Supplementary Video S1 from Senescence Rewires Microenvironment Sensing to Facilitate Antitumor Immunity

RNA-Seq data of proliferating (PRO) or senescent (SEN) NSP liver tumor cells, for both p53-restoration and drug-induced (trametinib+palbociclib) settings. PRO and SEN cells were also treated with the BET inhibitor JQ-1 (500 n, 48 h), to expose BRD4-mediated transcriptional output in each cellular state.

Supplementary figures complement main figures to show that senescent cells have a rewired environmental signal sensing phenotype, exemplified by an enhanced IFN-g signaling, to facilitate anti-tumor immunity.

ABSTRACT:Components of normal tissue architecture serve as barriers to tumor progression. Inflammatory and wound-healing programs are requisite features of solid tumorigenesis, wherein alterations to immune and nonimmune stromal elements enable loss of homeostasis during tumor onset. The precise mechanisms by which normal stromal cell states limit tissue plasticity and tumorigenesis, and which are lost during tumor progression, remain largely unknown. In this study, we show that healthy pancreatic mesenchyme expresses the paracrine signaling molecule KITL, also known as stem cell factor, and identify the loss of stromal KITL during tumorigenesis as tumor promoting. Genetic inhibition of mesenchymal KITL in the contexts of health, injury, and cancer together indicates a role for KITL signaling in the maintenance of pancreas tissue architecture, such that the loss of the stromal KITL pool increased tumor growth and reduced survival of tumor-bearing mice. Together, these findings implicate the loss of mesenchymal KITL as a mechanism for establishing a tumor-permissive microenvironment. SIGNIFICANCE:By analyzing transcriptional programs in healthy and tumor-associated pancreatic mesenchyme, we find that a subpopulation of mesenchymal cells in healthy pancreas tissue expresses the paracrine signaling factor KITL. The loss of mesenchymal KITL is an accompanying and permissive feature of pancreas tumor evolution, with potential implications for cancer interception. See related article by Dolskii and Cukierman, p. 872.

ABSTRACT:Perturbations in intermediary metabolism contribute to the pathogenesis of acute myeloid leukemia (AML) and can produce therapeutically actionable dependencies. Here, we probed whether α-ketoglutarate (αKG) metabolism represents a specific vulnerability in AML. Using functional genomics, metabolomics, and mouse models, we identified the αKG dehydrogenase complex, which catalyzes the conversion of αKG to succinyl coenzyme A, as a molecular dependency across multiple models of adverse-risk AML. Inhibition of 2-oxoglutarate dehydrogenase (OGDH), the E1 subunit of the αKG dehydrogenase complex, impaired AML progression and drove differentiation. Mechanistically, hindrance of αKG flux through the tricarboxylic acid (TCA) cycle resulted in rapid exhaustion of aspartate pools and blockade of de novo nucleotide biosynthesis, whereas cellular bioenergetics was largely preserved. Additionally, increased αKG levels after OGDH inhibition affected the biosynthesis of other critical amino acids. Thus, this work has identified a previously undescribed, functional link between certain TCA cycle components and nucleotide biosynthesis enzymes across AML. This metabolic node may serve as a cancer-specific vulnerability, amenable to therapeutic targeting in AML and perhaps in other cancers with similar metabolic wiring.

Low (50 pg/ml) and high (1 ng/ml) dose of IFN-γ treatment in proliferating and senescent NSP cells.

Supplementary Video S2 from Senescence Rewires Microenvironment Sensing to Facilitate Antitumor Immunity

Supplementary Figures S1-S25

Differential expression analyses of CD8 T and macrophages populations of proliferating (p53 off) vs. senescent (p53 on) tumors by scRNA-seq.

Although sequence-based studies show that basal-like features lead to worse prognosis and chemotherapy-resistance compared to the classical subtype in advanced pancreatic ductal adenocarcinoma (PDAC), a surrogate biomarker distinguishing between these subtypes in routine diagnostic practice remains to be identified. We aimed to evaluate the utility of immunohistochemistry (IHC) expression subtypes generated by unsupervised hierarchical clustering based on staining scores of four markers (CK5/6, p63, GATA6, HNF4a) applied to endoscopic ultrasound-guided fine needle aspiration biopsy (EUS-FNAB) materials. EUS-FNAB materials taken from 190 treatment-naïve advanced PDAC patients were analyzed, and three IHC patterns were established (Classical, Transitional, and Basal-like pattern). Basal-like pattern (high co-expression of CK5/6 and p63 with low expression of GATA6 and HNF4a) was significantly associated with squamous differentiation histology (p < 0.001) and demonstrated the worst overall survival among our cohort (p = 0.004). IHC expression subtype (Transitional, Basal vs Classical) was an independent poor prognosticator in multivariate analysis [HR 1.58 (95% CI 1.01–2.38), p = 0.047]. Furthermore, CK5/6 expression was an independent poor prognostic factor in histological glandular type PDAC [HR 2.82 (95% CI 1.31–6.08), p = 0.008]. Our results suggest that IHC expression patterns successfully predict molecular features indicative of the Basal-like subgroup in advanced PDAC. These results provide the basis for appropriate stratification for therapeutic selection and prognostic estimation of advanced PDAC in a simplified manner.

Senescence triggers an immune evasion-to-immune recognition tumor switch. A, Representative images of CD45 and GFP staining marking immune cells and tumor cells, respectively, in p53-suppressed and p53-restored tumor (7 days after p53 restoration). Right, the quantification of the area of CD45+ staining calculated from 3 random fields per mouse. Each dot represents a mouse. B, Flow cytometry analysis of the global immune landscape in an orthotopic NSP liver tumor model. Immunophenotyping of senescent tumors is performed 9 days after Dox withdrawal, a time point when the senescent state is fully established, yet preceding the massive tumor regression. G-MDSC, granulocytic myeloid-derived suppressor cells; M-MDSC, monocytic myeloid-derived suppressor cells. Data are pooled from 2 independent experiments, with n = 7 in the proliferating group and n = 9 in the senescent group. Note that, as the absolute number of CD45+ cells increases in senescent NSP tumor lesions (A), so do the total numbers of the indicated cell types. C, Flow cytometry analysis of CD8 T cells. Data are pooled from 2 independent experiments, with n = 11 in the proliferating and n = 10 in the senescent groups. Experiments were performed 9 days after Dox withdrawal. D, Representative tissue clearing images of the orthotopic NSP liver tumors. T cells, neutrophils, and vasculature are labeled by CD3, MPO, and CD31 staining, respectively. Samples were collected 9 days after Dox withdrawal. E, Tumor size change measured by ultrasound upon p53 restoration in mice after depleting specific immune cell types using antibodies or drugs. F, Left, uniform manifold approximation and projection (UMAP) plot of CD8 T cells isolated from p53-suppressed proliferating (PRO) and p53-reactivated senescent (SEN) tumors. Right, gene set enrichment analysis of T-cell exhaustion marker genes in CD8+ T cells from proliferating (p53-suppressed) versus senescent (p53-reactivated) tumors. NES, normalized enrichment score; Pval, P value. G, UMAP plot of the expression of selected genes (Cd8a, Cd44, Tnfrsf9, Cd69, Tox, and Fasl) between CD8 T cells isolated from senescent (p53-reactivated) and proliferating (p53-suppressed) tumors. H, Representative immunofluorescence images of CD8 T cells and F4/80-positive macrophage staining in the orthotopic NSP liver tumor. Tumor samples were collected 9 days after Dox withdrawal. Data are presented as mean ± SEM. All scale bars, 100 μm. A two-tailed Student t test was used. *, P < 0.05; **, P < 0.01.

Cellular senescence is characterized by stable cell-cycle arrest and a secretory program that modulates the tissue microenvironment1,2. Physiologically, senescence serves as a tumour-suppressive mechanism that prevents the expansion of premalignant cells3,4 and has a beneficial role in wound-healing responses5,6. Pathologically, the aberrant accumulation of senescent cells generates an inflammatory milieu that leads to chronic tissue damage and contributes to diseases such as liver and lung fibrosis, atherosclerosis, diabetes and osteoarthritis1,7. Accordingly, eliminating senescent cells from damaged tissues in mice ameliorates the symptoms of these pathologies and even promotes longevity1,2,8-10. Here we test the therapeutic concept that chimeric antigen receptor (CAR) T cells that target senescent cells can be effective senolytic agents. We identify the urokinase-type plasminogen activator receptor (uPAR)11 as a cell-surface protein that is broadly induced during senescence and show that uPAR-specific CAR T cells efficiently ablate senescent cells in vitro and in vivo. CAR T cells that target uPAR extend the survival of mice with lung adenocarcinoma that are treated with a senescence-inducing combination of drugs, and restore tissue homeostasis in mice in which liver fibrosis is induced chemically or by diet. These results establish the therapeutic potential of senolytic CAR T cells for senescence-associated diseases.

Abstract Chimeric Antigen Receptor (CAR) T cells are a modality of immunotherapy that act to eliminate cancer cells by redirecting the cytolytic activity through targeting a protein overexpressed on the surface of the cancer cell. In contrast to move conventional cancer therapies, their anti-cancer activity does not depend on a cancer-specific molecular vulnerability but rather the differential expression of the target antigen on tumor cells compared to normal tissues. We have developed CAR T cells targeting the urokinase plasminogen activator receptor (uPAR), which is overexpressed on senescent cells but not expressed highly in vital organs, to selectively target senescent cells in a range of tissue damage pathologies where they are known to be pathogenic. uPAR is also highly overexpressed in a wide range of cancer types, including pancreatic, kidney, bladder, brain and ovarian carcinomas, respectively, raising the possibility that CAR T cells targeting uPAR may also be effective against cancer. Indeed, leveraging an electroporation-based genetically-engineered mouse model of ovarian cancer, we demonstrate the robust anti-tumor efficacy of murine uPAR CAR T cells in immunocompetent syngeneic mice. Moreover, through an exhaustive functional screening of 37 distinct human uPAR single-chain fragment variants (scFVs), we have successfully identified lead scFVs exhibiting subnanomolar affinity to membrane-anchored uPAR. Significantly, these human uPAR CAR T cells exhibit the capability to eliminate both orthotopic and metastatic human HGSOC xenograft tumors without inducing severe adverse effects. Ongoing efforts encompass the assessment of the long-term safety and toxicity profiles of uPAR CAR T cells utilizing a humanized mouse model platform. Our results provide a strong rationale for developing uPAR CAR T cells as an anticancer strategy relevant to a broad range of tumor types, and provide an avenue for safety profiling of uPAR CAR T cells prior to clinical testing in non-cancer patients harboring senescence-related pathologies. Citation Format: Zeda Zhang, Xin Fang, Yu-jui Ho, Sascha Haubner, Friederike Kogel, Clemens Hinterleitner, Stella Paffenholz, Kevin Chen, Wei Luan, Amanda Kulick, Gertrude Gunset, Andreina Garcia Angus, Jing Zhang, Zijian Xu, Adam Wang, Qingwen Jiang, Elisa de Stanchina, Britta Weigelt, Dmitriy Zamarin, Aveline Filliol, Judith Feucht, Jorge Mansilla-Soto, Corina Amor, Michel Sadelain, Scott Lowe. Developing uPAR CAR T Cells for High-Grade Serous Ovarian Cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 115.

INTRODUCTION:Copy number alterations of chromosome 9p, or parts thereof, impair immune response and confer immune-checkpoint therapy (ICT) resistance by direct elimination of immune-regulatory genes on this arm, notably interferon (IFN)-γ (at 9p24.1) and type I IFN (IFN-I) cluster (9p21.3) genes. Nevertheless, the primary 9p-loss human tumor immune readout is indirect (CXCL9/10 depletion at 4q21.1), and molecular alteration of chromosomes with engineered tandem elements-engineered 9p21.3-syntenic deletions in mice, Cdkn2a/b±Mtap (ΔS) versus larger Cdkn2a/b+Mtap+IFN-I (ΔL), revealed the causal link of IFN-I, primarily IFNϵ, to immune evasion. METHODS:This report updates and explicates the rapidly emerging body of clinical 9p ICT-cohort data and executes human (tumor, cell line) and mouse-model intrinsic 9p, IFN-I, and tumor-immune microenvironment CXCL9/10 deconvolution, mediation, and experimental studies. We analyzed CXCL9/10-CXCR3 cell sources and regulation by 9p deletion (size and depth) and mouse spatial single-cell RNA sequencing (scRNA-seq) syntenic chr4qC4 IFN-I (ΔS versus ΔL immune-evasive model) studies of immune-cell type, subtype, and subcluster Cxcl9/10+ numbers, fractions, and per-cell expression. RESULTS:Chr9p (9p, 9p21.3, 9p24.1) copy number loss is associated with immune-cold, programmed cell death protein 1 axis ICT-resistant human papillomavirus-negative head and neck squamous cancer, nonsquamous NSCLC, melanoma, urothelial cancer, and mesothelioma (13 reports, 36 ICT cohorts; <4 y). IFN-I has been associated with IFNα and ICT resistance. In human papillomavirus-negative head and neck squamous cancer, IFNE was the most highly expressed (and suppressed in 9p loss) IFN-I gene in tumors and cell lines, driven by 9p21.3 (q = 0.03; versus 9p24.1, q = 0.27); direct link to effector T-cell suppression (CD8 strongest, p = 0.006; mediation analysis), exhibited striking TP53 mutation co-occurrence and IFN-response pathway depletion. Progressively deep 9p21.3 loss (wild-type, shallow, deep) correlated with progressive IFNE and CXCL9/10-CXCR3 suppression; 9p21.3 ΔS (versus ΔL) IFN-I impact on CD8, NK (CD4, B, CD103) levels. Pan-tumor IFNE loss/tumor-immune microenvironment patterns were profoundly tissue-specific (Z ≤ 1.95 in 4/34 tumor types). IFN-intact ΔS (versus ΔL) KPC pancreatic model was linked to Cxcl9/10+ dendritic cell (DC), macrophage, and neutrophil number (confirmed in KPL-3M nonsquamous NSCLC), and macrophage per-cell expression. DC and macrophage subclustering revealed heterogeneity at the level of M1, Ccl5, and conventional type 1 DC (cDC1), particularly high in ΔS. CONCLUSION:IFNϵ is the elusive, cell-intrinsic 9p21 IFN-I signal to human CD8 T-cell, myeloid DC, CXCL9/10, murine DC, and macrophage subtype and subcluster Cxcl9/10 expression. 9p-loss IFN-I and IFN-γ pathway (e.g., JAK2) genes at p21 and p24 lack the capacity of endogenous CXCL9/10 induction in an immune-desert, ICT-resistant state. These findings, 9p-loss/ICT-resistance data, and DC vaccine lung trials have led to a DC-CXCL9/10 vaccine, designed to bypass the severe chemokine deficit in 9p-loss tumors.

There is optimism that cancer drug resistance can be addressed through appropriate combination therapy, but success requires understanding the growing complexity of resistance mechanisms, including the evolution and population dynamics of drug-sensitive and drug-resistant clones over time. Using DNA barcoding to trace individual prostate tumor cells in vivo , we find that the evolutionary path to acquired resistance to androgen receptor signaling inhibition (ARSI) is dependent on the timing of treatment. In established tumors, resistance occurs through polyclonal adaptation of drug-sensitive clones, despite the presence of rare subclones with known, pre-existing ARSI resistance. Conversely, in an experimental setting designed to mimic minimal residual disease, resistance occurs through outgrowth of pre-existing resistant clones and not by adaptation. Despite these different evolutionary paths, the underlying mechanisms responsible for resistance are shared across the two evolutionary paths. Furthermore, mixing experiments reveal that the evolutionary path to adaptive resistance requires cooperativity between subclones. Thus, despite the presence of pre-existing ARSI-resistant subclones, acquired resistance in established tumors occurs primarily through cooperative, polyclonal adaptation of drug-sensitive cells. This tumor ecosystem model of resistance has new implications for developing effective combination therapy.

IFNγ signaling in senescent tumor cells is necessary for immune surveillance. A,Ifngr1 KO of both proliferating and senescent NSP cells validated by flow cytometry. B, Tumor regression phenotype of Ifngr1 KO or control sgRNA–transfected tumor cells orthotopically injected into Bl/6N mice upon p53 restoration. A control sgRNA targeting a gene desert located on Chr8 (Ctrl KO) serves as a control. C, Tumor regression phenotype of parental NSP tumor cells orthotopically injected into WT or Ifng KO mice upon p53 restoration. D, Representative macroscopic images of tumor collected at day 21 after p53 restoration from C. E, Flow cytometry analysis of CD45 abundance in tumor from indicated groups. F, Representative immunofluorescence in p53-suppressed (proliferating) and p53-restored (senescent, 7 days after p53 restoration) tumor from the indicated host. NSP tumor cells were transduced with GFP-expressing vector for visualization. Scale bars, 50 μm. Data are presented as mean ± SEM. Two-tailed Student t test was used. **, P < 0.01; ***, P < 0.001.

Senescence remodels tissue-sensing programs and cell-surfaceome landscape. A, Gene set enrichment analysis (Reactome) of RNA-seq data from proliferating (PRO, p53 off) versus senescent (SEN, p53 on for 8 days) NSP liver tumor cells in vitro. NES, normalized enrichment score. B, Subcellular localization of DEGs (P < 0.05; fold change > 2) in all detected genes [transcripts per kilobase million (TPM) > 1] from RNA-seq. C, Gene ontology (GO) analysis of DEGs encoding PM proteins upregulated in senescent cells. TM, transmembrane. D, Transcriptomic analysis of all DEGs (proliferating vs. senescent) in the presence or absence of JQ1 treatment. The C1 cluster (in red) contains the senescence-specific genes sensitive to JQ1, and the C4 cluster (in blue) contains the proliferation-specific genes sensitive to JQ1. E, Meta-analysis of RNA-seq dataset from SENESCopedia by performing subcellular localization of DEGs (same as Fig. 2D) and Fisher exact test to examine the relative enrichment of upregulated and downregulated EC/PM-DEGs deviated from the random distribution. See also Supplementary Fig. S7E and S7F. F, Mass spectrometry (MS) analysis of PM-enriched proteome in proliferating and senescent cells. Protein level is normalized to mean expression of the protein of all samples. Controls are the samples without biotin labeling serving as background. Red and blue boxes represent proteins enriched in senescent and proliferating cells, respectively. n = 6 for both the senescent and proliferating experimental groups, and n = 3 and 4, respectively, for their control. G, Distribution of upregulated and downregulated GeneCards-annotated PM proteins profiled by MS. NC, no change. H, Volcano plot of GeneCards-annotated PM proteins profiled by MS.

Senescent cells, which accumulate in organisms over time, contribute to age-related tissue decline. Genetic ablation of senescent cells can ameliorate various age-related pathologies, including metabolic dysfunction and decreased physical fitness. While small-molecule drugs that eliminate senescent cells (‘senolytics’) partially replicate these phenotypes, they require continuous administration. We have developed a senolytic therapy based on chimeric antigen receptor (CAR) T cells targeting the senescence-associated protein urokinase plasminogen activator receptor (uPAR), and we previously showed these can safely eliminate senescent cells in young animals. We now show that uPAR-positive senescent cells accumulate during aging and that they can be safely targeted with senolytic CAR T cells. Treatment with anti-uPAR CAR T cells improves exercise capacity in physiological aging, and it ameliorates metabolic dysfunction (for example, improving glucose tolerance) in aged mice and in mice on a high-fat diet. Importantly, a single administration of these senolytic CAR T cells is sufficient to achieve long-term therapeutic and preventive effects.

Driver gene mutations can increase the metastatic potential of the primary tumor1-3, but their role in sustaining tumor growth at metastatic sites is poorly understood. A paradigm of such mutations is inactivation of SMAD4 - a transcriptional effector of TGFβ signaling - which is a hallmark of multiple gastrointestinal malignancies4,5. SMAD4 inactivation mediates TGFβ's remarkable anti- to pro-tumorigenic switch during cancer progression and can thus influence both tumor initiation and metastasis6-14. To determine whether metastatic tumors remain dependent on SMAD4 inactivation, we developed a mouse model of pancreatic ductal adenocarcinoma (PDAC) that enables Smad4 depletion in the pre-malignant pancreas and subsequent Smad4 reactivation in established metastases. As expected, Smad4 inactivation facilitated the formation of primary tumors that eventually colonized the liver and lungs. By contrast, Smad4 reactivation in metastatic disease had strikingly opposite effects depending on the tumor's organ of residence: suppression of liver metastases and promotion of lung metastases. Integrative multiomic analysis revealed organ-specific differences in the tumor cells' epigenomic state, whereby the liver and lungs harbored chromatin programs respectively dominated by the KLF and RUNX developmental transcription factors, with Klf4 depletion being sufficient to reverse Smad4's tumor-suppressive activity in liver metastases. Our results show how epigenetic states favored by the organ of residence can influence the function of driver genes in metastatic tumors. This organ-specific gene-chromatin interplay invites consideration of anatomical site in the interpretation of tumor genetics, with implications for the therapeutic targeting of metastatic disease.

Senescent cells are primed to sense and amplify IFNγ signaling. A and B, IFNGR1 level on proliferating and senescent cells profiled by mass spectrometry (A) and validated by flow cytometry (B). AU, arbitrary unit. Data are presented as mean ± SEM. n = 6 for both the proliferating and senescent groups. C, Transcriptomic analysis of selected genes regulating IFNγ signaling from RNA-seq data of 3 independent p53-restorable cell lines (NSP, NSM2, and NSP5) restoring p53 along with NSP cells treated with two other senescence triggers. SEN/PRO, senescent/proliferating; T + P, trametinib plus palbociclib. D, mRNA expression of selected genes involved in IFNγ signaling in human cell lines triggered to senesce. Treatment: Ali, alisertib; Eto, etoposide; number indicates the length of treatment (days). Data are obtained from the public dataset SENESCopedia (44). E, Top, immunoblot analysis of NSP cells under different senescent triggers in the presence or absence of IFNγ (1 ng/mL). Bottom, quantification of the intensity of signal from immunoblot. p-STAT1, phospho-STAT1 (Tyr701).