Smart, CD;Fehrenbach, DJ;Wassenaar, JW;Agrawal, V;Fortune, NL;Dixon, DD;Cottam, MA;Hasty, AH;Hemnes, AR;Doran, AC;Gupta, DK;Madhur, MS;
PMID: 37314125 | DOI: 10.1093/cvr/cvad093
Heart failure with preserved ejection fraction (HFpEF) is characterized by diastolic dysfunction, microvascular dysfunction, and myocardial fibrosis with recent evidence implicating the immune system in orchestrating cardiac remodeling. Here, we show the mouse model of deoxycorticosterone acetate (DOCA)-salt hypertension induces key elements of HFpEF, including diastolic dysfunction, exercise intolerance, and pulmonary congestion in the setting of preserved ejection fraction. A modified single cell sequencing approach, CITE-seq, of cardiac immune cells reveals an altered abundance and transcriptional signature in multiple cell types, most notably cardiac macrophages. The DOCA-salt model results in differential expression of several known and novel genes in cardiac macrophages, including upregulation of Trem2, which has been recently implicated in obesity and atherosclerosis. The role of Trem2 in hypertensive heart failure, however, is unknown. We found that mice with genetic deletion of Trem2 exhibit increased cardiac hypertrophy, diastolic dysfunction, renal injury, and decreased cardiac capillary density after DOCA-salt treatment compared to wild-type controls. Moreover, Trem2-deficient macrophages have impaired expression of pro-angiogenic gene programs and increased expression of pro-inflammatory cytokines. Furthermore, we found that plasma levels of soluble TREM2 are elevated in DOCA-salt treated mice and humans with heart failure. Together, our data provide an atlas of immunological alterations that can lead to improved diagnostic and therapeutic strategies for HFpEF. We provide our dataset in an easy to explore and freely accessible web application making it a useful resource for the community. Finally, our results suggest a novel cardioprotective role for Trem2 in hypertensive heart failure.
Chen, Z;He, Q;Lu, T;Wu, J;Shi, G;He, L;Zong, H;Liu, B;Zhu, P;
PMID: 36849569 | DOI: 10.1038/s41467-023-36651-5
Liver tumour-initiating cells (TICs) contribute to tumour initiation, metastasis, progression and drug resistance. Metabolic reprogramming is a cancer hallmark and plays vital roles in liver tumorigenesis. However, the role of metabolic reprogramming in TICs remains poorly explored. Here, we identify a mitochondria-encoded circular RNA, termed mcPGK1 (mitochondrial circRNA for translocating phosphoglycerate kinase 1), which is highly expressed in liver TICs. mcPGK1 knockdown impairs liver TIC self-renewal, whereas its overexpression drives liver TIC self-renewal. Mechanistically, mcPGK1 regulates metabolic reprogramming by inhibiting mitochondrial oxidative phosphorylation (OXPHOS) and promoting glycolysis. This alters the intracellular levels of α-ketoglutarate and lactate, which are modulators in Wnt/β-catenin activation and liver TIC self-renewal. In addition, mcPGK1 promotes PGK1 mitochondrial import via TOM40 interactions, reprogramming metabolism from oxidative phosphorylation to glycolysis through PGK1-PDK1-PDH axis. Our work suggests that mitochondria-encoded circRNAs represent an additional regulatory layer controlling mitochondrial function, metabolic reprogramming and liver TIC self-renewal.
Bockmayr, M;Harnisch, K;Pohl, L;Schweizer, L;Mohme, T;Körner, M;Alawi, M;Suwala, A;Dorostkar, M;Monoranu, C;Hasselblatt, M;Wefers, A;Capper, D;Hench, J;Frank, S;Richardson, T;Tran, I;Liu, E;Snuderl, M;Engertsberger, L;Benesch, M;von Deimling, A;Obrecht, D;Mynarek, M;Rutkowski, S;Glatzel, M;Neumann, J;Schüller, U;
| DOI: 10.1093/neuonc/noac079.143
Myxopapillary ependymoma (MPE) is a heterogeneous disease regarding histopathology and outcome. The underlying molecular biology is poorly understood, and markers that reliably predict the patients’ clinical course are unknown. We assembled a cohort of 185 tumors classified as MPE based on DNA methylation from pediatric, adolescent, and adult patients. Methylation patterns, copy number profiles, and MGMT promoter methylation were analyzed for all tumors, 106 tumors were evaluated histomorphologically, and RNA sequencing was performed for 37 cases. Based on methylation profiling, we defined two subtypes MPE-A and MPEB, and explored associations with epidemiological, clinical, pathological, and molecular characteristics of these tumors. Tumors in the methylation class MPE were histologically diagnosed as WHO grade I (59%), WHO grade II (37%), or WHO grade III tumors (4%). 75/77 analyzed tumors expressed HOXB13, which is a diagnostic feature not detected in other spinal ependymal tumors. Based on DNA methylation, our series split into two subtypes. MPE-A occurred in younger patients (median age 27 vs. 45 years, p=7.3e-05). They were enriched with WHO grade I tumors and associated with papillary morphology and MGMT promoter hypermethylation (all p<0.001). MPE-B included most tumors initially diagnosed as WHO grade II and cases with tanycytic morphology. Copy number alterations were more common in MPE-A. RNA sequencing revealed an enrichment for extracellular matrix and immune system-related signatures in MPE-A. 15/30 MPE-A could not be totally resected compared to 1/58 MPE-B (p=6.3e-08), and progression-free survival was significantly better for MPE-B (p=3.4e-06, 10-year relapse rate 33% vs. 85%). We unraveled the morphological and clinical heterogeneity of MPE by identifying two molecularly distinct subtypes. These subtypes significantly differed in progression-free survival and will likely need different protocols for surveillance and treatment.
He, S;Bhatt, R;Brown, C;Brown, EA;Buhr, DL;Chantranuvatana, K;Danaher, P;Dunaway, D;Garrison, RG;Geiss, G;Gregory, MT;Hoang, ML;Khafizov, R;Killingbeck, EE;Kim, D;Kim, TK;Kim, Y;Klock, A;Korukonda, M;Kutchma, A;Lewis, ZR;Liang, Y;Nelson, JS;Ong, GT;Perillo, EP;Phan, JC;Phan-Everson, T;Piazza, E;Rane, T;Reitz, Z;Rhodes, M;Rosenbloom, A;Ross, D;Sato, H;Wardhani, AW;Williams-Wietzikoski, CA;Wu, L;Beechem, JM;
PMID: 36203011 | DOI: 10.1038/s41587-022-01483-z
Resolving the spatial distribution of RNA and protein in tissues at subcellular resolution is a challenge in the field of spatial biology. We describe spatial molecular imaging, a system that measures RNAs and proteins in intact biological samples at subcellular resolution by performing multiple cycles of nucleic acid hybridization of fluorescent molecular barcodes. We demonstrate that spatial molecular imaging has high sensitivity (one or two copies per cell) and very low error rate (0.0092 false calls per cell) and background (~0.04 counts per cell). The imaging system generates three-dimensional, super-resolution localization of analytes at ~2 million cells per sample. Cell segmentation is morphology based using antibodies, compatible with formalin-fixed, paraffin-embedded samples. We measured multiomic data (980 RNAs and 108 proteins) at subcellular resolution in formalin-fixed, paraffin-embedded tissues (nonsmall cell lung and breast cancer) and identified >18 distinct cell types, ten unique tumor microenvironments and 100 pairwise ligand-receptor interactions. Data on >800,000 single cells and ~260 million transcripts can be accessed at http://nanostring.com/CosMx-dataset .
Journal for ImmunoTherapy of Cancer
Jabado, O;Fan, L;Souza, P;Harris, A;Chaparro, A;Qutaish, M;Si, H;Dannenberg, J;Sasser, K;Couto, S;Fereshteh, M;
| DOI: 10.1136/jitc-2021-sitc2021.928
BackgroundPancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with short overall survival; the standard of care (SoC) is chemotherapy. Immunotherapies in development aim to remodel the stroma by depleting immunosuppressive cell types or using T-cell redirection to kill tumor cells. To date, none of these methods have improved overall survival beyond SoC. Next generation immunotherapies that employ histopathology and molecular subtyping1 for target and patient selection may succeed. Here we leverage a spatial transcriptomics platform (Nanostring Digital Spatial Profiling, DSP) to reveal molecular signaling in tumoral and stromal cells in 57 PDAC patients using tumor microarrays (TMAs). This approach is rapid and clinically relevant as molecular and histology data can be easily bridged.MethodsTMAs generated from surgical resection tissue were commercially sourced. DSP was performed using the CTA RNA panel (1,800 target genes) using PanCK fluorescence for tumor/stroma segmentation. In parallel, slides were chromogenically stained for T-cells (CD3) and macrophages (CD68/CD163). Differential gene expression, gene signature and gene co-expression network analysis was performed using linear models in R.2 3ResultsDifferential gene expression analysis and correlation to IHC confirmed the DSP platform successfully profiled tumor and stromal compartments (figure 1). Immune cell signatures4 and pathway analysis revealed a heterogenous stromal environment. Using a fibroblast gene signature derived from single-cell RNAseq5 we found fibroblast density was positively correlated to PDGFR signaling and MHC-II expression but negatively correlated to B, CD4+ T and neutrophil cell levels (figure 2a). This finding supports the idea that atypical antigen presentation in cancer associated fibroblasts (CAFs) may be exploitable for immunotherapies.6 We constructed a co-expression network from in-situ stromal gene expression and used it to identify receptors coordinately expressed with the immunosuppressive macrophage marker CSF1R as a bispecific antibody partner (figure 2b).7 Classical macrophage markers were identified but also receptors with lesser-known functions in macrophages (TIM3/HAVCR2, FPR3, MS4A6A, LILRB4). Surveying target pairs in this method allows rapid, patient-specific confirmation in serial TMA sections with singleplex IHC or RNAscope.Abstact 928 Figure 1Segmentation strategy and validation of DSP (A) PanCK, CD68 and CD3 staining from two representative tumor cores; (B, C) correlation of gene transcripts in stroma to cell counts from chromogenic staining; (D) heatmap of selected genes differentially expressed in tumor and stroma (n=57 patients).Abstract 928 Figure 2Exploration of the stromal compartment in PDAC TMAs. (A) Heatmap of selected cell type and gene signatures from gene expression in the stroma, color represents single sample enrichment score using GSVA method; (B) a gene co-expression subnetwork in the stroma centered on CSF1R, edge thickness represents strength of correlation, green nodes have evidence for cell surface expression based on proteomic profiling.7ConclusionsIn this study we were able to recapitulate known PDAC biology using very small samples of primary tumors. The combination of TMAs and DSP enables a rapid validation of targets and hypothesis generation for bispecific parings. Further analysis of untreated (n=14) and post-adjuvant chemotherapy (n=26) patients using RNA DSP, IHC and bulk RNAseq is under way. Results from this cohort will enable an integrated histopathology and molecular approach to developing next-generation immunotherapies.ReferencesCollisson EA, Bailey P, Chang DK, Biankin AV. Molecular subtypes of pancreatic cancer. Nat Rev Gastroenterol Hepatol 2019 April;16(4):207-220.Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK (2015). “limma powers differential expression analyses for RNA-sequencing and microarray studies.” Nucleic Acids Research 43(7):e47.Hänzelmann S, Castelo R, Guinney J (2013). “GSVA: gene set variation analysis for microarray and RNA-Seq data.” BMC Bioinformatics 14,7.Charoentong P, Finotello F, Angelova M, Mayer C, Efremova M, Rieder D, Hackl H, Trajanoski Z. Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade. Cell Rep 2017 January 3;18(1):248-262.Tirosh I, Izar B, Prakadan SM, Wadsworth MH 2nd, Treacy D, Trombetta JJ, Rotem A, Rodman C, Lian C, Murphy G, Fallahi-Sichani M, Dutton-Regester K, Lin JR, Cohen O, Shah P, Lu D, Genshaft AS, Hughes TK, Ziegler CG, Kazer SW, Gaillard A, Kolb KE, Villani AC, Johannessen CM, Andreev AY, Van Allen EM, Bertagnolli M, Sorger PK, Sullivan RJ, Flaherty KT, Frederick DT, Jané-Valbuena J, Yoon CH, Rozenblatt-Rosen O, Shalek AK, Regev A, Garraway LA. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 2016 April 8;352(6282):189-96.Elyada E, Bolisetty M, Laise P, Flynn WF, Courtois ET, Burkhart RA, Teinor JA, Belleau P, Biffi G, Lucito MS, Sivajothi S, Armstrong TD, Engle DD, Yu KH, Hao Y, Wolfgang CL, Park Y, Preall J, Jaffee EM, Califano A, Robson P, Tuveson DA. Cross-species single-cell analysis of pancreatic ductal adenocarcinoma reveals antigen-presenting cancer-associated fibroblasts. Cancer Discov 2019 August;9(8):1102-1123. Bausch-Fluck D, Hofmann A, Bock T, Frei AP, Cerciello F, Jacobs A, Moest H, Omasits U, Gundry RL, Yoon C, Schiess R, Schmidt A, Mirkowska P, Härtlová A, Van Eyk JE, Bourquin JP, Aebersold R, Boheler KR, Zandstra P, Wollscheid B. A mass spectrometric-derived cell surface protein atlas. PLoS One 2015 April 20;10(3):e0121314.Ethics ApprovalSpecimens were harvested from unused tissue after a surgical tumor resection procedure. A discrete legal consent form from both hospital and individuals was obtained by the commercial tissue vendor BioMax US for all samples analyzed in this abstract. All human tissues are collected under HIPPA approved protocols.ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.
Park, J;Foox, J;Hether, T;Danko, D;Warren, S;Kim, Y;Reeves, J;Butler, D;Mozsary, C;Rosiene, J;Shaiber, A;Afshin, E;MacKay, M;Rendeiro, A;Bram, Y;Chandar, V;Geiger, H;Craney, A;Velu, P;Melnick, A;Hajirasouliha, I;Beheshti, A;Taylor, D;Saravia-Butler, A;Singh, U;Wurtele, E;Schisler, J;Fennessey, S;Corvelo, A;Zody, M;Germer, S;Salvatore, S;Levy, S;Wu, S;Tatonetti, N;Shapira, S;Salvatore, M;Westblade, L;Cushing, M;Rennert, H;Kriegel, A;Elemento, O;Imielinski, M;Rice, C;Borczuk, A;Meydan, C;Schwartz, R;Mason, C;
| DOI: 10.1016/j.xcrm.2022.100522
The molecular mechanisms underlying the clinical manifestations of COVID-19 and what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome, remains poorly understood. To address these challenges, we combine transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues to define body-wide transcriptome changes in response to COVID-19. We then match this data with spatial protein and expression profiling across 357 tissue sections from 16 representative patient lung samples and identify tissue compartment-specific damage wrought by SARS-CoV-2 infection, evident as a function of varying viral loads during the clinical course of infection and tissue type specific expression states. Overall, our findings reveal a systemic disruption of canonical cellular and transcriptional pathways across all tissues, which can inform subsequent studies to combat the mortality of COVID-19 and to better understand the molecular dynamics of lethal SARS-CoV-2 and other respiratory infections.