Margaret M. Cavenagh

Criteria for the use of omics-based predictors in clinical trials

The US National Cancer Institute (NCI), in collaboration with scientists representing multiple areas of expertise relevant to ‘omics’-based test development, has developed a checklist of criteria that can be used to determine the readiness of omics-based tests for guiding patient care in clinical trials. The checklist criteria cover issues relating to specimens, assays, mathematical modelling, clinical trial design, and ethical, legal and regulatory aspects. Funding bodies and journals are encouraged to consider the checklist, which they may find useful for assessing study quality and evidence strength. The checklist will be used to evaluate proposals for NCI-sponsored clinical trials in which omics tests will be used to guide therapy.

Functional characterization of human bitter taste receptors

The T2Rs belong to a multi-gene family of G-protein-coupled receptors responsible for the detection of ingested bitter-tasting compounds. The T2Rs are conserved among mammals with the human and mouse gene families consisting of about 25 members. In the present study we address the signalling properties of human and mouse T2Rs using an in vitro reconstitution system in which both the ligands and G-proteins being assayed can be manipulated independently and quantitatively assessed. We confirm that the mT2R5, hT2R43 and hT2R47 receptors respond selectively to micromolar concentrations of cycloheximide, aristolochic acid and denatonium respectively. We also demonstrate that hT2R14 is a receptor for aristolochic acid and report the first characterization of the ligand specificities of hT2R7, which is a broadly tuned receptor responding to strychnine, quinacrine, chloroquine and papaverine. Using these defined ligand-receptor interactions, we assayed the ability of the ligand-activated T2Rs to catalyse GTP binding on divergent members of the G(alpha) family including three members of the G(alphai) subfamily (transducin, G(alphai1) and G(alphao)) as well as G(alphas) and G(alphaq). The T2Rs coupled with each of the three G(alphai) members tested. However, none of the T2Rs coupled to either G(alphas) or G(alphaq), suggesting the T2Rs signal primarily through G(alphai)-mediated signal transduction pathways. Furthermore, we observed different G-protein selectivities among the T2Rs with respect to both G(alphai) subunits and G(betagamma) dimers, suggesting that bitter taste is transduced by multiple G-proteins that may differ among the T2Rs.

Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration

High-throughput ‘omics’ technologies that generate molecular profiles for biospecimens have been extensively used in preclinical studies to reveal molecular subtypes and elucidate the biological mechanisms of disease, and in retrospective studies on clinical specimens to develop mathematical models to predict clinical endpoints. Nevertheless, the translation of these technologies into clinical tests that are useful for guiding management decisions for patients has been relatively slow. It can be difficult to determine when the body of evidence for an omics-based test is sufficiently comprehensive and reliable to support claims that it is ready for clinical use, or even that it is ready for definitive evaluation in a clinical trial in which it may be used to direct patient therapy. Reasons for this difficulty include the exploratory and retrospective nature of many of these studies, the complexity of these assays and their application to clinical specimens, and the many potential pitfalls inherent in the development of mathematical predictor models from the very high-dimensional data generated by these omics technologies. Here we present a checklist of criteria to consider when evaluating the body of evidence supporting the clinical use of a predictor to guide patient therapy. Included are issues pertaining to specimen and assay requirements, the soundness of the process for developing predictor models, expectations regarding clinical study design and conduct, and attention to regulatory, ethical, and legal issues. The proposed checklist should serve as a useful guide to investigators preparing proposals for studies involving the use of omics-based tests. The US National Cancer Institute plans to refer to these guidelines for review of proposals for studies involving omics tests, and it is hoped that other sponsors will adopt the checklist as well.

Expression and regulation of the mammalian SUMO-1 E1 enzyme

SUMO‐1 is a small ubiquitin‐related protein. SUMO‐1 conjugation requires enzymes with sequence and biochemical similarity to ubiquitin E1 and E2 enzymes. We have examined the expression, localization, and biochemical behavior of Aos1 and Uba2, subunits of the mammalian SUMO‐1 E1 enzyme. Both of these proteins are expressed in multiple tissues and localized to the nucleus. Aos1 protein levels vary through the cell cycle. These changes in Aos1 concentration may play a role in the regulation of the SUMO‐1 pathway, because they correlate with changes in the abundance of some SUMO‐1‐conjugated species. Biochemical analysis reveals that Aos1 and Uba2 associate with each other in a simple heterodimeric complex without other subunits, unlike the budding yeast Uba2 homologue, which apparently associates with several different proteins. Although it is possible to reconstitute SUMO‐1 conjugation with purified Uba2, Aos1, and Ubc9, this reaction is significantly less efficient than conjugation observed in cellular extracts, suggesting the possibility that there may be activators of SUMO‐1 conjugation in vivo that have not yet been characterized. Taken together, these observations reveal that the SUMO‐1 pathway is controlled on multiple levels during the cell cycle.

Modifications to the C-terminus of Arf1 alter cell functions and protein interactions.

Arf family proteins are ≈21‐kDa GTP‐binding proteins that are critical regulators of membrane traffic and the actin cytoskeleton. Studies examining the complex signaling pathways underlying Arf action have relied on recombinant proteins comprised of Arf fused to epitope tags or proteins, such as glutathione S‐transferase or green fluorescent protein, for both cell‐based mammalian cell studies and bacterially expressed recombinant proteins for biochemical assays. However, the effects of such protein fusions on the biochemical properties relevant to the cellular function have been only incompletely studied at best. Here, we have characterized the effect of C‐terminal tagging of Arf1 on (i) function in Saccharomyces cerevisiae, (ii) in vitro nucleotide exchange and (iii) interaction with guanine nucleotide exchange factors and GTPase‐activating proteins. We found that the tagged Arfs were substantially impaired or altered in each assay, compared with the wild‐type protein, and these changes are certain to alter actions in cells. We discuss the results related to the interpretation of experiments using these reagents and we propose that authors and editors consistently adopt a few simple rules for describing and discussing results obtained with Arf family members that can be readily applied to other proteins.

Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): An Abridged Explanation and Elaboration.

Abstract The Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) were developed to address widespread deficiencies in the reporting of such studies. The REMARK checklist consists of 20 items to report for published tumor marker prognostic studies. A detailed paper was published explaining the rationale behind checklist items, providing positive examples and giving empirical evidence of the quality of reporting. REMARK provides a comprehensive overview to educate on good reporting and provide a valuable reference for the many issues to consider when designing, conducting, and analyzing tumor marker studies and prognostic studies in medicine in general. Despite support for REMARK from major cancer journals, prognostic factor research studies remain poorly reported. To encourage dissemination and uptake of REMARK, we have produced this considerably abridged version of the detailed explanatory manuscript, which may also serve as a brief guide to key issues for investigators planning tumor marker prognostic studies. To summarize the current situation, more recent papers investigating the quality of reporting and related reporting guidelines are cited, but otherwise the literature is not updated. Another important impetus for this paper is that it serves as a basis for literal translations into other languages. Translations will help to bring key information to a larger audience world-wide. Many more details can be found in the original paper.

Criteria for use of omics-based predictors in NCI-sponsored clinical trials.

58 Background: High-throughput omics technologies (e.g., genomics, epigenomics, proteomics, metabolomics) offer exciting opportunities for new biological insights into cancer. The IOM report on translational omics defined omics as the study of related sets of biological molecules in a comprehensive fashion. (IOM (Institute of Medicine) 2012. Evolution of Translational Omics: Lessons Learned and the Path Forward. Washington, DC: The National Academic Press.) The promise of omics technologies has proven problematic to translate into clinically useful tests. Difficulty obtaining biospecimens, unrecognized preanalytical influences, and suboptimal assay analytical performance can lead to unreliable results and conflicting reports. Poor reporting of study details and limited access to data and computer code can thwart efforts to replicate published results or to detect flaws in study design and analysis methods. METHODS NCI held an interactive workshop for a wide variety of stakeholders to explore better approaches to omics-based test development and validation. This workshop heavily informed the ideas presented here. Recommendations are stated concisely, then explained. RESULTS A checklist of items to consider when evaluating the evidence for clinical use of an omics-based predictor, including in a trial where it will guide therapy, is presented. It covers specimen and assay requirements, the predictor model development process, clinical study design and conduct, and regulatory, ethical, and legal issues. The list applies to any trial involving investigational use of an omics test that will alter the clinical management of patients. The criteria also largely apply to situations in which the test will be evaluated retrospectively on specimens collected from patients who were prospectively enrolled on clinical studies. CONCLUSIONS The proposed checklist should serve as a useful guide to investigators planning to submit proposals for NCI-funded studies involving use of an omics-based test. Ideally, this checklist will be consulted in the assay planning and development phases so that the necessary evidence will have been collected in a well-documented fashion by the time definitive evaluation of the test is desired.