Mutational signatures in tumours induced by high and low energy radiation in Trp53 deficient mice.

Ionising radiation (IR) is a recognised carcinogen responsible for cancer development in patients previously treated using radiotherapy, and in individuals exposed as a result of accidents at nuclear energy plants. However, the mutational signatures induced by distinct types and doses of radiation are unknown. Here, we analyse the genetic architecture of mammary tumours, lymphomas and sarcomas induced by high (56Fe-ions) or low (gamma) energy radiation in mice carrying Trp53 loss of function alleles. In mammary tumours, high-energy radiation is associated with induction of focal structural variants, leading to genomic instability and Met amplification. Gamma-radiation is linked to large-scale structural variants and a point mutation signature associated with oxidative stress. The genomic architecture of carcinomas, sarcomas and lymphomas arising in the same animals are significantly different. Our study illustrates the complex interactions between radiation quality, germline Trp53 deficiency and tissue/cell of origin in shaping the genomic landscape of IR-induced tumours

DNA repair deficiency biomarkers and the 70-gene ultra-high risk signature as predictors of veliparib/carboplatin response in the I-SPY 2 breast cancer trial.

Veliparib combined with carboplatin (VC) was an experimental regimen evaluated in the biomarker-rich neoadjuvant I-SPY 2 trial for breast cancer. VC showed improved efficacy in the triple negative signature. However, not all triple negative patients achieved pathologic complete response and some HR+HER2- patients responded. Pre-specified analysis of five DNA repair deficiency biomarkers (BRCA1/2 germline mutation; PARPi-7, BRCA1ness, and CIN70 expression signatures; and PARP1 protein) was performed on 116 HER2- patients (VC: 72 and concurrent controls: 44). We also evaluated the 70-gene ultra-high risk signature (MP1/2), one of the biomarkers used to define subtype in the trial. We used logistic modeling to assess biomarker performance. Successful biomarkers were combined using a simple voting scheme to refine the 'predicted sensitive' group and Bayesian modeling used to estimate the pathologic complete response rates. BRCA1/2 germline mutation status associated with VC response, but its low prevalence precluded further evaluation. PARPi-7, BRCA1ness, and MP1/2 specifically associated with response in the VC arm but not the control arm. Neither CIN70 nor PARP1 protein specifically predicted VC response. When we combined the PARPi-7 and MP1/2 classifications, the 42% of triple negative patients who were PARPi7-high and MP2 had an estimated pCR rate of 75% in the VC arm. Only 11% of HR+/HER2- patients were PARPi7-high and MP2; but these patients were also more responsive to VC with estimated pathologic complete response rates of 41%. PARPi-7, BRCA1ness and MP1/2 signatures may help refine predictions of VC response, thereby improving patient care

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

Systemic complement profiling in multiple sclerosis as a biomarker of disease state

Background: There is increasing evidence of significant and dynamic systemic activation and upregulation of complement in multiple sclerosis (MS), which may contribute to disease pathogenesis. Objective: We aimed to investigate the pathological role of complement in MS and the potential role for complement profiling as a biomarker of MS disease state. Methods: Key components of the classical, alternative and terminal pathways of complement were measured in plasma and cerebrospinal fluid (CSF) of patients with MS in different clinical phases of disease and in matched controls. Results: Increased plasma levels of C3 (p<0.003), C4 (p<0.001), C4a (p<0.001), C1 inhibitor (p<0.001), and factor H (p<0.001), and reduced levels of C9 (p<0.001) were observed in MS patients compared with controls. Combined profiling of these analytes produced a statistical model with a predictive value of 97% for MS and 73% for clinical relapse when combined with selected demographic data. CSF-plasma correlations suggested that source of synthesis of these components was both systemic and central. Conclusion: These data provide further evidence of alterations in both local and systemic expression and activation of complement in MS and suggest that complement profiling may be informative as a biomarker of MS disease, although further work is needed to determine its use in distinguishing MS from its differential

Seasonal variation in multiple sclerosis relapse

Relapses are a characteristic clinical feature of multiple sclerosis (MS), but an appreciation of factors that cause them remains elusive. In this study, we have examined seasonal variation of relapse in a large population-based MS cohort and correlated observed patterns with age, sex, disease course, and climatic factors. Relapse data were recorded prospectively in 2076 patients between 2005 and 2014. 3902 events were recorded in 1158 patients (range 0–24). There was significant seasonal variation in relapse rates (p < 0.0001) and this was associated with monthly hours of sunshine (odds ratio OR 1.08, p = 0.02). Relapse rates were highest in patients under the age of 30 (OR 1.42, p = 0.0005) and decreased with age. There was no evidence of different relapse rates for males compared to females (OR 0.90, p = 0.19). Identification of potentially modifiable environmental factors associated with temporal variation in relapse rates may allow alteration of risk on a population basis and alteration of outcome of established disease once established. Future epidemiological studies should examine dynamic environmental factors with serial prospective measurements and biological sampling. Significant seasonal differences in relapse rates highlight the importance of environmental factors in disease expression and should be taken into account when planning clinical trials in which relapse frequency is an outcome. In addition, identification of potentially modifiable factors associated with this variation may offer unique opportunities for alteration of risk of relapse and long-term outcome on a population level, and suggest putative biological mechanisms for relapse initiation

SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors

Motivation: Next-generation sequencing (NGS) has enabled whole genome and transcriptome single nucleotide variant (SNV) discovery in cancer. NGS produces millions of short sequence reads that, once aligned to a reference genome sequence, can be interpreted for the presence of SNVs. Although tools exist for SNV discovery from NGS data, none are specifically suited to work with data from tumors, where altered ploidy and tumor cellularity impact the statistical expectations of SNV discovery

Protocol for a retrospective, controlled cohort study of the impact of a change in Nature journals' editorial policy for life sciences research on the completeness of reporting study design and execution

In recent years there has been increasing concern about the rigor of laboratory research. Here we present the protocol for a study comparing the completeness of reporting of in vivo and in vitro research carried in Nature Publication Group journals before and after the introduction of a change in editorial policy (the introduction of a set of guidelines for reporting); and in similar research published in other journals in the same periods. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11192-016-1964-8) contains supplementary material, which is available to authorized users

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