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.

Consistent with her previous position promoting a private policy model for genetic testing as a more appropriate response to bioethical and biopolicy issues (1992), Andrea Bonnicksen (1994) advocates developing national policies before international approaches with respect to pre-implantation diagnosis (PD) and pre-implantation therapy (PT?or human germ-line gene therapy). The argument is that even on a national level, biopolicy is "often elusive,*' "unwise," and "codifies answers'* (Bonnicksen, 1992:53, 61). National policies, then, should serve as

Genetic choices: a paradigm for prospective international ethics?

A deluge of genetic and health-related data is being generated about patients with dementia. International sharing of these data accelerates dementia research. Seeking consent to data sharing is a challenge for dementia research where patients have lost or risk losing legal capacity. The laws of most countries enable substitute decision makers (SDMs) to consent on behalf of incapable adults to research participation. We compare regulatory frameworks governing capacity, research, and personal data protection across eight countries to determine when SDMs can consent to data sharing. In most countries, an SDM can consent to data sharing in the incapable adult's best interests. Best interests typically include consideration of the individual's previously expressed wishes, values and beliefs; well-being; and inclusion in decision making. Countries differ in how these considerations are balanced. A clear previous consent or refusal to share data typically binds the discretion of an SDM. Though generally permissive, National patchworks of laws and guidelines cause confusion. Clarity on the applicable law and processes to enhance ethical decision making are needed to facilitate substitute consent. Researchers can encourage patients to communicate their research preferences before a loss of capacity, and educate SDMs about their ethical and legal duties. The research community must also continue to promote the importance of data sharing in dementia.

/pdf/substitute-consent-to-data-sharing-a-way-forward-for-52d65hg2rt.pdf

Substitute consent to data sharing: a way forward for international dementia research?

There is a noticeable lack of international regulation on personal data exchange and management in research. This artcle sheds lights in this area by describing how the International Cancer Genome Consortium is developing policies and procedures to address the ethical and legal issues raised by the international transfer of data and results. These policies and procedures aim, first and most
importantly, to safeguard the interests of the research participants and other
involved stakeholders and, secondly, to facilitate the sharing of data and results
to realize greater benefits from this kind of internationally collaborative genetic research.

Legal aspects of genetic databases for international biomedical research: the example of the International Cancer Genome Consortium (ICGC)

Biomedical research post sequencing of the first human genome is increasingly eroding a traditional ecology of individualist science. It is, furthermore, normalising collective innovation and shared scientific discovery.1 ,2 Achieving sound statistical power in a genome-wide association study, for example, can often be well beyond the scope of any one researcher's capacity. For this reason and others, the scientific imperative of research collaboration can be more pronounced in the ‘omics’ disciplines,3 where millions of data points are needed to make global inferences about links between the human genome and disease.4 From the scientific necessity to adequately power a study through research collaborations is also born an ethical imperative to do so. That is, the anticipated benefits and harms of a particular study are justified based on the researchers’ sound predictions about potential outcomes and contributions to knowledge. Either underestimating or overestimating translational possibilities can disturb the benefit–harm balance due largely to insufficient statistical power.5

Two important milestones, therefore, rest on this bench-to-bedside continuum for ‘omics’ research, and are essential for any clinical translation endeavour: research ethics and data-access reviews. The former ensures appropriate ongoing ethical oversight and participant protections, while the latter enables research collaboration by providing researchers with access to data. Debates surrounding traditional issues facing such reviews are ubiquitous in the literature, yet little attention has been paid to how these issues are exacerbated when studies span across multiple jurisdictions. This is particularly true for research typified in the ‘omics’ disciplines, where international collaboration is the norm rather than the exception.

Here, a distinction between multi-site and multi-jurisdictional research should be emphasised. While multi-site research implies that the project takes place across many individual sites, multi-jurisdictional research involves sites in different legal jurisdictions. Multi-jurisdictional research along with the ethics review processes required to …

https://jmg.bmj.com/content/jmedgenet/52/8/566.full.pdf

Bartha Maria Knoppers

Papers

Genetic choices: a paradigm for prospective international ethics?

Substitute consent to data sharing: a way forward for international dementia research?

Legal aspects of genetic databases for international biomedical research: the example of the International Cancer Genome Consortium (ICGC)

Streamlining review of research involving humans: Canadian models

Genetic predisposition to cancer--issues to consider.