Review of the Gene-Environment Interaction Literature in Cancer: What Do We Know?

The Interaction of Smoking with Gene Polymorphisms on Four Digestive Cancers: A Systematic Review and Meta-Analysis

The main purpose of this study was to perform a meta-analysis to assess the interaction between smoking and nine genes (GSTM1, GSTT1, GSTP1, CYP1A1, NAT2, SULT1A1, hOGG1, XRCC1 and p53) on colorectal cancer, gastric cancer, liver cancer and oesophageal cancer. Published articles from the PubMed, ISI and EMBASE databases were retrieved. A total of 67 case-control studies or nested case-control studies were identified for the analysis. The pooled jodds ratio (OR) with 95% confidence interval (CI) was calculated using the random effect model. The overall study showed that the GSTM1 polymorphism was associated with the risk of the four digestive cancers among Asian population (OR 1.284, 95% CI: 1.122-1.470, p: 0). Subgroup analyses by cancer site showed that GSTM1 null genotype increased the gastric cancer risk in total population (OR 1.335, 95% CI: 1.145-1.556, p: 0). However, the association of GSTM1 null genotype with the oesophageal cancer risk was found in smokers (OR 1.382, 95% CI: 1.009-1.894, p:0.044), but not in non-smokers (OR 1.250, 95% CI: 0.826-1.891, p:0.290). Moreover, smokers with the CYP1A1 IIe462Val polymorphism were at an increased cancer risk in Asian population (OR=1.585, 95% CI 1.029-2.442, p: 0.037). None of the other gene-smoking interactions was observed in the above cancers. This meta-analysis reveals two potential gene-smoking interactions, one is between smoking and GSTM1 on oesophageal cancer, and the other is between smoking and CYP1A1 IIe462Val on the four cancers in Asian population. Future studies need to be conducted to verify the conclusions.

Early Life Exposures and Adult Cancer Risk

Very little is known about the influence of early life exposures on adult cancer risk. The purpose of this narrative review was to summarize the epidemiologic evidence relating early life tobacco use, obesity, diet, and physical activity to adult cancer risk; describe relevant theoretical frameworks and methodological strategies for studying early life exposures; and discuss policies and research initiatives focused on early life. Our findings suggest that in utero exposures may indirectly influence cancer risk by modifying biological pathways associated with carcinogenesis; however, more research is needed to firmly establish these associations. Initiation of exposures during childhood and adolescence may impact cancer risk by increasing duration and lifetime exposure to carcinogens and/or by acting during critical developmental periods. To expand the evidence base, we encourage the use of life course frameworks, causal inference methods such as Mendelian randomization, and statistical approaches such as group-based trajectory modeling in future studies. Further, we emphasize the need for objective exposure biomarkers and valid surrogate endpoints to reduce misclassification. With the exception of tobacco use, there is insufficient evidence to support the development of new cancer prevention policies; however, we highlight existing policies that may reduce the burden of these modifiable risk factors in early life.

Critical research gaps and recommendations to inform research prioritisation for more effective prevention and improved outcomes in colorectal cancer

OBJECTIVE

Colorectal cancer (CRC) leads to significant morbidity/mortality worldwide. Defining critical research gaps (RG), their prioritisation and resolution, could improve patient outcomes.

DESIGN

RG analysis was conducted by a multidisciplinary panel of patients, clinicians and researchers (n=71). Eight working groups (WG) were constituted: discovery science; risk; prevention; early diagnosis and screening; pathology; curative treatment; stage IV disease; and living with and beyond CRC. A series of discussions led to development of draft papers by each WG, which were evaluated by a 20-strong patient panel. A final list of RGs and research recommendations (RR) was endorsed by all participants.

RESULTS

Fifteen critical RGs are summarised below: RG1: Lack of realistic models that recapitulate tumour/tumour micro/macroenvironment; RG2: Insufficient evidence on precise contributions of genetic/environmental/lifestyle factors to CRC risk; RG3: Pressing need for prevention trials; RG4: Lack of integration of different prevention approaches; RG5: Lack of optimal strategies for CRC screening; RG6: Lack of effective triage systems for invasive investigations; RG7: Imprecise pathological assessment of CRC; RG8: Lack of qualified personnel in genomics, data sciences and digital pathology; RG9: Inadequate assessment/communication of risk, benefit and uncertainty of treatment choices; RG10: Need for novel technologies/interventions to improve curative outcomes; RG11: Lack of approaches that recognise molecular interplay between metastasising tumours and their microenvironment; RG12: Lack of reliable biomarkers to guide stage IV treatment; RG13: Need to increase understanding of health related quality of life (HRQOL) and promote residual symptom resolution; RG14: Lack of coordination of CRC research/funding; RG15: Lack of effective communication between relevant stakeholders.

CONCLUSION

Prioritising research activity and funding could have a significant impact on reducing CRC disease burden over the next 5 years.

Effects of interactions between common genetic variants and smoking on colorectal cancer

Background

Although genome-wide association studies (GWAS) have identified variants in approximately 40 susceptibility loci for colorectal cancer (CRC), there are few studies on the interactions between identified single-nucleotide polymorphisms (SNPs) and lifestyle risk factors. We evaluated whether smoking could modify associations between these genetic variants and CRC risk.

Methods

A total of 703 CRC patients and 1406 healthy controls were included in this case-control study from the National Cancer Center in Korea. Thirty CRC susceptibility SNPs identified in previous GWAS were genotyped. A logistic regression model was used to examine associations between the SNPs and smoking behaviors by sex. The interaction was estimated by including an additional interaction term in the model.

Results

In men, an increased CRC risk was observed for longer durations (OR_{>28 vs. ≤28years} = 1.49 (95% CI = 1.11–1.98)), greater quantities (OR_{≥20 vs. <20cigarettes/day} = 2.12 (1.61–2.79)), and longer pack-years of smoking (OR_{≥21 vs. <21pack-years} = 1.78 (1.35–2.35)). In women, longer pack-years of smoking significantly increased CRC risk (OR_{≥5 vs. <5pack-years} = 6.11 (1.10–34.00)). Moreover, there were significant interactions between smoking status and the polymorphisms rs1957636 at 14q22.3 (P_interaction = 5.5 × 10⁻⁴) and rs4813802 at 20p12.3 (P_interaction = 0.04) in men. Interactions between smoking status and the rs6687758 at 1q41 (P_interaction = 0.03), duration and the rs174537 at 11q12.2 (P_interaction = 0.05), and pack-years and the rs4813802 (P_interaction = 0.04) were also found in women.

Conclusions

Associations between susceptibility SNPs and CRC risk may be modified by smoking behaviors, supporting the existence of gene-smoking interactions.

Electronic supplementary material

The online version of this article (10.1186/s12885-017-3886-0) contains supplementary material, which is available to authorized users.

Assessing health risks from multiple environmental stressors: Moving from G×E to I×E

Research on disease causation often attempts to isolate the effects of individual factors, including individual genes or environmental factors. This reductionist approach has generated many discoveries, but misses important interactive and cumulative effects that may help explain the broad range of variability in disease occurrence observed across studies and individuals. A disease rarely results from a single factor, and instead results from a broader combination of factors, characterized here as intrinsic (I) and extrinsic (E) factors. Intrinsic vulnerability or resilience emanates from a variety of both fixed and shifting biological factors including genetic traits, while extrinsic factors comprise all biologically-relevant external stressors encountered across the lifespan. The I×E concept incorporates the multi-factorial and dynamic nature of health and disease and provides a unified, conceptual basis for integrating results from multiple areas of research, including genomics, G×E, developmental origins of health and disease, and the exposome. We describe the utility of the I×E concept to better understand and characterize the cumulative impact of multiple extrinsic and intrinsic factors on individual and population health. New research methods increasingly facilitate the measurement of multifactorial and interactive effects in epidemiological and toxicological studies. Tiered or indicator-based approaches can guide the selection of potentially relevant I and E factors for study and quantification, and exposomics methods may eventually produce results that can be used to generate a response function over the life course. Quantitative data on I×E interactive effects should generate a better understanding of the variability in human response to environmental factors. The proposed I×E concept highlights the role for broader study design in order to identify extrinsic and intrinsic factors amenable to interventions at the individual and population levels in order to enhance resilience, reduce vulnerability and improve health.

How to not detonate the bomb: the case of the Italian National Health Service

Why is Italy one of the world's highest ranked for ability and quality of healthcare in relationship to the resources invested? The last decade has been characterized by many Italian Regions with Recovery Plans, whose main focus was on short-term issues with a high impact on healthcare costs. Italy is now leaving this phase and at the regional level there will be an increase of new hirings in the healthcare sectors, as stated by the Ministry of Health. There is a large amount of scientific literature that supports the role of factors such as lifestyles, diet and genetics as the base of population health. The success of the Italian National Health Service (INHS) function is rooted in the ability of a system to adapt to evolving situations, but it is also important to ensure a mechanism of positive feedback correction. In the future, INHS will require a new set of reforms, like the redefinition of structures and mechanisms of governance, the implementation of strategic plans that conjugate better clinical and financial issues. In this context, Health Data Entanglement could be an option to improve the effectiveness of the health governance system in order to develop better quality of care. In Public Health several criticisms could detonate the bomb, and above all the decreasing levels of primary prevention in the fight to obesity (promoting the Mediterranean Diet and physical activity), to smoking and alcohol consumption, as well as to infectious diseases (promoting high vaccination rates). Secondary prevention is also key to this function as a practical experience of re-engineering of the public expense, giving much attention to what works in terms of cost effectiveness, and in particular to cancer screening.

Genetic and epigenetic determinants of inter-individual variability in responses to toxicants

It is well established that genetic variability has a major impact on susceptibility to common diseases, responses to drugs and toxicants, and influences disease-related outcomes. The appreciation that epigenetic marks also vary across the population is growing with more data becoming available from studies in humans and model organisms. In addition, the links between genetic variability, toxicity outcomes and epigenetics are being actively explored. Recent studies demonstrate that gene-by-environment interactions involve both chromatin states and transcriptional regulation, and that epigenetics provides important mechanistic clues to connect expression-related quantitative trait loci (QTL) and disease outcomes. However, studies of Gene×Environment×Epigenetics further extend the complexity of the experimental designs and create a challenge for selecting the most informative epigenetic readouts that can be feasibly performed to interrogate multiple individuals, exposures, tissue types and toxicity phenotypes. We propose that among the many possible epigenetic experimental methodologies, assessment of chromatin accessibility coupled with total RNA levels provides a cost-effective and comprehensive option to sufficiently characterize the complexity of epigenetic and regulatory activity in the context of understanding the inter-individual variability in responses to toxicants.

Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases

Recently, many new approaches, study designs, and statistical and analytical methods have emerged for studying gene-environment interactions (G×Es) in large-scale studies of human populations. There are opportunities in this field, particularly with respect to the incorporation of -omics and next-generation sequencing data and continual improvement in measures of environmental exposures implicated in complex disease outcomes. In a workshop called "Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases," held October 17-18, 2014, by the National Institute of Environmental Health Sciences and the National Cancer Institute in conjunction with the annual American Society of Human Genetics meeting, participants explored new approaches and tools that have been developed in recent years for G×E discovery. This paper highlights current and critical issues and themes in G×E research that need additional consideration, including the improved data analytical methods, environmental exposure assessment, and incorporation of functional data and annotations.

Precision Nutrition for Targeting Lipid Metabolism in Colorectal Cancer

Cancer is a multistage and multifactorial condition with genetic and environmental factors modulating tumorogenesis and disease progression. Nevertheless, cancer is preventable, as one third of cancer deaths could be avoided by modifying key risk factors. Nutrients can directly affect fundamental cellular processes and are considered among the most important risk factors in colorectal cancer (CRC). Red and processed meat, poultry consumption, fiber, and folate are the best-known diet components that interact with colorectal cancer susceptibility. In addition, the direct association of an unhealthy diet with obesity and dysbiosis opens new routes in the understanding of how daily diet nutrients could influence cancer prognosis. In the “omics” era, traditional nutrition has been naturally evolved to precision nutrition where technical developments have contributed to a more accurate discipline. In this sense, genomic and transcriptomic studies have been extensively used in precision nutrition approaches. However, the relation between CRC carcinogenesis and nutrition factors is more complex than originally expected. Together with classical diet-nutrition-related genes, nowadays, lipid-metabolism-related genes have acquired relevant interest in precision nutrition studies. Lipids regulate very diverse cellular processes from ATP synthesis and the activation of essential cell-signaling pathways to membrane organization and plasticity. Therefore, a wide range of tumorogenic steps can be influenced by lipid metabolism, both in primary tumours and distal metastasis. The extent to which genetic variants, together with the intake of specific dietary components, affect the risk of CRC is currently under investigation, and new therapeutic or preventive applications must be explored in CRC models. In this review, we will go in depth into the study of co-occurring events, which orchestrate CRC tumorogenesis and are essential for the evolution of precision nutrition paradigms. Likewise, we will discuss the application of precision nutrition approaches to target lipid metabolism in CRC.

Genomic approaches to accelerate cancer interception

Although major advances have been reported in the last decade in the treatment of late-stage cancer with targeted and immune-based therapies, there is a crucial unmet need to develop new approaches to improve the prevention and early detection of cancer. Advances in genomics and computational biology offer unprecedented opportunities to understand the earliest molecular events associated with carcinogenesis, enabling novel strategies to intercept the development of invasive cancers. This Series paper will highlight emerging big data genomic approaches with the potential to accelerate advances in cancer prevention, screening, and early detection across various tumour types, and the challenges inherent in the development of these tools for clinical use. Through coordinated multicentre consortia, these genomic approaches are likely to transform the landscape of cancer interception in the coming years.

Interaction between genes and macronutrient intake on the risk of developing type 2 diabetes: systematic review and findings from European Prospective Investigation into Cancer (EPIC)-InterAct

Background: Gene-diet interactions have been reported to contribute to the development of type 2 diabetes (T2D). However, to our knowledge, few examples have been consistently replicated to date.Objective: We aimed to identify existing evidence for gene-macronutrient interactions and T2D and to examine the reported interactions in a large-scale study.Design: We systematically reviewed studies reporting gene-macronutrient interactions and T2D. We searched the MEDLINE, Human Genome Epidemiology Network, and WHO International Clinical Trials Registry Platform electronic databases to identify studies published up to October 2015. Eligibility criteria included assessment of macronutrient quantity (e.g., total carbohydrate) or indicators of quality (e.g., dietary fiber) by use of self-report or objective biomarkers of intake. Interactions identified in the review were subsequently examined in the EPIC (European Prospective Investigation into Cancer)-InterAct case-cohort study (n = 21,148, with 9403 T2D cases; 8 European countries). Prentice-weighted Cox regression was used to estimate country-specific HRs, 95% CIs, and P-interaction values, which were then pooled by random-effects meta-analysis. A primary model was fitted by using the same covariates as reported in the published studies, and a second model adjusted for additional covariates and estimated the effects of isocaloric macronutrient substitution.Results: Thirteen observational studies met the eligibility criteria (n < 1700 cases). Eight unique interactions were reported to be significant between macronutrients [carbohydrate, fat, saturated fat, dietary fiber, and glycemic load derived from self-report of dietary intake and circulating n-3 (ω-3) polyunsaturated fatty acids] and genetic variants in or near transcription factor 7-like 2 (TCF7L2), gastric inhibitory polypeptide receptor (GIPR), caveolin 2 (CAV2), and peptidase D (PEPD) (P-interaction < 0.05). We found no evidence of interaction when we tried to replicate previously reported interactions. In addition, no interactions were detected in models with additional covariates.Conclusions: Eight gene-macronutrient interactions were identified for the risk of T2D from the literature. These interactions were not replicated in the EPIC-InterAct study, which mirrored the analyses undertaken in the original reports. Our findings highlight the importance of independent replication of reported interactions.

Tumor necrosis factor alpha-238G/A polymorphism and risk of breast cancer: An update by meta-analysis

BACKGROUND

The association between the tumor necrosis factor-alpha gene (TNF-a) -238G/A polymorphism and the breast cancer has been analyzed in several studies, but the results have been inconclusive. We then performed a meta-analysis to get a precise estimation of the association.

METHODS

Eight case-control studies with a total of 37,257 cases and 39,564 controls were identified by searching the ISI Web of Knowledge database and the PubMed database up to August 2014.

RESULTS

Overall, no association was found between TNF-alpha-238G/A polymorphism and breast cancer in any of genetic model (additive model OR = 1.06, 95%CI: 0.94-1.21, Pheterogeneity = .02; homozygous model OR = 1.04, 95%CI: 0.83-1.30, Pheterogeneity = .98; dominant model OR = 1.06, 95%CI: 0.92-1.21, Pheterogeneity = .01; recessive model OR = 1.04, 95%CI: 0.83-1.30, Pheterogeneity = .98). Furthermore, no significant association was identified when stratified by ethnicity (Caucasian, Asian).

CONCLUSION

This meta-analysis indicated that the TNF-alpha-238G/A polymorphism is not associated with breast cancer risk in the overall population.

Pathway analysis of complex diseases for GWAS, extending to consider rare variants, multi-omics and interactions

BACKGROUND

Genome-wide association studies (GWAS) is a major method for studying the genetics of complex diseases. Finding all sequence variants to explain fully the aetiology of a disease is difficult because of their small effect sizes. To better explain disease mechanisms, pathway analysis is used to consolidate the effects of multiple variants, and hence increase the power of the study. While pathway analysis has previously been performed within GWAS only, it can now be extended to examining rare variants, other "-omics" and interaction data.

SCOPE OF REVIEW

1. Factors to consider in the choice of software for GWAS pathway analysis. 2. Examples of how pathway analysis is used to analyse rare variants, other "-omics" and interaction data.

MAJOR CONCLUSIONS

To choose appropriate software tools, factors for consideration include covariate compatibility, null hypothesis, one- or two-step analysis required, curation method of gene sets, size of pathways, and size of flanking regions to define gene boundaries. For rare variants, analysis performance depends on consistency between assumed and actual effect distribution of variants. Integration of other "-omics" data and interaction can better explain gene functions.

GENERAL SIGNIFICANCE

Pathway analysis methods will be more readily used for integration of multiple sources of data, and enable more accurate prediction of phenotypes.

Energy restriction at young age, genetic variants in the insulin-like growth factor pathway and colorectal cancer risk in the Netherlands Cohort Study

The energy restriction (ER)-colorectal cancer (CRC) association is inconsistent in literature. To strengthen the biological plausibility of the ER-CRC association, we investigated whether genetic variation in the insulin-like growth factor (IGF) pathway, a putative underlying mechanism, modulated this association in the Netherlands Cohort Study. Participants completed a questionnaire (n = 120,852) and provided toenail clippings for DNA (∼75%) at baseline. Individuals living in a Western city during the Hunger Winter (1944-45) or Western rural versus non-Western area were exposed to (severe) ER at young age. Genotyping was performed for 3,768 subcohort members and 2,580 CRC cases (case-cohort with 16.3 years follow-up). Cox hazard ratios for CRC were estimated across combined categories of ER and a genetic sum score of unfavorable alleles based on 18 single nucleotide polymorphisms in IGF-related genes and ER and an IGF1 19-CA repeat polymorphism. The reference included ER exposed individuals, so that increased hazard ratios were expected in higher combined categories for calculating relative excess risks due to interaction (additive interactions). Wald tests for multiplicative interactions were also performed. Multiplicative and additive interactions were nonsignificant. Combined ER-genetic sum score categories showed increasing CRC risks in men, but confidence intervals were wide. Women carrying two variant IGF1 19-CA repeat alleles versus those carrying two wild type IGF1 19-CA repeat alleles were at an ∼50% decreased CRC risk, irrespective of ER exposure. In conclusion, data indicate that the IGF pathway might be involved in the ER-CRC association in men, but not women, although interactions were nonsignificant, hampering definite conclusions.

Decreased risk of developing cancer in subjects carrying SLC52A3 rs13042395 polymorphism: proof from a meta-analysis

AIM

This study aimed to conduct a meta-analysis to explore the association between SLC52A3 rs13042395 polymorphism and cancer risk.

MATERIALS & METHODS

A comprehensive literature search was performed to confirm the relationship evaluated using STATA 12.0 software.

RESULTS

Overall, SLC52A3 rs13042395 C>T polymorphism was associated with cancer risk in two genetic models (TT vs CC: odds ratio: 0.86; 95% CI: 0.80-0.93; p < 0.001, TT vs CC + CT: odds ratio: 0.88; 95% CI: 0.82-0.95; p = 0.001). Significant associations were found between SLC52A3 rs13042395 polymorphism and decreased cancer risk among esophageal cancer, Asians, female, normal BMI and old age groups. No significant associations were observed in alcohol and smoking groups.

CONCLUSION

SLC52A3 rs13042395 C>T polymorphism might be a potential biomarker for cancer susceptibility.