Dependence on RAD52 and RAD1 for anticancer drug resistance mediated by inactivation of mismatch repair genes

AbstractMismatch repair (MMR) proteins repair mispaired DNA bases and have an important role in maintaining the integrity of the genome [1]. Loss of MMR has been correlated with resistance to a variety of DNA-damaging agents, including many anticancer drugs [2]. How loss of MMR leads to resistance is not understood, but is proposed to be due to loss of futile MMR activity and/or replication stalling [3,4]. We report that inactivation of MMR genes (MLH1, MLH2, MSH2, MSH3, MSH6, but not PMS1) in isogenic strains of Saccharomyces cerevisiae led to increased resistance to the anticancer drugs cisplatin, carboplatin and doxorubicin, but had no effect on sensitivity to ultraviolet C (UVC) radiation. Sensitivity to cisplatin and doxorubicin was increased in mlh1 mutant strains when the MLH1 gene was reintroduced, demonstrating a direct involvement of MMR proteins in sensitivity to these DNA-damaging agents. Inactivation of MLH1, MLH2 or MSH2 had no significant effect, however, on drug sensitivities in the rad52 or rad1 mutant strains that are defective in mitotic recombination and removing unpaired DNA single strands. We propose a model whereby MMR proteins – in addition to their role in DNA-damage recognition – decrease adduct tolerance during DNA replication by modulating the levels of recombination-dependent bypass. This hypothesis is supported by the finding that, in human ovarian tumour cells, loss of hMLH1 correlated with acquisition of cisplatin resistance and increased cisplatin-induced sister chromatid exchange, both of which were reversed by restoration of hMLH1 expression

Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes

IntroductionDrug resistance is a major obstacle in cancer treatment and can involve a variety of different factors. Identifying effective therapies for drug resistant tumors is integral for improving patient outcomes.MethodsIn this study, we applied a computational drug repositioning approach to identify potential agents to sensitize primary drug resistant breast cancers. We extracted drug resistance profiles from the I-SPY 2 TRIAL, a neoadjuvant trial for early stage breast cancer, by comparing gene expression profiles of responder and non-responder patients stratified into treatments within HR/HER2 receptor subtypes, yielding 17 treatment-subtype pairs. We then used a rank-based pattern-matching strategy to identify compounds in the Connectivity Map, a database of cell line derived drug perturbation profiles, that can reverse these signatures in a breast cancer cell line. We hypothesize that reversing these drug resistance signatures will sensitize tumors to treatment and prolong survival.ResultsWe found that few individual genes are shared among the drug resistance profiles of different agents. At the pathway level, however, we found enrichment of immune pathways in the responders in 8 treatments within the HR+HER2+, HR+HER2-, and HR-HER2- receptor subtypes. We also found enrichment of estrogen response pathways in the non-responders in 10 treatments primarily within the hormone receptor positive subtypes. Although most of our drug predictions are unique to treatment arms and receptor subtypes, our drug repositioning pipeline identified the estrogen receptor antagonist fulvestrant as a compound that can potentially reverse resistance across 13/17 of the treatments and receptor subtypes including HR+ and triple negative. While fulvestrant showed limited efficacy when tested in a panel of 5 paclitaxel resistant breast cancer cell lines, it did increase drug response in combination with paclitaxel in HCC-1937, a triple negative breast cancer cell line.ConclusionWe applied a computational drug repurposing approach to identify potential agents to sensitize drug resistant breast cancers in the I-SPY 2 TRIAL. We identified fulvestrant as a potential drug hit and showed that it increased response in a paclitaxel-resistant triple negative breast cancer cell line, HCC-1937, when treated in combination with paclitaxel

Surgical Standards for Management of the Axilla in Breast Cancer Clinical Trials with Pathological Complete Response Endpoint.

Advances in the surgical management of the axilla in patients treated with neoadjuvant chemotherapy, especially those with node positive disease at diagnosis, have led to changes in practice and more judicious use of axillary lymph node dissection that may minimize morbidity from surgery. However, there is still significant confusion about how to optimally manage the axilla, resulting in variation among practices. From the viewpoint of drug development, assessment of response to neoadjuvant chemotherapy remains paramount and appropriate assessment of residual disease-the primary endpoint of many drug therapy trials in the neoadjuvant setting-is critical. Therefore decreasing the variability, especially in a multicenter clinical trial setting, and establishing a minimum standard to ensure consistency in clinical trial data, without mandating axillary lymph node dissection, for all patients is necessary. The key elements which include proper staging and identification of nodal involvement at diagnosis, and appropriately targeted management of the axilla at the time of surgical resection are presented. The following protocols have been adopted as standard procedure by the I-SPY2 trial for management of axilla in patients with node positive disease, and present a framework for prospective clinical trials and practice

Erratum: Author Correction: Surgical Standards for Management of the Axilla in Breast Cancer Clinical Trials with Pathological Complete Response Endpoint.

[This corrects the article DOI: 10.1038/s41523-018-0074-6.]

Effect of Pembrolizumab Plus Neoadjuvant Chemotherapy on Pathologic Complete Response in Women With Early-Stage Breast Cancer: An Analysis of the Ongoing Phase 2 Adaptively Randomized I-SPY2 Trial.

Importance: Approximately 25% of patients with early-stage breast cancer who receive (neo)adjuvant chemotherapy experience a recurrence within 5 years. Improvements in therapy are greatly needed. Objective: To determine if pembrolizumab plus neoadjuvant chemotherapy (NACT) in early-stage breast cancer is likely to be successful in a 300-patient, confirmatory randomized phase 3 neoadjuvant clinical trial. Design, Setting, and Participants: The I-SPY2 study is an ongoing open-label, multicenter, adaptively randomized phase 2 platform trial for high-risk, stage II/III breast cancer, evaluating multiple investigational arms in parallel. Standard NACT serves as the common control arm; investigational agent(s) are added to this backbone. Patients with ERBB2 (formerly HER2)-negative breast cancer were eligible for randomization to pembrolizumab between November 2015 and November 2016. Interventions: Participants were randomized to receive taxane- and anthracycline-based NACT with or without pembrolizumab, followed by definitive surgery. Main Outcomes and Measures: The primary end point was pathologic complete response (pCR). Secondary end points were residual cancer burden (RCB) and 3-year event-free and distant recurrence-free survival. Investigational arms graduated when demonstrating an 85% predictive probability of success in a hypothetical confirmatory phase 3 trial. Results: Of the 250 women included in the final analysis, 181 were randomized to the standard NACT control group (median [range] age, 47 [24.77] years). Sixty-nine women (median [range] age, 50 [27-71] years) were randomized to 4 cycles of pembrolizumab in combination with weekly paclitaxel followed by AC; 40 hormone receptor (HR)-positive and 29 triple-negative. Pembrolizumab graduated in all 3 biomarker signatures studied. Final estimated pCR rates, evaluated in March 2017, were 44% vs 17%, 30% vs 13%, and 60% vs 22% for pembrolizumab vs control in the ERBB2-negative, HR-positive/ERBB2-negative, and triple-negative cohorts, respectively. Pembrolizumab shifted the RCB distribution to a lower disease burden for each cohort evaluated. Adverse events included immune-related endocrinopathies, notably thyroid abnormalities (13.0%) and adrenal insufficiency (8.7%). Achieving a pCR appeared predictive of long-term outcome, where patients with pCR following pembrolizumab plus chemotherapy had high event-free survival rates (93% at 3 years with 2.8 years\u27 median follow-up). Conclusions and Relevance: When added to standard neoadjuvant chemotherapy, pembrolizumab more than doubled the estimated pCR rates for both HR-positive/ERBB2-negative and triple-negative breast cancer, indicating that checkpoint blockade in women with early-stage, high-risk, ERBB2-negative breast cancer is highly likely to succeed in a phase 3 trial. Pembrolizumab was the first of 10 agents to graduate in the HR-positive/ERBB2-negative signature. Trial Registration: ClinicalTrials.gov Identifier: NCT01042379

Improving our understanding of the in vivo modelling of psychotic disorders: a systematic review and meta-analysis

Psychotic disorders represent a severe category of mental disorders affecting about one percent of the population. Individuals experience a loss or distortion of contact with reality alongside other symptoms, many of which are still not adequately managed using existing treatments. While animal models of these disorders could offer insights into these disorders and potential new treatments, translation of this knowledge has so far been poor in terms of informing clinical trials and practice. The aim of this project was to improve our understanding of these pre-clinical studies and identify potential weaknesses underlying translational failure. I carried out a systematic search of the literature to provide an unbiased summary of publications reporting animal models of schizophrenia and other psychotic disorders. From these publications, data were extracted to quantify aspects of the field including reported quality of studies, study characteristics and behavioural outcome data. The latter of these data were then used to calculate estimates of efficacy using random-effects meta-analysis. Having identified 3847 publications of relevance, including 852 different methods used to induce the model, over 359 different outcomes tested in them and almost 946 different treatments reported to be administered. I show that a large proportion of studies use simple pharmacological interventions to induce their models of these disorders, despite the availability of models using other interventions that are arguably of higher translational relevance. I also show that the reported quality of these studies is low, and only 22% of studies report taking measures to reduce the risk of biases such as randomisation and blinding, which has been shown to affect the reliability of results drawn. Through this work it becomes apparent that the literature is incredibly vast for studies looking at animal models of psychotic disorders and that some of the relevant work potentially overlaps with studies describing other conditions. This means that drawing reliable conclusions from these data is affected by what is made available in the literature, how it is reported and identified in a search and the time that it takes to reach these conclusions. I introduce the idea of using computer-assisted tools to overcome one of these problems in the long term. Translation of results from studies looking at animals modelling uniquely-human psychotic disorders to clinical successes might be improved by better reporting of studies including publishing of all work carried out, labelling of studies more uniformly so that it is identifiable, better reporting of study design including improving on reporting of measures taken to reduce the risk of bias and focusing on models with greater validity to the human condition