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.

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.

A comparative study of survival models for breast cancer prognostication revisited: the benefits of multi-gene models.

BACKGROUND: The development of clinical -omic biomarkers for predicting patient prognosis has mostly focused on multi-gene models. However, several studies have described significant weaknesses of multi-gene biomarkers. Indeed, some high-profile reports have even indicated that multi-gene biomarkers fail to consistently outperform simple single-gene ones. Given the continual improvements in -omics technologies and the availability of larger, better-powered datasets, we revisited this "single-gene hypothesis" using new techniques and datasets. RESULTS: By deeply sampling the population of available gene sets, we compare the intrinsic properties of single-gene biomarkers to multi-gene biomarkers in twelve different partitions of a large breast cancer meta-dataset. We show that simple multi-gene models consistently outperformed single-gene biomarkers in all twelve partitions. We found 270 multi-gene biomarkers (one per ~11,111 sampled) that always made better predictions than the best single-gene model. CONCLUSIONS: The single-gene hypothesis for breast cancer does not appear to retain its validity in the face of improved statistical models, lower-noise genomic technology and better-powered patient cohorts. These results highlight that it is critical to revisit older hypotheses in the light of newer techniques and datasets.

Valection: design optimization for validation and verification studies.

BACKGROUND: Platform-specific error profiles necessitate confirmatory studies where predictions made on data generated using one technology are additionally verified by processing the same samples on an orthogonal technology. However, verifying all predictions can be costly and redundant, and testing a subset of findings is often used to estimate the true error profile. RESULTS: To determine how to create subsets of predictions for validation that maximize accuracy of global error profile inference, we developed Valection, a software program that implements multiple strategies for the selection of verification candidates. We evaluated these selection strategies on one simulated and two experimental datasets. CONCLUSIONS: Valection is implemented in multiple programming languages, available at: http://labs.oicr.on.ca/boutros-lab/software/valection.

Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection.

The detection of somatic mutations from cancer genome sequences is key to understanding the genetic basis of disease progression, patient survival and response to therapy. Benchmarking is needed for tool assessment and improvement but is complicated by a lack of gold standards, by extensive resource requirements and by difficulties in sharing personal genomic information. To resolve these issues, we launched the ICGC-TCGA DREAM Somatic Mutation Calling Challenge, a crowdsourced benchmark of somatic mutation detection algorithms. Here we report the BAMSurgeon tool for simulating cancer genomes and the results of 248 analyses of three in silico tumors created with it. Different algorithms exhibit characteristic error profiles, and, intriguingly, false positives show a trinucleotide profile very similar to one found in human tumors. Although the three simulated tumors differ in sequence contamination (deviation from normal cell sequence) and in subclonality, an ensemble of pipelines outperforms the best individual pipeline in all cases. BAMSurgeon is available at https://github.com/adamewing/bamsurgeon/.

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.

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.

Cross-species transcriptomic analysis elucidates constitutive aryl hydrocarbon receptor activity.

BACKGROUND: Research on the aryl hydrocarbon receptor (AHR) has largely focused on variations in toxic outcomes resulting from its activation by halogenated aromatic hydrocarbons. But the AHR also plays key roles in regulating pathways critical for development, and after decades of research the mechanisms underlying physiological regulation by the AHR remain poorly characterized. Previous studies identified several core genes that respond to xenobiotic AHR ligands across a broad range of species and tissues. However, only limited inferences have been made regarding its role in regulating constitutive gene activity, i.e. in the absence of exogenous ligands. To address this, we profiled transcriptomic variations between AHR-active and AHR-less-active animals in the absence of an exogenous agonist across five tissues, three of which came from rats (hypothalamus, white adipose and liver) and two of which came from mice (kidney and liver). Because AHR status alone has been shown sufficient to alter transcriptomic responses, we reason that by contrasting profiles amongst AHR-variant animals, we may elucidate effects of the AHR on constitutive mRNA abundances. RESULTS: We found significantly more overlap in constitutive mRNA abundances amongst tissues within the same species than from tissues between species and identified 13 genes (Agt, Car3, Creg1, Ctsc, E2f6, Enpp1, Gatm, Gstm4, Kcnj8, Me1, Pdk1, Slc35a3, and Sqrdl) that are affected by AHR-status in four of five tissues. One gene, Creg1, was significantly up-regulated in all AHR-less-active animals. We also find greater overlap between tissues at the pathway level than at the gene level, suggesting coherency to the AHR signalling response within these processes. Analysis of regulatory motifs suggests that the AHR mostly mediates transcriptional regulation via direct binding to response elements. CONCLUSIONS: These findings, though preliminary, present a platform for further evaluating the role of the AHR in regulation of constitutive mRNA levels and physiologic function.

Common maternal health problems and their correlates in early post-partum mothers.

BACKGROUND: Mothers experience a wide range of maternal health problems after childbirth, which in turn, affect their well-being and ability to care for their newborn. These problems may be influenced by factors such as mode of delivery or socio-economic status. OBJECTIVE: This study aims to investigate the prevalence of common maternal health problems and their correlates in a public primary healthcare institution in Singapore. DESIGN: This was a cross-sectional study, based on a self-administered questionnaire. METHODS: A total of 373 mothers (mean age 31.9 years) who accompanied their infants for their 4- to 8-week development assessments at a public primary care clinic in Singapore completed a self-administered questionnaire from June 2021 to December 2021. The questionnaire assessed demographic factors, mode of delivery, number of children, number of individuals providing significant help, and the frequency of common physical and mental maternal health problems using a 5-point Likert-type scale. RESULTS: The five most common maternal health problems were fatigue (77.7%), lower back pain (59.3%), Caesarean wound pain (54.3%), upper back pain (53.0%) and vaginal pain (41.2%). The prevalence of depression and anxiety was 22.0% and 11.3%, respectively. With respect to the symptoms' correlates, pain on passing urine was more frequent after assisted vaginal deliveries than all other forms of deliveries (all pairwise p < 0.01), and pain on passing motion was more frequent in vaginal deliveries than in Caesarean deliveries (all pairwise p < 0.05). Mothers having a larger number of children more frequently experienced headaches (ß = 0.17, SE = 0.05, p = 0.002) and less frequently experienced breastfeeding difficulties (ß = -0.28, SE = 0.08, p < 0.001). CONCLUSION: Mothers experienced a high prevalence of maternal health problems in multiple domains during the first 8 weeks after childbirth. Mode of delivery and number of children were associated with increased prevalence of certain problems. Mothers' physical and mental well-being should be investigated early after delivery and addressed with adequate treatments and resources.

Measuring change in health-system pharmacy over 50 years: "reflecting" on the mirror, part I.

The Director's Forum guides pharmacy leaders in establishing patient-centered services in hospitals and health systems. August 2013 marked the 50th anniversary of the publication of the Mirror to Hospital Pharmacy, which was a comprehensive study of hospital pharmacy services in the United States. This iconic textbook was co-authored by Donald Francke, Clifton J. Latiolais, Gloria N. Francke, and Norman Ho. The Mirror profiled hospital pharmacy of the 1950s and established goals for the profession in 6 paradigms: (1) professional philosophy and ethics, (2) scientific and technical expansion of health-system pharmacy, (3) development of administrative and managerial acumen, (4) increased practice competence, (5) wage and salary compensation commensurate with professional responsibilities, and (6) health-system pharmacy as a vehicle for advancing the profession as a whole. This article critically reviews the profession's progress on the first 3 goals; an article in the January 2014 issue of Hospital Pharmacy will review the final 3 goals. An understanding of the profession's progress on these goals since the seminal work of the Mirror provides directors of pharmacy a platform from which to develop strategies to enhance patient-centered pharmacy services.

Inter-strain heterogeneity in rat hepatic transcriptomic responses to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD).

The biochemical and toxic effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) have been the subject of intense study for decades. It is now clear that essentially all TCDD-induced toxicities are mediated by DNA-protein interactions involving the Aryl Hydrocarbon Receptor (AHR). Nevertheless, it remains unknown which AHR target genes cause TCDD toxicities. Several groups, including our own, have developed rodent model systems to probe these questions. mRNA expression profiling of these model systems has revealed significant inter-species heterogeneity in rodent hepatic responses to TCDD. It has remained unclear if this variability also exists within a species, amongst rodent strains. To resolve this question, we profiled the hepatic transcriptomic response to TCDD of diverse rat strains (L-E, H/W, F344 and Wistar rats) and two lines derived from L-E×H/W crosses, at consistent age, sex, and dosing (100 µg/kg TCDD for 19 h). Using this uniquely consistent dataset, we show that the majority of TCDD-induced alterations in mRNA abundance are strain/line-specific: only 11 genes were affected by TCDD across all strains, including well-known dioxin-responsive genes such as Cyp1a1 and Nqo1. Our analysis identified two novel universally dioxin-responsive genes as well as 4 genes induced by TCDD in dioxin-sensitive rats only. These 6 genes are strong candidates to explain TCDD-related toxicities, so we validated them using 152 animals in time-course (0 to 384 h) and dose-response (0 to 3000 µg/kg) experiments. This study reveals that different rat strains exhibit dramatic transcriptional heterogeneity in their hepatic responses to TCDD and that inter-strain comparisons can help identify candidate toxicity-related genes.

Recent advances in induced proximity modalities.

Challenging disease targets necessitate new approaches for therapeutic intervention. Rewiring protein-biomolecule interactions with proximity-inducing agents extends intervention opportunities beyond target agonism or inhibition. Spanning varied molecular phenotypes and diverse target classes, proximity-inducing agents demonstrate immense potential across target degradation, cleavage, and post-translational editing. Here, we review a selection of exciting developments in the concepts and mechanisms of induced proximity-driven strategies from the last two years. Key technological advances that enable these discoveries and expand the scope of targets and machinery for induced-proximity modalities are highlighted.

Taming transcription factors with TRAFTACs.

Transcription factors play central roles in numerous diseases yet are notoriously challenging targets for drug development. In this issue of Cell Chemical Biology, Samarasinghe et al. (2021) describe a modular approach to targeting transcription factors for degradation with TRAFTACs, without the need for extensive ligand development campaigns.

Successful Implicit Vocabulary Intervention for Three Cantonese-Speaking Toddlers: A Replicated Single-Case Design.

Purpose We report on a replicated single-case design study that measured the feasibility of an expressive vocabulary intervention for three Cantonese-speaking toddlers with small expressive lexicons relative to their age. The aim was to assess the cross-cultural and cross-linguistic feasibility of an intervention method developed for English-speaking children. Method A nonconcurrent multiple-baseline design was used with four baseline data points and 16 intervention sessions per participant. The intervention design incorporated implicit learning principles, high treatment dosage, and control of the phonological neighborhood density of the stimuli. The children (24-39 months) attended 7-9 weeks of twice weekly input-based treatment in which no explicit verbal production was required from the child. Each target word was provided as input a minimum of 64 times in at least two intervention sessions. Treatment feasibility was measured by comparison of how many of the target and control words the child produced across the intervention period, and parent-reported expressive vocabulary checklists were completed for comparison of pre- and postintervention child spoken vocabulary size. An omnibus effect size for the treatment effect of the number of target and control words produced across time was calculated using Kendall's Tau. Results There was a significant treatment effect for target words learned in intervention relative to baselines, and all children produced significantly more target than control words across the intervention period. The effect of phonological neighborhood density on expressive word production could not be evaluated because two of the three children learned all target words. Conclusion The results provide cross-cultural evidence of the feasibility of a model of intervention that incorporated a high-dosage, cross-situational statistical learning paradigm to teach spoken word production to children with small expressive lexicons.

Towards personalized induction therapy for esophageal adenocarcinoma: organoids derived from endoscopic biopsy recapitulate the pre-treatment tumor.

Esophageal adenocarcinoma has few known recurrent mutations and therefore robust, reliable and reproducible patient-specific models are needed for personalized treatment. Patient-derived organoid culture is a strategy that may allow for the personalized study of esophageal adenocarcinoma and the development of personalized induction therapy. We therefore developed a protocol to establish EAC organoids from endoscopic biopsies of naïve esophageal adenocarcinomas. Histologic characterization and molecular characterization of organoids by whole exome sequencing demonstrated recapitulation of the tumors' histology and genomic (~ 60% SNV overlap) characteristics. Drug testing using clinically appropriate chemotherapeutics and targeted therapeutics showed an overlap between the patient's tumor response and the corresponding organoids' response. Furthermore, we identified Barrett's esophagus epithelium as a potential source of organoid culture contamination. In conclusion, organoids can be robustly cultured from endoscopic biopsies of esophageal adenocarcinoma and recapitulate the originating tumor. This model demonstrates promise as a tool to better personalize therapy for esophageal adenocarcinoma patients.

Generation of Genetically Engineered Mouse Lung Organoid Models for Squamous Cell Lung Cancers Allows for the Study of Combinatorial Immunotherapy.

PURPOSE: Lung squamous cell carcinoma (LSCC) is a deadly disease for which only a subset of patients responds to immune checkpoint blockade (ICB) therapy. Therefore, preclinical mouse models that recapitulate the complex genetic profile found in patients are urgently needed. EXPERIMENTAL DESIGN: We used CRISPR genome editing to delete multiple tumor suppressors in lung organoids derived from Cre-dependent SOX2 knock-in mice. We investigated both the therapeutic efficacy and immunologic effects accompanying combination PD-1 blockade and WEE1 inhibition in both mouse models and LSCC patient-derived cell lines. RESULTS: We show that multiplex gene editing of mouse lung organoids using the CRISPR-Cas9 system allows for efficient and rapid means to generate LSCCs that closely mimic the human disease at the genomic and phenotypic level. Using this genetically defined mouse model and three-dimensional tumoroid culture system, we show that WEE1 inhibition induces DNA damage that primes the endogenous type I IFN and antigen presentation system in primary LSCC tumor cells. These events promote cytotoxic T-cell-mediated clearance of tumor cells and reduce the accumulation of tumor-infiltrating neutrophils. Beneficial immunologic features of WEE1 inhibition are further enhanced by the addition of anti-PD-1 therapy. CONCLUSIONS: We developed a mouse model system to investigate a novel combinatory approach that illuminates a clinical path hypothesis for combining ICB with DNA damage-inducing therapies in the treatment of LSCC.

Organoid Cultures as Preclinical Models of Non-Small Cell Lung Cancer.

PURPOSE: Non-small cell lung cancer (NSCLC) is the most common cause of cancer-related deaths worldwide. There is an unmet need to develop novel clinically relevant models of NSCLC to accelerate identification of drug targets and our understanding of the disease. EXPERIMENTAL DESIGN: Thirty surgically resected NSCLC primary patient tissue and 35 previously established patient-derived xenograft (PDX) models were processed for organoid culture establishment. Organoids were histologically and molecularly characterized by cytology and histology, exome sequencing, and RNA-sequencing analysis. Tumorigenicity was assessed through subcutaneous injection of organoids in NOD/SCID mice. Organoids were subjected to drug testing using EGFR, FGFR, and MEK-targeted therapies. RESULTS: We have identified cell culture conditions favoring the establishment of short-term and long-term expansion of NSCLC organoids derived from primary lung patient and PDX tumor tissue. The NSCLC organoids recapitulated the histology of the patient and PDX tumor. They also retained tumorigenicity, as evidenced by cytologic features of malignancy, xenograft formation, preservation of mutations, copy number aberrations, and gene expression profiles between the organoid and matched parental tumor tissue by whole-exome and RNA sequencing. NSCLC organoid models also preserved the sensitivity of the matched parental tumor to targeted therapeutics, and could be used to validate or discover biomarker-drug combinations. CONCLUSIONS: Our panel of NSCLC organoids closely recapitulates the genomics and biology of patient tumors, and is a potential platform for drug testing and biomarker validation.

A community effort to create standards for evaluating tumor subclonal reconstruction.

Tumor DNA sequencing data can be interpreted by computational methods that analyze genomic heterogeneity to infer evolutionary dynamics. A growing number of studies have used these approaches to link cancer evolution with clinical progression and response to therapy. Although the inference of tumor phylogenies is rapidly becoming standard practice in cancer genome analyses, standards for evaluating them are lacking. To address this need, we systematically assess methods for reconstructing tumor subclonality. First, we elucidate the main algorithmic problems in subclonal reconstruction and develop quantitative metrics for evaluating them. Then we simulate realistic tumor genomes that harbor all known clonal and subclonal mutation types and processes. Finally, we benchmark 580 tumor reconstructions, varying tumor read depth, tumor type and somatic variant detection. Our analysis provides a baseline for the establishment of gold-standard methods to analyze tumor heterogeneity.

Cdc48p is required for the cell cycle commitment point at Start via degradation of the G1-CDK inhibitor Far1p.

The budding yeast Cdc48p and its mammalian homologue p97 are involved in many important cellular activities. Because previous cdc48 mutants have exclusive G2/M arrest, Cdc48p was thought to play an essential role only during mitosis. We found that Cdc48p is required for the execution of Start (a yeast cell cycle commitment point equivalent to the restriction point in mammalian cells) in both a normal mitotic cell cycle and cell cycle reentry after mating pheromone withdrawal through degradation of the G1-cyclin-dependent kinase inhibitor Far1p. Our work is the first to uncover novel roles of Cdc48p as a critical cell cycle regulator in G1, and to shed new light on cell cycle regulation of Far1p, which is the first cyclin-dependent kinase inhibitor shown to be a substrate of an essential proteolysis event mediated by Cdc48p.