Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting

Background: Genome editing by CRISPR-Cas9 technology allows large-scale screening of gene essentiality in cancer. A confounding factor when interpreting CRISPR-Cas9 screens is the high false-positive rate in detecting essential genes within copy number amplified regions of the genome. We have developed the computational tool CRISPRcleanR which is capable of identifying and correcting gene-independent responses to CRISPR-Cas9 targeting. CRISPRcleanR uses an unsupervised approach based on the segmentation of single-guide RNA fold change values across the genome, without making any assumption about the copy number status of the targeted genes. Results: Applying our method to existing and newly generated genome-wide essentiality profiles from 15 cancer cell lines, we demonstrate that CRISPRcleanR reduces false positives when calling essential genes, correcting biases within and outside of amplified regions, while maintaining true positive rates. Established cancer dependencies and essentiality signals of amplified cancer driver genes are detectable post-correction. CRISPRcleanR reports sgRNA fold changes and normalised read counts, is therefore compatible with downstream analysis tools, and works with multiple sgRNA libraries. Conclusions: CRISPRcleanR is a versatile open-source tool for the analysis of CRISPR-Cas9 knockout screens to identify essential genes

HDAC4-regulated STAT1 activation mediates platinum resistance in ovarian cancer

Ovarian cancer frequently acquires resistance to platinum chemotherapy, representing a major challenge for improving patient survival. Recent work suggests resistant clones exist within a larger drug sensitive cell-population prior to chemotherapy, implying that resistance is selected for rather than generated by treatment. We sought to compare clinically-derived, intra-patient paired models of initial platinum response and subsequent resistant relapse to define molecular determinants of evolved resistance. Transcriptional analysis of a matched cell-line series from three patients with high-grade serous ovarian cancer before and after development of clinical platinum resistance (PEO1/PEO4/PEO6, PEA1/PEA2, PEO14/PEO23) identified 91 up- and 126 down-regulated genes common to acquired resistance. Significantly enhanced apoptotic response to platinum treatment in resistant cells was observed following knockdown of HDAC4, FOLR2, PIK3R1 or STAT1 (p<0.05). Interestingly, HDAC4 and STAT1 were found to physically interact. Acetyl-STAT1 was detected in platinum sensitive but not HDAC4 over-expressing platinum resistant cells from the same patient. In resistant cells, STAT1 phosphorylation/nuclear translocation was seen following platinum exposure, whereas silencing of HDAC4 increased acetyl-STAT1 levels, prevented platinum induced STAT1 activation and restored cisplatin sensitivity. Conversely, matched sensitive cells were refractory to STAT1 phosphorylation on platinum treatment. Analysis of 16 paired tumor biopsies taken before and after development of clinical platinum resistance showed significantly increased HDAC4 expression in resistant tumors (n=7/16[44%]; p=0.04). Therefore, clinical selection of HDAC4 overexpressing tumor cells upon exposure to chemotherapy promotes STAT1 deacetylation and cancer cell survival. Together, our findings identify HDAC4 as a novel, therapeutically tractable target to counter platinum resistance in ovarian cancer

Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE).

PURPOSE: Gene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. EXPERIMENTAL DESIGN: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting. RESULTS: Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations. CONCLUSIONS: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications.See related commentary by McMullen et al., p. 5271.Core funding for this project was provided by the National Institutes of Health (R01-CA172404, PI: S.J. Ramus; and R01-CA168758, PIs: J.A. Doherty and M.A.Rossing), the Canadian Institutes for Health Research (Proof-of-Principle I program, PIs: D.G.Huntsman and M.S. Anglesio), the United States Department of Defense Ovarian Cancer Research Program (OC110433, PI: D.D. Bowtell). A. Talhouk is funded through a Michael Smith Foundation for Health Research Scholar Award. M.S. Anglesio is funded through a Michael Smith Foundation for Health Research Scholar Award and the Janet D. Cottrelle Foundation Scholars program managed by the BC Cancer Foundation. J. George was partially supported by the NIH/National Cancer Institute award number P30CA034196. C. Wang was a Career Enhancement Awardee of the Mayo Clinic SPORE in Ovarian Cancer (P50 CA136393). D.G. Huntsman receives support from the Dr. Chew Wei Memorial Professorship in Gynecologic Oncology, and the Canada Research Chairs program (Research Chair in Molecular and Genomic Pathology). M. Widschwendter receives funding from the European Union’s Horizon 2020 European Research Council Programme, H2020 BRCA-ERC under Grant Agreement No. 742432 as well as the charity, The Eve Appeal (https://eveappeal.org.uk/), and support of the National Institute for Health Research (NIHR) and the University College London Hospitals (UCLH) Biomedical Research Centre. G.E. Konecny is supported by the Miriam and Sheldon Adelson Medical Research Foundation. B.Y. Karlan is funded by the American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124. H.R. Harris is 20 supported by the NIH/National Cancer Institute award number K22 CA193860. OVCARE (including the VAN study) receives support through the BC Cancer Foundation and The VGH+UBC Hospital Foundation (authors AT, BG, DGH, and MSA). The AOV study is supported by the Canadian Institutes of Health Research (MOP86727). The Gynaecological Oncology Biobank at Westmead, a member of the Australasian Biospecimen Network-Oncology group, was funded by the National Health and Medical Research Council Enabling Grants ID 310670 & ID 628903 and the Cancer Institute NSW Grants ID 12/RIG/1-17 & 15/RIG/1-16. The Australian Ovarian Cancer Study Group was supported by the U.S. Army Medical Research and Materiel Command under DAMD17-01-1-0729, The Cancer Council Victoria, Queensland Cancer Fund, The Cancer Council New South Wales, The Cancer Council South Australia, The Cancer Council Tasmania and The Cancer Foundation of Western Australia (Multi-State Applications 191, 211 and 182) and the National Health and Medical Research Council of Australia (NHMRC; ID199600; ID400413 and ID400281). BriTROC-1 was funded by Ovarian Cancer Action (to IAM and JDB, grant number 006) and supported by Cancer Research UK (grant numbers A15973, A15601, A18072, A17197, A19274 and A19694) and the National Institute for Health Research Cambridge and Imperial Biomedical Research Centres. Samples from the Mayo Clinic were collected and provided with support of P50 CA136393 (E.L.G., G.L.K, S.H.K, M.E.S.)

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Comparing the Characteristics of Gene Expression Profiles Derived by Univariate and Multivariate Classification Methods

One application of gene expression arrays is to derive molecular profiles, i.e., sets of genes, which discriminate well between two classes of samples, for example between tumour types. Users are confronted with a multitude of classification methods of varying complexity that can be applied to this task. To help decide which method to use in a given situation, we compare important characteristics of a range of classification methods, including simple univariate filtering, penalised likelihood methods and the random forest.Classification accuracy is an important characteristic, but the biological interpretability of molecular profiles is also important. This implies both parsimony and stability, in the sense that profiles should not vary much when there are slight changes in the training data. We perform a random resampling study to compare these characteristics between the methods and across a range of profile sizes. We measure stability by adopting the Jaccard index to assess the similarity of resampled molecular profiles.We carry out a case study on five well-established cancer microarray data sets, for two of which we have the benefit of being able to validate the results in an independent data set. The study shows that those methods which produce parsimonious profiles generally result in better prediction accuracy than methods which don't include variable selection. For very small profile sizes, the sparse penalised likelihood methods tend to result in more stable profiles than univariate filtering while maintaining similar predictive performance.

Preventing damage limitation: targeting DNA-PKcs and DNA double strand break repair pathways for ovarian cancer therapy

Platinum-based chemotherapy is the cornerstone of ovarian cancer treatment, and its efficacy is dependent on the generation of DNA damage, with subsequent induction of apoptosis. Inappropriate or aberrant activation of the DNA damage response network is are associated with resistance to platinum, and defects in DNA repair pathways play critical roles in determining patient response to chemotherapy. In ovarian cancer, tumour cell defects in homologous recombination - a repair pathway activated in response to DNA double strand breaks (DSB) - are most commonly associated with platinum sensitive disease. However, despite initial sensitivity, the emergence of resistance is frequent. Here, we review strategies for directly interfering with DNA repair pathways, with particular focus on direct inhibition of non-homologous end joining (NHEJ), another DSB repair pathway. DNA-PKcs is a core component of NHEJ and it has shown considerable promise as a chemosensitization target in numerous cancer types, including ovarian cancer where it functions to promote platinum-induced survival signalling, via AKT activation. The development of pharmacological inhibitors of DNA-PKcs is on-going, and clinic-ready agents offer real hope to patients with chemoresistant disease

DNA-PK Mediates AKT Activation and Apoptosis Inhibition in Clinically Acquired Platinum Resistance12

Clinical resistance to chemotherapy is a frequent event in cancer treatment and is closely linked to poor outcome. High-grade serous (HGS) ovarian cancer is characterized by p53 mutation and high levels of genomic instability. Treatment includes platinum-based chemotherapy and initial response rates are high; however, resistance is frequently acquired, at which point treatment options are largely palliative. Recent data indicate that platinum-resistant clones exist within the sensitive primary tumor at presentation, implying resistant cell selection after treatment with platinum chemotherapy. The AKT pathway is central to cell survival and has been implicated in platinum resistance. Here, we show that platinum exposure induces an AKT-dependent, prosurvival, DNA damage response in clinically platinum-resistant but not platinum-sensitive cells. AKT relocates to the nucleus of resistant cells where it is phosphorylated specifically on S473 by DNA-dependent protein kinase (DNA-PK), and this activation inhibits cisplatin-mediated apoptosis. Inhibition of DNA-PK or AKT, but not mTORC2, restores platinum sensitivity in a panel of clinically resistant HGS ovarian cancer cell lines: we also demonstrate these effects in other tumor types. Resensitization is associated with prevention of AKT-mediated BAD phosphorylation. Strikingly, in patient-matched sensitive cells, we do not see enhanced apoptosis on combining cisplatin with AKT or DNA-PK inhibition. Insulin-mediated activation of AKT is unaffected by DNA-PK inhibitor treatment, suggesting that this effect is restricted to DNA damage-mediated activation of AKT and that, clinically, DNA-PK inhibition might prevent platinum-induced AKT activation without interfering with normal glucose homeostasis, an unwanted toxicity of direct AKT inhibitors