Copy number variants underlie the major selective sweeps in insecticide resistance genes in Anopheles arabiensis from Tanzania.

To keep ahead of the evolution of resistance to insecticides in mosquitoes, national malaria control programmes must make use of a range of insecticides, both old and new, while monitoring resistance mechanisms. Knowledge of the mechanisms of resistance remains limited in Anopheles arabiensis, which in many parts of Africa is of increasing importance because it is apparently less susceptible to many indoor control interventions. Furthermore, comparatively little is known in general about resistance to non-pyrethroid insecticides such as pirimiphos-methyl (PM), which are crucial for effective control in the context of resistance to pyrethroids. We performed a genome-wide association study to determine the molecular mechanisms of resistance to deltamethrin (commonly used in bednets) and PM, in An. arabiensis from two regions in Tanzania. Genomic regions of positive selection in these populations were largely driven by copy number variants (CNVs) in gene families involved in resistance to these two insecticides. We found evidence of a new gene cluster involved in resistance to PM, identifying a strong selective sweep tied to a CNV in the Coeae2g-Coeae6g cluster of carboxylesterase genes. Using complementary data from An. coluzzii in Ghana, we show that copy number at this locus is significantly associated with PM resistance. Similarly, for deltamethrin, resistance was strongly associated with a novel CNV allele in the Cyp6aa / Cyp6p cluster. Against this background of metabolic resistance, target site resistance was very rare or absent for both insecticides. Mutations in the pyrethroid target site Vgsc were at very low frequency in Tanzania, yet combining these samples with three An. arabiensis individuals from West Africa revealed a startling diversity of evolutionary origins of target site resistance, with up to 5 independent origins of Vgsc-995 mutations found within just 8 haplotypes. Thus, despite having been first recorded over 10 years ago, Vgsc resistance mutations in Tanzanian An. arabiensis have remained at stable low frequencies. Overall, our results provide a new copy number marker for monitoring resistance to PM in malaria mosquitoes, and reveal the complex picture of resistance patterns in An. arabiensis.

On dosimetric characteristics of detectors for relative dosimetry in small fields: a multicenter experimental study.

Objective. In this multicentric collaborative study, we aimed to verify whether the selected radiation detectors satisfy the requirements of TRS-483 Code of Practice for relative small field dosimetry in megavoltage photon beams used in radiotherapy, by investigating four dosimetric characteristics. Furthermore, we intended to analyze and complement the recommendations given in TRS-483.Approach. Short-term stability, dose linearity, dose-rate dependence, and leakage were determined for 17 models of detectors considered suitable for small field dosimetry. Altogether, 47 detectors were used in this study across ten institutions. Photon beams with 6 and 10 MV, with and without flattening filters, generated by Elekta Versa HDTMor Varian TrueBeamTMlinear accelerators, were used.Main results. The tolerance level of 0.1% for stability was fulfilled by 70% of the data points. For the determination of dose linearity, two methods were considered. Results from the use of a stricter method show that the guideline of 0.1% for dose linearity is not attainable for most of the detectors used in the study. Following the second approach (squared Pearson's correlation coefficientr2), it was found that 100% of the data fulfill the criteriar2> 0.999 (0.1% guideline for tolerance). Less than 50% of all data points satisfied the published tolerance of 0.1% for dose-rate dependence. Almost all data points (98.2%) satisfied the 0.1% criterion for leakage.Significance. For short-term stability (repeatability), it was found that the 0.1% guideline could not be met. Therefore, a less rigorous criterion of 0.25% is proposed. For dose linearity, our recommendation is to adopt a simple and clear methodology and to define an achievable tolerance based on the experimental data. For dose-rate dependence, a realistic criterion of 1% is proposed instead of the present 0.1%. Agreement was found with published guidelines for background signal (leakage).

Genome-wide association studies reveal novel loci associated with pyrethroid and organophosphate resistance in Anopheles gambiae and Anopheles coluzzii.

Resistance to insecticides in Anopheles mosquitoes threatens the effectiveness of malaria control, but the genetics of resistance are only partially understood. We performed a large scale multi-country genome-wide association study of resistance to two widely used insecticides: deltamethrin and pirimiphos-methyl, using sequencing data from An. gambiae and An. coluzzii from ten locations in West Africa. Resistance was highly multi-genic, multi-allelic and variable between populations. While the strongest and most consistent association with deltamethrin resistance came from Cyp6aa1, this was based on several independent copy number variants (CNVs) in An. coluzzii, and on a non-CNV haplotype in An. gambiae. For pirimiphos-methyl, signals included Ace1, cytochrome P450s, glutathione S-transferases and the nAChR target site of neonicotinoid insecticides. The regions around Cyp9k1 and the Tep family of immune genes showed evidence of cross-resistance to both insecticides. These locally-varying, multi-allelic patterns highlight the challenges involved in genomic monitoring of resistance, and may form the basis for improved surveillance methods.

Genome-wide association studies reveal novel loci associated with pyrethroid and organophosphate resistance in Anopheles gambiae s.l.

Resistance to insecticides in Anopheles mosquitoes threatens the effectiveness of the most widespread tools currently used to control malaria. The genetic underpinnings of resistance are still only partially understood, with much of the variance in resistance phenotype left unexplained. We performed a multi-country large scale genome-wide association study of resistance to two insecticides widely used in malaria control: deltamethrin and pirimiphos-methyl. Using a bioassay methodology designed to maximise the phenotypic difference between resistant and susceptible samples, we sequenced 969 phenotyped female An. gambiae and An. coluzzii from ten locations across four countries in West Africa (Benin, Côte d'Ivoire, Ghana and Togo), identifying single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) segregating in the populations. The patterns of resistance association were highly multiallelic and variable between populations, with different genomic regions contributing to resistance, as well as different mutations within a given region. While the strongest and most consistent association with deltamethrin resistance came from the region around Cyp6aa1 , this resistance was based on a combination of several independent CNVs in An. coluzzii , and on a non-CNV bearing haplotype in An. gambiae . Further signals involved a range of cytochrome P450, mitochondrial, and immunity genes. Similarly, for pirimiphos-methyl, while the strongest signal came from the region of Ace1 , more widespread signals included cytochrome P450s, glutathione S-transferases, and a subunit of the nAChR target site of neonicotinoid insecticides. The regions around Cyp9k1 and the Tep family of immune genes were associated with resistance to both insecticide classes, suggesting possible cross-resistance mechanisms. These locally-varying, multigenic and multiallelic patterns highlight the challenges involved in genomic monitoring and surveillance of resistance, and form the basis for improvement of methods used to detect and predict resistance. Based on simulations of resistance variants, we recommend that yet larger scale studies, exceeding 500 phenotyped samples per population, are required to better identify associated genomic regions.

Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19.

Background: The COVID-19 pandemic has created pressure on healthcare systems worldwide. Tools that can stratify individuals according to prognosis could allow for more efficient allocation of healthcare resources and thus improved patient outcomes. It is currently unclear if blood gene expression signatures derived from patients at the point of admission to hospital could provide useful prognostic information. Methods: Gene expression of whole blood obtained at the point of admission from a cohort of 78 patients hospitalised with COVID-19 during the first wave was measured by high resolution RNA sequencing. Gene signatures predictive of admission to Intensive Care Unit were identified and tested using machine learning and topological data analysis, TopMD. Results: The best gene expression signature predictive of ICU admission was defined using topological data analysis with an accuracy: 0.72 and ROC AUC: 0.76. The gene signature was primarily based on differentially activated pathways controlling epidermal growth factor receptor (EGFR) presentation, Peroxisome proliferator-activated receptor alpha (PPAR-α) signalling and Transforming growth factor beta (TGF-ß) signalling. Conclusions: Gene expression signatures from blood taken at the point of admission to hospital predicted ICU admission of treatment naïve patients with COVID-19.

Physical activity levels, lifestyle behaviour and musculoskeletal health profiles among seated video gamers during COVID-19.

OBJECTIVES: The aim of this research study was to determine the physical activity levels of non-active video gamers, and to determine how much other time was spent with sedentary behaviours, both in recreational and occupational domains. METHODS: The study used the International Physical Activity Questionnaire, and investigated physical activity levels and health data of seated gamers. Typical weekly gaming habits, self-reported musculoskeletal pain and physical activity levels experienced by participants while gaming was also obtained. RESULTS: Out of a total of 102 participants, 69.6% stated that they game for 3 hours or more on a typical weekday. Most participants video game seated or reclined (96.1%, p=0.01), with only four participants engaging in some form of active video gaming. In relation to physical activity levels, despite the high frequency and duration of gameplay, 87.3% of participants stated they engaged in moderate-intensity physical activity (p=0.02). There was an association with video gaming and musculoskeletal pain, with over half of the participants stating they experienced pain while gaming. There was also a link between seated video gaming and musculoskeletal pain among participants. CONCLUSION: Findings from this study show that the high frequency and duration of video gaming among gamers does not affect physical activity for moderate and vigorous intensities, but does affect musculoskeletal pain. Further research is required to determine whether video gaming has a significant effect on lifestyle, sedentary habits and musculoskeletal health, especially in the context of the COVID-19 pandemic where sedentary behaviour has likely increased.

The genetic architecture of target-site resistance to pyrethroid insecticides in the African malaria vectors Anopheles gambiae and Anopheles coluzzii.

Resistance to pyrethroid insecticides is a major concern for malaria vector control. Pyrethroids target the voltage-gated sodium channel (VGSC), an essential component of the mosquito nervous system. Substitutions in the amino acid sequence can induce a resistance phenotype. We use whole-genome sequence data from phase 2 of the Anopheles gambiae 1000 Genomes Project (Ag1000G) to provide a comprehensive account of genetic variation in the Vgsc gene across 13 African countries. In addition to known resistance alleles, we describe 20 other non-synonymous nucleotide substitutions at appreciable population frequency and map these variants onto a protein model to investigate the likelihood of pyrethroid resistance phenotypes. Thirteen of these novel alleles were found to occur almost exclusively on haplotypes carrying the known L995F kdr (knock-down resistance) allele and may enhance or compensate for the L995F resistance genotype. A novel mutation I1527T, adjacent to a predicted pyrethroid-binding site, was found in tight linkage with V402L substitutions, similar to allele combinations associated with resistance in other insect species. We also analysed genetic backgrounds carrying resistance alleles, to determine which alleles have experienced recent positive selection, and describe ten distinct haplotype groups carrying known kdr alleles. Five of these groups are observed in more than one country, in one case separated by over 3000 km, providing new information about the potential for the geographical spread of resistance. Our results demonstrate that the molecular basis of target-site pyrethroid resistance in malaria vectors is more complex than previously appreciated, and provide a foundation for the development of new genetic tools for insecticide resistance management.

Resistance to pirimiphos-methyl in West African Anopheles is spreading via duplication and introgression of the Ace1 locus.

Vector population control using insecticides is a key element of current strategies to prevent malaria transmission in Africa. The introduction of effective insecticides, such as the organophosphate pirimiphos-methyl, is essential to overcome the recurrent emergence of resistance driven by the highly diverse Anopheles genomes. Here, we use a population genomic approach to investigate the basis of pirimiphos-methyl resistance in the major malaria vectors Anopheles gambiae and A. coluzzii. A combination of copy number variation and a single non-synonymous substitution in the acetylcholinesterase gene, Ace1, provides the key resistance diagnostic in an A. coluzzii population from Côte d'Ivoire that we used for sequence-based association mapping, with replication in other West African populations. The Ace1 substitution and duplications occur on a unique resistance haplotype that evolved in A. gambiae and introgressed into A. coluzzii, and is now common in West Africa primarily due to selection imposed by other organophosphate or carbamate insecticides. Our findings highlight the predictive value of this complex resistance haplotype for phenotypic resistance and clarify its evolutionary history, providing tools to for molecular surveillance of the current and future effectiveness of pirimiphos-methyl based interventions.

Evolution of the Insecticide Target Rdl in African Anopheles Is Driven by Interspecific and Interkaryotypic Introgression.

The evolution of insecticide resistance mechanisms in natural populations of Anopheles malaria vectors is a major public health concern across Africa. Using genome sequence data, we study the evolution of resistance mutations in the resistance to dieldrin locus (Rdl), a GABA receptor targeted by several insecticides, but most notably by the long-discontinued cyclodiene, dieldrin. The two Rdl resistance mutations (296G and 296S) spread across West and Central African Anopheles via two independent hard selective sweeps that included likely compensatory nearby mutations, and were followed by a rare combination of introgression across species (from A. gambiae and A. arabiensis to A. coluzzii) and across nonconcordant karyotypes of the 2La chromosomal inversion. Rdl resistance evolved in the 1950s as the first known adaptation to a large-scale insecticide-based intervention, but the evolutionary lessons from this system highlight contemporary and future dangers for management strategies designed to combat development of resistance in malaria vectors.

A sensory appendage protein protects malaria vectors from pyrethroids.

Pyrethroid-impregnated bed nets have driven considerable reductions in malaria-associated morbidity and mortality in Africa since the beginning of the century1. The intense selection pressure exerted by bed nets has precipitated widespread and escalating resistance to pyrethroids in African Anopheles populations, threatening to reverse the gains that been made by malaria control2. Here we show that expression of a sensory appendage protein (SAP2), which is enriched in the legs, confers pyrethroid resistance to Anopheles gambiae. Expression of SAP2 is increased in insecticide-resistant populations and is further induced after the mosquito comes into contact with pyrethroids. SAP2 silencing fully restores mortality of the mosquitoes, whereas SAP2 overexpression results in increased resistance, probably owing to high-affinity binding of SAP2 to pyrethroid insecticides. Mining of genome sequence data reveals a selective sweep near the SAP2 locus in the mosquito populations of three West African countries (Cameroon, Guinea and Burkina Faso) with the observed increase in haplotype-associated single-nucleotide polymorphisms mirroring the increasing resistance of mosquitoes to pyrethroids reported in Burkina Faso. Our study identifies a previously undescribed mechanism of insecticide resistance that is likely to be highly relevant to malaria control efforts.

Whole-genome sequencing reveals high complexity of copy number variation at insecticide resistance loci in malaria mosquitoes.

Polymorphisms in genetic copy number can influence gene expression, coding sequence, and zygosity, making them powerful actors in the evolutionary process. Copy number variants (CNVs) are however understudied, being more difficult to detect than single-nucleotide polymorphisms. We take advantage of the intense selective pressures on the major malaria vector Anopheles gambiae, caused by the widespread use of insecticides for malaria control, to investigate the role of CNVs in the evolution of insecticide resistance. Using the whole-genome sequencing data from 1142 samples in the An. gambiae 1000 genomes project, we identified 250 gene-containing CNVs, encompassing a total of 267 genes of which 28 were in gene families linked to metabolic insecticide resistance, representing significant enrichment of these families. The five major gene clusters for metabolic resistance all contained CNVs, with 44 different CNVs being found across these clusters and multiple CNVs frequently covering the same genes. These 44 CNVs are widespread (45% of individuals carry at least one of them) and have been spreading through positive selection, indicated by their high local frequencies and extended haplotype homozygosity. Our results demonstrate the importance of CNVs in the response to selection, highlighting the urgent need to identify the contribution of each CNV to insecticide resistance and to track their spread as the use of insecticides in malaria endemic countries intensifies and as the operational deployment of next-generation bed nets targeting metabolic resistance gathers pace. Our detailed descriptions of CNVs found across the species range provide the tools to do so.

BPG: Seamless, automated and interactive visualization of scientific data.

BACKGROUND: We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. RESULTS: This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines. CONCLUSION: BPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general.

Compendium of TCDD-mediated transcriptomic response datasets in mammalian model systems.

BACKGROUND: 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is the most potent congener of the dioxin class of environmental contaminants. Exposure to TCDD causes a wide range of toxic outcomes, ranging from chloracne to acute lethality. The severity of toxicity is highly dependent on the aryl hydrocarbon receptor (AHR). Binding of TCDD to the AHR leads to changes in transcription of numerous genes. Studies evaluating the transcriptional changes brought on by TCDD may provide valuable insight into the role of the AHR in human health and disease. We therefore compiled a collection of transcriptomic datasets that can be used to aid the scientific community in better understanding the transcriptional effects of ligand-activated AHR. RESULTS: Specifically, we have created a datasets package - TCDD.Transcriptomics - for the R statistical environment, consisting of 63 unique experiments comprising 377 samples, including various combinations of 3 species (human derived cell lines, mouse and rat), 4 tissue types (liver, kidney, white adipose tissue and hypothalamus) and a wide range of TCDD exposure times and doses. These datasets have been fully standardized using consistent preprocessing and annotation packages (available as of September 14, 2015). To demonstrate the utility of this R package, a subset of "AHR-core" genes were evaluated across the included datasets. Ahrr, Nqo1 and members of the Cyp family were significantly induced following exposure to TCDD across the studies as expected while Aldh3a1 was induced specifically in rat liver. Inmt was altered only in liver tissue and primarily by rat-AHR. CONCLUSIONS: Analysis of the "AHR-core" genes demonstrates a continued need for studies surrounding the impact of AHR-activity on the transcriptome; genes believed to be consistently regulated by ligand-activated AHR show surprisingly little overlap across species and tissues. Until now, a comprehensive assessment of the transcriptome across these studies was challenging due to differences in array platforms, processing methods and annotation versions. We believe that this package, which is freely available for download ( http://labs.oicr.on.ca/boutros-lab/tcdd-transcriptomics ) will prove to be a highly beneficial resource to the scientific community evaluating the effects of TCDD exposure as well as the variety of functions of the AHR.

Genomic hallmarks of localized, non-indolent prostate cancer.

Prostate tumours are highly variable in their response to therapies, but clinically available prognostic factors can explain only a fraction of this heterogeneity. Here we analysed 200 whole-genome sequences and 277 additional whole-exome sequences from localized, non-indolent prostate tumours with similar clinical risk profiles, and carried out RNA and methylation analyses in a subset. These tumours had a paucity of clinically actionable single nucleotide variants, unlike those seen in metastatic disease. Rather, a significant proportion of tumours harboured recurrent non-coding aberrations, large-scale genomic rearrangements, and alterations in which an inversion repressed transcription within its boundaries. Local hypermutation events were frequent, and correlated with specific genomic profiles. Numerous molecular aberrations were prognostic for disease recurrence, including several DNA methylation events, and a signature comprised of these aberrations outperformed well-described prognostic biomarkers. We suggest that intensified treatment of genomically aggressive localized prostate cancer may improve cure rates.

A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing.

As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼ 100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.

Clinical implementation of photon beam flatness measurements to verify beam quality.

This work describes the replacement of Tissue Phantom Ratio (TPR) measurements with beam profile flatness measurements to determine photon beam quality during routine quality assurance (QA) measurements. To achieve this, a relationship was derived between the existing TPR15/5 energy metric and beam flatness, to provide baseline values and clinically relevant tolerances. The beam quality was varied around two nominal beam energy values for four matched Elekta linear accelerators (linacs) by varying the bending magnet currents and reoptimizing the beam. For each adjusted beam quality the TPR15/5 was measured using an ionization chamber and Solid Water phantom. Two metrics of beam flatness were evaluated using two identical commercial ionization chamber arrays. A linear relationship was found between TPR15/5 and both metrics of flatness, for both nominal energies and on all linacs. Baseline diagonal flatness (FDN) values were measured to be 103.0% (ranging from 102.5% to 103.8%) for 6 MV and 102.7% (ranging from 102.6% to 102.8%) for 10 MV across all four linacs. Clinically acceptable tolerances of ± 2% for 6 MV, and ± 3% for 10 MV, were derived to equate to the current TPR15/5 clinical tolerance of ± 0.5%. Small variations in the baseline diagonal flatness values were observed between ionization chamber arrays; however, the rate of change of TPR15/5 with diagonal flatness was found to remain within experimental uncertainty. Measurements of beam flatness were shown to display an increased sensitivity to variations in the beam quality when compared to TPR measurements. This effect is amplified for higher nominal energy photons. The derivation of clinical baselines and associated tolerances has allowed this method to be incorporated into routine QA, streamlining the process whilst also increasing versatility. In addition, the effect of beam adjustment can be observed in real time, allowing increased practicality during corrective and preventive maintenance interventions.

Spatial genomic heterogeneity within localized, multifocal prostate cancer.

Herein we provide a detailed molecular analysis of the spatial heterogeneity of clinically localized, multifocal prostate cancer to delineate new oncogenes or tumor suppressors. We initially determined the copy number aberration (CNA) profiles of 74 patients with index tumors of Gleason score 7. Of these, 5 patients were subjected to whole-genome sequencing using DNA quantities achievable in diagnostic biopsies, with detailed spatial sampling of 23 distinct tumor regions to assess intraprostatic heterogeneity in focal genomics. Multifocal tumors are highly heterogeneous for single-nucleotide variants (SNVs), CNAs and genomic rearrangements. We identified and validated a new recurrent amplification of MYCL, which is associated with TP53 deletion and unique profiles of DNA damage and transcriptional dysregulation. Moreover, we demonstrate divergent tumor evolution in multifocal cancer and, in some cases, tumors of independent clonal origin. These data represent the first systematic relation of intraprostatic genomic heterogeneity to predicted clinical outcome and inform the development of novel biomarkers that reflect individual prognosis.

Tumour genomic and microenvironmental heterogeneity for integrated prediction of 5-year biochemical recurrence of prostate cancer: a retrospective cohort study.

BACKGROUND: Clinical prognostic groupings for localised prostate cancers are imprecise, with 30-50% of patients recurring after image-guided radiotherapy or radical prostatectomy. We aimed to test combined genomic and microenvironmental indices in prostate cancer to improve risk stratification and complement clinical prognostic factors. METHODS: We used DNA-based indices alone or in combination with intra-prostatic hypoxia measurements to develop four prognostic indices in 126 low-risk to intermediate-risk patients (Toronto cohort) who will receive image-guided radiotherapy. We validated these indices in two independent cohorts of 154 (Memorial Sloan Kettering Cancer Center cohort [MSKCC] cohort) and 117 (Cambridge cohort) radical prostatectomy specimens from low-risk to high-risk patients. We applied unsupervised and supervised machine learning techniques to the copy-number profiles of 126 pre-image-guided radiotherapy diagnostic biopsies to develop prognostic signatures. Our primary endpoint was the development of a set of prognostic measures capable of stratifying patients for risk of biochemical relapse 5 years after primary treatment. FINDINGS: Biochemical relapse was associated with indices of tumour hypoxia, genomic instability, and genomic subtypes based on multivariate analyses. We identified four genomic subtypes for prostate cancer, which had different 5-year biochemical relapse-free survival. Genomic instability is prognostic for relapse in both image-guided radiotherapy (multivariate analysis hazard ratio [HR] 4·5 [95% CI 2·1-9·8]; p=0·00013; area under the receiver operator curve [AUC] 0·70 [95% CI 0·65-0·76]) and radical prostatectomy (4·0 [1·6-9·7]; p=0·0024; AUC 0·57 [0·52-0·61]) patients with prostate cancer, and its effect is magnified by intratumoral hypoxia (3·8 [1·2-12]; p=0·019; AUC 0·67 [0·61-0·73]). A novel 100-loci DNA signature accurately classified treatment outcome in the MSKCC low-risk to intermediate-risk cohort (multivariate analysis HR 6·1 [95% CI 2·0-19]; p=0·0015; AUC 0·74 [95% CI 0·65-0·83]). In the independent MSKCC and Cambridge cohorts, this signature identified low-risk to high-risk patients who were most likely to fail treatment within 18 months (combined cohorts multivariate analysis HR 2·9 [95% CI 1·4-6·0]; p=0·0039; AUC 0·68 [95% CI 0·63-0·73]), and was better at predicting biochemical relapse than 23 previously published RNA signatures. INTERPRETATION: This is the first study of cancer outcome to integrate DNA-based and microenvironment-based failure indices to predict patient outcome. Patients exhibiting these aggressive features after biopsy should be entered into treatment intensification trials. FUNDING: Movember Foundation, Prostate Cancer Canada, Ontario Institute for Cancer Research, Canadian Institute for Health Research, NIHR Cambridge Biomedical Research Centre, The University of Cambridge, Cancer Research UK, Cambridge Cancer Charity, Prostate Cancer UK, Hutchison Whampoa Limited, Terry Fox Research Institute, Princess Margaret Cancer Centre Foundation, PMH-Radiation Medicine Program Academic Enrichment Fund, Motorcycle Ride for Dad (Durham), Canadian Cancer Society.

Hotspot activating PRKD1 somatic mutations in polymorphous low-grade adenocarcinomas of the salivary glands.

Polymorphous low-grade adenocarcinoma (PLGA) is the second most frequent type of malignant tumor of the minor salivary glands. We identified PRKD1 hotspot mutations encoding p.Glu710Asp in 72.9% of PLGAs but not in other salivary gland tumors. Functional studies demonstrated that this kinase-activating alteration likely constitutes a driver of PLGA.

SeqControl: process control for DNA sequencing.

As high-throughput sequencing continues to increase in speed and throughput, routine clinical and industrial application draws closer. These 'production' settings will require enhanced quality monitoring and quality control to optimize output and reduce costs. We developed SeqControl, a framework for predicting sequencing quality and coverage using a set of 15 metrics describing overall coverage, coverage distribution, basewise coverage and basewise quality. Using whole-genome sequences of 27 prostate cancers and 26 normal references, we derived multivariate models that predict sequencing quality and depth. SeqControl robustly predicted how much sequencing was required to reach a given coverage depth (area under the curve (AUC) = 0.993), accurately classified clinically relevant formalin-fixed, paraffin-embedded samples, and made predictions from as little as one-eighth of a sequencing lane (AUC = 0.967). These techniques can be immediately incorporated into existing sequencing pipelines to monitor data quality in real time. SeqControl is available at http://labs.oicr.on.ca/Boutros-lab/software/SeqControl/.