The empire of cancer: Gene patents and cancer voices

In his book, The Emperor of All Maladies, Siddhartha Mukherjee writes a history of cancer — "It is a chronicle of an ancient disease — once a clandestine, 'whispered-about' illness — that has metamorphosed into a lethal shape-shifting entity imbued with such penetrating metaphorical, medical, scientific, and political potency that cancer is often described as the defining plague of our generation." Increasingly, an important theme in the history of cancer is the role of law, particularly in the field of intellectual property law. It is striking that a number of contemporary policy debates over intellectual property and public health have concerned cancer research, diagnosis, and treatment. In the area of access to essential medicines, there has been much debate over Novartis’ patent application in respect of Glivec, a treatment for leukaemia. India’s Supreme Court held that the Swiss company’s patent application violated a safeguard provision in India’s patent law designed to stop evergreening. In the field of tobacco control, the Australian Government introduced plain packaging for tobacco products in order to address the health burdens associated with the tobacco epidemic. This regime was successfully defended in the High Court of Australia. In the area of intellectual property and biotechnology, there have been significant disputes over the Utah biotechnology company Myriad Genetics and its patents in respect of genetic testing for BRCA1 and BRCA2, which are related to breast cancer and ovarian cancer. The Federal Court of Australia handed down a decision on the validity of Myriad Genetics’ patent in respect of genetic testing for BRCA1 in February 2013. The Supreme Court of the United States heard a challenge to the validity of Myriad Genetics’ patents in this area in April 2013, and handed down a judgment in July 2013. Such disputes have involved tensions between intellectual property rights, and public health. This article focuses upon one of these important test cases involving intellectual property, public health, and cancer research. In June 2010, Cancer Voices Australia and Yvonne D’Arcy brought an action in the Federal Court of Australia against the validity of a BRCA1 patent — held by Myriad Genetics Inc, the Centre de Recherche du Chul, the Cancer Institute of Japan and Genetic Technologies Limited. Yvonne D’Arcy — a Brisbane woman who has had treatment for breast cancer — maintained: "I believe that what they are doing is morally and ethically corrupt and that big companies should not control any parts of the human body." She observed: "For my daughter, I've had her have [sic] mammograms, etc, because of me but I would still like her to be able to have the test to see if the mutation gene is in there from me." The applicants made the following arguments: "Genes and the information represented by human gene sequences are products of nature universally present in each individual, and the information content of a human gene sequence is fixed. Genetic variations or mutations are products of nature. The isolation of the BRCA1 gene mutation from the human body constitutes no more than a medical or scientific discovery of a naturally occurring phenomenon and does not give rise to a patentable invention." The applicants also argued that "the alleged invention is not a patentable invention in that, so far as claimed in claims 1–3, it is not a manner of manufacture within the meaning of s 6 of the Statute of Monopolies". The applicants suggested that "the alleged invention is a mere discovery". Moreover, the applicants contended that "the alleged invention of each of claims 1-3 is not a patentable invention because they are claims for biological processes for the generation of human beings". The applicants, though, later dropped the argument that the patent claims related to biological processes for the generation of human beings. In February 2013, Nicholas J of the Federal Court of Australia considered the case brought by Cancer Voices Australia and Yvonne D’Arcy against Myriad Genetics. The judge presented the issues in the case, as follows: "The issue that arises in this case is of considerable importance. It relates to the patentability of genes, or gene sequences, and the practice of 'gene patenting'. Briefly stated, the issue to be decided is whether under the Patents Act 1990 (Cth) a valid patent may be granted for a claim that covers naturally occurring nucleic acid — either deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) — that has been 'isolated'". In this context, the word "isolated" implies that naturally occurring nucleic acid found in the cells of the human body, whether it be DNA or RNA, has been removed from the cellular environment in which it naturally exists and separated from other cellular components also found there. The genes found in the human body are made of nucleic acid. The particular gene with which the patent in suit is concerned (BRCA1) is a human breast and ovarian cancer disposing gene. Various mutations that may be present in this gene have been linked to various forms of cancer including breast cancer and ovarian cancer.' The judge held in this particular case that Myriad Genetics’ patent claims were a "manner of manufacture" under s 6 of the Statute of Monopolies and s 18(1)(a) of the Patents Act 1990 (Cth). The matter is currently under appeal in the Full Court of the Federal Court of Australia. This article interprets the dispute over Myriad Genetics in light of the scholarly work of Nobel Laureate Professor Joseph Stiglitz on inequality. Such work has significant explanatory power in the context of intellectual property and biotechnology. First, Stiglitz has contended that "societal inequality was a result not just of the laws of economics, but also of how we shape the economy — through politics, including through almost every aspect of our legal system". Stiglitz is concerned that "our intellectual property regime … contributes needlessly to the gravest form of inequality." He maintains: "The right to life should not be contingent on the ability to pay." Second, Stiglitz worries that "some of the most iniquitous aspects of inequality creation within our economic system are a result of 'rent-seeking': profits, and inequality, generated by manipulating social or political conditions to get a larger share of the economic pie, rather than increasing the size of that pie". He observes that "the most iniquitous aspect of this wealth appropriation arises when the wealth that goes to the top comes at the expense of the bottom." Third, Stiglitz comments: "When the legal regime governing intellectual property rights is designed poorly, it facilitates rent-seeking" and "the result is that there is actually less innovation and more inequality." He is concerned that intellectual property regimes "create monopoly rents that impede access to health both create inequality and hamper growth more generally." Finally, Stiglitz has recommended: "Government-financed research, foundations, and the prize system … are alternatives, with major advantages, and without the inequality-increasing disadvantages of the current intellectual property rights system.’" This article provides a critical analysis of the Australian litigation and debate surrounding Myriad Genetics’ patents in respect of genetic testing for BRCA1. First, it considers the ruling of Nicholas J in the Federal Court of Australia that Myriad Genetics’ patent was a manner of manufacture as it related to an artificially created state of affairs, and not mere products of nature. Second, it examines the policy debate over gene patents in Australia, and its relevance to the litigation involving Myriad Genetics. Third, it examines comparative law, and contrasts the ruling by Nicholas J in the Federal Court of Australia with developments in the United States, Canada, and the European Union. Fourth, this piece considers the reaction to the decision of Nicholas at first instance in Australia. Fifth, the article assesses the prospects of an appeal to the Full Federal Court of Australia over the Myriad Genetics’ patents. Finally, this article observes that, whatever happens in respect of litigation against Myriad Genetics, there remains controversy over Genetic Technologies Limited. The Melbourne firm has been aggressively licensing and enforcing its related patents on non-coding DNA and genomic mapping.

23andMe Inc.: Patent law and lifestyle genetics

The venture, 23andMe Inc., raises a host of issues in respect of patent law, policy, and practice in respect of lifestyle genetics and personalised medicine. The company observes: ‘We recognize that the availability of personal genetic information raises important issues at the nexus of ethics, law, and public policy’. 23andMe Inc. has tested the boundaries of patent law, with its patent applications, which cut across information technology, medicine, and biotechnology. The company’s research raises fundamental issues about patentability, especially in light of the litigation in Bilski v. Kappos, Mayo Collaborative Services v. Prometheus Laboratories Inc. and Association for Molecular Pathology v. United States Patent and Trademark Office and Myriad Genetics Inc. There has been much debate and controversy over 23andMe Inc. filing patent applications – particularly in respect of its granted patent on ‘Polymorphisms associated with Parkinson’s Disease’. The direct-to-consumer marketing of genetic testing by 23andMe Inc. has also raised important questions of bioethics and human rights. It is queried whether the terms of service for 23andMe Inc. provide adequate recognition of the concepts of informed consent and benefit-sharing, especially in light of litigation in this area in the United States. Given the patent thickets surrounding genetic testing, the case study of 23andMe Inc. also highlights questions about patent infringement and patent exceptions. The future reform of patent law, policy, and practice needs to take into account new developments in lifestyle genetics and personalised medicine – as exemplified by 23andMe Inc.

The genographic project: Traditional knowledge and population genetics

This article considers the debate over patent law, informed consent, and benefit-sharing in the context of biomedical research in respect of Indigenous communities. In particular, it focuses upon three key controversies over large-scale biology projects, involving Indigenous populations. These case studies are representative of the tensions between research organisations, Indigenous communities, and funding agencies. Section two considers the aims and origins of the Human Genome Diversity Project, and criticisms levelled against the venture by Indigenous peak bodies and anti-biotechnology groups, such as the Rural Advancement Foundation International. It examines the ways in which the United Nations Educational, Scientific, and Cultural Organization (UNESCO) grappled with questions of patent law, informed consent, and benefit sharing in relation to population genetics. Section three focuses upon the ongoing litigation in Tilousi v. Arizona State University, and the Havasupai Tribe v. Arizona State University. In this matter, the Havasupai tribe from the Grand Canyon in the United States brought legal action against the Arizona State University and its researchers for using genetic data for unauthorised purposes - namely, genetic research into schizophrenia, migration, and inbreeding. The litigation raises questions about informed consent, negligence, and larger matters of human rights. Section four explores the legal and ethical issues raised by the Genographic Project. It considers the aims and objectives of the venture, and the criticisms levelled against it by Indigenous communities, and anti-biotechnology groups. It examines the response of the United Nations Permanent Forum on Indigenous Issues to the Genographic Project. It charts the debate over the protection of traditional knowledge in various international fora. The conclusion recommends a number of measures to better regulate large-scale biology projects involving the participation of Indigenous communities.

Mapping the regional influence of genetics on brain structure variability - A Tensor-Based Morphometry study

Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.

Brain fiber architecture, genetics, and intelligence: a high angular resolution diffusion imaging (HARDI) study

We developed an analysis pipeline enabling population studies of HARDI data, and applied it to map genetic influences on fiber architecture in 90 twin subjects. We applied tensor-driven 3D fluid registration to HARDI, resampling the spherical fiber orientation distribution functions (ODFs) in appropriate Riemannian manifolds, after ODF regularization and sharpening. Fitting structural equation models (SEM) from quantitative genetics, we evaluated genetic influences on the Jensen-Shannon divergence (JSD), a novel measure of fiber spatial coherence, and on the generalized fiber anisotropy (GFA) a measure of fiber integrity. With random-effects regression, we mapped regions where diffusion profiles were highly correlated with subjects' intelligence quotient (IQ). Fiber complexity was predominantly under genetic control, and higher in more highly anisotropic regions; the proportion of genetic versus environmental control varied spatially. Our methods show promise for discovering genes affecting fiber connectivity in the brain.

Genetics of brain fiber architecture and intellectual performance

The study is the first to analyze genetic and environmental factors that affect brain fiber architecture and its genetic linkage with cognitive function. We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4 Tesla), in 92 identical and fraternal twins. White matter integrity, quantified using fractional anisotropy (FA), was used to fit structural equation models (SEM) at each point in the brain, generating three-dimensional maps of heritability. We visualized the anatomical profile of correlations between white matter integrity and full-scale, verbal, and performance intelligence quotients (FIQ, VIQ, and PIQ). White matter integrity (FA) was under strong genetic control and was highly heritable in bilateral frontal (a 2 = 0.55, p = 0.04, left; a 2 = 0.74, p = 0.006, right), bilateral parietal (a 2 = 0.85, p < 0.001, left; a 2 = 0.84, p < 0.001, right), and left occipital (a 2 = 0.76, p = 0.003) lobes, and was correlated with FIQ and PIQ in the cingulum, optic radiations, superior fronto- occipital fasciculus, internal capsule, callosal isthmus, and the corona radiata (p = 0.04 for FIQ and p = 0.01 for PIQ, corrected for multiple comparisons). In a cross-trait mapping approach, common genetic factors mediated the correlation between IQ and white matter integrity, suggesting a common physiological mechanism for both, and common genetic determination. These genetic brain maps reveal heritable aspects of white matter integrity and should expedite the discovery of single-nucleotide polymorphisms affecting fiber connectivity and cognition.

Genetics of white matter development: A DTI study of 705 twins and their siblings aged 12 to 29

White matter microstructure is under strong genetic control, yet it is largely unknown how genetic influences change from childhood into adulthood. In one of the largest brain mapping studies ever performed, we determined whether the genetic control over white matter architecture depends on age, sex, socioeconomic status (SES), and intelligence quotient (IQ). We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4-Tesla), in 705 twins and their siblings (age range 12-29; 290. M/415. F). White matter integrity was quantified using a widely accepted measure, fractional anisotropy (FA). We fitted gene-environment interaction models pointwise, to visualize brain regions where age, sex, SES and IQ modulate heritability of fiber integrity. We hypothesized that environmental factors would start to outweigh genetic factors during late childhood and adolescence. Genetic influences were greater in adolescence versus adulthood, and greater in males than in females. Socioeconomic status significantly interacted with genes that affect fiber integrity: heritability was higher in those with higher SES. In people with above-average IQ, genetic factors explained over 80% of the observed FA variability in the thalamus, genu, posterior internal capsule, and superior corona radiata. In those with below-average IQ, however, only around 40% FA variability in the same regions was attributable to genetic factors. Genes affect fiber integrity, but their effects vary with age, sex, SES and IQ. Gene-environment interactions are vital to consider in the search for specific genetic polymorphisms that affect brain integrity and connectivity.

Meeting the challenges of neuroimaging genetics

As research encompassing neuroimaging and genetics gains momentum, extraordinary information will be uncovered on the genetic architecture of the human brain. However, there are significant challenges to be addressed first. Not the least of these challenges is to accomplish the sample size necessary to detect subtle genetic influences on the morphometry and function of the healthy brain. Aside from sample size, image acquisition and analysis methods need to be refined in order to ensure optimum sensitivity to genetic and complementary environmental influences. Then there is the vexing issue of interpreting the resulting data. We describe how researchers from the east coast of Australia and the west coast of America have embarked upon a collaboration to meet these challenges using data currently being collected from a large-scale twin study, and offer some opinions about future directions in the field.

Reducing structural variation to determine the genetics of white matter integrity across hemispheres - a dti study of 100 twins

Studies of cerebral asymmetry can open doors to understanding the functional specialization of each brain hemisphere, and how this is altered in disease. Here we examined hemispheric asymmetries in fiber architecture using diffusion tensor imaging (DTI) in 100 subjects, using high-dimensional fluid warping to disentangle shape differences from measures sensitive to myelination. Confounding effects of purely structural asymmetries were reduced by using co-registered structural images to fluidly warp 3D maps of fiber characteristics (fractional and geodesic anisotropy) to a structurally symmetric minimal deformation template (MDT). We performed a quantitative genetic analysis on 100 subjects to determine whether the sources of the remaining signal asymmetries were primarily genetic or environmental. A twin design was used to identify the heritable features of fiber asymmetry in various regions of interest, to further assist in the discovery of genes influencing brain micro-architecture and brain lateralization. Genetic influences and left/right asymmetries were detected in the fiber architecture of the frontal lobes, with minor differences depending on the choice of registration template.

Genetics of anisotropy asymmetry: Registration and sample size effects

Brain asymmetry has been a topic of interest for neuroscientists for many years. The advent of diffusion tensor imaging (DTI) allows researchers to extend the study of asymmetry to a microscopic scale by examining fiber integrity differences across hemispheres rather than the macroscopic differences in shape or structure volumes. Even so, the power to detect these microarchitectural differences depends on the sample size and how the brain images are registered and how many subjects are studied. We fluidly registered 4 Tesla DTI scans from 180 healthy adult twins (45 identical and fraternal pairs) to a geometrically-centered population mean template. We computed voxelwise maps of significant asymmetries (left/right hemisphere differences) for common fiber anisotropy indices (FA, GA). Quantitative genetic models revealed that 47-62% of the variance in asymmetry was due to genetic differences in the population. We studied how these heritability estimates varied with the type of registration target (T1- or T2-weighted) and with sample size. All methods consistently found that genetic factors strongly determined the lateralization of fiber anisotropy, facilitating the quest for specific genes that might influence brain asymmetry and fiber integrity.

Genetics of path lengths in brain connectivity networks: HARDI-based maps in 457 adults

Brain connectivity analyses are increasingly popular for investigating organization. Many connectivity measures including path lengths are generally defined as the number of nodes traversed to connect a node in a graph to the others. Despite its name, path length is purely topological, and does not take into account the physical length of the connections. The distance of the trajectory may also be highly relevant, but is typically overlooked in connectivity analyses. Here we combined genotyping, anatomical MRI and HARDI to understand how our genes influence the cortical connections, using whole-brain tractography. We defined a new measure, based on Dijkstra's algorithm, to compute path lengths for tracts connecting pairs of cortical regions. We compiled these measures into matrices where elements represent the physical distance traveled along tracts. We then analyzed a large cohort of healthy twins and show that our path length measure is reliable, heritable, and influenced even in young adults by the Alzheimer's risk gene, CLU.

Labeling white matter tracts in hardi by fusing multiple tract atlases with applications to genetics

Accurate identification of white matter structures and segmentation of fibers into tracts is important in neuroimaging and has many potential applications. Even so, it is not trivial because whole brain tractography generates hundreds of thousands of streamlines that include many false positive fibers. We developed and tested an automatic tract labeling algorithm to segment anatomically meaningful tracts from diffusion weighted images. Our multi-atlas method incorporates information from multiple hand-labeled fiber tract atlases. In validations, we showed that the method outperformed the standard ROI-based labeling using a deformable, parcellated atlas. Finally, we show a high-throughput application of the method to genetic population studies. We use the sub-voxel diffusion information from fibers in the clustered tracts based on 105-gradient HARDI scans of 86 young normal twins. The whole workflow shows promise for larger population studies in the future.

Automatic clustering of white matter fibers in brain diffusion mri with an application to genetics

To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion - a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.

The multivariate A/C/E model and the genetics of fiber architecture

We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 monozygotic (MZ) twins and 25 dizygotic (DZ) twin pairs (100 subjects total). First, the structural and DT scans were linearly co-registered. Structural MR scans were nonlinearly mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. After tensor re-orientation to realign them to the anatomy, we computed several scalar and multivariate DT-derived measures including the geodesic anisotropy (GA), the tensor eigenvalues and the full diffusion tensors. A covariance-weighted distance was measured between twins in the Log-Euclidean framework [2], and used as input to a maximum-likelihood based algorithm to compute the contributions from genetics (A), common environmental factors (C) and unique environmental ones (E) to fiber architecture. Quanititative genetic studies can take advantage of the full information in the diffusion tensor, using covariance weighted distances and statistics on the tensor manifold.

Neuroimaging and genetics: Exploring, searching, and finding

This issue on the genetics of brain imaging phenotypes is a celebration of the happy marriage between two of science's highly interesting fields: neuroscience and genetics. The articles collected here are ample evidence that a good deal of synergy exists in this marriage. A wide selection of papers is presented that provide many different perspectives on how genes cause variation in brain structure and function, which in turn influence behavioral phenotypes (including psychopathology). They are examples of the many different methodologies in contemporary genetics and neuroscience research. Genetic methodology includes genome-wide association (GWA), candidate-gene association, and twin studies. Sources of data on brain phenotypes include cortical gray matter (GM) structural/volumetric measures from magnetic resonance imaging (MRI); white matter (WM) measures from diffusion tensor imaging (DTI), such as fractional anisotropy; functional- (activity-) based measures from electroencephalography (EEG), and functional MRI (fMRI). Together, they reflect a combination of scientific fields that have seen great technological advances, whether it is the single-nucleotide polymorphism (SNP) array in genetics, the increasingly high-resolution MRI imaging, or high angular resolution diffusion imaging technique for measuring WM connective properties.