Community perspectives on the return of research results and ownership of data and specimens for brain tumor genomic research

BACKGROUND Return of research results and ownership of data and biospecimens are ethically complex issues in genomic research. This study explored perspectives on ROR and data/specimen ownership among individuals affected by low-grade glioma (LGG) and other community representatives. METHODS In 2022, we conducted 11 community-engaged facilitated discussions using three platforms: a Research Advisory Council (RAC), Twitter (now X), and a private LGG Facebook group. Participants included individuals with brain cancer (including LGG), care partners, clinicians, researchers, and regulatory experts. Discussions focused on strategies for enhancing trust and participation in brain cancer genomic research and were guided by ethical principles—autonomy, ownership, privacy, and relevance. Transcripts were analyzed using qualitative content analysis. RESULTS 352 unique participants contributed to discussions. Across platforms, participants perceived continued ownership over their data and biospecimens and emphasized a strong expectation of reciprocity: contributing data and biospecimens should be met with access to both individual and aggregate research findings. Individuals with LGG viewed return of individual and overall research results as a means of maintaining autonomy; they saw individual results as highly relevant for making informed medical decisions, even when results lacked clinical validation. Trust in researchers to protect privacy was high. While researchers and clinicians also acknowledged the value of returning results, they expressed concerns about returning results prematurely, especially when clinical significance was unknown. CONCLUSIONS As part of an ethical research partnership, participants in LGG genomic research have an expectation of reciprocity: in return for sharing their health information and biospecimens, they expect access to both individual and research results. Despite limitations in clinical validity and contradictory policy, return of results is seen as empowering, personally relevant, and a way of recognizing participants’ contributions to scientific advancement. Addressing these expectations may enhance trust and participation in genomic research.

BACKGROUND The International Low Grade Glioma (LGG) Registry is a community of people with LGGs who have contributed data and specimens to facilitate genomic research. The Registry aims to discover the roles genetics and the environment play in glioma risk factors and treatment response. To ensure findings apply to a range of diverse populations and settings, it is crucial to build trust and encourage representative participation in the Registry. METHODS Three engagement strategies were used to gather recommendations for improving trust and participation in LGG genomic research. We established a Research Advisory Council (RAC) consisting of 25 members, including people with LGG, care partners, clinicians, researchers, advocates, and genomics and ethics experts. Additionally, we engaged two existing social media communities (the #BTSM community on Twitter, the Oligodendroglioma/LGG Warriors Facebook group) through separate discussions with each group over four months. Topics included: 1) Trust and benefits of genomic research; 2) Registry recruitment; 3) Registry data collection; and 4) Return of results. We used qualitative methods to summarize recommendations. RESULTS Feedback received from community members indicated a willingness to share information with the Registry. Recommendations related to recruitment message content and packaging, communication channels, data security, and conveying the individual- and population-level impacts of genomic research. The Registry’s messages should include clear information about how data and specimens are being used. Both research and individual-level findings should be shared back with participants and the broader community using accessible language, but without being paternalistic or promising cures or “miracles.” CONCLUSIONS Engaging an advisory council and existing social media communities were effective approaches for identifying recommendations for enhancing trust and participation in genomic research. Regular, consistent, transparent communication with participants throughout the research process is key. Future efforts will operationalize and evaluate the impact of these recommendations on equity and representativeness of Registry participants.

Return of research results from genomic biobanks: cost matters

BackgroundGenomic research is challenging the tradition of informed consent. Genomic researchers in the USA, Canada and parts of Europe are encouraged to use informed consent to address the prospect of...

as genetic and genomic research proliferates, debate has ensued about returning results to participants. In addition to consideration of the benefits and harms to participants, researchers must also consider the logistical and financial feasibility of returning research results. However, little data exist of actual researcher practices. we conducted an online survey of 446 corresponding authors of genetic/genomic studies conducted in the United States and published in 2006-2007 to assess the frequency with which they considered, offered to, or actually returned research results, what factors influenced these decisions, and the method of communicating results. the response rate was 24% (105/446). Fifty-four percent of respondents considered the issue of returning research results to participants, 28% offered to return individual research results, and 24% actually returned individual research results. Of those who considered the issue of returning research results during the study planning phase, the most common factors considered were whether research results were deemed clinically useful (18%) and respect for participants (13%). Researchers who had a medical degree and conducted studies on children were significantly more likely to offer to return or actually return individual results compared to those with a Ph.D. only. we speculate that issues associated with clinical validity and respect for participants dominated concerns of time and expense given the prominent and continuing ethical debates surrounding genetics and genomics research. The substantial number of researchers who did not consider returning research results suggests that researchers and institutional review boards need to devote more attention to a topic about which research participants are interested.

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The past, present, and future of the debate over return of research results and incidental findings

The return of individual results to research participants has been vigorously debated. Consensus statements indicate that researchers and bioethicists consider the return of research results most appropriate when the findings are clinically relevant. Even when clinical utility is the motivator, however, the return of individual research results is not equivalent to clinical care. There are important differences in the domains of research and medical care, both from a legal standpoint and in terms of the ethical responsibilities of clinicians and researchers. As a corollary, researchers risk promoting a therapeutic misconception if they create quasi‐clinical settings for return of clinically relevant research results. Rather, efforts should be focused on clarity in the provision of research results, appropriate caveats and, most important, appropriate referrals when the results may be helpful to consider in medical care. © 2014 Wiley Periodicals, Inc.

Gliomas are the most common primary tumor of the brain and are classified into grades I-IV of the World Health Organization (WHO), based on their invasively histological appearance. Gliomas grading plays an important role to determine the treatment plan and prognosis prediction. In this study we propose two novel methods for automatic, non-invasively distinguishing low-grade (Grades II and III) glioma (LGG) and high-grade (grade IV) glioma (HGG) on conventional MRI images by using deep convolutional neural networks (CNNs). All MRI images have been preprocessed first by rigid image registration and intensity inhomogeneity correction. Both proposed methods consist of two steps: (a) three-dimensional (3D) brain tumor segmentation based on a modification of the popular U-Net model; (b) tumor classification on segmented brain tumor. In the first method, the slice with largest area of tumor is determined and the state-of-the-art mask R-CNN model is employed for tumor grading. To improve the performance of the grading model, a two-dimensional (2D) data augmentation has been implemented to increase both the amount and the diversity of the training images. In the second method, denoted as 3DConvNet, a 3D volumetric CNNs is applied directly on bounding image regions of segmented tumor for classification, which can fully leverage the 3D spatial contextual information of volumetric image data. The proposed schemes were evaluated on The Cancer Imaging Archive (TCIA) low grade glioma (LGG) data, and the Multimodal Brain Tumor Image Segmentation (BraTS) Benchmark 2018 training datasets with fivefold cross validation. All data are divided into training, validation, and test sets. Based on biopsy-proven ground truth, the performance metrics of sensitivity, specificity, and accuracy are measured on the test sets. The results are 0.935 (sensitivity), 0.972 (specificity), and 0.963 (accuracy) for the 2D Mask R-CNN based method, and 0.947 (sensitivity), 0.968 (specificity), and 0.971 (accuracy) for the 3DConvNet method, respectively. In regard to efficiency, for 3D brain tumor segmentation, the program takes around ten and a half hours for training with 300 epochs on BraTS 2018 dataset and takes only around 50s for testing of a typical image with a size of 160×216×176. For 2D Mask R-CNN based tumor grading, the program takes around 4h for training with around 60000 iterations, and around 1s for testing of a 2D slice image with size of 128×128. For 3DConvNet based tumor grading, the program takes around 2h for training with 10000 iterations, and 0.25s for testing of a 3D cropped image with size of 64×64×64, using a DELL PRECISION Tower T7910, with two NVIDIA Titan Xp GPUs. Two effective glioma grading methods on conventional MRI images using deep convolutional neural networks have been developed. Our methods are fully automated without manual specification of region-of-interests and selection of slices for model training, which are common in traditional machine learning based brain tumor grading methods. This methodology may play a crucial role in selecting effective treatment options and survival predictions without the need for surgical biopsy.

P52a: Multiplex analysis of 27 cytokines produced by low-grade and high-grade glioma cells

The majority of suspected occupational risk factors for adult brain tumours have yet to be confirmed as etiologically relevant. Within an international case-control study on brain tumours, lifelong occupational histories and information on exposures to specific substances were obtained by direct interviews to further investigate occupational risk factors for glioma. This is one of the largest studies of brain tumours in adults, including 1,178 cases and 1987 population controls from 8 collaborating study centres matched for age, gender and centre. All occupational information, was aggregated into 16 occupational categories. In a pooled analysis, odds ratios (OR), adjusted for education, were estimated separately for men and women and for high-grade glioma (HGG) and low-grade glioma (LGG), focusing especially on 6 categories defined a priori: agricultural, chemical, construction, metal, electrical/electronic and transport. For men, an elevated OR of glioma associated with the category "metal" (OR = 1.24, 95% CI 0.96-1.62) was seen, which appeared to be largely accounted for by LGG (OR = 1.59, 95% CI 1.00-2.52). For the other 5 occupational categories, no elevated risks for glioma were observed. For women the only noteworthy observation for the 6 a priori categories was an inverse association with the "agriculture" category (OR = 0.60, 95% CI 0.36-0.99). Apart from the 6 major categories, women working in food production or food processing (category "food") showed an increased OR of 1.95 (95% CI 1.04-3.68). None of the 20 substance groups was positively associated with glioma risk. Although some other point estimates were elevated, they lacked statistical significance. The results do not provide evidence of a strong association between occupational exposures and glioma development.

There are many research biobanks in the world, including a small number in the Middle East. The Saudi biobank, one of the newly established biobanks, has just started to collect data and samples in 2016. A survey was conducted to assess the opinions of stakeholders regarding the return of individual research results. A total of 180 adults from three different groups (researchers, physicians, and laypeople) participated in this cross-sectional study. There was strong agreement among all respondents that the biobank has the duty and donors have the right to be provided with important results that may have direct or indirect benefits. Moreover, there was strong support for the view that donors have the right to refuse to receive any research results. These results are compatible with many other studies and are in line with the governance of the Saudi biobank.

In conducting medical and genetic research an ethical dilemma is faced as to whether individual genetic research results should be disclosed where such results may be relevant to the consideration of an individual’s health and medical care. Japan’s participation in this debate has yielded no consensus on policy as yet but has influenced the establishment of certain national guidelines. Japan established principles in 2000 that emphasized participants’ rights to know their genetic research results, and incorporated this policy into governmental guidelines for genetic/genomic research in 2001, as the stance of in principle. The newly-revised guidelines in 2013 retained the in principle, and added stipulations regarding disclosure giving a greater role to researchers in creating disclosure policies of genetic research results. The process of their revisions was strongly influenced by the Act on the Protection of Personal Information 2003. This article considers the management of clinically significant findings in the context of the revision of the genetic/genomic research guidelines. We argue that the governmental guidelines based on the Act have the potential to give rise to practical and ethical challenges, which suggest the clear need for additional mechanisms for governing disclosure decisions. This method includes that the revised Guidelines can be interpreted to permit genomics researchers to adopt more active research disclosure policies with more participant-focused ethical consideration. This is consistent with researchers’ ethical responsibilities to carefully consider the rights and interests of research participants to ensure the public’s trust and confidence in research is maintained. The Japanese experience has implications for the international debate, as there is, as yet no clear and agreed guidance for researchers determining policies on the return of research results in other countries.

Return of Research Results from Pharmacogenomic Versus Disease Susceptibility Studies: What‘s Drugs got to do with it?

Understanding participants' preferences for the return of individual research results (IRR) in genomic research may allow for the implementation of more beneficial result disclosure methods. We tested four preference-setting models through cognitive interviews of parents to explore how parents conceptualize the process of setting preferences and which disease characteristics they believe to be most important when deciding what results to receive on their child. Severity and preventability of a condition were highly influential in decision making and certain groups of research results were anticipated by participants to have negative psychological effects. These findings informed the development of an educational tool and preference-setting model that can be scaled for use in the return of IRR from large biobank studies.