"Drivers" of translational cancer epidemiology in the 21st century: needs and opportunities

Home testing for COVID-19 and other virus outbreaks: The complex system of translating to communities

Home testing is an emerging innovation that can enable nations and health care systems to safely and efficiently test large numbers of patients to manage COVID-19 and other viral outbreaks.  In this position paper, we explore the process of moving home testing across the translational continuum from labs to households, and ultimately into practice and communities for optimal public health impact. We focus on the four translational science drivers to accelerate the implementation of systems-wide home testing programmes 1) collaboration and team science, 2) technology, 3) multilevel interventions, and 4) knowledge integration. We use the Socio Ecological Model (SEM) as a framework to illustrate our vision for the ideal future state of a comprehensive system of stakeholders utilising tech-enabled home testing for COVID-19 and other virus outbreaks, and we suggest SEM as a tool to address key translational readiness and response questions.

The future of translational research on alcohol use disorder

In March 2019, a scientific meeting was held at the University of California, Los Angeles (UCLA) Luskin Center to discuss approaches to expedite the translation of neurobiological insights to advances in the treatment of alcohol use disorder (AUD). A guiding theme that emerged was that while translational research in AUD is clearly a challenge, it is also a field ripe with opportunities. Herein, we seek to summarize and disseminate the recommendations for the future of translational AUD research using four sections. First, we briefly review the current landscape of AUD treatment including the available evidence-based treatments and their uptake in clinical settings. Second, we discuss AUD treatment development efforts from a translational science viewpoint. We review current hurdles to treatment development as well as opportunities for mechanism-informed treatment. Third, we consider models of translational science and public health impact. Together, these critical insights serve as the bases for a series of recommendations and future directions. Towards the goal of improving clinical care and population health for AUD, scientists are tasked with bolstering the clinical applicability of their research findings so as to expedite the translation of knowledge into patient care.

Training the Twenty-First Century Cancer Epidemiologist

To assess and advance training of twenty-first century cancer epidemiologists, the National Cancer Institute (NCI) sought to obtain a snapshot of the cancer epidemiology training landscape by conducting a survey across academic institutions and cancer centers, focusing on four key training areas driving current cancer epidemiology research ("drivers"): (1) collaboration, (2) novel methods/technologies, (3) multilevel analysis, and (4) knowledge integration. Complementary to the survey, we conducted a portfolio analysis of active NCI-funded training grants. In the present report, we provide our findings from this effort and contribute to the on-going conversation regarding the training of next-generation cancer epidemiologists. Analyses and insights gained from conversations with leaders/educators across 24 academic institutions/cancer centers and the portfolio analysis of training grants echoed contemporaneous conversation that cancer epidemiology training must adapt to meet the needs of the changing research environment. Currently, with the exception of novel methods/technologies, cancer epidemiology trainees receive the majority of their training in collaboration, multilevel approaches, and knowledge integration/translation either informally, ad hoc, or not at all; exposure to these identified drivers varied considerably by institution, mentor, and other external as well as internal factors.

Rural Primary Care Offices and Cancer Survivorship Care: Part of the Care Trajectory for Cancer Survivors

Background:

A cancer diagnosis is a monumental event in a patient’s life and with the number of cancer survivors increasing; most of these patients will be taken care of by a primary care provider at some point after their cancer therapy. The purpose of this study is to identify primary care physician’s needs to care for a patient who has had cancer.

Methods:

A cross-sectional survey of the physician members of the Iowa Research Network was conducted. The survey was designed to measure physician confidence in cancer survivor’s care, office strategies regarding cancer survivorship care, and resources available for patients with cancer. Two hundred seventy-four Iowa Research Network members were invited to participate in this survey.

Results:

Eighty-two physicians (30%) completed the questionnaire with 96% reporting that they are aware of their patient’s cancer survivorship status. Seventy-one physicians reported they were aware of cancer survivorship status by an oncologist sending a note to the office, 68 being diagnosed in their office, 61 by the patient keeping the office apprised, and 15 receiving a survivorship care plan. Physicians reported the top changes in a cancer survivor’s physical health as fatigue (81%) and pain (59%). Sixty-two physicians reported not feeling confident for managing chemobrain, cardiotoxicity (71%), and skin changes (35%). Male physicians were significantly more confident managing patients’ skin changes (P = .049) and musculoskeletal disturbances than female physicians (P = .027), while female physicians were significantly more confident managing early-onset menopause than male physicians (P = .027).

Conclusion:

Most respondents are aware of their patients who are cancer survivors and are mostly confident in the care they provide for them related to long-term effects and side effects of cancer therapies with limited receipt of cancer survivorship care plans.

Adding the Team into T1 Translational Research: A Case Study of Multidisciplinary Team Science in the Evaluation of Biomarkers of Prostate Cancer Risk and Prognosis

BACKGROUND

Given translational research challenges, multidisciplinary team science is promoted to increase the likelihood of moving from discovery to health effect. We present a case study documenting the utility of multidisciplinary team science in prostate cancer tissue biomarker validation.

METHODS

We used primary data generated by a team consisting of a pathologist, cancer biologists, a biostatistician, and epidemiologists. We examined their contributions by phase of biomarker evaluation to identify when, through the practice of team science, threats to internal validity were recognized and solved. Next, we quantified the extent of bias avoided in evaluating the association of Ki67 (immunohistochemistry), stromal cell telomere length (fluorescence in situ hybridization), and microRNA (miRNA) (miR-21, miR-141, miR-221; quantitative RT-PCR) with prostate cancer risk or recurrence in nested case-control studies.

RESULTS

Threats to validity were tissue storage time (Ki67, miRNA) and laboratory equipment maintenance (telomeres). Solutions were all in the data analysis phase and involved using tissue storage-time specific cutpoints and/or batch-specific cutpoints. Bias in the regression coefficient for quantiles of each biomarker ranged from 24% to 423%, and the coefficient for the test for trend ranged from 15% to 910%. The interpretation of the associations changed as follows: Ki67, null to positive; stromal cell telomere length, null to positive; miR-21 and miR-141 remained null; miR-221, weak to moderate inverse.

CONCLUSIONS

In this case study, we documented the inferential benefits of multidisciplinary team science when the team's collaboration and coordination led to the identification of threats to validity and the implementation of appropriate solutions.

Secretion of tumoricidal human tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) by recombinant Lactococcus lactis: optimization of in vitro synthesis conditions

BACKGROUND

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) selectively eliminates tumor cells. However, the short biological half-life of this molecule limits its potential use in the clinic. Our aim was to construct a recombinant strain of nonpathogenic Lactococcus lactis bacteria as a vector for effective and prolonged human TRAIL production. Herein, we examined the expression and secretion conditions leading to the production of biologically active protein in vitro.

RESULTS

The human soluble TRAIL-cDNA (hsTRAIL-cDNA) with optimized codons was designed to fit the codon usage pattern (codon bias) of the L. lactis host. This cDNA construct was synthesized and cloned in lactococcal plasmid secretion vector pNZ8124 under the control of the nisin-induced PnisA promoter. The pNZ8124-hsTRAIL plasmid vector was transformed into the L. lactis NZ9000 host strain cells by electroporation. Secretion of the protein occurred at the neutral pH during induction, with optimized concentration of the inducer and presence of serine proteases inhibitor. Using Western blotting and amino acid sequencing method we found that TRAIL was secreted in two forms, as visualized by the presence of two distinct molecular size bands, both deprived of the usp45 protein, the bacterial signal peptide. By the use of MTS assay we were able to prove that hsTRAIL present in supernatant from L. lactis (hsTRAIL+) broth culture was cytotoxic to human HCT116 colon cancer cells but not to normal human fibroblasts. Flow cytometry analysis revealed TRAIL-induced apoptosis of cancer cells.

CONCLUSIONS

We designed recombinant L. lactis bacteria, which efficiently produce biologically active, anti-tumorigenic human TRAIL in vitro. Further studies in tumor-bearing NOD-SCID mice will reveal whether the TRAIL-secreting L. lactis bacteria can be used as a safe carrier of this protein, capable of inducing effective elimination of human colon cancer cells in vivo.

A collaborative translational research framework for evaluating and implementing the appropriate use of human genome sequencing to improve health

In a Policy Forum, Muin Khoury and colleagues discuss research on the clinical application of genome sequencing data.

A training program for nurse scientists to promote intervention translation

BACKGROUND

To reduce the burden of chronic illness, prevention and management interventions must be efficacious, adopted and implemented with fidelity, and reach those at greatest risk. Yet, many research-tested interventions are slow to translate into practice.

PURPOSE

This paper describes how The University of North Carolina at Chapel Hill School of Nursing's NINR-funded institutional pre- and postdoctoral research-training program is addressing the imperative to speed knowledge translation across the research cycle.

METHODS

The training emphasizes six research methods ("catalysts") to speed translation: stakeholder engagement, patient-centered outcomes, intervention optimization and sequential multiple randomized trials (SMART), pragmatic trials, mixed methods approaches, and dissemination and implementation science strategies. Catalysts are integrated into required coursework, biweekly scientific and integrative seminars, and experiential research training. Trainee and program success is evaluated based on benchmarks applicable to all PhD program students, supplemented by indicators specific to the catalysts. Trainees must also demonstrate proficiency in at least two of the six catalysts in their scholarly products. Proficiency is assessed through their works in progress presentations and peer reviews at T32 integrative seminars.

DISCUSSION

While maintaining the emphasis on theory-based interventions, we have integrated six catalysts into our ongoing research training to expedite the dynamic process of intervention development, testing, dissemination and implementation.

CONCLUSIONS

Through a variety of training activities, our research training focused on theory-based interventions and the six catalysts will generate future nurse scientists who speed translation of theory-based interventions into practice to maximize health outcomes for patients, families, communities and populations affected by chronic illness.

Contextual effects and cancer outcomes in the United States: a systematic review of characteristics in multilevel analyses

PURPOSE

There is increasing call for the utilization of multilevel modeling to explore the relationship between place-based contextual effects and cancer outcomes in the United States. To gain a better understanding of how contextual factors are being considered, we performed a systematic review.

METHODS

We reviewed studies published between January 1, 2002 and December 31, 2016 and assessed the following attributes: (1) contextual considerations such as geographic scale and contextual factors used; (2) methods used to quantify contextual factors; and (3) cancer type and outcomes. We searched PubMed, Scopus, and Web of Science and initially identified 1060 studies. One hundred twenty-two studies remained after exclusions.

RESULTS

Most studies utilized a two-level structure; census tracts were the most commonly used geographic scale. Socioeconomic factors, health care access, racial/ethnic factors, and rural-urban status were the most common contextual factors addressed in multilevel models. Breast and colorectal cancers were the most common cancer types, and screening and staging were the most common outcomes assessed in these studies.

CONCLUSIONS

Opportunities for future research include deriving contextual factors using more rigorous approaches, considering cross-classified structures and cross-level interactions, and using multilevel modeling to explore understudied cancers and outcomes.

Transdisciplinary approaches enhance the production of translational knowledge

The primary goal of translational research is to generate and apply knowledge that can improve human health. Although research conducted within the confines of a single discipline has helped us to achieve this goal in many settings, this unidisciplinary approach may not be optimal when disease causation is complex and health decisions are pressing. To address these issues, we suggest that transdisciplinary approaches can facilitate the progress of translational research, and we review publications that demonstrate what these approaches can look like. These examples serve to (1) demonstrate why transdisciplinary research is useful, and (2) stimulate a conversation about how it can be further promoted. While we note that open-minded communication is a prerequisite for germinating any transdisciplinary work and that epidemiologists can play a key role in promoting it, we do not propose a rigid protocol for conducting transdisciplinary research, as one really does not exist. These achievements were developed in settings where typical disciplinary and institutional barriers were surmountable, but they were not accomplished with a single predetermined plan. The benefits of cross-disciplinary communication are hard to predict a priori and a detailed research protocol or process may impede the realization of novel and important insights. Overall, these examples demonstrate that enhanced cross-disciplinary information exchange can serve as a starting point that helps researchers frame better questions, integrate more relevant evidence, and advance translational knowledge more effectively. Specifically, we discuss examples where transdisciplinary approaches are helping us to better explore, assess, and intervene to improve human health.

Mapping the evolving definitions of translational research

OBJECTIVE

Systematic review and analysis of definitions of translational research.

MATERIALS AND METHODS

The final corpus was comprised of 33 papers, each read by at least 2 reviewers. Definitions were mapped to a common set of research processes for presentation and analysis. Influence of papers and definitions was further evaluated using citation analysis and agglomerative clustering.

RESULTS

All definitions were mapped to common research processes, revealing most common labels for each process. Agglomerative clustering revealed 3 broad families of definitions. Citation analysis showed that the originating paper of each family has been cited ~10 times more than any other member.

DISCUSSION

Although there is little agreement between definitions, we were able to identify an emerging consensus 5-phase (T0-T4) definition for translational research. T1 involves processes that bring ideas from basic research through early testing in humans. T2 involves the establishment of effectiveness in humans and clinical guidelines. T3 primarily focuses on implementation and dissemination research while T4 focuses on outcomes and effectiveness in populations. T0 involves research such as genome-wide association studies which wrap back around to basic research.

CONCLUSION

We used systematic review and analysis to identify emerging consensus between definitions of translational research phases.

Designing a learning health organization for collective impact

This commentary reviews how the San Francisco Department of Public Health has used organization design concepts and continuous improvement frameworks to reorganize from autonomous, categorical silos of public health services to an integrated, community-centered Population Health Division.

A novel web informatics approach for automated surveillance of cancer mortality trends

Cancer surveillance data are collected every year in the United States via the National Program of Cancer Registries (NPCR) and the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute (NCI). General trends are closely monitored to measure the nation's progress against cancer. The objective of this study was to apply a novel web informatics approach for enabling fully automated monitoring of cancer mortality trends. The approach involves automated collection and text mining of online obituaries to derive the age distribution, geospatial, and temporal trends of cancer deaths in the US. Using breast and lung cancer as examples, we mined 23,850 cancer-related and 413,024 general online obituaries spanning the timeframe 2008-2012. There was high correlation between the web-derived mortality trends and the official surveillance statistics reported by NCI with respect to the age distribution (ρ=0.981 for breast; ρ=0.994 for lung), the geospatial distribution (ρ=0.939 for breast; ρ=0.881 for lung), and the annual rates of cancer deaths (ρ=0.661 for breast; ρ=0.839 for lung). Additional experiments investigated the effect of sample size on the consistency of the web-based findings. Overall, our study findings support web informatics as a promising, cost-effective way to dynamically monitor spatiotemporal cancer mortality trends.

From Molecules to Patients: The Clinical Applications of Translational Bioinformatics

OBJECTIVE

In order to realize the promise of personalized medicine, Translational Bioinformatics (TBI) research will need to continue to address implementation issues across the clinical spectrum. In this review, we aim to evaluate the expanding field of TBI towards clinical applications, and define common themes and current gaps in order to motivate future research.

METHODS

Here we present the state-of-the-art of clinical implementation of TBI-based tools and resources. Our thematic analyses of a targeted literature search of recent TBI-related articles ranged across topics in genomics, data management, hypothesis generation, molecular epidemiology, diagnostics, therapeutics and personalized medicine.

RESULTS

Open areas of clinically-relevant TBI research identified in this review include developing data standards and best practices, publicly available resources, integrative systemslevel approaches, user-friendly tools for clinical support, cloud computing solutions, emerging technologies and means to address pressing legal, ethical and social issues.

CONCLUSIONS

There is a need for further research bridging the gap from foundational TBI-based theories and methodologies to clinical implementation. We have organized the topic themes presented in this review into four conceptual foci - domain analyses, knowledge engineering, computational architectures and computation methods alongside three stages of knowledge development in order to orient future TBI efforts to accelerate the goals of personalized medicine.

Molecular and clinical diseasome of comorbidities in exacerbated COPD patients

The frequent occurrence of comorbidities in patients with chronic obstructive pulmonary disease (COPD) suggests that they may share pathobiological processes and/or risk factors.To explore these possibilities we compared the clinical diseasome and the molecular diseasome of 5447 COPD patients hospitalised because of an exacerbation of the disease. The clinical diseasome is a network representation of the relationships between diseases, in which diseases are connected if they co-occur more than expected at random; in the molecular diseasome, diseases are linked if they share associated genes or interaction between proteins.The results showed that about half of the disease pairs identified in the clinical diseasome had a biological counterpart in the molecular diseasome, particularly those related to inflammation and vascular tone regulation. Interestingly, the clinical diseasome of these patients appears independent of age, cumulative smoking exposure or severity of airflow limitation.These results support the existence of shared molecular mechanisms among comorbidities in COPD.

Invited commentary: driving for further evolution

The concept of translational cancer epidemiology has evolved since its early beginnings in 1937 with the establishment of the National Cancer Institute. Conceptual models of cancer control research have also evolved over the last 30 years, to the point where we now have 4 stages of translational research (T0-T4). The current review by Lam et al. (Am J Epidemiol. 2015;181(7):451-458) covers cancer epidemiology research supported by the National Cancer Institute and a selected sample of the cancer epidemiology literature. It suggests that most cancer epidemiology in the last 10 years has been in pure discovery research. Current "drivers" of cancer epidemiology research, including new technologies, team science multilevel research, and knowledge integration, are not strongly represented in the review. However, the use of epidemiology in the latter stages of translation may not have been captured by the scope of this review. The closer epidemiologists get to advanced stages of translation, the more likely they are to work with investigators in other disciplines in other sectors of society. An argument can be made that regardless of whether this kind of research is not happening or was just missed by the current review, the field of cancer epidemiology can expand its scope and further evolve towards more effective applications in population health.

Evolution of the "drivers" of translational cancer epidemiology: analysis of funded grants and the literature

Concurrently with a workshop sponsored by the National Cancer Institute, we identified key "drivers" for accelerating cancer epidemiology across the translational research continuum in the 21st century: emerging technologies, a multilevel approach, knowledge integration, and team science. To map the evolution of these "drivers" and translational phases (T0-T4) in the past decade, we analyzed cancer epidemiology grants funded by the National Cancer Institute and published literature for 2000, 2005, and 2010. For each year, we evaluated the aims of all new/competing grants and abstracts of randomly selected PubMed articles. Compared with grants based on a single institution, consortium-based grants were more likely to incorporate contemporary technologies (P = 0.012), engage in multilevel analyses (P = 0.010), and incorporate elements of knowledge integration (P = 0.036). Approximately 74% of analyzed grants and publications involved discovery (T0) or characterization (T1) research, suggesting a need for more translational (T2-T4) research. Our evaluation indicated limited research in 1) a multilevel approach that incorporates molecular, individual, social, and environmental determinants and 2) knowledge integration that evaluates the robustness of scientific evidence. Cancer epidemiology is at the cusp of a paradigm shift, and the field will need to accelerate the pace of translating scientific discoveries in order to impart population health benefits. While multi-institutional and technology-driven collaboration is happening, concerted efforts to incorporate other key elements are warranted for the discipline to meet future challenges.

Charting a future for epidemiologic training

PURPOSE

To identify macro-level trends that are changing the needs of epidemiologic research and practice and to develop and disseminate a set of competencies and recommendations for epidemiologic training that will be responsive to these changing needs.

METHODS

There were three stages to the project: (1) assembling of a working group of senior epidemiologists from multiple sectors, (2) identifying relevant literature, and (3) conducting key informant interviews with 15 experienced epidemiologists.

RESULTS

Twelve macro trends were identified along with associated actions for the field and educational competencies. The macro trends include the following: (1) "Big Data" or informatics, (2) the changing health communication environment, (3) the Affordable Care Act or health care system reform, (4) shifting demographics, (5) globalization, (6) emerging high-throughput technologies (omics), (7) a greater focus on accountability, (8) privacy changes, (9) a greater focus on "upstream" causes of disease, (10) the emergence of translational sciences, (11) the growing centrality of team and transdisciplinary science, and (12) the evolving funding environment.

CONCLUSIONS

Addressing these issues through curricular change is needed to allow the field of epidemiology to more fully reach and sustain its full potential to benefit population health and remain a scientific discipline that makes critical contributions toward ensuring clinical, social, and population health.

The next generation of large-scale epidemiologic research: implications for training cancer epidemiologists

There is expanding consensus on the need to modernize the training of cancer epidemiologists to accommodate rapidly emerging technological advancements and the digital age, which are transforming the practice of cancer epidemiology. There is also a growing imperative to extend cancer epidemiology research that is etiological to that which is applied and has the potential to affect individual and public health. Medical schools and schools of public health are recognizing the need to develop such integrated programs; however, we lack the data to estimate how many current training programs are effectively equipping epidemiology students with the knowledge and tools to design, conduct, and analyze these increasingly complex studies. There is also a need to develop new mentoring approaches to account for the transdisciplinary team-science environment that now prevails. With increased dialogue among schools of public health, medical schools, and cancer centers, revised competencies and training programs at predoctoral, doctoral, and postdoctoral levels must be developed. Continuous collection of data on the impact and outcomes of such programs is also recommended.

Genetic simulation tools for post-genome wide association studies of complex diseases

Genetic simulation programs are used to model data under specified assumptions to facilitate the understanding and study of complex genetic systems. Standardized data sets generated using genetic simulation are essential for the development and application of novel analytical tools in genetic epidemiology studies. With continuing advances in high-throughput genomic technologies and generation and analysis of larger, more complex data sets, there is a need for updating current approaches in genetic simulation modeling. To provide a forum to address current and emerging challenges in this area, the National Cancer Institute (NCI) sponsored a workshop, entitled "Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases" at the National Institutes of Health (NIH) in Bethesda, Maryland on March 11-12, 2014. The goals of the workshop were to (1) identify opportunities, challenges, and resource needs for the development and application of genetic simulation models; (2) improve the integration of tools for modeling and analysis of simulated data; and (3) foster collaborations to facilitate development and applications of genetic simulation. During the course of the meeting, the group identified challenges and opportunities for the science of simulation, software and methods development, and collaboration. This paper summarizes key discussions at the meeting, and highlights important challenges and opportunities to advance the field of genetic simulation.

An action plan for translating cancer survivorship research into care

To meet the complex needs of a growing number of cancer survivors, it is essential to accelerate the translation of survivorship research into evidence-based interventions and, as appropriate, recommendations for care that may be implemented in a wide variety of settings. Current progress in translating research into care is stymied, with results of many studies un- or underutilized. To better understand this problem and identify strategies to encourage the translation of survivorship research findings into practice, four agencies (American Cancer Society, Centers for Disease Control and Prevention, LIVE STRONG: Foundation, National Cancer Institute) hosted a meeting in June, 2012, titled: "Biennial Cancer Survivorship Research Conference: Translating Science to Care." Meeting participants concluded that accelerating science into care will require a coordinated, collaborative effort by individuals from diverse settings, including researchers and clinicians, survivors and families, public health professionals, and policy makers. This commentary describes an approach stemming from that meeting to facilitate translating research into care by changing the process of conducting research-improving communication, collaboration, evaluation, and feedback through true and ongoing partnerships. We apply the T0-T4 translational process model to survivorship research and provide illustrations of its use. The resultant framework is intended to orient stakeholders to the role of their work in the translational process and facilitate the transdisciplinary collaboration needed to translate basic discoveries into best practices regarding clinical care, self-care/management, and community programs for cancer survivors. Finally, we discuss barriers to implementing translational survivorship science identified at the meeting, along with future directions to accelerate this process.

Discovery of colorectal cancer PIK3CA mutation as potential predictive biomarker: power and promise of molecular pathological epidemiology

Regular use of aspirin reduces incidence and mortality of various cancers, including colorectal cancer. Anticancer effect of aspirin represents one of the 'Provocative Questions' in cancer research. Experimental and clinical studies support a carcinogenic role for PTGS2 (cyclooxygenase-2), which is an important enzymatic mediator of inflammation, and a target of aspirin. Recent 'molecular pathological epidemiology' (MPE) research has shown that aspirin use is associated with better prognosis and clinical outcome in PIK3CA-mutated colorectal carcinoma, suggesting somatic PIK3CA mutation as a molecular biomarker that predicts response to aspirin therapy. The PI3K (phosphatidylinositol-4,5-bisphosphonate 3-kinase) enzyme has a pivotal role in the PI3K-AKT signaling pathway. Activating PIK3CA oncogene mutations are observed in various malignancies including breast cancer, ovarian cancer, brain tumor, hepatocellular carcinoma, lung cancer and colon cancer. The prevalence of PIK3CA mutations increases continuously from rectal to cecal cancers, supporting the 'colorectal continuum' paradigm, and an important interplay of gut microbiota and host immune/inflammatory reaction. MPE represents an interdisciplinary integrative science, conceptually defined as 'epidemiology of molecular heterogeneity of disease'. As exposome and interactome vary from person to person and influence disease process, each disease process is unique (the unique disease principle). Therefore, MPE concept and paradigm can extend to non-neoplastic diseases including diabetes mellitus, cardiovascular diseases, metabolic diseases, and so on. MPE research opportunities are currently limited by paucity of tumor molecular data in the existing large-scale population-based studies. However, genomic, epigenomic and molecular pathology testings (for example, analyses for microsatellite instability, MLH1 promoter CpG island methylation, and KRAS and BRAF mutations in colorectal tumors) are becoming routine clinical practices. In order for integrative molecular and population science to be routine practice, we must first reform education curricula by integrating both population and molecular biological sciences. As consequences, next-generation hybrid molecular biological and population scientists can advance science, moving closer to personalized precision medicine and health care.

Accelerating translation of physical activity and cancer survivorship research into practice: recommendations for a more integrated and collaborative approach

Physical activity has been deemed safe and effective in reducing many negative side effects of treatment for cancer survivors and promoting better overall health. However, most of this research has focused on highly controlled randomized trials and little of this research has been translated into care or policy for survivors. The purpose of the present article is to present a research agenda for the field to accelerate the dissemination and implementation of empirically supported physical activity interventions into care. We provide rationale for the role of basic, behavioral, clinical implementation, and population scientists in moving this science forward and call for a more coordinated effort across different phases of research. In addition, we provide key strategies and examples for ongoing and future studies using the RE-AIM (reach, efficacy/effectiveness, adoption, implementation, and maintenance) framework and pose recommendations for collaborations between researchers and stakeholders to enhance the integration of this research into policy and practice. Overall, we recommend that physical activity and cancer survivorship research use additional study designs, include relevant stakeholders, and be more collaborative, integrated, contextual, and representative in terms of both setting and participants.

Collaborative cancer epidemiology in the 21st century: the model of cancer consortia

During the last two decades, epidemiology has undergone a rapid evolution toward collaborative research. The proliferation of multi-institutional, interdisciplinary consortia has acquired particular prominence in cancer research. Herein, we describe the characteristics of a network of 49 established cancer epidemiology consortia (CEC) currently supported by the Epidemiology and Genomics Research Program (EGRP) at the National Cancer Institute (NCI). This collection represents the largest disease-based research network for collaborative cancer research established in population sciences. We describe the funding trends, geographic distribution, and areas of research focus. The CEC have been partially supported by 201 grants and yielded 3,876 publications between 1995 and 2011. We describe this output in terms of interdisciplinary collaboration and translational evolution. We discuss challenges and future opportunities in the establishment and conduct of large-scale team science within the framework of CEC, review future prospects for this approach to large-scale, interdisciplinary cancer research, and describe a model for the evolution of an integrated Network of Cancer Consortia optimally suited to address and support 21st-century epidemiology.

Integrating genetic and genomic information into effective cancer care in diverse populations

This paper provides an overview of issues in the integration of genetic (related to hereditary DNA) and genomic (related to genes and their functions) information in cancer care for individuals and families who are part of health care systems worldwide, from low to high resourced. National and regional cancer plans have the potential to integrate genetic and genomic information with a goal of identifying and helping individuals and families with and at risk of cancer. Healthcare professionals and the public have the opportunity to increase their genetic literacy and communication about cancer family history to enhance cancer control, prevention, and tailored therapies.

Transforming epidemiology for 21st century medicine and public health

In 2012, the National Cancer Institute (NCI) engaged the scientific community to provide a vision for cancer epidemiology in the 21st century. Eight overarching thematic recommendations, with proposed corresponding actions for consideration by funding agencies, professional societies, and the research community emerged from the collective intellectual discourse. The themes are (i) extending the reach of epidemiology beyond discovery and etiologic research to include multilevel analysis, intervention evaluation, implementation, and outcomes research; (ii) transforming the practice of epidemiology by moving toward more access and sharing of protocols, data, metadata, and specimens to foster collaboration, to ensure reproducibility and replication, and accelerate translation; (iii) expanding cohort studies to collect exposure, clinical, and other information across the life course and examining multiple health-related endpoints; (iv) developing and validating reliable methods and technologies to quantify exposures and outcomes on a massive scale, and to assess concomitantly the role of multiple factors in complex diseases; (v) integrating "big data" science into the practice of epidemiology; (vi) expanding knowledge integration to drive research, policy, and practice; (vii) transforming training of 21st century epidemiologists to address interdisciplinary and translational research; and (viii) optimizing the use of resources and infrastructure for epidemiologic studies. These recommendations can transform cancer epidemiology and the field of epidemiology, in general, by enhancing transparency, interdisciplinary collaboration, and strategic applications of new technologies. They should lay a strong scientific foundation for accelerated translation of scientific discoveries into individual and population health benefits.

Bridging the gap between biologic, individual, and macroenvironmental factors in cancer: a multilevel approach

To address the complex nature of cancer occurrence and outcomes, approaches have been developed to simultaneously assess the role of two or more etiologic agents within hierarchical levels including the: (i) macroenvironment level (e.g., health care policy, neighborhood, or family structure); (ii) individual level (e.g., behaviors, carcinogenic exposures, socioeconomic factors, and psychologic responses); and (iii) biologic level (e.g., cellular biomarkers and inherited susceptibility variants). Prior multilevel approaches tend to focus on social and environmental hypotheses, and are thus limited in their ability to integrate biologic factors into a multilevel framework. This limited integration may be related to the limited translation of research findings into the clinic. We propose a "Multi-level Biologic and Social Integrative Construct" (MBASIC) to integrate macroenvironment and individual factors with biology. The goal of this framework is to help researchers identify relationships among factors that may be involved in the multifactorial, complex nature of cancer etiology, to aid in appropriate study design, to guide the development of statistical or mechanistic models to study these relationships, and to position the results of these studies for improved intervention, translation, and implementation. MBASIC allows researchers from diverse fields to develop hypotheses of interest under a common conceptual framework, to guide transdisciplinary collaborations, and to optimize the value of multilevel studies for clinical and public health activities.

Provocative questions in cancer epidemiology in a time of scientific innovation and budgetary constraints

In a time of scientific and technological developments and budgetary constraints, the National Cancer Institute's (NCI) Provocative Questions Project offers a novel funding mechanism for cancer epidemiologists. We reviewed the purposes underlying the Provocative Questions Project, present information on the contributions of epidemiologic research to the current Provocative Questions portfolio, and outline opportunities that the cancer epidemiology community might capitalize on to advance a research agenda that spans a translational continuum from scientific discoveries to population health impact.