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.

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

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

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.

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.

Abstract Pancreatic ductal adenocarcinoma (PDAC) is generally diagnosed at advanced late stages when current treatments are usually ineffective. It is initiated from a poorly understood interplay between genetic mutations (mutant KRAS) and inflammatory insults that cooperatively remodel the pancreatic epithelium and its tissue environment. Through integrating innovative autochthonous mouse models, single-cell technologies, and genomics methods, we recently identified early, tumor-specific chromatin changes induced by cooperative effects between mutant KRAS and inflammation, and which establish functionally-relevant cell-cell communication networks that direct pancreatic tumorigenesis (Alonso-Curbelo et al. Nature 2021; Burdziak*, Alonso-Curbelo* et al. Science 2023). These findings provide a molecular and cellular framework to understand inflammation-driven tumorigenesis, and raise the possibility of harnessing epigenetically-dysregulated cell-cell communication traits of KRAS-mutant cells to detect or block PDAC development. Towards this end, we are currently combining single-cell multiomics, multiplexed tissue analyses, and functional approaches in pre-clinical models to identify how tissue signals shape the state and fate of early KRAS-mutant cells, define paracrine effects of these changes in reprogramming the immune microenvironment, and establish the functional significance of these interactions in disease progression. With the advent of inhibitors targeting mutant KRAS, we expect that the proposed dissection of the cell-cell crosstalk networks cooperating with mutant KRAS in driving tumor development will uncover tissue-level mechanisms that may be harnessed for the interception and rationale treatment of PDAC. Citation Format: Katharina Woess, Sandra Blázquez Araguás, Andrea Diéguez, Lidia Mateo, Direna Alonso Curbelo. Investigating oncogene-inflammation cooperativity in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C040.

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).

How spreading tumour cells gain the ability to grow in organs away from where they originated is not fully understood. The discovery that normal liver cells help invading tumour cells to thrive in this organ sheds light on this process. How healthy cells influence whether cancer spreads at a secondary site.

Abstract Cellular senescence involves a stable cell-cycle arrest coupled to a secretory program that, in some instances, stimulates the immune clearance of senescent cells. Using an immune-competent liver cancer model in which senescence triggers CD8 T cell–mediated tumor rejection, we show that senescence also remodels the cell-surface proteome to alter how tumor cells sense environmental factors, as exemplified by type II interferon (IFNγ). Compared with proliferating cells, senescent cells upregulate the IFNγ receptor, become hypersensitized to microenvironmental IFNγ, and more robustly induce the antigen-presenting machinery—effects also recapitulated in human tumor cells undergoing therapy-induced senescence. Disruption of IFNγ sensing in senescent cells blunts their immune-mediated clearance without disabling the senescence state or its characteristic secretory program. Our results demonstrate that senescent cells have an enhanced ability to both send and receive environmental signals and imply that each process is required for their effective immune surveillance. Significance: Our work uncovers an interplay between tissue remodeling and tissue-sensing programs that can be engaged by senescence in advanced cancers to render tumor cells more visible to the adaptive immune system. This new facet of senescence establishes reciprocal heterotypic signaling interactions that can be induced therapeutically to enhance antitumor immunity. See the interview with Direna Alonso-Curbelo, PhD, recipient of the inaugural Cancer Discovery Early Career Award: https://vimeo.com/992987447 See related article by Marin et al., p. 410. This article is highlighted in the In This Issue feature, p. 247