of single cells, the accuracy and reproducibility of the results may be undermined by numerous factors affecting experimental design, sample preparation, data acquisition, and data analysis. Broadly accepted community guidelines and standardized metrics will enhance rigor, data quality, and alignment between laboratories. Here we propose best practices, quality controls, and data reporting recommendations to assist in the broad adoption of reliable quantitative workflows for single-cell proteomics., Supporting website: https://single-cell.net/guidelines

SummaryStrategies for maximizing the potency and specificity of cancer immunotherapies have sparked efforts to identify recurrent epitopes presented in the context of defined tumor-associated neoantigens. Discovering these “neoepitopes” can be difficult owing to the limited number of peptides that arise from a single point mutation, a low number of copies presented on the cell surface, and variable binding specificity of the human leukocyte antigen (HLA) class I complex. Due to these limitations, many discovery efforts focus on identifying neoepitopes from a small number of cancer neoantigens in the context of few HLA alleles. Here we describe a systematic workflow to characterize binding and presentation of neoepitopes derived from 47 shared cancer neoantigens in the context of 15 HLA alleles. Through the development of a high-throughput neoepitope-HLA binding assay, we surveyed 24,149 candidate neoepitope-HLA combinations resulting in 587 stable complexes. These data were supplemented by computational prediction that identified an additional 257 neoepitope-HLA pairs, resulting in a total of 844 unique combinations. We used these results to build sensitive targeted mass spectrometry assays to validate neoepitope presentation on a panel of HLA-I monoallelic cell lines engineered to express neoantigens of interest as a single polypeptide. Altogether, our analyses detected 84 unique neoepitope-HLA pairs derived from 37 shared cancer neoantigens and presented across 12 HLA alleles. We subsequently identified multiple TCRs which specifically recognized two of these neoantigen-HLA combinations. Finally, these novel TCRs were utilized to elicit a T cell response suggesting that these neoepitopes are likely to be immunogenic. Together these data represent a validated, extensive resource of therapeutically relevant neoepitopes and the HLA context in which they can be targeted.

Mitogen-activated protein kinases (MAPKs) drive key signaling cascades during neuronal survival and degeneration. The localization of kinases to specific subcellular compartments is a critical mechanism to locally control signaling activity and specificity upon stimulation. However, how MAPK signaling components tightly control their localization remains largely unknown. Here, we systematically analyzed the phosphorylation and membrane localization of all MAPKs expressed in dorsal root ganglia (DRG) neurons, under control and stress conditions. We found that MAP3K12/dual leucine zipper kinase (DLK) becomes phosphorylated and palmitoylated, and it is recruited to sphingomyelin-rich vesicles upon stress. Stress-induced DLK vesicle recruitment is essential for kinase activation; blocking DLK-membrane interaction inhibits downstream signaling, while DLK recruitment to ectopic subcellular structures is sufficient to induce kinase activation. We show that the localization of DLK to newly formed vesicles is essential for local signaling. Inhibition of membrane internalization blocks DLK activation and protects against neurodegeneration in DRG neurons. These data establish vesicular assemblies as dynamically regulated platforms for DLK signaling during neuronal stress responses.