High-quality genome assemblies are crucial to many biological studies, and utilizing long sequencing reads can help achieve higher assembly contiguity. While long reads can resolve complex and repetitive regions of a genome, their relatively high associated error rates are still a major limitation. Long reads generally produce draft genome assemblies with lower base quality, which must be corrected with a genome polishing step. Hybrid genome polishing solutions can greatly improve the quality of long-read genome assemblies by utilizing more accurate short reads to validate bases and correct errors. Currently available hybrid polishing methods rely on read alignments, and are therefore memory-intensive and do not scale well to large genomes. Here we describe ntEdit+Sealer, an alignment-free, k-mer-based genome finishing protocol that employs memory-efficient Bloom filters. The protocol includes ntEdit for correcting base errors and small indels, and for marking potentially problematic regions, then Sealer for filling both assembly gaps and problematic regions flagged by ntEdit. ntEdit+Sealer produces highly accurate, error-corrected genome assemblies, and is available as a Makefile pipeline from https://github.com/bcgsc/ntedit_sealer_protocol. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Automated long-read genome finishing with short reads Support Protocol: Selecting optimal values for k-mer lengths (k) and Bloom filter size (b).
Background: Structural aspects of health care systems, such as limited access to specialized surgical and perioperative care, can negatively affect the outcomes and resource use of patients undergoing elective and emergency surgical procedures. The aim of this study was to compare postoperative outcomes of Nunavut Inuit and non-Inuit patients at a Canadian quaternary care centre.
Methods: We conducted a retrospective cohort study involving adult (age ≥ 18 yr) patients undergoing inpatient surgery from 2011 to 2018 at The Ottawa Hospital, the quaternary referral hospital for the Qikiqtaaluk Region of Nunavut. The study was designed and conducted in collaboration with Nunavut Tunngavik Incorporated. The primary outcome was a composite of in-hospital death or complications.Secondary outcomes included postoperative length of stay in hospital, adverse discharge disposition, readmissions within 30 days and total hospitalization costs.
Results: A total of 98 701 episodes of inpatient surgical care occurred among patients aged 18 to 104 years; 928 (0.9%) of these involved Nunavut Inuit, and 97 773 involved non-Inuit patients. Death or postoperative complication occurred more often among Nunavut Inuit than non-Inuit patients (159 [17.2%] v. 15 691 [16.1%]), which was significantly different after adjustment for age, sex, surgical specialty, risk and urgency (odds ratio [OR] 1.25, 95% confidence interval [CI] 1.03-1.51). This association was most pronounced in cases of cancer (OR 1.63, 95% CI 1.03-2.58) and elective surgery (OR 1.58, 95% CI 1.20-2.10). Adjusted rates of readmission, adverse discharge disposition, length of stay and total costs were significantly higher for Nunavut Inuit.
Interpretation: Nunavut Inuit had a 25% relative increase in their odds of morbidity and death after surgery at a major quaternary care hospital in Canada compared with non-Inuit patients, while also having higher rates of other adverse outcomes and resource use. An examination of perioperative systems involving patients, Inuit leadership, health care providers and governments is required to address these differences in health outcomes.
GABARAPL2 was initially characterized for its involvement in protein transport and membrane fusion events, but has since gained notoriety for its role in autophagy. GABARAPL2 is frequently studied alongside its GABARAP subfamily members, GABARAP and GABARAPL1. Although functional redundancy exists among the subfamily members, a complex network of molecular interactions, physiological processes and pathologies can be primarily related to GABARAPL2. GABARAPL2 has a multifaceted role, ranging from cellular differentiation to intracellular degradation. Much of what we know about GABARAPL2 is gained through identifying its interacting partners-a list that is constantly growing. In this article, we review both the autophagy-dependent and autophagy-independent roles of GABARAPL2, and emphasize their implications for both health and disease.
Formalin fixation of paraffin-embedded tissue samples is a well-established method for preserving tissue and is routinely used in clinical settings. Although formalin-fixed, paraffin-embedded (FFPE) tissues are deemed crucial for research and clinical applications, the fixation process results in molecular damage to nucleic acids, thus confounding their use in genome sequence analysis. Methods to improve genomic data quality from FFPE tissues have emerged, but there remains significant room for improvement. Here, we use whole-genome sequencing (WGS) data from matched Fresh Frozen (FF) and FFPE tissue samples to optimize a sensitive and precise FFPE single nucleotide variant (SNV) calling approach. We present methods to reduce the prevalence of false-positive SNVs by applying combinatorial techniques to five publicly available variant callers. We also introduce FFPolish, a novel variant classification method that efficiently classifies FFPE-specific false-positive variants. Our combinatorial and statistical techniques improve precision and F1 scores compared to the results of publicly available tools when tested individually.
Chronic inflammation with aging ("inflammaging") plays a prominent role in the pathogenesis of myeloid malignancies. Aberrant inflammatory activity impacts many different cells in the marrow, including normal blood and stromal marrow elements and leukemic cells, in unique and distinct ways. Inflammation can promote selective clonal expansion through differential immune-mediated suppression of normal hematopoietic cells and malignant clones. We review these complex roles, how they can be understood by separating cell-intrinsic from extrinsic effects, and how this informs future clinical trials.
Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10-8 as genome-wide significant, and p-values < 1 × 10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10-7), which showed genome-wide significant interaction (p-value = 3.8 × 10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.
Background: We explored health professionals' views on the utility of circulating tumor DNA (ctDNA) testing in hereditary cancer syndrome (HCS) management.
Materials and methods: A qualitative interpretive description study was conducted, using semi-structured interviews with professionals across Canada. Thematic analysis employing constant comparison was used for analysis. 2 investigators coded each transcript. Differences were reconciled through discussion and the codebook was modified as new codes and themes emerged from the data.
Results: Thirty-five professionals participated and included genetic counselors (n = 12), geneticists (n = 9), oncologists (n = 4), family doctors (n = 3), lab directors and scientists (n = 3), a health-system decision maker, a surgeon, a pathologist, and a nurse. Professionals described ctDNA as "transformative" and a "game-changer". However, they were divided on its use in HCS management, with some being optimistic (optimists) while others were hesitant (pessimists). Differences were driven by views on 3 factors: (1) clinical utility, (2) ctDNA's role in cancer screening, and (3) ctDNA's invasiveness. Optimists anticipated ctDNA testing would have clinical utility for HCS patients, its role would be akin to a diagnostic test and would be less invasive than standard screening (eg imaging). Pessimistic participants felt ctDNA testing would add limited utility; it would effectively be another screening test in the pathway, likely triggering additional investigations downstream, thereby increasing invasiveness.
Conclusions: Providers anticipated ctDNA testing will transform early cancer detection for HCS families. However, the contrasting positions on ctDNA's role in the care pathway raise potential practice variations, highlighting a need to develop evidence to support clinical implementation and guidelines to standardize adoption.
Purpose: Pulmonary involvement is rare in metastatic hormone-sensitive prostate cancer (mHSPC) that recurs after treatment for localized disease. Guidelines recommend intensive systemic therapy, similar to patients with liver metastases, but some lung-recurrent mHSPC may have good outcomes. Genomic features of lung metastases may clarify disease aggression, but are poorly understood since lung biopsy is rarely performed. We present a comparative assessment of genomic drivers and heterogeneity in metachronous prostate tumors and lung metastases.
Methods: We leveraged a prospective functional imaging study of 208 biochemically recurrent prostate cancers to identify 10 patients with lung-recurrent mHSPC. Histologic diagnosis was attained via thoracic surgery or fine-needle lung biopsy. We retrieved clinical data and performed multiregion sampling of primary tumors and metastases. Targeted and/or whole-exome sequencing was applied to 46 primary and 32 metastatic foci.
Results: Unusually for mHSPC, all patients remained alive despite a median follow-up of 11.5 years. Several patients experienced long-term freedom from systemic treatment. The genomic landscape of lung-recurrent mHSPC was typical of curable prostate cancer with frequent PTEN, SPOP, and chromosome 8p alterations, and there were no deleterious TP53 and DNA damage repair gene mutations that characterize aggressive prostate cancer. Despite a long median time to recurrence (76.8 months), copy number alterations and clonal mutations were highly conserved between metastatic and primary foci, consistent with intrapatient homogeneity and limited genomic evolution.
Conclusion: In this retrospective hypothesis-generating study, we observed indolent genomic etiology in selected lung-recurrent mHSPC, cautioning against grouping these patients together with liver or bone-predominant mHSPC. Although our data do not generalize to all patients with lung metastases, the results encourage prospective efforts to stratify lung-recurrent mHSPC by genomic features.
Survival analysis is a technique for identifying prognostic biomarkers and genetic vulnerabilities in cancer studies. Large-scale consortium-based projects have profiled >11 000 adult and >4000 pediatric tumor cases with clinical outcomes and multiomics approaches. This provides a resource for investigating molecular-level cancer etiologies using clinical correlations. Although cancers often arise from multiple genetic vulnerabilities and have deregulated gene sets (GSs), existing survival analysis protocols can report only on individual genes. Additionally, there is no systematic method to connect clinical outcomes with experimental (cell line) data. To address these gaps, we developed cSurvival (https://tau.cmmt.ubc.ca/cSurvival). cSurvival provides a user-adjustable analytical pipeline with a curated, integrated database and offers three main advances: (i) joint analysis with two genomic predictors to identify interacting biomarkers, including new algorithms to identify optimal cutoffs for two continuous predictors; (ii) survival analysis not only at the gene, but also the GS level; and (iii) integration of clinical and experimental cell line studies to generate synergistic biological insights. To demonstrate these advances, we report three case studies. We confirmed findings of autophagy-dependent survival in colorectal cancers and of synergistic negative effects between high expression of SLC7A11 and SLC2A1 on outcomes in several cancers. We further used cSurvival to identify high expression of the Nrf2-antioxidant response element pathway as a main indicator for lung cancer prognosis and for cellular resistance to oxidative stress-inducing drugs. Altogether, these analyses demonstrate cSurvival's ability to support biomarker prognosis and interaction analysis via gene- and GS-level approaches and to integrate clinical and experimental biomedical studies.