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      Clearance of senescent glial cells prevents tau-dependent pathology and cognitive decline

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          Abstract

          Cellular senescence, characterized by an irreversible cell-cycle arrest 1 accompanied by a distinctive secretory phenotype 2 , can be induced through a variety of intracellular and extracellular factors. Senescent cells expressing the cell cycle inhibitory protein p16INK4A, have been found to actively drive naturally occurring age-related tissue deterioration 3,4 and contribute to several aging-associated diseases, including atherosclerosis 5 and osteoarthritis 6 . Various markers of senescence have been observed in patients suffering from neurodegenerative diseases 7-9 , however, a role for senescent cells in the etiology of these pathologies is unknown. Here we show a causal link between the accumulation of senescent cells and cognition-associated neuronal loss. We found that the MAPT P301S PS19 mouse model of tau-dependent neurodegenerative disease 10 accumulates p16Ink4a-positive senescent astrocytes and microglia. Clearance of these cells as they arise using INK-ATTAC transgenic mice prevented gliosis, hyper-phosphorylation of both soluble and insoluble tau leading to neurofibrillary tangle (NFT) deposition, and degeneration of cortical and hippocampal neurons to preserved cognitive function. Lastly, pharmacological intervention with a first generation senolytic modulated tau aggregation. Collectively, these results demonstrate that senescent cells play a role in tau-mediated disease initiation and progression; suggesting that targeting senescent cells may provide a therapeutic avenue for treating these pathologies. Senescent cells accumulate with aging and have been shown to contribute to tissue dysfunction 11 , although their role in neurodegenerative disease has remained elusive. To address this key open question, we selected the tau MAPT P301S PS19 (hereafter PS19) transgenic mouse line that expresses high levels of mutant human tau specifically in neurons under the regulation of the mouse prion promoter 10 . The model is characterized by gliosis, neurofibrillary tangle (NFT) deposition, neurodegeneration, and loss of cognitive function. Pathology typically initiates in the hippocampus and radiates outwards to the neocortex 10 . First, we performed RT-qPCR for p16 Ink4a on isolated hippocampi and cortices from Wildtype and PS19 littermates. p16 Ink4a expression was significantly increased beginning at 4 months of age in the hippocampus and at 6 months in the cortex (Fig. 1a), which precedes the onset of NFT deposition 10 . Importantly, increased p16 Ink4a expression correlated with expression of widely established senescence markers (Extended Data Fig. 1), indicating that senescent cells accumulate at sites of pathology in the PS19 model. To investigate the role of senescent cells in disease development, we crossed the INK-ATTAC transgene (hereafter ATTAC) to the PS19 strain to eliminate p16 Ink4a-expressing senescent cells through biweekly administration of AP20187 (hereafter AP) 3,4 from weaning age (Fig. 1b). Hippocampi and cortices isolated from 6-month-old vehicle administered PS19;ATTAC mice displayed an elevated level of the ATTAC transgene as measured by Casp8 and GFP (Fig. 1c and Extended Data Fig. 2). Senescence indicators, including the cell cycle regulators p16 Ink4a, p19 Arf, p21 Cip1/Waf1 and the pro-inflammatory genes Pai1 (also called Serpine1), Il-6, and Il-1β, were also elevated (Fig. 1c, Extended Data Fig. 2). AP administration in PS19;ATTAC mice maintained the expression of these genes at a level comparable to control mice (Fig. 1c, Extended Data Fig. 2). Importantly, AP treatment of ATTAC mice lacking the PS19 transgene had no impact on the expression of these markers (Extended Data Fig. 2). Thus, AP administration effectively and selectively cleared senescent cells in the hippocampus and cortex of PS19;ATTAC mice. To understand the mechanistic contribution of senescence to tau–mediated pathology, we sought to identify the specific cell types that were becoming senescent. Firstly, we stained cortices and hippocampi from 6-month-old vehicle-treated ATTAC and PS19;ATTAC and AP-treated PS19;ATTAC mice for senescence-associated-β-galactosidase (SA-β-Gal) 12 and screened for cells that contained X-Gal crystals by transmission electron microscopy (TEM) 13 . We found that cells that clearly and morphologically resembled astrocytes or microglia contained X-Gal crystals, irrespectively of the mouse group (Fig. 1d). In contrast, no crystals were found in any clearly identifiable neurons (Extended Data Fig. 3). Vehicle-treated PS19;ATTAC mice had nearly double the number of cells containing X-Gal crystals in both the hippocampus and cortex (Fig. 1e), whereas AP-treated PS19;ATTAC mice had a similar incidence of X-Gal crystals as control mice (Fig. 1e). To validate that senescence was impacting astrocytes and microglia, we performed FACS on 6-month-old Wildtype and PS19 mice (Extended Data Fig. 4a). Isolated astrocytes and microglia had increased expression of senescence-associated genes, including p16 Ink4a (Extended Data Fig. 4b, c). A similar induction was not observed in oligodendrocytes or neuron-enriched CD56+ cells (Extended Data Fig. 4d, e and Extended Data Fig. 5), supporting the conclusion that senescence occurs in astrocytes and microglia of PS19 mice. To verify that AP administration selectively targeted senescent cells, we made in vitro cultures of primary microglia and astrocytes isolated from ATTAC mice. These cultures were not sensitive to AP-mediated elimination in the absence of senescence-inducing stimuli (Extended Data Fig. 6). Furthermore, short-term AP administration did not promote excessive cellular death (Extended Data Fig. 7a) or increased proliferation of microglia with extended treatment of ATTAC transgenic mice in vivo (Extended Data Fig. 7b). PS19 mice present progressive gliosis with disease progression 10 . To assess if AP administration impacted this process, RT-qPCR was performed on 6-month-old hippocampi for markers of astrocytes (GFAP and S100β) and microglia (Cd11b). Vehicle-treated PS19;ATTAC mice had an ~2–3 fold induction in these markers, whereas AP-treated PS19;ATTAC mice expressed these markers at a similar level to control mice (Extended Data Fig. 8a, b). Immunohistochemistry (IHC) for GFAP and Iba1 confirmed these observations (Extended Data Fig. 8c, d). Taken together, these results suggest that both gliosis and glial cell senescence in the PS19 mouse model are effectively eliminated upon the administration of AP in ATTAC mice. A distinguishing characteristic of PS19 mice is the development of aggregates consisting of hyperphosphorylated tau protein by 6 months of age 10 . To assess if tau aggregation was impacted with senescence clearance, we probed for the levels of soluble total and phosphorylated tau (Ser202/Thr205) in addition to the level of insoluble phosphorylated tau in vehicle-treated PS19;ATTAC and AP-treated ATTAC and PS19;ATTAC mice. As expected 10 , vehicle-treated PS19;ATTAC mice displayed increased soluble total and phosphorylated tau and insoluble phosphorylated tau (Fig. 2a, Extended Data Fig. 9a, b). AP-treated PS19;ATTAC mice showed identical levels of soluble total tau protein to vehicle-treated PS19;ATTAC mice (Fig. 2a), indicating that tau over-expression from the transgene was maintained. Surprisingly, AP treatment of PS19;ATTAC mice significantly reduced the amount of phosphorylated tau in both the soluble and insoluble fraction (Fig. 2a, Extended Data Fig. 9b). IHC staining for phospho-tau modifications at S202/T205, T231, and S396 confirmed that senescent cell clearance attenuated tau phosphorylation at a number of residues relevant for tau aggregation (Fig. 2b, Extended Data Fig. 9c). Furthermore, thioflavin S staining of 8-month-old mice from these same groups revealed that NFT deposition in the dentate gyrus, the site of neurogenesis in the hippocampus traditionally associated with memory formation and cognition 14 , was substantially reduced when senescent cells were removed (Fig. 2c). Collectively, these results indicate that senescent cell accumulation promotes the formation of hyperphosphorylated tau aggregates. PS19 mice show neurodegeneration by 8 months of age 10 . As NFT deposition was attenuated with AP treatment in both the cortex and hippocampus of PS19;ATTAC mice, we performed assessments for degeneration in these areas. Overt brain size of vehicle-treated PS19;ATTAC mice was reduced compared to both ATTAC and AP-treated PS19;ATTAC mice (Fig. 3a). In addition, we observed localized neurodegeneration in the dentate gyrus of the hippocampus through Nissl staining in vehicle-treated PS19;ATTAC mice (Fig. 3b). AP administration prevented thinning of the dentate gyrus and increased neuron density. Sequential coronal sectioning and NeuN staining revealed that the dentate gyrus was significantly reduced in vehicle-treated PS19;ATTAC mice (Fig. 3c), further demonstrating that senescent cells promote neurodegeneration in PS19 mice. To test whether this improved cognitive function, we performed novel scent discrimination assessments to test for changes in short-term memory (see experimental setup Fig. 3d) 15 . Whereas AP-treated ATTAC mice were more inquisitive to the novel scent during the testing phase, vehicle-treated PS19;ATTAC mice were not (Fig. 3d). In contrast, AP-treated PS19;ATTAC mice behaved nearly identically to control mice, indicating that senescent cell elimination mitigated the short-term memory loss observed in vehicle-treated PS19;ATTAC mice. Importantly, the overall distance traveled by mice in all groups was unchanged (data not shown) and similar results were obtained with novel object discrimination tests using the same setup using visual cues instead of scents (Extended Data Fig. 10). Thus, these results demonstrate that senescent cells drive neurodegeneration and loss of cognition in PS19 mice. Lastly, we tested whether pharmacological elimination of senescent cells with the senolytic ABT263 (navitoclax) 5,6,16,17 exhibited similar impacts to our genetic interventions in PS19 mice. Recent work has demonstrated a therapeutic effect in orthotopically implanted glioblastomas with peripheral administration pf ABT263 18 . WT and PS19 mice were treated with a repeating schedule of ABT263 beginning at weaning age until the mice reached 6 months of age. Importantly, this treatment prevented the upregulation of senescence-associated genes (Fig. 4a) and attenuated tau phosphorylation in PS19 mice (Fig. 4b), indicating that senolytic interventions can recapitulate key observations from transgenic mouse models of senescent cell ablation. The mechanistic contribution of cells with features reminiscent of senescence to the pathophysiology of neurodegenerative diseases has been a common question in recent years 7–9,19–21 . Furthermore, recent work has suggested that senescent cells may contribute to Parkinson’s disease pathology in both mice and humans 22 . Here we show that continuous clearance of p16 Ink4a-expressing senescent cells prior to disease onset in a model of aggressive tauopathy has a significant impact on various aspects of disease progression including gliosis, NFT formation, neurodegeneration, and cognitive decline. Remarkably, senescent cell clearance has a significant impact on the accumulation of phosphorylated tau protein in both the soluble and insoluble fractions. The amount of total soluble tau was unchanged in AP-treated PS19;ATTAC mice (Fig. 2a), indicating that the aberrant hyper-phosphorylation of tau protein and subsequent aggregation into NFTs is mediated by extracellular signaling from p16 Ink4a-expressing senescent glial cells. The molecular mechanisms that senescent astrocytes and microglia exploit to promote pathological conversion of tau into NFTs within neurons require additional investigation. The absence of neurodegeneration in AP-treated mice (Fig. 3) demonstrates that attenuated disease severity is not due to clearance of neurons harboring NFTs. However, it is important to leave open the possibility that other neurodegenerative disease models may exhibit senescence-associated alterations in cell types not observed in the present study. Regardless, it is likely that intervention in senescent cell accumulation in these models would also reduce disease severity based on our observations. As this study was designed to prevent senescent cells from accumulating to determine how this impacts disease, future studies of senolysis in established disease models will be necessary to determine the utility of senolytic strategies to translate into the clinic to stall or perhaps revert disease. As senescent cells exhibit a unique and identifiable SASP, exploiting this phenotype may serve as a possible therapeutic avenue to attenuate many tau-dependent pathologies. Our observation that p16 Ink4a expression increases prior to NFT aggregation further supports the now commonly held belief that early intervention in these diseases is essential to provide more favorable impacts to patients. Methods Mouse strains and drug treatment MAPT P301S PS19 (PS19) mice were purchased from The Jackson Laboratory (stock #008169) and bred to C57BL/6 for three generations. C57BL/6 ATTAC transgenic mice are as described 3,4 . Male PS19 mice were bred to ATTAC females to generate cohorts of ATTAC and PS19;ATTAC mice. All mice were on a pure C57BL/6 genetic background. Mice from this cohort were randomly assigned to receive AP20187 (AP; B/B homodimerizer; Clontech) or vehicle twice a week beginning at weaning age (3 weeks). Dosing of AP was 2.0 mg kg–1 body weight. 6-month-old short-term AP pulse treated animals (Extended Data Fig. 6a) received a dose of 10 mg kg–1 body weight for 5 consecutive days prior to tissue collection. Senolytic intervention was performed in C57BL/6 WT and PS19 animals. At weaning, mice were assigned to receive either ABT263 (Cayman, 923564–51-6) or vehicle (Phosal 50 PG, Lipoid NC0130871 – 60%; PEG400, Sigma 91893 – 30%, EtOH – 10%). ABT263 was administered by oral gavage at a dose of 50 mg kg–1 body on a repeating regiment of five consecutive days of treatment followed by 16 days of rest. Animals were housed in a 12h L/D cycle environment in pathogen-free barrier conditions as described in detail 3 . Compliance with relevant ethical regulations and all animal procedures were reviewed and approved by the Mayo Clinic Institutional Animal Care and Use Committee. Statistical analysis Prism software was used for all statistical analysis. A student’s two-tailed unpaired t-test with Welch’s correction was used in Fig. 1a and Extended Data Fig. 4b – e; two-way ANOVA with Tukey’s multiple comparisons test was used for Fig. 3d and Extended Data Fig. 10; and one-way ANOVA with Tukey’s multiple comparisons test was used in all other figures. For consistency in these comparisons, the following denotes significance in all figures: *P < 0.05, **P < 0.01, ***P < 0.001. We note that no power calculations were used. Sample sizes are based on previously published experiments where differences were observed. No samples were excluded. Investigators were blinded to allocation during experiments and outcomes assessment, except for rare instances where blinding was not possible. All source data and exact P values (if applicable) for every figure are included in the supporting information that accompanies the paper. Senescence-associated β-galactosidase transmission electron microscopy (Gal-TEM) Detection of X-Gal crystals by transmission electron microscopy (TEM) after senescence-associated β-galactosidase (SA-β-Gal) staining was performed as described 3,5 with the following alterations to accommodate central nervous tissue. Mice were transcardially perfused with ice-cold Dulbecco’s phosphate-buffered saline (DPBS; pH 7.4) until fluid runoff was clear. This was followed by perfusion with 4% paraformaldehyde (PFA) for 10 minutes at a rate of 3 ml per minute, and then ice-cold DPBS was perfused again for 2 minutes at the same rate to remove the remaining fixative. Brains were then isolated and the hippocampus and cortex were dissected out. A 1 mm x 1 mm piece from the CA1 and M1 region, respectively, was then incubated in SA-β-Gal staining solution (Cell Signaling) at 37°C for 6 h (hippocampus) or 18 h (cortex). The samples were placed in Trump’s fixative overnight at 4°C before being processed for routine transmission electron microscopy (dehydration by xylene-alcohol series, osmium tetroxide staining, and Epon resin embedding). Images were acquired and quantified using a Jeol 1400+ electron microscope with 80 kV acceleration voltage. Two grids from each tissue were produced, and >100 cells were scanned per grid at a magnification of 20,000x to detect X-Gal crystal containing cells. On average, half of all cells examined were neurons. Cells with one or more crystals and the total number of cells were counted. Cells containing crystals were imaged and independently assessed for distinguishing morphology. To define cell type, the following criteria were applied: 1) astrocytes – circular nucleus with spattered electron density pattern; 2) microglia – abnormally shaped nucleus with a much darker, often phagosome containing cytoplasm; and 3) neuron – large circular nucleus with less electron density and periodically denoted by an offshooting axon. Only cells with morphology consistent of astrocytes or microglia were clearly X-gal crystal positive. Western blotting for soluble and sarkosyl insoluble proteins Half brains were weighed and homogenized in 5X volume of Buffer I (50 mM Tris base [pH 7.4], 50mM NaCl, 1mM EDTA, 1mM PMSF, 1X Halt™ Protease and Phosphatase Inhibitor Cocktail [Thermo]). 250ul of the homogenate was then added to an equal volume of Buffer S (50 mM Tris [pH 8.0], 274 mM NaCl, 5 mM KCl, 1 mM PMSF, 1X Halt™ Protease and Phosphatase Inhibitor Cocktail [Thermo]) and ultracentrifuged at 150,000g for 15 minutes at 4°C. The supernatant (S1-soluble protein fraction) was transferred to a new tube and the pellet homogenized in 3x volume of sucrose buffer (10 mM Tris [pH7.4], 0.8M NaCl, 10% sucrose, 1mM EGTA, 1 mM PMSF) before being ultracentrifuged at 150,000g for 15 minutes at 4°C. The pellet was discarded and the supernatant incubated with sarkosyl (Sodium lauroyl sarcosinate) at a final concentration of 1% for 1 hour at 37°C. Following incubation, the samples were ultracentrifuged at 150,000g for 30 minutes at 4°C. The supernatant was discarded and the pellet was re-suspended in 25ul Buffer F (10 mM Tris [pH8.0], 1mM EDTA) to get the insoluble protein fraction (S2). Equal parts of 2x laemmli buffer (Bio-Rad) containing 5% β-mercaptoethanol was added to each fraction (S1 and S2) and boiled at 100°C for 15 minutes to prepare the sarkosyl soluble and insoluble protein lysates. For total protein lysate, 90ul of the homogenate (half brain in 5X volume Buffer I) was added to 110ul of Buffer T (2% SDS, 50 mM Tris [pH7.4], 274 mM NaCl, 5 mM KCl, 5mM EDTA, 1% Triton-X-100, 1 mM PMSF, X Halt™ Protease and Phosphatase Inhibitor Cocktail [Thermo]). The samples were then sonicated and centrifuged at 16,000g for 15 minutes at 4°C to remove debris. The supernatant was removed and added to equal parts 2x laemmli buffer with 5% β-mercaptoethanol and boiled at 100°C for 15 minutes to prepare the total protein lysate. Western blotting was performed as previously described 23 . Blots were probed with antibodies for total tau (ThermoFisher; MN1000, 1:5000) and phospho-tau S202/T205 (ThermoFisher; MN1020, 1:1000). Ponceau S staining was performed to normalize lysate loading for the total and S1 fraction lysates. Quantification was performed using ImageJ as described 3 . Quantitative RT-PCR RNA extraction, cDNA synthesis, and RT-qPCR analysis were performed on hippocampi and cortical samples from mouse brains as previously described 24 . Primers used to amplify Casp8, GFP, p16 Ink4a , p19 Arf , p21, Pai1, Il-6, Il-1b and Cd11b were as previously described 3,5,24 . The following additional primers were used: GFAP forward 5’-CCTTCTGACACGGATTTGGT-3’, reverse 5’-TAAGCTAGCCCTGGACATCG-3’; S100β forward 5’-CCGGAGTACTGGTGGAAGAC-3’, reverse 5’-GGACACTGAAGCCAGAGAGG-3’; Aqp4 forward 5’-TGAGCTCCACATCAGGACAG-3’, reverse 5’-TCCAGCTCGATCTTTTGGAC-3’; Cx3cr1 forward 5’-GTTCCAAAGGCCACAATGTC-3’, reverse 5’-TGAGTGACTGGCACTTCCTG-3’; Olig forward 5’-CCCCAGGGATGATCTAAGC-3’, reverse 5’-CAGAGCCAGGTTCTCCTCC-3’; NeFL forward 5’-AGGCCATCTTGACATTGAGG-3’, reverse 5’-GCAGAATGCAGACATTAGCG-3’; TBP forward 5’-GGCCTCTCAGAAGCATCACTA-3’, reverse 5’-GCCAAGCCCTGAGCATAA-3’. Expression for all experiments was normalized first to TBP. Immunohistochemistry and immunofluorescence staining Mice were transcardially perfused as described above. Brains were stored in 4% PFA overnight at 4°C and then cryoprotected by incubating in a 30% sucrose solution for 48 hours at 4°C. Samples were sectioned into 30 μM thick coronal sections and stored in antifreeze solution (300g Sucrose, 300 mL Ethylene Glycol, 500 mL PBS) at −20°C. Nissl staining (Bregma −2.1 to −2.4 mm), thioflavin S staining (Bregma −1.4 to −1.6 mm), and phospho-tau S202/S205 (ThermoFisher, MN1020; 1:500), phospho-tau T231 (ThermoFisher, MN1040; 1:500), phospho-tau S396 (Abcam, 109390; 1:500), and Gfap (Dako, Z0334; 1:500) and Iba1 (Novus, NB100–1028; 1:100) IHC staining (Bregma 1.6 to 1.0 mm and Lateral 2.0 to 2.7 mm) was performed on free-floating sections as described 25–27 . NeuN staining (EMD, MAB377; 1:200) of five sections (between Bregma −1.3 to −2.5) to measure dentate gyrus area was performed as previously described 28 . For cellular proliferation assays, animals were injected with EdU (Carbosynth, NE08701; 75mg/kg) intraperitoneally 24 hours prior to sacrifice. Imaging of EdU positive cells (Lateral 0.75 to 1.25 mm) was performed following manufacturer’s instructions (Invitrogen - Click-iT™ EdU Alexa Fluor™ 488 Imaging Kit, C10337). Iba1 (Wako, 019–19741; 1:500) immunofluorescent staining and Iba1/EdU colocalization assessments were performed as previously described 28 . TUNEL staining (Lateral 0.75 to 1.25 mm) was performed according to the manufacturer’s instructions (Roche In Situ Cell Death Detection Kit, Fluorescein: 11684795910). Thioflavin S, EdU/Iba1 colocalization, and in vivo TUNEL stained images were acquired on a Zeiss LSM 780 confocal system using multi-track configuration. Single cell preparation and FACS Dissociation of cerebral tissue was performed using the Adult Brain Dissociation kit from Miltenyi (MACS, 130–107-677) according to the manufacturer’s instructions. Samples were then incubated with a viability dye, LIVE/DEAD Aqua (Invitrogen, L34966; 1:250) followed by incubation with Cd11b eFluor 450 (eBioscience, 48–0112-80, 1:100), Cd45 APC eFluor 780 (eBioscience, 47–0451-82; 1:200), Glast1 PE (Miltenyi Biotec, 130–095-821; 1:100), O1 AF 700 (R&D Systems, FAB1327N-100UG; 1:100), and Cd56 APC (R&D Systems, FAB7820A; 1:100). These samples were then sorted using a FACSAria IIu SORP (BD Biosciences), with gating parameters created using FACSDiva 8.0.1 (BD Biosciences). A precise gating strategy was used to maximize the purification of each isolated cell population. Briefly, populations were isolated first by a negative report of the viability dye indicating the cell is viable (Extended Data Figure 4), followed by a positive report of the desired marker, then negative reports of the other labels used. This strategy allowed for live cells containing only the desired marker to be sorted, while eliminating dead cells. Cells were sorted directly into lysis buffer and RNA was extracted with RNeasy Micro kits according to manufacturer’s instruction (Qiagen, cat #: 74004). cDNA synthesis and RT-qPCR analysis were performed as described above. Novel object recognition Novel object recognition testing was performed as previously described 15 . Briefly, mice from each cohort were acclimated to a 50 cm x 50 cm testing environment for a period of two minutes. After acclimation, the mice were removed, the testing area was cleaned with 70% EtOH, and two identical scented candles were placed in either corner of the testing area approximately 5 cm from either wall. Mice were reintroduced, and the ratio of both the number of visits and time spent at each candle was recorded for a period of ten minutes. Recording was performed from above (Panasonic WV-CP294) and all video files were analyzed with TopScan Version 3.00 (Clever Sys Inc.). Afterwards, the mice were removed, the testing area cleaned with 70% EtOH, and one candle was replaced with a novel scent. The mice were reintroduced and the number of visits and total time per candle was recorded as before. Testing also was performed with visual stimuli by placing identical toy brick towers at either corner and then replacing with a different toy brick tower in the testing phase using the same experimental paradigm monitoring for the number of investigations. In vitro astrocyte and microglia culture Astrocyte and microglia primary cultures were prepared in tandem from mixed glial cultures as previously described 29 . C57BL/6 WT and ATTAC pups (p0-p3) were sacrificed, and the cerebellum was discarded. The remaining tissue had its meninges removed using forceps and a dissection scope. Cleaned cerebral tissue was placed in chilled Earle’s Balanced Salt Solution with HEPES (EBSH) (NaCl [120 mM], NaH2PO4 [10 mM], KCl [2.5 mM], C6H12O6 [20 mM], HEPES [20 mM], NaHCO3 [10 mM], BSA [0.3%], H2O) until the remaining animals were sacrificed, and then animals were pooled together based on genotype (3–4 brains/group). The tissue was minced using a razor blade and dissociated by shaking in a 0.025% Trypsin/EBSH solution at 37°C for 30 minutes. FBS and MgSO4 (3.82%)/ DNAse I (1mg/ml) were added, and the sample was placed on ice for 5 minutes to halt trypsinization. Samples were mixed and centrifuged at 200g at 25°C for 5 minutes. The supernatant was discarded, and the remaining pellet was resuspended in EBSH. Tissue was triturated using a 1 ml pipet to completely dissociate the sample and allowed to settle for 5 minutes to remove large debris. Samples were then transferred to clean tubes and underlayed with a 4% BSA/EBSH solution. The tissue was then centrifuged at 100g at 25°C for 8 minutes. Cells were counted using trypan blue and a hemocytometer and plated on a PDL-coated T75 dish (7–10 million cells/flask) with glial cell culture media (GCM) consisting of DMEM with 10% FBS, C3H3NaO3 (1mM), Pen/Strep (500 ug/ml), and InvivoGen Primocin. Cultures were grown for 14 days (37°C ambient O2) with media changes every 4 days. Microglia were isolated as previously described 30 using the EasySep Mouse CD11b Positive Selection Kit from Stem Cell (cat #: 18970). Microglia were collected and plated on 10-well glass slides (5,000 cells/well) and cultured for 6 days in GCM with LADMAC-conditioned media (20%, generously provided by the Howe Laboratory) before further experimentation. This conditioned media aids in the proliferation and maintenance of microglia cultures through the secretion of M-CSF by the LADMAC cells 31 . Microglia were allowed to proliferate for 6 days prior to experimentation. The mixed glial culture flow-through from the EasySep CD11b kit was replated in GCM on a PDL-coated T75 dish (10 million cells/flask). These cultures then underwent purification for astrocytes as previously described 29 . After 48 hours, flasks were placed on an orbital shaker and agitated at 200 rpm for two 24-hour periods with media refreshed once during and after the shaking. Flasks were then exposed to GCM containing liposomal clodronate (Clodrosome, 8909; 100 µg/ml) for 72 hours to remove any remaining microglia from the culture. The liposomal clodronate media was then removed and culture plates washed prior to further experimentation. Microglia activation and TUNEL staining Microglia samples were exposed to media containing IFNy (R&D Systems, 285-IF; 200ng/ml), LPS (Sigma, L2654; 100ng/ml) or a combination of both for a period of 24 hours to induce an inflammatory response 32 . Cells were then processed for immunofluorescence to determine inflammation state as previously described 33 . Anti-Cd11b antibody (BioRad, MCA711G; 1:500) and goat-anti-rat AlexaFluor 594 (Invitrogen, A-11007; 1:500) staining was counterstained with DAPI (Invitrogen, D1306; 1:1000). To assess AP-mediated cell clearance specificity, activated or basal microglia were exposed to AP20187 (Clontech, 635059; 10nM or 100nM) for a period of 24 hours. TUNEL staining was then performed according to manufacturer’s instructions (Roche In Situ Cell Death Detection Kit, Fluorescein: 11684795910). All imaging was performed using an Olympus BX53 Fluorescence microscope and DP80 digital camera. Analysis was performed using the Fiji distribution of ImageJ (version 1.51n) 34 . To obtain a TUNEL positive percentage, a region of interest was defined using Li Auto Thresholding of the DAPI channel, and the colocalization percentage was calculated using the colocalization threshold plugin bound by that region. Incucyte tracking of basal and activated astrocytes To track basal and activated astrocytic response to AP, astrocytes were plated in a 48 well culture plate (10,000 cells/well) and placed into the IncuCyte S3 Live-Cell Analysis System. The IncuCyte System is a time-lapse imaging system that records cell culture changes through photographic capture of the culture well within the incubator. Cultures were acclimated to the system for a period of 6 hours, then exposed to media containing IFNy (R&D Systems, 285-IF; 200ng/ml), LPS (Sigma, L2654; 100ng/ml) or a combination of both for a period of 24 hours to induce an inflammatory response 35 . Cells were also plated on 10-well slides and processed in tandem for immunofluorescence staining to verify activation status with anti-Gfap (DAKO, Z0334; 1:500) and counterstained with DAPI (Invitrogen, D1306; 1:1000). After activation, astrocytes were exposed to AP20187 (Clontech, 635059; 10nM or 100nM) for a period of 24 hours. The IncuCyte captured phase images of each culture well were taken every 30 minutes over this period using the following settings: (Segmentation Adjustment: 0.8, Hole Fill: 450, Adjust size (pixels): −1, Minimum area (uM 2 ): 0.1). Phase confluency difference was calculated by subtracting the final phase confluency of each image from its initial value. Extended Data Extended Data Figure 1. Senescent cells accumulate in PS19 mice. RT-qPCR analysis for senescence-associated genes in hippocampi (left) and cortices (right) of 3- and 10-month-old male mice (animal numbers indicated in the legend, 2 independent experiments; normalized to 3 m Wildtype group). Data are mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001 (one-way ANOVA with Tukey’s multiple comparisons test). Exact P values can be found in the accompanying source data file. Extended Data Figure 2. AP-mediated clearance selectively removes senescent cells that accumulate in brains of PS19;ATTAC mice. Expression of senescence markers from 6-month-old female hippocampus (left) and cortex (cortex) either vehicle (–AP) or AP20187 (+AP) treated assessed by RT-qPCR (animal numbers indicated in the legend; normalized to ATTAC –AP group). p21 is also known as Cdkn1a; Pai1 is also known as Serpine1. Data are mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001 (one-way ANOVA with Tukey’s multiple comparisons test). Exact P values can be found in the accompanying source data file. Extended Data Figure 3. Neurons do not exhibit X-Gal crystals by Gal-TEM. Representative electron microscopy image of neurons after SA-β-Gal staining from a 6-month-old vehicle-treated PS19;ATTAC male mouse (n = 3 male mice, 2 independent experiments). The image has been artificially colored to denote individual cell bodies. Scale bar: 10 µm. Extended Data Figure 4. Increased senescence-associated gene expression is observed in astrocytes and microglia isolated from PS19 mice. a–e, Gating strategy (a) for FACS isolation of living astrocytes (b), microglia (c), oligodendrocytes (d), and neuron-enriched Cd56+ cells (e) from cortices from 6-month-old WT and PS19 mice. b, Astrocyte (Cd11b–,Cd45–,O1–,GLAST+,Cd56–) fraction (left) and RT-qPCR analysis (right). c, Microglia (Cd11b+,Cd45+,O1,GLAST+,Cd56–) fraction (left) and RT-qPCR analysis (right). d, Oligodendrocyte (Cd11b–,Cd45–,O1+,GLAST–,Cd56–) fraction (left) and RT-qPCR analysis (right). e, Neuron-enriched Cd56+ (Cd11b–,Cd45–,O1–,GLAST–,Cd56+) fraction (left) and RT-qPCR analysis (right). p21 is also known as Cdkn1a; Pai1 is also known as Serpine1. Individual numbers of independent animal cell population isolations are indicated in the parentheses above p16 Ink4a columns (2 independent experiments). Data are mean ± s.e.m. *P < 0.05; **P < 0.01 (unpaired two-sided t-tests with Welch’s correction). Exact P values can be found in the accompanying source data file. Extended Data Figure 5. Cell identity verification of cell populations isolated by FACS. a–d, RT-qPCR analysis for cell identity markers from cell populations isolated from 6-month-old Wildtype and PS19 mice for Aqp4 expression enriched in astrocytes (a), Cx3cr1 expression enriched in microglia (b), Olig expression enriched in oligodendrocytes (c), and Nefl expression enriched in neurons (d). Expression is normalized to intact cortices of 6-month-old Wildtype mice (n = 4 biologically independent cell isolations for each group, 2 independent experiments). Data are mean ± s.e.m. ***P < 0.001 (one-way ANOVA with Tukey’s multiple comparisons test). Exact P values can be found in the accompanying source data file. Extended Data Figure 6. AP administration does not precociously eliminate non-senescent glial cells isolated from ATTAC mice. a, Cd11b staining of primary microglia treated with IFNγ (200 ng/ml), LPS (100 ng/ml), or a combination of both (n = 3 biologically independent samples). b, Quantification of TUNEL positive bodies in basal or activated microglia (n = 4 WT and 8 ATTAC cultures for each treatment group, 2 independent experiments). c, GFAP staining of primary astrocytes treated with IFNγ, LPS, or a combination of both as described in (a) (n = 3 biologically independent samples). d, Quantification of confluency change over 24 hours in basal or activated astrocytes (n = 4 biologically independent cultures of each genotype and treatment). Scale Bars, 100 μm (a and c). Data are mean ± s.e.m. *P < 0.05; ***P < 0.001 (one-way ANOVA with Tukey’s multiple comparisons test (b and d)). Exact P values can be found in the accompanying source data file. Extended Data Figure 7. AP-administration does not broadly eliminate cells or increase proliferation of microglia. a, Quantification of TUNEL positive bodies (as a percentage of all cells) at the transition between the CA2 and CA3 within the hippocampus after a short-term AP administration in 6-month-old mice (n = 3 mice per genotype and treatment group). b, Quantification of Iba1/EdU double positive cells in hippocampus and cortex from 6-month-old mice administered AP beginning at weaning age (n = 4 mice per genotype and treatment group). Data are mean ± s.e.m. We note that no comparison is statistically significant (one-way ANOVA with Tukey’s multiple comparisons test). Exact P values can be found in the accompanying source data file. Extended Data Figure 8. Senescent cells promote gliosis. a, RT-qPCR analysis for Gfap, S100β, and Cd11b in hippocampi of 6-month-old male mice (n = 5 mice per group; normalized to ATTAC –AP group). b, RT-qPCR analysis as in (a) in hippocampi of 6-month-old female mice (animal number indicated in legend; normalized to ATTAC –AP group). c, Representative Gfap IHC staining in the hippocampus of 6-month-old vehicle and AP-treated ATTAC and PS19;ATTAC female mice (n = 4 mice per group, 2 independent experiments). d, Representative Iba1 staining in the hippocampus of 6-month-old vehicle and AP-treated ATTAC and PS19;ATTAC female mice (n = 4 mice per group, 2 independent experiments). Scale bar, 100 µm (c) and 50 µm (d). Data are mean ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001 (one-way ANOVA with Tukey’s multiple comparisons test). Exact P values can be found in the accompanying source data file. Extended Data Figure 9. AP treatment attenuates tau phosphorylation. a, Ponceau S loading controls for western blot lysates of 6-month-old whole brain total-tau (left) and phosphorylated tau (S202/T205; right) shown in Figure 3a. b, Quantification of westerns blot analysis from 6-month-old whole brain for soluble tau (left), soluble phosphorylated tau (S202/T205; middle), and insoluble phosphorylated tau (S202/T205; right). Biologically independent animal numbers are indicated, data are from ≥ 3 independent experiments. c, Immunostaining of 6-month-old cortex for phosphorylated tau protein at T231 (top) and S396 (bottom; n = 4 mice per group, 2 independent experiments). Scale bar, 100µm. Data are mean ± s.e.m. ***P < 0.001 (one-way ANOVA with Tukey’s multiple comparisons test). Exact P values can be found in the accompanying source data file. Extended Data Figure 10. Vision-based novel object discrimination remains intact in AP-treated PS19;ATTAC mice. Objects used for novel object recognition during the training and testing phase for visual discrimination (left) and the average ratio for the number of investigations (right, n = 8 female mice per group). Data are mean ± s.e.m. **P < 0.01; ***P < 0.001 (two-way ANOVA with Tukey’s multiple comparisons test). Exact P values can be found in the accompanying source data file. Supplementary Material 1 2

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              Senescence-Associated Secretory Phenotypes Reveal Cell-Nonautonomous Functions of Oncogenic RAS and the p53 Tumor Suppressor

              Introduction Cancer is a multistep disease in which cells acquire increasingly malignant phenotypes. These phenotypes are acquired in part by somatic mutations, which derange normal controls over cell proliferation (growth), survival, invasion, and other processes important for malignant tumorigenesis [1]. In addition, there is increasing evidence that the tissue microenvironment is an important determinant of whether and how malignancies develop [2,3]. Normal tissue environments tend to suppress malignant phenotypes, whereas abnormal tissue environments such at those caused by inflammation can promote cancer progression. Cancer development is restrained by a variety of tumor suppressor genes. Some of these genes permanently arrest the growth of cells at risk for neoplastic transformation, a process termed cellular senescence [4–6]. Two tumor suppressor pathways, controlled by the p53 and p16INK4a/pRB proteins, regulate senescence responses. Both pathways integrate multiple aspects of cellular physiology and direct cell fate towards survival, death, proliferation, or growth arrest, depending on the context [7,8]. Several lines of evidence indicate that cellular senescence is a potent tumor-suppressive mechanism [4,9,10]. Many potentially oncogenic stimuli (e.g., dysfunctional telomeres, DNA damage, and certain oncogenes) induce senescence [6,11]. Moreover, mutations that dampen the p53 or p16INK4a/pRB pathways confer resistance to senescence and greatly increase cancer risk [12,13]. Most cancers harbor mutations in one or both of these pathways [14,15]. Lastly, in mice and humans, a senescence response to strong mitogenic signals, such as those delivered by certain oncogenes, prevents premalignant lesions from progressing to malignant cancers [16–19]. Interestingly, some tumor cells retain the ability to senesce in response to DNA-damaging chemotherapy or p53 reactivation; in mice, this response arrests tumor progression [20–22]. Despite support for the idea that senescence is a beneficial anticancer mechanism, indirect evidence suggests that senescent cells can also be deleterious and might contribute to age-related pathologies [10,23–25]. The apparent paradox of contributing to both tumor suppression and aging is consistent with an evolutionary theory of aging, termed antagonistic pleiotropy [26]. Organisms generally evolve in environments that are replete with extrinsic hazards, and so old individuals tend to be rare in natural populations. Therefore, there is little selective pressure for tumor suppressor mechanisms to be effective well into old age; rather, these mechanisms need to be sufficiently effective only to ensure successful reproduction. Further, tumor suppressor mechanisms could in principle even be deleterious at advanced ages, as predicted by evolutionary antagonistic pleiotropy. Consistent with this view, senescent cells increase with age in mammalian tissues [27], and have been found at sites of age-related pathologies such as osteoarthritis and atherosclerosis [28–30]. Moreover, in mice, chronically active p53 both promotes cellular senescence and accelerates aging phenotypes [31,32]. How might senescent cells be deleterious? Senescent cells acquire many changes in gene expression, mostly documented as altered mRNA abundance, including increased expression of secreted proteins [33–41]. Some of these secreted proteins act in an autocrine manner to reinforce the senescence growth arrest [37,38,40,41]. Moreover, cell culture and mouse xenograft studies suggest that proteins secreted by senescent cells can promote degenerative or hyperproliferative changes in neighboring cells [35,39,42,43]. Thus, although the cell-autonomous senescence growth arrest suppresses cancer, factors secreted by senescent cells might have deleterious cell-nonautonomous effects that alter the tissue microenvironment. To date, a comprehensive analysis of the secretory profile of senescent cells is lacking, as is knowledge regarding how this profile varies with cell type or senescence inducer, or how it relates to the tumor suppressor proteins that control senescence. To fill these gaps in our knowledge, we modified antibody arrays to be quantitative and sensitive over a wide dynamic range and defined the senescence-associated secretory phenotype (SASP). We show that this phenotype is complex, containing elements associated with inflammation and tumorigenesis, and is induced only by genotoxic stress of sufficient magnitude to cause senescence. SASPs are expressed by senescent human fibroblasts and epithelial cells in culture. Moreover, epithelial tumor cells exposed to DNA-damaging chemotherapy senesce and express a SASP in vivo. The arrays allowed us to identify two new malignant phenotypes promoted by senescent cells (the epithelial–mesenchyme transition and invasiveness), and the SASP factors responsible for them (interleukin [IL]-6 and IL-8). Strikingly, the SASP was markedly amplified by oncogenic RAS or loss of p53 function. Our results identify a mechanism by which p53 acts as a cell-nonautonomous tumor suppressor, and RAS as a cell-nonautonomous oncogene, and provide a novel framework for understanding how age-related cancers might progress. Results Senescence-Associated Secretory Phenotypes Expressed by Human Fibroblasts To determine whether tissue of origin, donor age, or genotype affected secretory phenotypes, we first studied five human fibroblast strains, derived from embryonic lung (WI-38, IMR-90), neonatal foreskin (BJ, HCA2), or adult breast (hBF184). We cultured the cells under standard conditions, and either atmospheric (∼20%) O2 or 3% O2, which is more physiological [44]. We made presenescent (PRE) cultures (>80% of cells capable of proliferation) quiescent by growing the cells to confluence in order to compare them to nondividing senescent (SEN) cultures ( 0.75) in human senescent cells cultured in 3% versus 20% O2. By contrast, the ambient O2 level strongly affects the secretory phenotype of mouse senescent cells (J. P. Coppe, C. K. Patil, F. Rodier, A. Krtolica, S. Parrinello, et al., unpublished data). We verified the secretion levels of several SASP proteins by ELISAs (Figure S1 and Text S1). Further, because secretion increased greater than 10-fold for some SASP factors, we could verify up-regulation by intracellular immunostaining. For example, IL-6 and IL-8 were barely visible in PRE cells but clearly detectable in SEN cells (Figure 1B, Figure S2, and Text S1). We performed the immunostaining on cells in 10% serum, which allowed us to rule out the possibility that the SASP was a senescence-specific response to the serum-free incubation needed to collect CM. Moreover, the SASPs of SEN cells induced by REP and XRA were highly correlated (r > 0.9; Figure 1C), indicating that the phenotype was not specific to one senescence inducer. The secretory profiles of fibroblast strains from the same tissues (e.g., BJ and HCA2 from neonatal foreskin; and IMR90 and Wi-38 from fetal lung) were highly correlated (Datasets S3 and S4). In subsequent figures, data from these related cell strains, as well as from REP and XRA samples from cells of the same type, were pooled and averaged in order to simplify the display. Because REP and XRA induce senescence primarily by causing genomic damage (from telomere shortening and DNA breaks, respectively), we asked whether the SASP was a primary DNA damage response. We irradiated cells using either 0.5 or 10 Gy. As expected, both doses initiated a DNA damage response, as determined by p53 stabilization and phosphorylation (see Figure S3 and Text S1). However, cells that received 0.5 Gy transiently arrested growth for only 24–48 h before resuming growth, whereas cells that received 10 Gy underwent a permanent senescence growth arrest (Figure 1D). Antibody arrays performed on CM collected between 2 and 10 d after irradiation showed that only 10 Gy induced a SASP (Figure 1D and Figure S3). Moreover, cells that senesced owing to DNA damage developed the SASP slowly, requiring 4–7 d after irradiation before expressing a robust SASP. These findings indicate the SASP is not a DNA damage response per se. However, it is induced by DNA damage of sufficient magnitude to cause senescence, after which it requires several days to develop. We also determined that proteins comprising the SASP were, in general, up-regulated at the level of mRNA abundance (Figure 1E and 1F, red symbols and line; Figure S4, and Text S1). However, for detectable proteins that showed little or no senescence-associated change in secretion, mRNA levels were a poor predictor of secreted protein levels (Figure 1F, blue symbols and line; and Figure S4). Thus, antibody arrays provide a more accurate assessment of the senescence-associated secretory signature than mRNA profiling. SASPs of Human Epithelial Cells To determine whether the SASP is limited to fibroblasts, we studied the secretory activity of epithelial cells. Normal human prostate epithelial cells (PrECs) underwent a classic senescence growth arrest in response to X-irradiation (see Table S1). We collected CM from PRE and SEN PrECs, and analyzed the factors secreted by these cells using antibody arrays. Normal PrECs expressed a robust SASP upon senescence (Figure 2A and Datasets S5–S8). Like fibroblasts, SEN PrECs secreted many factors at significantly higher levels compared to PRE PrECs. To compare the SASPs of normal human epithelial and stromal cells senesced under similar conditions, we analyzed factors that showed a significant change (p 66% overlap between normal fibroblasts and normal epithelial cells. More specifically, both SASPs included inflammatory or immune factors such as IL-6, IL-8, or MCP-1, growth modulators such as GRO and IGFBP-2, cell survival regulators such as OPG or sTNF RI, and shed surface molecules such as uPAR or ICAM-1 (Figure 2A). Not surprising, there were also differences between the SASPs of fibroblasts and PrECs. In contrast to fibroblasts, three factors (Acrp30, BTC, and IGFBP-6) were significantly down-regulated by SEN in PrECs. Moreover, IL-1α or HGF were SASP factors unique to either normal epithelial SASP or normal fibroblast SASP, respectively. This result indicates that the SASP is not limited to normal stromal cells, and that a substantial overlap between normal senescent cells of different tissue origins exists. Figure 2 SASP of Human Epithelial Cells (A) Soluble factors secreted by the indicated normal cell type (epithelial vs. stromal) were detected by antibody arrays and analyzed as described in the text, Materials and Methods, and Datasets S5–S8. Normal prostate epithelial cells (PrECs) were induced to senesce by 10 Gy irradiation, and CM from the PRE and SEN cells were analyzed. The SASP of PrECs was compared side by side to the SASP of SEN(XRA) fibroblasts (WI-38, IMR-90, HCA-2, and BJ). The PRE values for each cell type served as the baseline. Signals higher than baseline are displayed in yellow; signals below baseline are displayed in blue. The heat map key (right) indicates log2-fold changes from the baseline. p-Values were calculated by the Student t-test, and are given to the right of the heat map. ns = not significant (p > 0.05) and defines non-SASP factors. (B) The log2-fold changes for all 120 proteins detected by the antibody arrays were plotted for SEN(XRA) PrECs and SEN(XRA) fibroblasts, relative to their PRE baseline. Seventy-nine secreted factors (66%) followed the same regulatory trend (in red). The remaining factors were not coregulated (depicted in blue). (C) Soluble factors produced by the indicated normal or transformed prostate epithelial cells were analyzed by antibody arrays and the results displayed as described for Figure 1A. For each cell strain or cell line, PRE and SEN signals were averaged and used as the baseline. Signals higher than the baseline are shown in yellow; signals below baseline are displayed in blue. An asterisk (*) indicates SASP factors that are conserved between all fibroblasts (Figure 1A) and all epithelial cells. Some tumor cells retain the ability to senesce in response to DNA damage, including DNA-damaging chemotherapy [20–22]. We therefore asked whether prostate cancer cells also developed a SASP. We studied three prostate tumor cell lines (BPH1 [45], RWPE1 [46], and PC3 [47], which differ in their degree of malignancy as follows: PC3 > RWPE1 > BPH1). As with normal epithelial cells (PrECs), we induced senescence by XRA, and analyzed CM using antibody arrays (Datasets S5–S8). SEN epithelial cells secreted significantly higher levels of numerous proteins compared to PRE counterparts (Figure 2C). The SASPs of prostate epithelial cells showed striking overlap between normal and transformed cells (Figure 2C and Dataset S8), and there was also striking similarities between the SASP of fibroblasts and all epithelial cells, transformed and not transformed (Figure 2C, asterisks indicate common secreted proteins, and Datasets S5–S8). Twenty-four proteins were shared between the SASPs of all fibroblasts (Figure 1A) and all epithelial cells (Figure 2C); this overlap was highly significant relative to the overlap predicted from chance (p = ∼10−5; see Materials and Methods). We conclude that normal fibroblasts and both normal and transformed epithelial cells can develop SASPs that significantly overlap, displaying many common, but also some distinct, features. Chemotherapy-Induced SASPs Occur In Vivo Many human tumor cells retain the ability to senesce, in culture and in vivo, in response to DNA-damaging chemotherapeutic agents [48,49]. Epithelial cell lines, as well as normal fibroblasts, underwent senescence in culture in response to mitoxantrone (MIT) (see Table S1), a topoisomerase 2β inhibitor that causes DNA breaks and is used to treat prostate cancer [50]. Antibody arrays (Figure 3A and Datasets S5–S8) and ELISAs for IL-6, IL-8, and GRO-α (Figure S1) showed that MIT induced a SASP that correlated well (r = 0.89) with the XRA-induced SASP (Figure 3A). Figure 3 Chemotherapy-Induced SASP in Culture and In Vivo (A) Overall correlation between XRA and mitoxantrone (MIT)-induced SASPs for all three prostate epithelial cancer cell lines (BPH-1, RWPE-1, and PC-3). Correlations for the individual cell lines are given in the table to the right. The senescence inducer (XRA or MIT) is given in parentheses. (B–E) Human tumor cells were isolated from biopsies obtained from the same patient before MIT chemotherapy and from prostate tissue following prostatectomy after MIT chemotherapy. Laser captured cells were analyzed by quantitative RT-PCR for the mRNAs encoding the indicated proteins, as described in Materials and Methods and Text S1. The results are displayed on a log10 scale indicating the values before (horizontal or x-axis) compared to after (vertical or y-axis) chemotherapy (top left panel in [B]). Each black dot in (B, C, and D) represents the results obtained from a single patient. The average values for all patients before versus after chemotherapy are indicated by a red dot (B–D); these values are also represented as a heat map in (E). (B) Values for mRNAs encoding proteins associated with senescence (p16 and p21) and proliferation (cyclin A, MCM-3, and PCNA). (C) Values for mRNAs encoding SASP-associated proteins (IL-6, IL-8, GM-CSF, GRO-α, IGFBP-2, and IL-1β). (D) Value for an mRNA encoding a non-SASP–associated protein (IL-2). (E) Averages for the values shown in (B–D). Overall p-values, determined by the Student t-test, and number of paired samples (or patients) analyzed for each mRNA are given to the right of the heat map. Signals higher than the prechemotherapy baseline are shown in red; signals below baseline are displayed in green. The finding that human prostatic tumor cells express a SASP in response to MIT in culture allowed us to determine whether MIT induced a SASP in vivo. We laser captured approximately 1,000 tumor epithelial cells in biopsies from human prostate cancer patients before MIT chemotherapy and in tissues removed after chemotherapy and prostatectomy [50]. By microscopic inspection, the captured cells were devoid of stromal cells and leukocytes. Since mRNA and secreted protein levels correlated well for significantly up-regulated SASP factors (Figure 1E and 1F and Figure S4), we used quantitative PCR to quantify mRNAs encoding senescence and proliferation markers and SASP factors. After chemotherapy, most of the tumors contained significantly higher levels of p16INK4a and p21 mRNAs, which are typically up-regulated in senescent cells (Figure 3B). They also contained significantly lower levels of proliferation-associated mRNAs encoding cyclin A, MCM-3, and PCNA (Figure 3B). These results suggest that MIT induced tumor cells to senesce in vivo. Importantly, most of the tumors contained significantly higher levels of mRNAs encoding the SASP components IL-6, IL-8, GM-CSF, GRO-α, IGFBP-2, and IL-1β (Figure 3C). However, the levels of mRNA encoding IL-2, which is not a SASP component, did not significantly change on average (Figure 3D). These findings (summarized in Figure 3E) suggest that the SASP is not limited to cultured cells, but also occurs when human cells senesce in vivo. SASPs Induce Epithelial–Mesenchyme Transitions and Invasiveness The epithelial–mesenchymal transition (EMT) confers invasive and metastatic properties on epithelial cells, and is an important step in cancer progression that presages the conversion of carcinomas in situ to potentially fatal invasive cancers [51,52]. We found that the fibroblast SASP induced a classic EMT in two nonaggressive human breast cancer cell lines (T47D and ZR75.1). Secreted factors from SEN, but not PRE, fibroblasts caused dose-dependent epithelial cell scattering, a mesenchymal characteristic (Figure 4A). Moreover, immunostaining showed that PRE CM preserved surface-associated β-catenin and E-cadherin, and strong cytokeratin 8/18 expression (Figure 4B), and western analysis showed that PRE CM preserved low expression of vimentin (see below). These features are epithelial characteristics frequently retained by nonaggressive cells [51,52]. By contrast, CM from SEN cells markedly decreased overall and cell surface β-catenin and E-cadherin and reduced cytokeratin expression (Figure 4B), consistent with a mesenchymal transition. Further, SEN CM down-regulated the tight junction protein claudin-1, leaving the remaining protein localized primarily to the nucleus (Figure 4B), a hallmark of an EMT and a feature of metastatic but not primary tumors [53]. Finally, SEN CM increased vimentin expression (see below), another mesenchymal marker and hallmark of an EMT [52]. Figure 4 Novel SASP Biological Activities and Key Factors (A) T47D and ZR75.1 cells were incubated for 2 d with CM from PRE fibroblasts, or SEN fibroblasts induced by XRA. The cells were photographed under phase contrast, or analyzed for cluster size using an automated Cellomix imager and software. Smaller cluster or clump sizes (pixel2) indicate greater scattering. The senescence inducer is given in parentheses. Quadruple asterisks (****) indicate p GSE) versus SEN(REP) in WI-38) and Datasets S13–S16). This finding indicates that p53 is not required to maintain an established SASP. Figure 6 p53 Restrains the SASP (A) CM containing factors secreted by the indicted cells were analyzed by antibody arrays and displayed, using PRE CM as the baseline. We pooled data from cells of the same genotype (p53 wild type or p53 deficient) under the same culture conditions. SEN indicates pooled data from cells originating from the same tissue (WI-38, IMR-90 from embryonic lung; and HCA-2, BJ from neonatal foreskin) and induced to senesce by REP or XRA. Pooling and averaging of highly correlated samples was performed as described for Figure 5, and details of the data processing are provided in Datasets S13–S16. The top four rows are the same top four rows in Figure 5A and are included to serve as a visual reference. The senescence inducer is given in parentheses. p53 status is indicated as either wild type (wt) or deficient (d) owing to either GSE22 expression or expression of an shRNA against p53. Manipulations are indicated in sequence, separated by a greater than symbol (>). The heat map key (right) indicates the log2-fold changes. Signals higher than the baseline are shown in yellow; signals below baseline are displayed in blue. Comparison between rows is accurately illustrated in (B) and (C) in which each genetically manipulated cell type is compared to its appropriate control baseline. (B) Log2-fold values for SASP factors that are significantly increased, or significantly and uniquely (as indicated by double asterisks [**]) elevated, in CM from SEN cells made p53 deficient by GSE22, using untreated wild-type SEN values as the baseline. Green indicates WI-38 cells made senescent by XRA, after which p53 was subsequently inactivated by expressing GSE22 using a lentivirus; these cells do not resume proliferation (“unreverted”) upon p53 inactivation (see Figure S6). Blue indicates WI-38 in which p16 was inactivated by an shRNA, induced to senesce by XRA, then infected with the GSE22-expressing lentivirus; these cells do revert (REV) after p53 inactivation. Pink indicates HCA2 cells made SEN by XRA, then infected with GSE22 lentivirus; these cells also revert after p53 inactivation. (C) Log2-fold values for SASP factors that are significantly increased, or significantly and uniquely (as indicated by double asterisks [**]) elevated, in CM from cells made p53-deficient (by GSE22 expression), then induced to senesce by REP, XRA, or RAS. Red indicates WI-38 and IMR90 (averaged) cells expressing GSE22, then induced to senesce by XRA or REP, using cells made SEN by XRA or REP as a baseline. Gray indicates WI-38, IMR-90, and HCA2 (averaged) expressing GSE22, then made senescent by RAS, using SEN by RAS as a baseline. (D) WI-38 cells expressing GSE22 were induced to senesce by XRA and then immunostained for the SASP proteins IL-6 and IL-8, the senescence marker p16INK4a, and p53, which accumulates in the presence of GSE22. (E) Comparative graphical representation of the secretory profiles of cells made senescent by XRA or REP (dotted line), RAS (black line), p53 inactivation (GSE22) followed by XRA or REP (blue line), or p53 inactivation (GSE22) followed by RAS (red line). The increased slopes (as indicated by the arrow)indicate amplified SASPs. (F) Hierarchical cluster analysis of all the cells analyzed in (A), plus the SASP induced by RAS (see Figure 5). RAS status is indicated as either wild type (wt) or oncogenic (o) owing to expression of Ha-RASv12. (G) WI-38 cells with wild-type (wt) or inactive (GSE) p53 were irradiated or induced to express oncogenic RAS (RAS), and CM was collected 4 or 10 d later. Soluble factors were analyzed by antibody arrays and displayed as described in Figure 1D, using PRE CM as the baseline (black column on the left; see also Figure S5C for details). Signals higher than baseline are shown in yellow; signals below baseline are in blue. n/a, not applicable. (H) Log2-fold values for prostate epithelial cell SASP factors that are significantly or uniquely (as indicated by double asterisks [**]) elevated in CM from p53-deficient cancer cells (PC3, BPH1, and RWPE1) that were induced to senesce by XRA, compared to primary p53 wild-type cells (PrECs) that were induced to senesce by XRA. Figure 7 Biological Activities of the Amplified SASP (A) T47D and ZR75.1 cells were incubated with the indicated CM for 3 d and then analyzed for cell scattering, immunostained for the indicated proteins, and analyzed for vimentin and actin levels by western blotting. Controls for the immunofluorescence from the same individual experiment are shown in Figure 4B. The senescence inducer is given in parentheses. p53 status was either wild type or deficient (GSE). Manipulations are indicated in sequence, separated by >. (B) Epithelial cells were incubated with CM from the indicated WI-38 cells and assayed for invasion as described in Materials and Methods and Figure 3C. Double asterisks (**) indicate p 0.95). At 4 d post 10 Gy irradiation, cells harboring a wild-type p53 pathway are still very similar to their PRE counterpart (correlation > 0.95), whereas at 10 d post 10 Gy irradiation, cells are very dissimilar to PRE (correlation < 0 ; they have developed a SASP). The clustering analysis also shows that cells that senesced in the absence of p53 function or due to oncogenic RAS overexpression resemble more each other than cells that senesced with a wild-type p53 background, suggesting that the loss of p53 and the gain of oncogenic RAS have similar dominant effects over SASP development and establishment. (142 KB PDF) Click here for additional data file. Figure S6 Growth Reversion of SEN Cells after p53 Inactivation SEN(REP) and SEN(XRA) WI-38 cells were monitored for cell growth for 20 d before infection with lenti-GSE (rectangle). Cell number was subsequently monitored for an additional 30 d thereafter. Because SEN WI-38 cells express p16, p53 inactivation by GSE does not revert the SEN growth arrest. Cells that do not express p16 at SEN (shp16-expressing WI-38 or unmodified HCA2 cells) were similarly monitored and infected. In contrast to SEN WI-38 cells, p16-deficient cells resumed growth (reverted) after p53-inactivation and proliferated for at least the ensuing 30 d. (79 KB PDF) Click here for additional data file. Dataset S1 Computational Analysis of Antibody Array Data Presented in Figure 1 (Human Fibroblasts; SEN(XRA) and SEN(REP)): Part 1 (31 KB DOC) Click here for additional data file. Dataset S2 Computational Analysis of Antibody Array Data Presented in Figure 1 (Human Fibroblasts; SEN(XRA) and SEN(REP)): Part 2 (28 KB XLS) Click here for additional data file. Dataset S3 Computational Analysis of Antibody Array Data Presented in Figure 1 (Human Fibroblasts; SEN(XRA) and SEN(REP)): Part 3 (142 KB XLS) Click here for additional data file. Dataset S4 Computational Analysis of Antibody Array Data Presented in Figure 1 (Human Fibroblasts; SEN(XRA) and SEN(REP)): Part 4 (162 KB XLS) Click here for additional data file. Dataset S5 Computational Analysis of Antibody Array Data Presented in Figure 2 and Figure 3 (Human Epithelial Cells; SEN(XRA)): Part 1 (31 KB DOC) Click here for additional data file. Dataset S6 Computational Analysis of Antibody Array Data Presented in Figure 2 and Figure 3 (Human Epithelial Cells; SEN(XRA)): Part 2 (39 KB XLS) Click here for additional data file. Dataset S7 Computational Analysis of Antibody Array Data Presented in Figure 2 and Figure 3 (Human Epithelial Cells; SEN(XRA)): Part 3 (78 KB XLS) Click here for additional data file. Dataset S8 Computational Analysis of Antibody Array Data Presented in Figure 2 and Figure 3 (Human Epithelial Cells; SEN(XRA)): Part 4 (159 KB XLS) Click here for additional data file. Dataset S9 Computational Analysis of Antibody Array Data Presented in Figure 5 (Oncogene-Induced Senescence): Part 1 (31 KB DOC) Click here for additional data file. Dataset S10 Computational Analysis of Antibody Array Data Presented in Figure 5 (Oncogene-Induced Senescence): Part 2 (19 KB XLS) Click here for additional data file. Dataset S11 Computational Analysis of Antibody Array Data Presented in Figure 5 (Oncogene-Induced Senescence): Part 3 (90 KB XLS) Click here for additional data file. Dataset S12 Computational Analysis of Antibody Array Data Presented in Figure 5 (Oncogene-Induced Senescence): Part 4 (61 KB XLS) Click here for additional data file. Dataset S13 Computational Analysis of Antibody Array Data Presented in Figure 6 (p53-Deficient Senescence): Part 1 (31 KB DOC) Click here for additional data file. Dataset S14 Computational Analysis of Antibody Array Data Presented in Figure 6 (p53-Deficient Senescence): Part 2 (25 KB XLS) Click here for additional data file. Dataset S15 Computational Analysis of Antibody Array Data Presented in Figure 6 (p53-Deficient Senescence): Part 3 (133 KB XLS) Click here for additional data file. Dataset S16 Computational Analysis of Antibody Array Data Presented in Figure 6 (p53-Deficient Senescence): Part 4 (81 KB XLS) Click here for additional data file. Table S1 Presenescent and Senescent Cells Characteristics Labeling index and senescence-associated beta-galactosidase (SA-bGal) staining of human fibroblasts and human prostate epithelial cells in vitro. (194 KB DOC) Click here for additional data file. Table S2 Complete Catalog of Entrez Gene IDs for All Proteins Corresponding to Antibodies on the Arrays (61 KB XLS) Click here for additional data file. Text S1 Supplemental Methods (42 KB DOC) Click here for additional data file. Text S2 Computational Processing, Analysis, and Validation of Antibody Arrays Digitization and quantification of antibody arrays; numerical and statistical methods; linearity; accuracy; and reliability. (289 KB DOC) Click here for additional data file.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                31 August 2018
                19 September 2018
                October 2018
                19 March 2019
                : 562
                : 7728
                : 578-582
                Affiliations
                [1 ]Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 First ST SW, Rochester, MN 55905, USA.
                [2 ]Department of Pediatric and Adolescent Medicine, Mayo Clinic, 200 First ST SW, Rochester, MN 55905, USA.
                Author notes

                Author Contributions

                T.J.B. and A.A. performed most of the experiments. C.F.M. assisted with the senescent cell identification by Gal-TEM and FACS. B.L.S. performed IHC assessments. J.v.D. assisted with experimental design and data interpretation. The manuscript was written by T.J.B. and D.J.B. All authors discussed results, made figures, and edited the manuscript. D.J.B. conceived, directed and supervised all aspects of the study.

                Author Information

                Reprints and permissions information is available at www.nature.com/reprints. D.J.B. is a co-inventor on patent applications licensed to or filed by Unity Biotechnology, a company developing senolytic medicines, including small molecules that selectively eliminate senescent cells. Research in his lab has been reviewed by the Mayo Clinic Conflict of Interest Review Board and is being conducted in compliance with Mayo Clinic Conflict of Interest policies.

                Mayo Clinic, 200 1 st ST SW, Rochester, MN, 55905, Tel: (507) 538-4097, Fax: (507) 284-3383, baker.darren@ 123456mayo.edu
                Article
                NIHMS1505435
                10.1038/s41586-018-0543-y
                6206507
                30232451

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