This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.

https://acsjournals.onlinelibrary.wiley.com/doi/pdf/10.3322/caac.21660

Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries.

Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS—the 1000 Genome pilot alone includes nearly five terabases—make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.

/pdf/the-genome-analysis-toolkit-a-mapreduce-framework-for-4aygfa9b66.pdf

The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data

Summary: Research over the last few years has revealed significant haplotype structure in the human genome. The characterization of these patterns, particularly in the context of medical genetic association studies, is becoming a routine research activity. Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface.

Availability: http://www.broad.mit.edu/mpg/haploview/

Contact: jcbarret@broad.mit.edu

/pdf/haploview-analysis-and-visualization-of-ld-and-haplotype-1p9iyir38a.pdf

Haploview: analysis and visualization of LD and haplotype maps

Motivation: DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly implemented methods allow for: (i) analyses on multiple data files; (ii) haplotype phasing; (iii) analyses on insertion/deletion polymorphism data; (iv) visualizing sliding window results integrated with available genome annotations in the UCSC browser.

Availability: Freely available to academic users from: http://www.ub.edu/dnasp

Contact: [email protected]

DnaSP v5

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

https://cdr.lib.unc.edu/downloads/v692t8920

A global reference for human genetic variation.

In 2009, Time Magazine identified biobanks as one of the ten ideas changing the world. Today, with many of these infrastructures gradually achieving their recruitment objectives, current initiatives are focusing on the orderly translation of research knowledge into beneficial clinical applications. Indeed, whether it is through international collaboration aimed at increasing statistical power, or broader access to comprehensive data meant to better understand the role of human genomic variation in “complex disease aetiology and treatment”, biobank researchers wish to realize the full benefits for which participants have provided their data and samples. This Special Issue “From Biobanks to the Clinic” examines the ways in which biobanks are facilitating this translation. Although the aggregation of health-related data has become a pressing need in these projects, the collection and use of large quantities of health information create challenges for patient privacy. The authors highlight some of these challenges, including the problem of specific informed consent procedures. They explain that genomics should also focus on the benefits for society as a whole. In order to improve researcher–patient relationships, researchers could consider patients as partners, and acknowledge them as valuable contributors to genetic research. In this way, the authors hope that biobanks will foster translational practices, while protecting individual rights.

Special Issue - From Biobanks to the Clinic

Purpose: This article proposes recommendations for the use of whole-genome and whole-exome (WGS/WES) sequencing in clinical practice, endorsed by the board of directors of the Canadian College of Medical Geneticists. The publication of statements and recommendations by several international and national organisations on clinical WGS/WES has prompted a need for Canadian specific guidance.Methods: A multi-disciplinary group consisting of lawyers, ethicists, genetic researchers, and clinical geneticists was assembled to review existing guidelines on WGS/WES and identify provisions relevant to the Canadian context.Results: Definitions were provided to orient the recommendations and to minimize confusion with other recommendations. Recommendations include the following: WGS/WES should be used in a judicious and cost-efficient manner; WGS/WES should be used to answer a clinical question; and physicians need to explain to adult patients the nature of the results that could arise, so as to allow them to make informed choices over whether to take the test and which results they wish to receive. Recommendations are also provided for WGS/WES in the pediatric context, and for when results implicate patients’ family members.Conclusion: These recommendations are only a proposal to be developed into comprehensive Canadian based guidelines. They aim to promote discussion about the reporting of WGS/WES results, and to encourage the ethical implementation of these new technologies in the clinical setting.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2634533_code1784114.pdf?abstractid=2634533&mirid=1&type=2

Reporting Results from Whole-Genome and Whole-Exome Sequencing in Clinical Practice: A Proposal for Canada?

Humanity across International Law and Biolaw: The concept of humanity and biogenetics

Data sharing is key to advancing our understanding of human health and well-being. While issues related to pediatric research warrant strong ethical protections, overly protectionist policies may serve to exclude minors from data sharing initiatives. Pediatric data sharing is critical to scientific research concerning health and well-being, to say nothing of understanding human development generally. For example, large-scale pediatric longitudinal studies, such as those in the DREAM-BIG Consortium, on the influence of prenatal adversity factors on child psychopathology, will provide prevention data and generate future health benefits. Recent initiatives have formulated sound policy to help enable and foster data sharing practices for pediatric research. To help translate these policy initiatives into practice, we discuss how model consent clauses for pediatric research can help address some of the issues and challenges of pediatric data sharing, while enabling data sharing.

/pdf/sharing-and-safeguarding-pediatric-data-3k6f5gy3.pdf

Sharing and Safeguarding Pediatric Data

This article posits that collaborative models of technology transfer could be considered for their remarkable ability to maintain or increase the pace and quality of scientific development in stem cell research rather than for their potential to fix problems that do not empirically exist. In light of this scientific field’s logistical constraints and its current stage of development, the open model appears to be a particularly suitable collaborative method of technology management for stem cell research.

https://revistas.ufpr.br/direito/article/download/15737/10443

Bartha Maria Knoppers

Papers

Special Issue - From Biobanks to the Clinic

Reporting Results from Whole-Genome and Whole-Exome Sequencing in Clinical Practice: A Proposal for Canada?

Humanity across International Law and Biolaw: The concept of humanity and biogenetics

Sharing and Safeguarding Pediatric Data

Descendo a toca do coelho: transferência de tecnologia no campo da pesquisa em células-tronco