Early-life prefrontal cortex inhibition and early-life stress lead to long-lasting behavioral, transcriptional, and physiological impairments.

Early-life stress has been linked to multiple neurodevelopmental and neuropsychiatric deficits. Our previous studies have linked maternal presence/absence from the nest in developing rat pups to changes in prefrontal cortex (PFC) activity. Furthermore, we have shown that these changes are modulated by serotonergic signaling. Here we test whether changes in PFC activity during early life affect the developing cortex leading to behavioral alterations in the adult. We show that inhibiting the PFC of mouse pups leads to cognitive deficits in the adult comparable to those seen following maternal separation. Moreover, we show that activating the PFC during maternal separation can prevent these behavioral deficits. To test how maternal separation affects the transcriptional profile of the PFC we performed single-nucleus RNA-sequencing. Maternal separation led to differential gene expression almost exclusively in inhibitory neurons. Among others, we found changes in GABAergic and serotonergic pathways in these interneurons. Interestingly, both maternal separation and early-life PFC inhibition led to changes in physiological responses in prefrontal activity to GABAergic and serotonergic antagonists that were similar to the responses of more immature brains. Prefrontal activation during maternal separation prevented these changes. These data point to a crucial role of PFC activity during early life in behavioral expression in adulthood.

Gene expression signatures of individual ductal carcinoma in situ lesions identify processes and biomarkers associated with progression towards invasive ductal carcinoma.

Ductal carcinoma in situ (DCIS) is considered a non-invasive precursor to breast cancer, and although associated with an increased risk of developing invasive disease, many women with DCIS will never progress beyond their in situ diagnosis. The path from normal duct to invasive ductal carcinoma (IDC) is not well understood, and efforts to do so are hampered by the substantial heterogeneity that exists between patients, and even within patients. Here we show gene expression analysis from > 2,000 individually micro-dissected ductal lesions representing 145 patients. Combining all samples into one continuous trajectory we show there is a progressive loss in basal layer integrity heading towards IDC, coupled with two epithelial to mesenchymal transitions, one early and a second coinciding with the convergence of DCIS and IDC expression profiles. We identify early processes and potential biomarkers, including CAMK2N1, MNX1, ADCY5, HOXC11 and ANKRD22, whose reduced expression is associated with the progression of DCIS to invasive breast cancer.

Occult polyclonality of preclinical pancreatic cancer models drives in vitro evolution.

Heterogeneity is a hallmark of cancer. The advent of single-cell technologies has helped uncover heterogeneity in a high-throughput manner in different cancers across varied contexts. Here we apply single-cell sequencing technologies to reveal inherent heterogeneity in assumptively monoclonal pancreatic cancer (PDAC) cell lines and patient-derived organoids (PDOs). Our findings reveal a high degree of both genomic and transcriptomic polyclonality in monolayer PDAC cell lines, custodial variation induced by growing apparently identical cell lines in different laboratories, and transcriptomic shifts in transitioning from 2D to 3D spheroid growth models. Our findings also call into question the validity of widely available immortalized, non-transformed pancreatic lines as contemporaneous "control" lines in experiments. We confirm these findings using a variety of independent assays, including but not limited to whole exome sequencing, single-cell copy number variation sequencing (scCNVseq), single-nuclei assay for transposase-accessible chromatin with sequencing, fluorescence in-situ hybridization, and single-cell RNA sequencing (scRNAseq). We map scRNA expression data to unique genomic clones identified by orthogonally-gathered scCNVseq data of these same PDAC cell lines. Further, while PDOs are known to reflect the cognate in vivo biology of the parental tumor, we identify transcriptomic shifts during ex vivo passage that might hamper their predictive abilities over time. The impact of these findings on rigor and reproducibility of experimental data generated using established preclinical PDAC models between and across laboratories is uncertain, but a matter of concern.

Retromer dysfunction in amyotrophic lateral sclerosis.

Retromer is a heteropentameric complex that plays a specialized role in endosomal protein sorting and trafficking. Here, we report a reduction in the retromer proteins-vacuolar protein sorting 35 (VPS35), VPS26A, and VPS29-in patients with amyotrophic lateral sclerosis (ALS) and in the ALS model provided by transgenic (Tg) mice expressing the mutant superoxide dismutase-1 G93A. These changes are accompanied by a reduction of levels of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor subunit GluA1, a proxy of retromer function, in spinal cords from Tg SOD1G93A mice. Correction of the retromer deficit by a viral vector expressing VPS35 exacerbates the paralytic phenotype in Tg SOD1G93A mice. Conversely, lowering Vps35 levels in Tg SOD1G93A mice ameliorates the disease phenotype. In light of these findings, we propose that mild alterations in retromer inversely modulate neurodegeneration propensity in ALS.

System-wide transcriptome damage and tissue identity loss in COVID-19 patients.

The molecular mechanisms underlying the clinical manifestations of coronavirus disease 2019 (COVID-19), and what distinguishes them from common seasonal influenza virus and other lung injury states such as acute respiratory distress syndrome, remain poorly understood. To address these challenges, we combine transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues to define body-wide transcriptome changes in response to COVID-19. We then match these data with spatial protein and expression profiling across 357 tissue sections from 16 representative patient lung samples and identify tissue-compartment-specific damage wrought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, evident as a function of varying viral loads during the clinical course of infection and tissue-type-specific expression states. Overall, our findings reveal a systemic disruption of canonical cellular and transcriptional pathways across all tissues, which can inform subsequent studies to combat the mortality of COVID-19 and to better understand the molecular dynamics of lethal SARS-CoV-2 and other respiratory infections.

Diverse tumorigenic consequences of human papillomavirus integration in primary oropharyngeal cancers.

Human papillomavirus (HPV) causes 5% of all cancers and frequently integrates into host chromosomes. The HPV oncoproteins E6 and E7 are necessary but insufficient for cancer formation, indicating that additional secondary genetic events are required. Here, we investigate potential oncogenic impacts of virus integration. Analysis of 105 HPV-positive oropharyngeal cancers by whole-genome sequencing detects virus integration in 77%, revealing five statistically significant sites of recurrent integration near genes that regulate epithelial stem cell maintenance (i.e., SOX2, TP63, FGFR, MYC) and immune evasion (i.e., CD274). Genomic copy number hyperamplification is enriched 16-fold near HPV integrants, and the extent of focal host genomic instability increases with their local density. The frequency of genes expressed at extreme outlier levels is increased 86-fold within ±150 kb of integrants. Across 95% of tumors with integration, host gene transcription is disrupted via intragenic integrants, chimeric transcription, outlier expression, gene breaking, and/or de novo expression of noncoding or imprinted genes. We conclude that virus integration can contribute to carcinogenesis in a large majority of HPV-positive oropharyngeal cancers by inducing extensive disruption of host genome structure and gene expression.

Metastatic pediatric sclerosing epithelioid fibrosarcoma.

Sclerosing epithelioid fibrosarcoma (SEF) is a rare and aggressive soft-tissue sarcoma thought to originate in fibroblasts of the tissues comprising tendons, ligaments, and muscles. Minimally responsive to conventional cytotoxic chemotherapies, >50% of SEF patients experience local recurrence and/or metastatic disease. SEF is most commonly discovered in middle-aged and elderly adults, but also rarely in children. A common gene fusion occurring between the EWSR1 and CREB3L1 genes has been observed in 80%-90% of SEF cases. We describe here the youngest SEF patient reported to date (a 3-yr-old Caucasian male) who presented with numerous bony and lung metastases. Additionally, we perform a comprehensive literature review of all SEF-related articles published since the disease was first characterized. Finally, we describe the generation of an SEF primary cell line, the first such culture to be reported. The patient described here experienced persistent disease progression despite aggressive treatment including multiple resections, radiotherapy, and numerous chemotherapies and targeted therapeutics. Untreated and locally recurrent tumor and metastatic tissue were sequenced by whole-genome, whole-exome, and deep-transcriptome next-generation sequencing with comparison to a patient-matched normal blood sample. Consistent across all sequencing analyses was the disease-defining EWSR1-CREB3L1 fusion as a single feature consensus. We provide an analysis of our genomic findings and discuss potential therapeutic strategies for SEF.

Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 115 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS), remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, evident as a function of varying viral load (high vs. low) during the course of infection and specific, transcriptional dysregulation in splicing isoforms, T cell receptor expression, and cellular expression states. In particular, cardiac and lung tissues revealed the largest degree of splicing isoform switching and cell expression state loss. Overall, these findings reveal a systemic disruption of cellular and transcriptional pathways from COVID-19 across all tissues, which can inform subsequent studies to combat the mortality of COVID-19, as well to better understand the molecular dynamics of lethal SARS-CoV-2 infection and other viruses.

Machine learning integration of scleroderma histology and gene expression identifies fibroblast polarisation as a hallmark of clinical severity and improvement.

OBJECTIVE: We sought to determine histologic and gene expression features of clinical improvement in early diffuse cutaneous systemic sclerosis (dcSSc; scleroderma). METHODS: Fifty-eight forearm biopsies were evaluated from 26 individuals with dcSSc in two clinical trials. Histologic/immunophenotypic assessments of global severity, alpha-smooth muscle actin (aSMA), CD34, collagen, inflammatory infiltrate, follicles and thickness were compared with gene expression and clinical data. Support vector machine learning was performed using scleroderma gene expression subset (normal-like, fibroproliferative, inflammatory) as classifiers and histology scores as inputs. Comparison of w-vector mean absolute weights was used to identify histologic features most predictive of gene expression subset. We then tested for differential gene expression according to histologic severity and compared those with clinical improvement (according to the Combined Response Index in Systemic Sclerosis). RESULTS: aSMA was highest and CD34 lowest in samples with highest local Modified Rodnan Skin Score. CD34 and aSMA changed significantly from baseline to 52 weeks in clinical improvers. CD34 and aSMA were the strongest predictors of gene expression subset, with highest CD34 staining in the normal-like subset (p<0.001) and highest aSMA staining in the inflammatory subset (p=0.016). Analysis of gene expression according to CD34 and aSMA binarised scores identified a 47-gene fibroblast polarisation signature that decreases over time only in improvers (vs non-improvers). Pathway analysis of these genes identified gene expression signatures of inflammatory fibroblasts. CONCLUSION: CD34 and aSMA stains describe distinct fibroblast polarisation states, are associated with gene expression subsets and clinical assessments, and may be useful biomarkers of clinical severity and improvement in dcSSc.

Identification of targetable BRAF ΔN486_P490 variant by whole-genome sequencing leading to dabrafenib-induced remission of a BRAF-mutant pancreatic adenocarcinoma.

The tumor genome of a patient with advanced pancreatic cancer was sequenced to identify potential therapeutic targetable mutations after standard of care failed to produce any significant overall response. Matched tumor-normal whole-genome sequencing revealed somatic mutations in BRAF, TP53, CDKN2A, and a focal deletion of SMAD4 The BRAF variant was an in-frame deletion mutation (ΔN486_P490), which had been previously demonstrated to be a kinase-activating alteration in the BRAF kinase domain. Working with the Novartis patient assistance program allowed us to treat the patient with the BRAF inhibitor, dabrafenib. The patient's overall clinical condition improved dramatically with dabrafenib. Levels of serum tumor marker dropped immediately after treatment, and a subsequent CT scan revealed a significant decrease in the size of both primary and metastatic lesions. The dabrafenib-induced remission lasted for 6 mo. Preclinical studies published concurrently with the patient's treatment showed that the BRAF in-frame mutation (ΔNVTAP) induces oncogenic activation by a mechanism distinct from that induced by V600E, and that this difference dictates the responsiveness to different BRAF inhibitors. This study describes a dramatic instance of how high-level genomic technology and analysis was necessary and sufficient to identify a clinically logical treatment option that was then utilized and shown to be of clinical value for this individual.

Correction to: Sequencing and curation strategies for identifying candidate glioblastoma treatments.

Following publication of the original article [1], it was reported that the given name of the fourteenth author was incorrectly published. The incorrect and the correct names are given below.

SCANVIS: a tool for SCoring, ANnotating and VISualizing splice junctions.

MOTIVATION: The association of splicing signatures with disease is a leading area of study for prognosis, diagnosis and therapy. We present a novel fast-performing annotation-dependent tool called SCANVIS for scoring and annotating splice junctions (SJs), with an efficient visualization tool that highlights SJ details such as frame-shifts and annotation support for individual samples or a sample cohort. RESULTS: Using publicly available samples, we show that the tissue specificity inherent in splicing signatures is maintained with the Relative Read Support scoring method in SCANVIS, and we showcase some visualizations to demonstrate the usefulness of incorporating annotation details into sashimi plots. AVAILABILITY AND IMPLEMENTATION: https://github.com/nygenome/SCANVIS and https://bioconductor.org/packages/SCANVIS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Sequencing and curation strategies for identifying candidate glioblastoma treatments.

BACKGROUND: Prompted by the revolution in high-throughput sequencing and its potential impact for treating cancer patients, we initiated a clinical research study to compare the ability of different sequencing assays and analysis methods to analyze glioblastoma tumors and generate real-time potential treatment options for physicians. METHODS: A consortium of seven institutions in New York City enrolled 30 patients with glioblastoma and performed tumor whole genome sequencing (WGS) and RNA sequencing (RNA-seq; collectively WGS/RNA-seq); 20 of these patients were also analyzed with independent targeted panel sequencing. We also compared results of expert manual annotations with those from an automated annotation system, Watson Genomic Analysis (WGA), to assess the reliability and time required to identify potentially relevant pharmacologic interventions. RESULTS: WGS/RNAseq identified more potentially actionable clinical results than targeted panels in 90% of cases, with an average of 16-fold more unique potentially actionable variants identified per individual; 84 clinically actionable calls were made using WGS/RNA-seq that were not identified by panels. Expert annotation and WGA had good agreement on identifying variants [mean sensitivity = 0.71, SD = 0.18 and positive predictive value (PPV) = 0.80, SD = 0.20] and drug targets when the same variants were called (mean sensitivity = 0.74, SD = 0.34 and PPV = 0.79, SD = 0.23) across patients. Clinicians used the information to modify their treatment plan 10% of the time. CONCLUSION: These results present the first comprehensive comparison of technical and machine augmented analysis of targeted panel and WGS/RNA-seq to identify potential cancer treatments.

Immunogenic neoantigens derived from gene fusions stimulate T cell responses.

Anti-tumor immunity is driven by self versus non-self discrimination. Many immunotherapeutic approaches to cancer have taken advantage of tumor neoantigens derived from somatic mutations. Here, we demonstrate that gene fusions are a source of immunogenic neoantigens that can mediate responses to immunotherapy. We identified an exceptional responder with metastatic head and neck cancer who experienced a complete response to immune checkpoint inhibitor therapy, despite a low mutational load and minimal pre-treatment immune infiltration in the tumor. Using whole-genome sequencing and RNA sequencing, we identified a novel gene fusion and demonstrated that it produces a neoantigen that can specifically elicit a host cytotoxic T cell response. In a cohort of head and neck tumors with low mutation burden, minimal immune infiltration and prevalent gene fusions, we also identified gene fusion-derived neoantigens that generate cytotoxic T cell responses. Finally, analyzing additional datasets of fusion-positive cancers, including checkpoint-inhibitor-treated tumors, we found evidence of immune surveillance resulting in negative selective pressure against gene fusion-derived neoantigens. These findings highlight an important class of tumor-specific antigens and have implications for targeting gene fusion events in cancers that would otherwise be less poised for response to immunotherapy, including cancers with low mutational load and minimal immune infiltration.

Genetic mechanisms of primary chemotherapy resistance in pediatric acute myeloid leukemia.

Acute myeloid leukemias (AML) are characterized by mutations of tumor suppressor and oncogenes, involving distinct genes in adults and children. While certain mutations have been associated with the increased risk of AML relapse, the genomic landscape of primary chemotherapy-resistant AML is not well defined. As part of the TARGET initiative, we performed whole-genome DNA and transcriptome RNA and miRNA sequencing analysis of pediatric AML with failure of induction chemotherapy. We identified at least three genetic groups of patients with induction failure, including those with NUP98 rearrangements, somatic mutations of WT1 in the absence of apparent NUP98 mutations, and additional recurrent variants including those in KMT2C and MLLT10. Comparison of specimens before and after chemotherapy revealed distinct and invariant gene expression programs. While exhibiting overt therapy resistance, these leukemias nonetheless showed diverse forms of clonal evolution upon chemotherapy exposure. This included selection for mutant alleles of FRMD8, DHX32, PIK3R1, SHANK3, MKLN1, as well as persistence of WT1 and TP53 mutant clones, and elimination of FLT3, PTPN11, and NRAS mutant clones. These findings delineate genetic mechanisms of primary chemotherapy resistance in pediatric AML, which should inform improved approaches for its diagnosis and therapy.

Human papillomavirus and the landscape of secondary genetic alterations in oral cancers.

Human papillomavirus (HPV) is a necessary but insufficient cause of a subset of oral squamous cell carcinomas (OSCCs) that is increasing markedly in frequency. To identify contributory, secondary genetic alterations in these cancers, we used comprehensive genomics methods to compare 149 HPV-positive and 335 HPV-negative OSCC tumor/normal pairs. Different behavioral risk factors underlying the two OSCC types were reflected in distinctive genomic mutational signatures. In HPV-positive OSCCs, the signatures of APOBEC cytosine deaminase editing, associated with anti-viral immunity, were strongly linked to overall mutational burden. In contrast, in HPV-negative OSCCs, T>C substitutions in the sequence context 5'-ATN-3' correlated with tobacco exposure. Universal expression of HPV E6*1 and E7 oncogenes was a sine qua non of HPV-positive OSCCs. Significant enrichment of somatic mutations was confirmed or newly identified in PIK3CA, KMT2D, FGFR3, FBXW7, DDX3X, PTEN, TRAF3, RB1, CYLD, RIPK4, ZNF750, EP300, CASZ1, TAF5, RBL1, IFNGR1, and NFKBIA Of these, many affect host pathways already targeted by HPV oncoproteins, including the p53 and pRB pathways, or disrupt host defenses against viral infections, including interferon (IFN) and nuclear factor kappa B signaling. Frequent copy number changes were associated with concordant changes in gene expression. Chr 11q (including CCND1) and 14q (including DICER1 and AKT1) were recurrently lost in HPV-positive OSCCs, in contrast to their gains in HPV-negative OSCCs. High-ranking variant allele fractions implicated ZNF750, PIK3CA, and EP300 mutations as candidate driver events in HPV-positive cancers. We conclude that virus-host interactions cooperatively shape the unique genetic features of these cancers, distinguishing them from their HPV-negative counterparts.

A recurrent novel MGA-NUTM1 fusion identifies a new subtype of high-grade spindle cell sarcoma.

NUTM1-rearranged tumors are defined by the presence of a gene fusion between NUTM1 and various gene partners and typically follow a clinically aggressive disease course with poor outcomes despite conventional multimodality therapy. NUTM1-rearranged tumors display histologic features of a poorly differentiated carcinoma with areas of focal squamous differentiation and typically express the BRD4-NUTM1 fusion gene defining a distinct clinicopathologic entity-NUT carcinoma (NC). NCs with mesenchymal differentiation have rarely been described in the literature. In this report, we describe the characterization of two cases of high-grade spindle cell sarcoma harboring a novel MGA-NUTM1 fusion. Whole-genome sequencing identified the presence of complex rearrangements resulting in a MGA-NUTM1 fusion gene in the absence of other significant somatic mutations. Genetic rearrangement was confirmed by fluorescence in situ hybridization, and expression of the fusion gene product was confirmed by transcriptomic analysis. The fusion protein was predicted to retain nearly the entire protein sequence of both MGA (exons 1-22) and NUTM1 (exons 3-8). Histopathologically, both cases were high-grade spindle cell sarcomas without specific differentiation markers. In contrast to typical cases of NC, these cases were successfully treated with aggressive local control measures (surgery and radiation) and both patients remain alive without disease. These cases describe a new subtype of NUTM1-rearranged tumors warranting expansion of diagnostic testing to evaluate for the presence of MGA-NUTM1 or alternative NUTM1 gene fusions in the diagnostic workup of high-grade spindle cell sarcomas or small round blue cell tumors of ambiguous lineage.

Analytical Validation of Clinical Whole-Genome and Transcriptome Sequencing of Patient-Derived Tumors for Reporting Targetable Variants in Cancer.

We developed and validated a clinical whole-genome and transcriptome sequencing (WGTS) assay that provides a comprehensive genomic profile of a patient's tumor. The ability to fully capture the mappable genome with sufficient sequencing coverage to precisely call DNA somatic single nucleotide variants, insertions/deletions, copy number variants, structural variants, and RNA gene fusions was analyzed. New York State's Department of Health next-generation DNA sequencing guidelines were expanded for establishing performance validation applicable to whole-genome and transcriptome sequencing. Whole-genome sequencing laboratory protocols were validated for the Illumina HiSeq X Ten platform and RNA sequencing for Illumina HiSeq2500 platform for fresh or frozen and formalin-fixed, paraffin-embedded tumor samples. Various bioinformatics tools were also tested, and CIs for sensitivity and specificity thresholds in calling clinically significant somatic aberrations were determined. The validation was performed on a set of 125 tumor normal pairs. RNA sequencing was performed to call fusions and to confirm the DNA variants or exonic alterations. Here, we present our results and WGTS standards for variant allele frequency, reproducibility, analytical sensitivity, and present limit of detection analysis for single nucleotide variant calling, copy number identification, and structural variants. We show that The New York Genome Center WGTS clinical assay can provide a comprehensive patient variant discovery approach suitable for directed oncologic therapeutic applications.

Identification of Three Rheumatoid Arthritis Disease Subtypes by Machine Learning Integration of Synovial Histologic Features and RNA Sequencing Data.

OBJECTIVE: In this study, we sought to refine histologic scoring of rheumatoid arthritis (RA) synovial tissue by training with gene expression data and machine learning. METHODS: Twenty histologic features were assessed in 129 synovial tissue samples (n = 123 RA patients and n = 6 osteoarthritis [OA] patients). Consensus clustering was performed on gene expression data from a subset of 45 synovial samples. Support vector machine learning was used to predict gene expression subtypes, using histologic data as the input. Corresponding clinical data were compared across subtypes. RESULTS: Consensus clustering of gene expression data revealed 3 distinct synovial subtypes, including a high inflammatory subtype characterized by extensive infiltration of leukocytes, a low inflammatory subtype characterized by enrichment in pathways including transforming growth factor ß, glycoproteins, and neuronal genes, and a mixed subtype. Machine learning applied to histologic features, with gene expression subtypes serving as labels, generated an algorithm for the scoring of histologic features. Patients with the high inflammatory synovial subtype exhibited higher levels of markers of systemic inflammation and autoantibodies. C-reactive protein (CRP) levels were significantly correlated with the severity of pain in the high inflammatory subgroup but not in the others. CONCLUSION: Gene expression analysis of RA and OA synovial tissue revealed 3 distinct synovial subtypes. These labels were used to generate a histologic scoring algorithm in which the histologic scores were found to be associated with parameters of systemic inflammation, including the erythrocyte sedimentation rate, CRP level, and autoantibody levels. Comparison of gene expression patterns to clinical features revealed a potentially clinically important distinction: mechanisms of pain may differ in patients with different synovial subtypes.

ATRX is a regulator of therapy induced senescence in human cells.

Senescence is a state of stable cell cycle exit with important implications for development and disease. Here, we demonstrate that the chromatin remodeling enzyme ATRX is required for therapy-induced senescence. ATRX accumulates in nuclear foci and is required for therapy-induced senescence in multiple types of transformed cells exposed to either DNA damaging agents or CDK4 inhibitors. Mobilization into foci depends on the ability of ATRX to interact with H3K9me3 histone and HP1. Foci form soon after cells exit the cell cycle, before other hallmarks of senescence appear. Eliminating ATRX in senescent cells destabilizes the senescence-associated heterochromatic foci. Additionally, ATRX binds to and suppresses expression from the HRAS locus; repression of HRAS is sufficient to promote the transition of quiescent cells into senescence and preventing repression blocks progression into senescence. Thus ATRX is a critical regulator of therapy-induced senescence and acts in multiple ways to drive cells into this state.Therapy induced senescence (TIS) is a growth suppressive program activated by cytostatic agents in some cancer cells. Here the authors show that the chromatin remodeling enzyme ATRX is a regulator of TIS and drives cells into this state via multiple mechanisms.