Public health implications from COGS and potential for risk stratification and screening

An alternative model for (breast) cancer predisposition

While environmental factors can greatly increase cancer risk, it is clear that an individual’s genetic constitution has strong impact on tumor formation. Hereby we present an alternative cancer predisposition model built on the assumption that efficiencies of DNA maintenance mechanisms in normal cells are similar but not identical for each person. Small variations in an individual’s genetic constitution may result in slightly increased genomic instability and generate typical mutational signatures in normal cells. With recent and expected advances in the next-generation sequencing field, qualitative and quantitative establishment of such mutational signatures in normal tissue must become feasible, and may meanwhile provide a more accurate estimation of individual cancer risks, even in persons without familial antecedents. An additional advantage of this approach is that cancer risk assessment will not strictly rely on the individual’s genetic identity, but will also consider other factors (e.g., environmental and age) that can affect genomic integrity.

Comparison of the efficiency of colorectal cancer screening programs based on age and genetic risk for reduction of colorectal cancer mortality

Given that colorectal cancer risk depends partly on inherited factors, screening program efficiency may be increased by incorporating genetic factors. We compared the efficiency of screening based on age and genetic risk in a simulated population. We simulated a population matching the size, age distribution and colorectal cancer incidence and mortality of Australia. We also simulated the distribution of genetic risk for colorectal cancer based on the expected number of inherited risk alleles of 45 single-nucleotide polymorphisms (SNPs) previously reported as associated with colorectal cancer. We compared the expected colorectal cancer deaths under three screening programs; age-based, genetic-based and combined age-based and genetic-based. The age-based program would prevent 25.4 deaths per 100 000 invited to screen, none of which would be under age 50; the genetic program would prevent 26.2 deaths per 100 000 invited to screen, 16 of which would be under age 50; and the combined program would prevent 24.4 deaths per 100 000 invited to screen, 16 of which would be under age 50. Genetic testing of 1.5 million 45-49 year olds would identify 91% of the people aged under 50 at sufficient risk to warrant screening, potentially saving 16 colorectal cancer deaths each year. Screening eligibility based on genetic risk profile for age is as efficient as eligibility based on age alone for preventing colorectal cancer mortality, but identifies an additional 7% of the population at sufficient risk to benefit from screening who would not normally be screened given they are aged under 50 years.

Primary care providers' cancer genetic testing-related knowledge, attitudes, and communication behaviors: A systematic review and research agenda

BACKGROUND

Primary care providers (PCPs) can play a critical role in helping patients receive the preventive health benefits of cancer genetic risk information. Thus, the objective of this systematic review was to identify studies of US PCPs' knowledge, attitudes, and communication-related behaviors regarding genetic tests that could inform risk-stratification approaches for breast, colorectal, and prostate cancer screening in order to describe current findings and research gaps.

METHODS

We conducted a systematic search of six electronic databases to identify peer-reviewed empirical articles relating to US PCPs and genetic testing for breast, colorectal, or prostate cancer published in English from 2008 to 2016. We reviewed these data and used narrative synthesis methods to integrate findings into a descriptive summary and identify research needs.

RESULTS

We identified 27 relevant articles. Most focused on genetic testing for breast cancer (23/27) and colorectal cancer risk (12/27); only one study examined testing for prostate cancer risk. Most articles addressed descriptive research questions (24/27). Many studies (24/27) documented PCPs' knowledge, often concluding that providers' knowledge was incomplete. Studies commonly (11/27) examined PCPs' attitudes. Across studies, PCPs expressed some concerns about ethical, legal, and social implications of testing. Attitudes about the utility of clinical genetic testing, including for targeted cancer screening, were generally favorable; PCPs were more skeptical of direct-to-consumer testing. Relatively fewer studies (9/27) examined PCPs' communication practices regarding cancer genetic testing.

DISCUSSION

This review indicates a need for investigators to move beyond descriptive research questions related to PCPs' knowledge and attitudes about cancer genetic testing. Research is needed to address important gaps regarding the development, testing, and implementation of innovative interventions and educational programs that can improve PCPs' genetic testing knowledge, assuage concerns about the appropriateness of cancer genetic testing, and promote open and effective patient-provider communication about genetic risk and genetic testing.

The CRISP colorectal cancer risk prediction tool: an exploratory study using simulated consultations in Australian primary care

Background

In Australia, screening for colorectal cancer (CRC) with colonoscopy is meant to be reserved for people at increased risk, however, currently there is a mismatch between individuals’ risk of CRC and the type of CRC screening they receive.

This paper describes the development and optimisation of a Colorectal cancer RISk Prediction tool (‘CRISP’) for use in primary care. The aim of the CRISP tool is to increase risk-appropriate CRC screening.

Methods

CRISP development was informed by previous experience with developing risk tools for use in primary care and a systematic review of the evidence. A CRISP prototype was used in simulated consultations by general practitioners (GPs) with actors as patients. GPs were interviewed to explore their experience of using CRISP, and practice nurses (PNs) and practice managers (PMs) were interviewed after a demonstration of CRISP. Transcribed interviews and video footage of the ‘consultations’ were qualitatively analyzed. Themes arising from the data were mapped onto Normalization Process Theory (NPT).

Results

Fourteen GPs, nine PNs and six PMs were recruited from 12 clinics. Results were described using the four constructs of NPT: 1) Coherence: Clinicians understood the rationale behind CRISP, particularly since they were familiar with using risk tools for other conditions; 2) Cognitive participation: GPs welcomed the opportunity CRISP provided to discuss healthy and unhealthy behaviors with their patients, but many GPs challenged the screening recommendation generated by CRISP; 3) Collective Action: CRISP disrupted clinician-patient flow if the GP was less comfortable with computers. GP consultation time was a major implementation barrier and overall consensus was that PNs have more capacity and time to use CRISP effectively; 4) Reflexive monitoring: Limited systematic monitoring of new interventions is a potential barrier to the sustainable embedding of CRISP.

Conclusions

CRISP has the potential to improve risk-appropriate CRC screening in primary care but was considered more likely to be successfully implemented as a nurse-led intervention.

Recommendations on breast cancer screening and prevention in the context of implementing risk stratification: impending changes to current policies

In recent years, risk stratification has sparked interest as an innovative approach to disease screening and prevention. The approach effectively personalizes individual risk, opening the way to screening and prevention interventions that are adapted to subpopulations. The international perspective project, which is developing risk stratification for breast cancer, aims to support the integration of its screening approach into clinical practice through comprehensive tool-building. Policies and guidelines for risk stratification-unlike those for population screening programs, which are currently well regulated-are still under development. Indeed, the development of guidelines for risk stratification reflects the translational aspects of perspective. Here, we describe the risk stratification process that was devised in the context of perspective, and we then explain the consensus-based method used to develop recommendations for breast cancer screening and prevention in a risk-stratification approach. Lastly, we discuss how the recommendations might affect current screening policies.

A Pilot Randomized Controlled Trial of the Feasibility, Acceptability, and Impact of Giving Information on Personalized Genomic Risk of Melanoma to the Public

BACKGROUND

Communication of personalized melanoma genomic risk information may improve melanoma prevention behaviors.

METHODS

We evaluated the feasibility and acceptability of communicating personalized genomic risk of melanoma to the public and its preliminary impact on behaviors and psychosocial outcomes. One hundred eighteen people aged 22 to 69 years provided a saliva sample and were randomized to the control (nonpersonalized educational materials) or intervention (personalized booklet presenting melanoma genomic risk as absolute and relative risks and a risk category based on variants in 21 genes, telephone-based genetic counseling, and nonpersonalized educational materials). Intention-to-treat analyses overall and by-risk category were conducted using ANCOVA adjusted for baseline values.

RESULTS

Consent to participate was 41%, 99% were successfully genotyped, and 92% completed 3-month follow-up. Intervention participants reported high satisfaction with the personalized booklet (mean = 8.6, SD = 1.6; on a 0-10 scale) and genetic counseling (mean = 8.1, SD = 2.2). No significant behavioral effects at 3-month follow-up were identified between intervention and control groups overall: objectively measured standard erythemal doses per day [-16%; 95% confidence interval (CI), -43% to 24%] and sun protection index (0.05; 95% CI, -0.07 to 0.18). There was increased confidence identifying melanoma at 3 months (0.40; 95% CI, 0.10-0.69). Stratified by risk category, effect sizes for intentional tanning and some individual sun protection items appeared stronger for the average-risk group. There were no appreciable group differences in skin cancer-related worry or psychologic distress.

CONCLUSIONS

Our results demonstrate feasibility and acceptability of providing personalized genomic risk of melanoma to the public.

IMPACT

Genomic risk information has potential as a melanoma prevention strategy. Cancer Epidemiol Biomarkers Prev; 26(2); 212-21. ©2016 AACR.

Breast Cancer Risk From Modifiable and Nonmodifiable Risk Factors Among White Women in the United States

IMPORTANCE

An improved model for risk stratification can be useful for guiding public health strategies of breast cancer prevention.

OBJECTIVE

To evaluate combined risk stratification utility of common low penetrant single nucleotide polymorphisms (SNPs) and epidemiologic risk factors.

DESIGN, SETTING, AND PARTICIPANTS

Using a total of 17 171 cases and 19 862 controls sampled from the Breast and Prostate Cancer Cohort Consortium (BPC3) and 5879 women participating in the 2010 National Health Interview Survey, a model for predicting absolute risk of breast cancer was developed combining information on individual level data on epidemiologic risk factors and 24 genotyped SNPs from prospective cohort studies, published estimate of odds ratios for 68 additional SNPs, population incidence rate from the National Cancer Institute-Surveillance, Epidemiology, and End Results Program cancer registry and data on risk factor distribution from nationally representative health survey. The model is used to project the distribution of absolute risk for the population of white women in the United States after adjustment for competing cause of mortality.

EXPOSURES

Single nucleotide polymorphisms, family history, anthropometric factors, menstrual and/or reproductive factors, and lifestyle factors.

MAIN OUTCOMES AND MEASURES

Degree of stratification of absolute risk owing to nonmodifiable (SNPs, family history, height, and some components of menstrual and/or reproductive history) and modifiable factors (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared], menopausal hormone therapy [MHT], alcohol, and smoking).

RESULTS

The average absolute risk for a 30-year-old white woman in the United States developing invasive breast cancer by age 80 years is 11.3%. A model that includes all risk factors provided a range of average absolute risk from 4.4% to 23.5% for women in the bottom and top deciles of the risk distribution, respectively. For women who were at the lowest and highest deciles of nonmodifiable risks, the 5th and 95th percentile range of the risk distribution associated with 4 modifiable factors was 2.9% to 5.0% and 15.5% to 25.0%, respectively. For women in the highest decile of risk owing to nonmodifiable factors, those who had low BMI, did not drink or smoke, and did not use MHT had risks comparable to an average woman in the general population.

CONCLUSIONS AND RELEVANCE

This model for absolute risk of breast cancer including SNPs can provide stratification for the population of white women in the United States. The model can also identify subsets of the population at an elevated risk that would benefit most from risk-reduction strategies based on altering modifiable factors. The effectiveness of this model for individual risk communication needs further investigation.

Genetic testing and personalized ovarian cancer screening: a survey of public attitudes

Background

Advances in genetic technologies are expected to make population-wide genetic testing feasible. This could provide a basis for risk stratified cancer screening; but acceptability in the target populations has not been explored.

Methods

We assessed attitudes to risk-stratified ovarian cancer (OC) screening based on prior genetic risk assessment using a survey design. Home-based interviews were carried out by the UK Office of National Statistics in a population-based sample of 1095 women aged 18–74. Demographic and personal correlates of attitudes to risk-stratified OC screening based on prior genetic risk assessment were determined using univariate analyses and adjusted logistic regression models.

Results

Full data on the key analytic questions were available for 829 respondents (mean age 46 years; 27 % ‘university educated’; 93 % ‘White’). Relatively few respondents felt they were at ‘higher’ or ‘much higher’ risk of OC than other women of their age group (7.4 %, n = 61). Most women (85 %) said they would ‘probably’ or ‘definitely’ take up OC genetic testing; which increased to 88 % if the test also informed about breast cancer risk. Almost all women (92 %) thought they would ‘probably’ or ‘definitely’ participate in risk-stratified OC screening. In multivariate logistic regression models, university level education was associated with lower anticipated uptake of genetic testing (p = 0.009), but with more positive attitudes toward risk-stratified screening (p <0.001). Perceived risk was not significantly associated with any of the outcome variables.

Conclusions

These findings give confidence in taking forward research on integration of novel genomic technologies into mainstream healthcare.

Developing and evaluating polygenic risk prediction models for stratified disease prevention

Knowledge of genetics and its implications for human health is rapidly evolving in accordance with recent events, such as discoveries of large numbers of disease susceptibility loci from genome-wide association studies, the US Supreme Court ruling of the non-patentability of human genes, and the development of a regulatory framework for commercial genetic tests. In anticipation of the increasing relevance of genetic testing for the assessment of disease risks, this Review provides a summary of the methodologies used for building, evaluating and applying risk prediction models that include information from genetic testing and environmental risk factors. Potential applications of models for primary and secondary disease prevention are illustrated through several case studies, and future challenges and opportunities are discussed.

Constructing Hypothetical Risk Data from the Area under the ROC Curve: Modelling Distributions of Polygenic Risk

Background

Modeling studies using hypothetical polygenic risk data can be an efficient tool for investigating the effectiveness of downstream applications such as targeting interventions to risk groups to justify whether empirical investigation is warranted. We investigated the assumptions underlying a method that simulates risk data for specific values of the area under the receiver operating characteristic curve (AUC).

Methods

The simulation method constructs risk data for a hypothetical population based on the population disease risk, and the odds ratios and frequencies of genetic variants. By systematically varying the parameters, we investigated under what conditions AUC values represent unique ROC curves with unique risk distributions for patients and nonpatients, and to what extend risk data can be simulated for precise values of the AUC.

Results

Using larger number of genetic variants each with a modest effect, we observed that the distributions of estimated risks of patients and nonpatients were similar for various combinations of the odds ratios and frequencies of the risk alleles. Simulated ROC curves overlapped empirical curves with the same AUC.

Conclusions

Polygenic risk data can be effectively and efficiently created using a simulation method. This allows to further investigate the potential applications of stratifying interventions on the basis of polygenic risk.

Genetic screening for gynecological cancer: where are we heading?

The landscape of cancer genetics in gynecological oncology is rapidly changing. The traditional family history-based approach has limitations and misses >50% mutation carriers. This is now being replaced by population-based approaches. The need for changing the clinical paradigm from family history-based to population-based BRCA1/BRCA2 testing in Ashkenazi Jews is supported by data that demonstrate population-based BRCA1/BRCA2 testing does not cause psychological harm and is cost effective. This article covers various genetic testing strategies for gynecological cancers, including population-based approaches, panel and direct-to-consumer testing as well as the need for innovative approaches to genetic counseling. Advances in genetic testing technology and computational analytics have facilitated an integrated systems medicine approach, providing increasing potential for population-based genetic testing, risk stratification, and cancer prevention. Genomic information along-with biological/computational tools will be used to deliver predictive, preventive, personalized and participatory (P4) and precision medicine in the future.

Refining Breast Cancer Risk Stratification: Additional Genes, Additional Information

Recent advances in genomic technology have enabled far more rapid, less expensive sequencing of multiple genes than was possible only a few years ago. Advances in bioinformatics also facilitate the interpretation of large amounts of genomic data. New strategies for cancer genetic risk assessment include multiplex sequencing panels of 5 to more than 100 genes (in which rare mutations are often associated with at least two times the average risk of developing breast cancer) and panels of common single-nucleotide polymorphisms (SNPs), combinations of which are generally associated with more modest cancer risks (more than twofold). Although these new multiple-gene panel tests are used in oncology practice, questions remain about the clinical validity and the clinical utility of their results. To translate this increasingly complex genetic information for clinical use, cancer risk prediction tools are under development that consider the joint effects of all susceptibility genes, together with other established breast cancer risk factors. Risk-adapted screening and prevention protocols are underway, with ongoing refinement as genetic knowledge grows. Priority areas for future research include the clinical validity and clinical utility of emerging genetic tests; the accuracy of developing cancer risk prediction models; and the long-term outcomes of risk-adapted screening and prevention protocols, in terms of patients' experiences and survival.

Population genetic testing for cancer susceptibility: founder mutations to genomes

The current standard model for identifying carriers of high-risk mutations in cancer-susceptibility genes (CSGs) generally involves a process that is not amenable to population-based testing: access to genetic tests is typically regulated by health-care providers on the basis of a labour-intensive assessment of an individual's personal and family history of cancer, with face-to-face genetic counselling performed before mutation testing. Several studies have shown that application of these selection criteria results in a substantial proportion of mutation carriers being missed. Population-based genetic testing has been proposed as an alternative approach to determining cancer susceptibility, and aims for a more-comprehensive detection of mutation carriers. Herein, we review the existing data on population-based genetic testing, and consider some of the barriers, pitfalls, and challenges related to the possible expansion of this approach. We consider mechanisms by which population-based genetic testing for cancer susceptibility could be delivered, and suggest how such genetic testing might be integrated into existing and emerging health-care structures. The existing models of genetic testing (including issues relating to informed consent) will very likely require considerable alteration if the potential benefits of population-based genetic testing are to be fully realized.

Public preferences for communicating personal genomic risk information: a focus group study

Background

Personalized genomic risk information has the potential to motivate behaviour change and promote population health, but the success of this will depend upon effective risk communication strategies.

Objective

To determine preferences for different graphical and written risk communication formats, and the delivery of genomic risk information including the mode of communication and the role of health professionals.

Design

Focus groups, transcribed and analysed thematically.

Participants

Thirty‐four participants from the public.

Methods

Participants were provided with, and invited to discuss, a hypothetical scenario giving an individual's personalized genomic risk of melanoma displayed in several graphical formats.

Results

Participants preferred risk formats that were familiar and easy to understand, such as a ‘double pie chart’ and ‘100 person diagram’ (pictograph). The 100 person diagram was considered persuasive because it humanized and personalized the risk information. People described the pie chart format as resembling bank data and food (such as cake and pizza). Participants thought that email, web‐based platforms and postal mail were viable options for communicating genomic risk information. However, they felt that it was important that a health professional (either a genetic counsellor or ‘informed’ general practitioner) be available for discussion at the time of receiving the risk information, to minimize potential negative emotional responses and misunderstanding. Face‐to‐face or telephone delivery was preferred for delivery of high‐risk results.

Conclusions

These public preferences for communication strategies for genomic risk information will help to guide translation of genome‐based knowledge into improved population health.

Cancer risk assessment tools in primary care: a systematic review of randomized controlled trials

PURPOSE

We conducted this review to identify published randomized controlled trials (RCTs) of cancer risk assessment tools used in primary care and to determine their impact on clinical utility (clinicians), screening uptake (patients), and psychosocial outcomes (patients).

METHODS

We searched EMBASE, PubMed and the Cochrane databases for RCTs of cancer risk assessment tools in primary care up to May 2014. Only studies set in primary care, with patients eligible for screening, and English-language articles were included.

RESULTS

The review included 11 trials of 7 risk tools. The trials were heterogeneous with respect to type of tool that was used, type(s) of cancer assessed, and outcomes measured. Evidence suggested risk tools improved patient risk perception, knowledge, and screening intentions, but not necessarily screening behavior. Overall, uptake of a tool was greater if initiated by patients, if used by a dedicated clinician, and when combined with decision support. There was no increase in cancer worry. Health promotion messages within the tool had positive effects on behavior change. Trials were limited by low-recruitment uptake, and the heterogeneity of the findings necessitated a narrative review rather than a meta-analysis.

CONCLUSIONS

Risk tools may increase intentions to have cancer screening, but additional interventions at the clinician or health system levels may be needed to increase risk-appropriate cancer screening behavior.

Do Health Professionals Need Additional Competencies for Stratified Cancer Prevention Based on Genetic Risk Profiling?

There is growing evidence that inclusion of genetic information about known common susceptibility variants may enable population risk-stratification and personalized prevention for common diseases including cancer. This would require the inclusion of genetic testing as an integral part of individual risk assessment of an asymptomatic individual. Front line health professionals would be expected to interact with and assist asymptomatic individuals through the risk stratification process. In that case, additional knowledge and skills may be needed. Current guidelines and frameworks for genetic competencies of non-specialist health professionals place an emphasis on rare inherited genetic diseases. For common diseases, health professionals do use risk assessment tools but such tools currently do not assess genetic susceptibility of individuals. In this article, we compare the skills and knowledge needed by non-genetic health professionals, if risk-stratified prevention is implemented, with existing competence recommendations from the UK, USA and Europe, in order to assess the gaps in current competences. We found that health professionals would benefit from understanding the contribution of common genetic variations in disease risk, the rationale for a risk-stratified prevention pathway, and the implications of using genomic information in risk-assessment and risk management of asymptomatic individuals for common disease prevention.

Public interest in and acceptability of the prospect of risk-stratified screening for breast and prostate cancer

BACKGROUND

For risk-stratified screening to be implemented as a screening program for breast and prostate cancer it has to be accepted among the general population. Investigating public interest in stratified screening and its acceptability to the public is therefore essential since as yet little is known.

METHOD

Cross-sectional web survey sent to a sample of 10 000 individuals (20-74 years of age) representative of the Swedish population as registered in 2009.

RESULTS

Among the responders (28%), a vast majority (94%) expressed an interest in knowing their breast or prostate cancer risk and stated wanting to know to 'avoid worrying'. Men and women were equally interested in knowing their prostate and breast cancer risk, respectively. However, men showed more certainty. Trusting the healthcare workers with personal information (63%) as well as genetic information (70%), in order to calculate the risk, did not seem to be a major issue. Furthermore, 87% would agree to get screened more often if identified with a high risk, whereas, if identified with a low risk, only 27% would agree to get screened less often. Finally, although a consultation with a physician seemed to be the preferred way to communicate the risk, a majority would agree to receive it via a letter or a phone call.

CONCLUSION

Risk-stratified screening has the possibility to be accepted by the general public. Knowledge about interest and acceptability of the prospect of risk-stratified screening for breast and prostate cancer will help when implementing new screening strategies.

Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2

We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88-0.92]; P-value = 1.58 × 10(-25)). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08-1.17]; P-value = 7.89 × 10(-09)) and rs13294895 (OR = 1.09 [1.06-1.12]; P-value = 2.97 × 10(-11)). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06-1.18]; P-value = 2.77 × 10(-05)). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis.

Prediction of breast cancer risk based on profiling with common genetic variants

BACKGROUND

Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking.

METHODS

We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates.

RESULTS

There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer.

CONCLUSIONS

The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.

Associations between breast density and a panel of single nucleotide polymorphisms linked to breast cancer risk: a cohort study with digital mammography

Background

Breast density and single-nucleotide polymorphisms (SNPs) have both been associated with breast cancer risk. To determine the extent to which these two breast cancer risk factors are associated, we investigate the association between a panel of validated SNPs related to breast cancer and quantitative measures of mammographic density in a cohort of Caucasian and African-American women.

Methods

In this IRB-approved, HIPAA-compliant study, we analyzed a screening population of 639 women (250 African American and 389 Caucasian) who were tested with a validated panel assay of 12 SNPs previously associated to breast cancer risk. Each woman underwent digital mammography as part of routine screening and all were interpreted as negative. Both absolute and percent estimates of area and volumetric density were quantified on a per-woman basis using validated software. Associations between the number of risk alleles in each SNP and the density measures were assessed through a race-stratified linear regression analysis, adjusted for age, BMI, and Gail lifetime risk.

Results

The majority of SNPs were not found to be associated with any measure of breast density. SNP rs3817198 (in LSP1) was significantly associated with both absolute area (p = 0.004) and volumetric (p = 0.019) breast density in Caucasian women. In African-American women, SNPs rs3803662 (in TNRC9/TOX3) and rs4973768 (in NEK10) were significantly associated with absolute (p = 0.042) and percent (p = 0.028) volume density respectively.

Conclusions

The majority of SNPs investigated in our study were not found to be significantly associated with breast density, even when accounting for age, BMI, and Gail risk, suggesting that these two different risk factors contain potentially independent information regarding a woman’s risk to develop breast cancer. Additionally, the few statistically significant associations between breast density and SNPs were different for Caucasian versus African American women. Larger prospective studies are warranted to validate our findings and determine potential implications for breast cancer risk assessment.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1159-3) contains supplementary material, which is available to authorized users.

HIV testing behaviour and use of risk reduction strategies by HIV risk category among MSM in Vancouver

We carried out an analysis of a serobehavioural study of men who have sex with men >19 years of age in Vancouver, Canada to examine HIV testing behaviour and use of risk reduction strategies by HIV risk category, as defined by routinely gathered clinical data. We restricted our analysis to those who self-identified as HIV-negative, completed a questionnaire, and provided a dried blood spot sample. Of 842 participants, 365 (43.3%) were categorised as lower-risk, 245 (29.1%) as medium-risk and 232 (27.6%) as higher-risk. The prevalence of undiagnosed HIV infection was low (lower 0.8%, medium 3.3%, higher 3.9%; p = 0.032). Participants differed by risk category in terms of having had an HIV test in the previous year (lower 46.5%, medium 54.6%, higher 67.0%; p < 0.001) and in their use of serosorting (lower 23.3%, medium 48.3%, higher 43.1%; p < 0.001) and only having sex with HIV-positive men if those men had low viral loads or were taking HIV medication (lower 5.1%, medium 4.8%, higher 10.9%; p = 0.021) as risk reduction strategies. These findings speak to the need to consider segmented health promotion services for men who have sex with men with differing risk profiles. Risk stratification could be used to determine who might benefit from tailored multiple health promotion interventions, including HIV pre-exposure prophylaxis.

The Human Genome Project, and recent advances in personalized genomics

The language of “personalized medicine” and “personal genomics” has now entered the common lexicon. The idea of personalized medicine is the integration of genomic risk assessment alongside other clinical investigations. Consistent with this approach, testing is delivered by health care professionals who are not medical geneticists, and where results represent risks, as opposed to clinical diagnosis of disease, to be interpreted alongside the entirety of a patient’s health and medical data. In this review we consider the evidence concerning the application of such personalized genomics within the context of population screening, and potential implications that arise from this. We highlight two general approaches which illustrate potential uses of genomic information in screening. The first is a narrowly targeted approach in which genetic profiling is linked with standard population-based screening for diseases; the second is a broader targeting of variants associated with multiple single gene disorders, performed opportunistically on patients being investigated for unrelated conditions. In doing so we consider the organization and evaluation of tests and services, the challenge of interpretation with less targeted testing, professional confidence, barriers in practice, and education needs. We conclude by discussing several issues pertinent to health policy, namely: avoiding the conflation of genetics with biological determinism, resisting the “technological imperative”, due consideration of the organization of screening services, the need for professional education, as well as informed decision making and public understanding.

From candidate gene studies to GWAS and post-GWAS analyses in breast cancer

There are now more than 90 established breast cancer risk loci, with 57 new ones, revealed through genome-wide-association studies (GWAS) during the last two years. Established high, moderate and low penetrance genetic variants currently explain ∼49% of familial breast cancer risk. GWAS-discovered variants account for 14%, and it is estimated that another 1000 yet-to-be-discovered loci could contribute an additional ∼14% of familial risk. Polygenic risk scores can already be used to stratify breast cancer risk in the female population and could improve the targeting of mammographic screening programmes, which are at present largely based on age-specific risks. Fine-scale mapping and functional analyses are revealing candidate causal variants and the molecular mechanisms by which GWAS-hits may act. Better-powered GWAS and genome-wide sequencing projects are likely to continue identifying new breast cancer causal variants.

The increase in cancer prevalence and hospital burden in Western Australia, 1992-2011

PURPOSE

To describe cancer prevalence and hospital service utilization by prevalent cancer patients in Western Australia from 1992 to 2011.

METHODS

This study was a population-based cohort study using the Western Australia (WA) Cancer Registry (1982 to 2011) as the source of incident cancer cases. These data were linked to mortality (1982 to 2011) and hospital morbidity (1998 to 2011) records via the WA Data Linkage System to ascertain complete and limited-duration prevalence and cancer-related hospitalizations over time. Prevalence rates were calculated using estimated residential population data from the Australian Bureau of Statistics.

RESULTS

In 2011, one in every 27 people living in WA had been diagnosed with cancer at some time in their lifetime, and one in 68 had been diagnosed within the previous five years. Between 1992 and 2011, complete cancer prevalence in Western Australia increased by a magnitude of 2.5-fold. Forty-five and 44% of the increase in complete cancer prevalence in males and females between 1992 and 2011 can be attributed to prostate and breast cancer, respectively. The absolute number of cancer-related bed days increased 81 and 74% in males and females, respectively, diagnosed within one year, between 1998 and 2011.

CONCLUSIONS

The prevalence of cancer and the burden it places on hospitals continues to rise, demanding ongoing efforts to prevent cancer through modifiable risk factors and better, more efficient use of health resources. Steps should to be taken to understand and address overdiagnosis and overtreatment.

The impact of genomics on public health practice

INTRODUCTION

Genomic science is developing rapidly, and engagement of public health professionals will be necessary to appraise new technologies and use them effectively.

SOURCES OF DATA

We use established domains of public health and draw on the literature and expert knowledge to illustrate how genomic technologies give rise to new applications.

AREAS OF AGREEMENT

Genomic technologies are useful in rare inherited disease, including population screening programmes, in health care and for surveillance, diagnosis and treatment of infectious disease.

AREAS OF CONTROVERSY

It is less clear when and how genetic susceptibility testing will be used for common chronic disease prevention or protection from environmental hazards.

GROWING POINTS

Developments in public health practice will be necessary to ensure rapid and effective implementation of genomic science.

AREAS TIMELY FOR DEVELOPING RESEARCH

Public health researchers should address how to accelerate the implementation of genomics for health benefit in developed and developing countries.

For debate: a new wave in public health improvement

The rising burden of chronic disease poses a challenge for all public health systems and requires innovative approaches to effectively improve population health. Persisting inequalities in health are of particular concern. Disadvantage because of education, income, or social position is associated with a larger burden of disease and, in particular, multimorbidity. Although much has been achieved to enhance population health, challenges remain, and approaches need to be revisited. In this paper, we join the debate about how a new wave of public health improvement might look. We start from the premise that population health improvement is conditional on a health-promoting societal context. It is characterised by a culture in which healthy behaviours are the norm, and in which the institutional, social, and physical environment support this mindset. Achievement of this ambition will require a positive, holistic, eclectic, and collaborative effort, involving a broad range of stakeholders. We emphasise three mechanisms: maximisation of the value of health and incentives for healthy behaviour; promotion of healthy choices as default; and minimisation of factors that create a culture and environment which promote unhealthy behaviour. We give examples of how these mechanisms might be achieved.

Combined associations of genetic and environmental risk factors: implications for prevention of breast cancer

Genome-wide association studies (GWAS) have identified hundreds of genetic susceptibility loci for cancers and other complex diseases. However, the public health and clinical relevance of these discoveries is unclear. Evaluating the combined associations of genetic and environmental risk factors, particularly those that can be modified, will be critical in assessing the utility of genetic information for risk stratified prevention. In this commentary, using breast cancer as a model, we show that genetic information in combination with other risk factors can provide levels of risk stratification that could be useful for individual decision-making or population-based prevention programs. Our projections are theoretical and rely on a number of assumptions, including multiplicative models for the combined associations of the different risk factors, which need confirmation. Thus, analyses of epidemiological studies with high-quality risk factor information, as well as prevention trials, are needed to empirically assess the impact of genetics in risk stratified prevention.

Risk determination and prevention of breast cancer

Breast cancer is an increasing public health problem. Substantial advances have been made in the treatment of breast cancer, but the introduction of methods to predict women at elevated risk and prevent the disease has been less successful. Here, we summarize recent data on newer approaches to risk prediction, available approaches to prevention, how new approaches may be made, and the difficult problem of using what we already know to prevent breast cancer in populations. During 2012, the Breast Cancer Campaign facilitated a series of workshops, each covering a specialty area of breast cancer to identify gaps in our knowledge. The risk-and-prevention panel involved in this exercise was asked to expand and update its report and review recent relevant peer-reviewed literature. The enlarged position paper presented here highlights the key gaps in risk-and-prevention research that were identified, together with recommendations for action. The panel estimated from the relevant literature that potentially 50% of breast cancer could be prevented in the subgroup of women at high and moderate risk of breast cancer by using current chemoprevention (tamoxifen, raloxifene, exemestane, and anastrozole) and that, in all women, lifestyle measures, including weight control, exercise, and moderating alcohol intake, could reduce breast cancer risk by about 30%. Risk may be estimated by standard models potentially with the addition of, for example, mammographic density and appropriate single-nucleotide polymorphisms. This review expands on four areas: (a) the prediction of breast cancer risk, (b) the evidence for the effectiveness of preventive therapy and lifestyle approaches to prevention, (c) how understanding the biology of the breast may lead to new targets for prevention, and (d) a summary of published guidelines for preventive approaches and measures required for their implementation. We hope that efforts to fill these and other gaps will lead to considerable advances in our efforts to predict risk and prevent breast cancer over the next 10 years.

Type II transmembrane serine protease gene variants associate with breast cancer

Type II transmembrane serine proteases (TTSPs) are related to tumor growth, invasion, and metastasis in cancer. Genetic variants in these genes may alter their function, leading to cancer onset and progression, and affect patient outcome. Here, 464 breast cancer cases and 370 controls were genotyped for 82 single-nucleotide polymorphisms covering eight genes. Association of the genotypes was estimated against breast cancer risk, breast cancer-specific survival, and survival in different treatment groups, and clinicopathological variables. SNPs in TMPRSS3 (rs3814903 and rs11203200), TMPRSS7 (rs1844925), and HGF (rs5745752) associated significantly with breast cancer risk (Ptrend = 0.008-0.042). SNPs in TMPRSS1 (rs12151195 and rs12461158), TMPRSS2 (rs2276205), TMPRSS3 (rs3814903), and TMPRSS7 (rs2399403) associated with prognosis (P = 0.004-0.046). When estimating the combined effect of the variants, the risk of breast cancer was higher with 4-5 alleles present compared to 0-2 alleles (P = 0.0001; OR, 2.34; 95% CI, 1.39-3.94). Women with 6-8 survival-associating alleles had a 3.3 times higher risk of dying of breast cancer compared to women with 1-3 alleles (P = 0.001; HR, 3.30; 95% CI, 1.58-6.88). The results demonstrate the combined effect of variants in TTSPs and their related genes in breast cancer risk and patient outcome. Functional analysis of these variants will lead to further understanding of this gene family, which may improve individualized risk estimation and development of new strategies for treatment of breast cancer.

Medical genetic counseling for breast cancer in primary care: a synthesis of major determinants of physicians' practices in primary care settings

OBJECTIVES

This paper aims to identify relevant potential predictors of medical genetic counseling for breast cancer (MGC-BC) in primary care and to develop a comprehensive questionnaire to study MGC-BC.

METHODS

A scoping review was conducted to identify the predictors of MGC-BC among primary care physicians. Relevant articles were identified in selected databases (PubMed, Embase, CINAHL, ISI Web of Science, PsycINFO, and Cochrane CENTRAL) and 4 selected relevant electronic journals.

RESULTS

An inductive analysis of the 193 quantitatively tested variables, conducted by 3 researchers, showed that 6 conceptual categories of determinants, namely (1) demographic, (2) organizational, (3) experiential, (4) professional, (5) psychological, and (6) cognitive, influence MGC-BC practices.

CONCLUSION

There is a scarcity of literature addressing the medical behavior determinants of MGC-BC. Future research is needed to identify effective strategies put into action to support the integration of MGC-BC in primary care medical practices and routines. However, our results shed light on 2 levels of actions that could improve genetic counseling services in primary care: (1) medical training and educational efforts emphasizing family history collection (individual level), and (2) clarification of roles and responsibilities in ordering and referral practices in genetic counseling and genetic testing for better healthcare management (organizational level).

Cancer screening and genetics: a tale of two paradigms

The long-standing medical tradition to "first do no harm" is reflected in population-wide evidence-based recommendations for cancer screening tests that focus primarily on reducing morbidity and mortality. The conventional cancer screening process is predicated on finding early-stage disease that can be treated effectively; yet emerging genetic and genomic testing technologies have moved the target earlier in the disease development process to identify a probabilistic predisposition to disease. Genetic risk information can have varying implications for the health and well-being of patients and their relatives, and has raised important questions about the evaluation and value of risk information. This article explores the paradigms that are being applied to the evaluation of conventional cancer screening tests and emerging genetic and genomic tests of cancer susceptibility, and how these perspectives are shifting and evolving in response to advances in our ability to detect cancer risks. We consider several challenges germane to the evaluation of both categories of tests, including defining benefits and harms in terms of personal and clinical utility, addressing healthcare consumers' information preferences, and managing scientific uncertainty. We encourage research and dialogue aimed at developing a better understanding of the value of all risk information, nongenetic and genetic, to people's lives. Cancer Epidemiol Biomarkers Prev; 23(6); 909-16. ©2014 AACR.

Stakeholder consultation insights on the future of genomics at the clinical-public health interface

In summer 2011, the Centers for Disease Control and Prevention Office of Public Health Genomics conducted a stakeholder consultation, administered by the University of Michigan Center for Public Health and Community Genomics, and Genetic Alliance, to recommend priorities for public health genomics from 2012 through 2017. Sixty-two responses from health professionals, administrators, and members of the public were pooled with 2 sets of key informant interviews and 3 discussion groups. NVivo 9 and manual methods were used to organize themes. This review offers an interim analysis of progress with respect to the final recommendations, which demonstrated a strong interest in moving genomic discoveries toward implementation and comparative effectiveness (T3/T4) translational research. A translational research continuum exists with familial breast and ovarian cancer at one end and prostate cancer at the other. Cascade screening for inherited arrhythmia syndromes and hypercholesterolemia lags stakeholder recommendations in the United States but not in Europe; implementation of health service-based screening for Lynch syndrome, and integration into electronic health information systems, is on pace with the recommended timeline. A number of options exist to address deficits in the funding of translational research, particularly for oncogenomic gene expression profiling. The goal of personalized risk assessment necessitates both research progress (eg, in whole genome sequencing, as well as provider education in the differentiation of low- vs high-risk status. The public health approach supports an emphasis on genetic test validation while endorsing clinical translation research inclusion of an environmental and population-based perspective.

'Personalized medicine': what's in a name?

Over the last decade genomics and other molecular biosciences have enabled new capabilities that, according to many, have the potential to revolutionize medicine and healthcare. These developments have been associated with a range of terminologies, including 'precision', 'personalized', 'individualized' and 'stratified' medicine. In this article, based on a literature review, we examine how the terms have arisen and their various meanings and definitions. We discuss the impact of the new technologies on disease classification, prevention and management. We suggest that although genomics and molecular biosciences will undoubtedly greatly enhance the power of medicine, they will not lead to a conceptually new paradigm of medical care. What is new is the portfolio of modern tools that medicine and healthcare can use for better targeted approaches to health and disease management, and the sociopolitical contexts within which these tools are applied.

Cancer genomics and inherited risk

Next-generation sequencing (NGS) has enabled whole-exome and whole-genome sequencing of tumors for causative mutations, allowing for more accurate targeting of therapies. In the process of sequencing the tumor, comparisons to the germline genome may identify variants associated with susceptibility to cancer as well as other hereditary diseases. Already, the combination of massively parallel sequencing and selective capture approaches has facilitated efficient simultaneous genetic analysis (multiplex testing) of large numbers of candidate genes. As the field of oncology incorporates NGS approaches into tumor and germline analyses, it has become clear that the ability to achieve high-throughput genotyping surpasses our current ability to interpret and appropriately apply the vast amounts of data generated from such technologies. A review of the current state of knowledge of rare and common genetic variants associated with cancer risk or treatment outcome reveals significant progress, as well as a number of challenges associated with the clinical translation of these discoveries. The combined efforts of oncologists, genetic counselors, and cancer geneticists will be required to drive the paradigm shift toward personalized or precision medicine and to ensure the incorporation of NGS technologies into the practice of preventive oncology.

Essential elements of personalized medicine

OBJECTIVES

Genomic information has been promoted as the basis for "personalized" health care. We considered the benefits provided by genomic testing in context of the concept of personalized medicine.

MATERIALS AND METHODS

We evaluated current and potential uses of genomic testing in health care, using prostate cancer as an example, and considered their implications for individualizing or otherwise improving health care.

RESULTS AND CONCLUSIONS

Personalized medicine is most accurately seen as a comprehensive effort to tailor health care to the individual, spanning multiple dimensions. While genomic tests will offer many potential opportunities to improve the delivery of care, including the potential for genomic research to offer opportunities to improve prostate cancer screening and treatment, such advances do not in themselves constitute a paradigm shift in the delivery of health care. Rather, personalized medicine is based on a partnership between clinician and patient that utilizes shared decision making to determine the best health care options among the available choices, weighing the patient's personal values and preferences together with clinical findings. This approach is particularly important for difficult clinical decisions involving uncertainty and trade-offs, such as those involved in prostate cancer screening and management. The delivery of personalized medicine also requires adequate health care access and assurance that basic health needs have been met. Substantial research investment will be needed to identify how genomic tests can contribute to this effort.

Ovarian cancer screening--current status, future directions

Evidence of a mortality benefit continues to elude ovarian cancer (OC) screening. Data from the US Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial which used a screening strategy incorporating CA125 cut-off and transvaginal ultrasound has not shown mortality benefit. The United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) is using the Risk of Ovarian Cancer (ROC) time series algorithm to interpret CA125, which has shown an encouraging sensitivity and specificity however the mortality data will only be available in 2015. The article explores the impact of growing insights into disease aetiology and evolution and biomarker discovery on future screening strategies. A better understanding of the target lesion, improved design of biomarker discovery studies, a focus on detecting low volume disease using cancer specific markers, novel biospecimens such as cervical cytology and targeted imaging and use of time series algorithms for interpreting markers profile suggests that a new era in screening is underway.

Inherited genetic susceptibility to breast cancer: the beginning of the end or the end of the beginning?

Genome-wide association studies have identified 72 loci associated with breast cancer susceptibility. Seventeen of these are known to predispose to other cancers. High-penetrance susceptibility loci for breast cancer usually result from coding alterations, principally in genes involved in DNA repair, whereas almost all of the associations identified through genome-wide association studies are found in noncoding regions of the genome and are likely to involve regulation of genes in multiple pathways. However, the genes underlying most associations are not yet known. In this review, we summarize the findings from genome-wide association studies in breast cancer and describe the genes and mechanisms that are likely to be involved in the tumorigenesis process. We also discuss approaches to fine-scale mapping of susceptibility regions used to identify the likely causal variant(s) underlying the associations, a major challenge in genetic epidemiology. Finally, we discuss the potential impact of such findings on personalized medicine and future avenues for screening, prediction, and prevention programs.

Hereditary breast cancer: ever more pieces to the polygenic puzzle

Several susceptibility genes differentially impact on the lifetime risk for breast cancer. Technological advances over the past years have enabled the detection of genetic risk factors through high-throughput screening of large breast cancer case-control series. High- to intermediate penetrance alleles have now been identified in more than 20 genes involved in DNA damage signalling and repair, and more than 70 low-penetrance loci have been discovered through recent genome-wide association studies. In addition to classical germ-line mutation and single-nucleotide polymorphism, copy number variation and somatic mosaicism have been proposed as potential predisposing mechanisms. Many of the identified loci also appear to influence breast tumour characteristics such as estrogen receptor status. In this review, we briefly summarize present knowledge about breast cancer susceptibility genes and discuss their implications for risk prediction and clinical practice.

Public attitudes towards genomic risk profiling as a component of routine population screening

Including low penetrance genomic variants in population-based screening might enable personalization of screening intensity and follow up. The application of genomics in this way requires formal evaluation. Even if clinically beneficial, uptake would still depend on the attitudes of target populations. We developed a deliberative workshop on two hypothetical applications (in colorectal cancer and newborn screening) in which we applied stepped, neutrally-framed, information sets. Data were collected using nonparticipant observation, free-text comments by individual participants, and a structured survey. Qualitative data were transcribed and analyzed using thematic content analysis. Eight workshops were conducted with 170 individuals (120 colorectal cancer screening and 50 newborn screening for type 1 diabetes). The use of information sets promoted informed deliberation. In both contexts, attitudes appeared to be heavily informed by assessments of the likely validity of the test results and its personal and health care utility. Perceived benefits included the potential for early intervention, prevention, and closer monitoring while concerns related to costs, education needs regarding the probabilistic nature of risk, the potential for worry, and control of access to personal genomic information. Differences between the colorectal cancer and newborn screening groups appeared to reflect different assessments of potential personal utility, particularly regarding prevention.

Personalized screening for cancers: should we consider polygenic profiling?

Polygenic profiling and risk stratification for population-based screening for cancer improve the efficiency of the screening programs. Translation of genomics into personalized screening programs requires evidence from empirical research on the balance of benefits and harms of personalized screening, and engagement with the public, professionals and policy makers.

Cancer systems biology in the genome sequencing era: part 2, evolutionary dynamics of tumor clonal networks and drug resistance

A tumor often consists of multiple cell subpopulations (clones). Current chemo-treatments often target one clone of a tumor. Although the drug kills that clone, other clones overtake it and the tumor recurs. Genome sequencing and computational analysis allows to computational dissection of clones from tumors, while singe-cell genome sequencing including RNA-Seq allows profiling of these clones. This opens a new window for treating a tumor as a system in which clones are evolving. Future cancer systems biology studies should consider a tumor as an evolving system with multiple clones. Therefore, topics discussed in Part 2 of this review include evolutionary dynamics of clonal networks, early-warning signals (e.g., genome duplication events) for formation of fast-growing clones, dissecting tumor heterogeneity, and modeling of clone-clone-stroma interactions for drug resistance. The ultimate goal of the future systems biology analysis is to obtain a 'whole-system' understanding of a tumor and therefore provides a more efficient and personalized management strategies for cancer patients.