Circulating tumour-derived KRAS mutations in pancreatic cancer cases are predominantly carried by very short fragments of cell-free DNA.

BACKGROUND: The DNA released into the bloodstream by malignant tumours· called circulating tumour DNA (ctDNA), is often a small fraction of total cell-free DNA shed predominantly by hematopoietic cells and is therefore challenging to detect. Understanding the biological properties of ctDNA is key to the investigation of its clinical relevance as a non-invasive marker for cancer detection and monitoring. METHODS: We selected 40 plasma DNA samples of pancreatic cancer cases previously reported to carry a KRAS mutation at the 'hotspot' codon 12 and re-screened the cell-free DNA using a 4-size amplicons strategy (57 bp, 79 bp, 167 bp and 218 bp) combined with ultra-deep sequencing in order to investigate whether amplicon lengths could impact on the capacity of detection of ctDNA, which in turn could provide inference of ctDNA and non-malignant cell-free DNA size distribution. FINDINGS: Higher KRAS amplicon size (167 bp and 218 bp) was associated with lower detectable cell-free DNA mutant allelic fractions (p < 0·0001), with up to 4·6-fold (95% CI: 2·6-8·1) difference on average when comparing the 218bp- and the 57bp-amplicons. The proportion of cases with detectable KRAS mutations was also hampered with increased amplicon lengths, with only half of the cases having detectable ctDNA using the 218 bp assay relative to those detected with amplicons less than 80 bp. INTERPRETATION: Tumour-derived mutations are carried by shorter cell-free DNA fragments than fragments of wild-type allele. Targeting short amplicons increases the sensitivity of cell-free DNA assays for pancreatic cancer and should be taken into account for optimized assay design and for evaluating their clinical performance. FUNDING: IARC; MH CZ - DRO; MH SK; exchange program between IARC and Sao Paulo medical Sciences; French Cancer League.

KRAS mutations in blood circulating cell-free DNA: a pancreatic cancer case-control.

The utility of KRAS mutations in plasma circulating cell-free DNA (cfDNA) samples as non-invasive biomarkers for the detection of pancreatic cancer has never been evaluated in a large case-control series. We applied a KRAS amplicon-based deep sequencing strategy combined with analytical pipeline specifically designed for the detection of low-abundance mutations to screen plasma samples of 437 pancreatic cancer cases, 141 chronic pancreatitis subjects, and 394 healthy controls. We detected mutations in 21.1% (N=92) of cases, of whom 82 (89.1%) carried at least one mutation at hotspot codons 12, 13 or 61, with mutant allelic fractions from 0.08% to 79%. Advanced stages were associated with an increased proportion of detection, with KRAS cfDNA mutations detected in 10.3%, 17,5% and 33.3% of cases with local, regional and systemic stages, respectively. We also detected KRAS cfDNA mutations in 3.7% (N=14) of healthy controls and in 4.3% (N=6) of subjects with chronic pancreatitis, but at significantly lower allelic fractions than in cases. Combining cfDNA KRAS mutations and CA19-9 plasma levels on a limited set of case-control samples did not improve the overall performance of the biomarkers as compared to CA19-9 alone. Whether the limited sensitivity and specificity observed in our series of KRAS mutations in plasma cfDNA as biomarkers for pancreatic cancer detection are attributable to methodological limitations or to the biology of cfDNA should be further assessed in large case-control series.

The time-evolution of DCIS size distributions with applications to breast cancer growth and progression.

Ductal carcinoma in situ (DCIS) lesions are non-invasive tumours of the breast that are thought to precede most invasive breast cancers (IBCs). As individual DCIS lesions are initiated, grow and invade (i.e. become IBC), the size distribution of the DCIS lesions present in a given human population will evolve. We derive a differential equation governing this evolution and show, for given assumptions about growth and invasion, that there is a unique distribution which does not vary with time. Further, we show that any initial distribution converges to this stationary distribution exponentially quickly. Therefore, it is reasonable to assume that the stationary distribution governs the size of DCIS lesions in human populations which are relatively stable with respect to the determinants of breast cancer. Based on this assumption and the size data of 110 DCIS lesions detected in a mammographic screening programme between 1993 and 2000, we produce maximum likelihood estimates for certain growth and invasion parameters. Assuming that DCIS size is proportional to a positive power p of the time since tumour initiation, we estimate p to be 0.50 with a 95% confidence interval of (0.35, 0.71). Therefore, we estimate that DCIS lesions follow a square-root growth law and hence that they grow rapidly when small and relatively slowly when large. Our approach and results should be useful for other mathematical studies of cancer, especially those investigating biological mechanisms of invasion.

Cancer risk in 680,000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 million Australians.

OBJECTIVE: To assess the cancer risk in children and adolescents following exposure to low dose ionising radiation from diagnostic computed tomography (CT) scans. DESIGN: Population based, cohort, data linkage study in Australia. COHORT MEMBERS: 10.9 million people identified from Australian Medicare records, aged 0-19 years on 1 January 1985 or born between 1 January 1985 and 31 December 2005; all exposures to CT scans funded by Medicare during 1985-2005 were identified for this cohort. Cancers diagnosed in cohort members up to 31 December 2007 were obtained through linkage to national cancer records. MAIN OUTCOME: Cancer incidence rates in individuals exposed to a CT scan more than one year before any cancer diagnosis, compared with cancer incidence rates in unexposed individuals. RESULTS: 60,674 cancers were recorded, including 3150 in 680,211 people exposed to a CT scan at least one year before any cancer diagnosis. The mean duration of follow-up after exposure was 9.5 years. Overall cancer incidence was 24% greater for exposed than for unexposed people, after accounting for age, sex, and year of birth (incidence rate ratio (IRR) 1.24 (95% confidence interval 1.20 to 1.29); P<0.001). We saw a dose-response relation, and the IRR increased by 0.16 (0.13 to 0.19) for each additional CT scan. The IRR was greater after exposure at younger ages (P<0.001 for trend). At 1-4, 5-9, 10-14, and 15 or more years since first exposure, IRRs were 1.35 (1.25 to 1.45), 1.25 (1.17 to 1.34), 1.14 (1.06 to 1.22), and 1.24 (1.14 to 1.34), respectively. The IRR increased significantly for many types of solid cancer (digestive organs, melanoma, soft tissue, female genital, urinary tract, brain, and thyroid); leukaemia, myelodysplasia, and some other lymphoid cancers. There was an excess of 608 cancers in people exposed to CT scans (147 brain, 356 other solid, 48 leukaemia or myelodysplasia, and 57 other lymphoid). The absolute excess incidence rate for all cancers combined was 9.38 per 100,000 person years at risk, as of 31 December 2007. The average effective radiation dose per scan was estimated as 4.5 mSv. CONCLUSIONS: The increased incidence of cancer after CT scan exposure in this cohort was mostly due to irradiation. Because the cancer excess was still continuing at the end of follow-up, the eventual lifetime risk from CT scans cannot yet be determined. Radiation doses from contemporary CT scans are likely to be lower than those in 1985-2005, but some increase in cancer risk is still likely from current scans. Future CT scans should be limited to situations where there is a definite clinical indication, with every scan optimised to provide a diagnostic CT image at the lowest possible radiation dose.

Childhood infections and the risk of asthma: a longitudinal study over 37 years.

BACKGROUND: Few studies have examined common childhood infections and adult asthma. We examined associations between childhood infectious diseases, childhood pneumonia, and current, persisting, and incident asthma to middle age. METHODS: We analyzed data from the Tasmanian Longitudinal Health Study (TAHS). A history of pneumonia was ascertained from their parents when the TAHS participants were 7 years old. Measles, rubella, mumps, chickenpox, diphtheria, and pertussis were identified from school medical records. Associations with current, persisting, or incident asthma were examined using regression techniques. RESULTS: Greater infectious diseases load was negatively associated with persisting asthma at all ages. Individually, pertussis (adjusted OR [aOR], 0.53; 95% CI, 0.28-1.00) was negatively associated with asthma persisting to age 13 years, chickenpox (aOR, 0.58; 95% CI, 0.38-0.88) was negatively associated with asthma persisting to age 32 years, and rubella was negatively associated with asthma persisting to ages 32 (aOR, 0.61; 95% CI, 0.31-0.96) and 44 years (aOR 0.53; 95% CI, 0.35-0.82). Pertussis was associated with preadolescent incident asthma (adjusted hazard ratio [aHR], 1.80; 95% CI, 1.10-2.96), whereas measles was associated with adolescent incident asthma (aHR, 1.66; 1.06-2.56). Childhood pneumonia was associated with current asthma at ages 7 (aOR, 3.12; 95% CI, 2.61-3.75) and 13 years (aOR, 1.32; 95% CI, 1.00-1.75), an association stronger in those without than those with eczema (aOR, 3.46; 95% CI, 2.83-4.24 vs aOR, 2.08; 95% CI, 1.38-3.12). CONCLUSIONS: Overall, childhood infectious diseases protected against asthma persisting in later life, but pertussis and measles were associated with new-onset asthma after childhood. Measles and pertussis immunization might lead to a reduction in incident asthma in later life.

Genetic polymorphisms in 15q25 and 19q13 loci, cotinine levels, and risk of lung cancer in EPIC.

BACKGROUNDS: Multiple polymorphisms affecting smoking behavior have been identified through genome-wide association studies. Circulating levels of the nicotine metabolite cotinine is a marker of recent smoking exposure. Hence, genetic variants influencing smoking behavior are expected to be associated with cotinine levels. METHODS: We conducted an analysis in a lung cancer case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. We investigated the effects of single-nucleotide polymorphisms (SNP) previously associated with smoking behavior on (i) circulating cotinine and (ii) lung cancer risk. A total of 894 cases and 1,805 controls were analyzed for cotinine and genotyped for 10 polymorphisms on 7p14, 8p11, 10q23, 15q25, and 19q13. RESULTS: Two variants in the nicotinic acetylcholine receptor subunit genes CHRNA5 and CHRNA3 on 15q25, rs16969968 and rs578776, were associated with cotinine (P = 0.001 and 0.03, respectively) in current smokers and with lung cancer risk (P < 0.001 and P = 0.001, respectively). Two 19q13 variants, rs7937 and rs4105144, were associated with increased cotinine (P = 0.003 and P < 0.001, respectively) but decreased lung cancer risk (P = 0.01 for both, after adjusting for cotinine). Variants in 7p14, 8p11, and 10q23 were not associated with cotinine or lung cancer risk. CONCLUSIONS: 15q25 and 19q13 SNPs were associated with circulating cotinine. The directions of association for 15q25 variants with cotinine were in accordance with that expected of lung cancer risk, whereas SNPs on 19q13 displayed contrasting associations of cotinine and lung cancer that require further investigation. IMPACT: This study is the largest to date investigating the effects of polymorphisms affecting smoking behavior on lung cancer risk using circulating cotinine measures as proxies for recent smoking behavior.

Factors influencing asthma remission: a longitudinal study from childhood to middle age.

OBJECTIVE: To examine asthma remission from childhood to middle age. METHODS: This was a population-based cohort study. In 1968 the Tasmanian Longitudinal Health Study enrolled 8583 7-year-old Tasmanian schoolchildren who were re-surveyed in 2004. Those reporting ever having asthma when last surveyed completed another questionnaire in 2007 ascertaining age at last asthma attack and asthma medication use. The main outcome measure was asthma remission, defined as no asthma attack for 2 years and no current asthma medication use, or no self-reported asthma in adult life but with parent-reported childhood asthma. RESULTS: Of 5729 respondents to the 2004 survey, 1238 self-reported asthma. A further 573 denied asthma, but had parent-reported childhood asthma, giving a study sample of 1811. Asthma had remitted in 1177 (65.0%) of whom 649 (55.1%) were male. Childhood (OR 0.38, 95% CI 0.25 to 0.58) and later-onset allergic rhinitis (0.42, 0.29 to 0.63), childhood (0.66, 0.47 to 0.94) and later-onset eczema (0.66, 0.47 to 0.92), maternal asthma (0.66, 0.47 to 0.92) and childhood chronic bronchitis (0.56, 0.41 to 0.76) were negatively associated with remission. There was weaker evidence for a negative association between passive smoking (0.75, 0.54 to 1.04) and lower socio-economic status (p-trend 0.09) and remission. Childhood-onset asthma (3.76, 2.58 to 5.49) was more likely to remit than adult-onset asthma. Adult smoking was positively associated with remission in childhood-onset asthma (1.49, 1.06 to 2.09). Sex did not influence remission. CONCLUSION: While inherited factors cannot be changed, the effect of allergic rhinitis or eczema on asthma remission might be altered by early, aggressive treatment. Every effort should be made to lessen passive exposure to tobacco smoke.

Rare, evolutionarily unlikely missense substitutions in CHEK2 contribute to breast cancer susceptibility: results from a breast cancer family registry case-control mutation-screening study.

INTRODUCTION: Both protein-truncating variants and some missense substitutions in CHEK2 confer increased risk of breast cancer. However, no large-scale study has used full open reading frame mutation screening to assess the contribution of rare missense substitutions in CHEK2 to breast cancer risk. This absence has been due in part to a lack of validated statistical methods for summarizing risk attributable to large numbers of individually rare missense substitutions. METHODS: Previously, we adapted an in silico assessment of missense substitutions used for analysis of unclassified missense substitutions in BRCA1 and BRCA2 to the problem of assessing candidate genes using rare missense substitution data observed in case-control mutation-screening studies. The method involves stratifying rare missense substitutions observed in cases and/or controls into a series of grades ordered a priori from least to most likely to be evolutionarily deleterious, followed by a logistic regression test for trends to compare the frequency distributions of the graded missense substitutions in cases versus controls. Here we used this approach to analyze CHEK2 mutation-screening data from a population-based series of 1,303 female breast cancer patients and 1,109 unaffected female controls. RESULTS: We found evidence of risk associated with rare, evolutionarily unlikely CHEK2 missense substitutions. Additional findings were that (1) the risk estimate for the most severe grade of CHEK2 missense substitutions (denoted C65) is approximately equivalent to that of CHEK2 protein-truncating variants; (2) the population attributable fraction and the familial relative risk explained by the pool of rare missense substitutions were similar to those explained by the pool of protein-truncating variants; and (3) post hoc power calculations implied that scaling up case-control mutation screening to examine entire biochemical pathways would require roughly 2,000 cases and controls to achieve acceptable statistical power. CONCLUSIONS: This study shows that CHEK2 harbors many rare sequence variants that confer increased risk of breast cancer and that a substantial proportion of these are missense substitutions. The study validates our analytic approach to rare missense substitutions and provides a method to combine data from protein-truncating variants and rare missense substitutions into a one degree of freedom per gene test.

A PALB2 mutation associated with high risk of breast cancer.

NTRODUCTION: As a group, women who carry germline mutations in partner and localizer of breast cancer 2 susceptibility protein (PALB2) are at increased risk of breast cancer. Little is known about by how much or whether risk differs by mutation or family history, owing to the paucity of studies of cases unselected for family history. METHODS: We screened 1,403 case probands for PALB2 mutations in a population-based study of Australian women with invasive breast cancer stratified by age at onset. The age-specific risk of breast cancer was estimated from the cancer histories of first- and second-degree relatives of mutation-carrying probands using a modified segregation analysis that included a polygenic modifier and was conditioned on the carrier case proband. Further screening for PALB2 c.3113G > A (W1038X) was conducted for 779 families with multiple cases of breast cancer ascertained through family cancer clinics in Australia and New Zealand and 764 population-based controls. RESULTS: We found five independent case probands in the population-based sample with the protein-truncating mutation PALB2 c.3113G > A (W1038X); 2 of 695 were diagnosed before age 40 years and 3 of 708 were diagnosed when between ages 40 and 59 years. Both of the two early-onset carrier case probands had very strong family histories of breast cancer. Further testing found that the mutation segregated with breast cancer in these families. No c.3113G > A (W1038X) carriers were found in 764 population-based unaffected controls. The hazard ratio was estimated to be 30.1 (95% confidence interval (CI), 7.5 to 120; P < 0.0001), and the corresponding cumulative risk estimates were 49% (95% CI, 15 to 93) to age 50 and 91% (95% CI, 44 to 100) to age 70. We found another eight families carrying this mutation in 779 families with multiple cases of breast cancer ascertained through family cancer clinics. CONCLUSIONS: The PALB2 c.3113G > A mutation appears to be associated with substantial risks of breast cancer that are of clinical relevance.

A melanoma epidemic in Iceland: possible influence of sunbed use.

Since 1980, sunbed use and travel abroad have dramatically increased in Iceland (64°-66°N). The authors assessed temporal trends in melanoma incidence by body site in Iceland in relation to sunbed use and travel abroad. Using joinpoint analysis, they calculated estimated annual percent changes (EAPCs) and identified the years during which statistically significant changes in EAPC occurred. Between 1954 and 2006, the largest increase in incidence in men was observed on the trunk (EAPC = 4.6%, 95% confidence interval: 3.2, 6.0). In women, the slow increase in trunk melanoma incidence before 1995 was followed by a significantly sharper increase in incidence, mainly among women aged less than 50 years, resembling an epidemic incidence curve (1995-2002: EAPC = 20.4%, 95% confidence interval: 9.3, 32.8). In 2002, the melanoma incidence on the trunk was higher than the incidence on the lower limbs for women. Sunbed use in Iceland expanded rapidly after 1985, mainly among young women, and in 2000, it was approximately 2 and 3 times the levels recorded in Sweden and in the United Kingdom, respectively. Travels abroad were more prevalent among older Icelanders. The high prevalence of sunbed use probably contributed to the sharp increase in the incidence of melanoma in Iceland.

Common genetic variants associated with breast cancer and mammographic density measures that predict disease.

Mammographic density for age and body mass index (BMI) is a heritable risk factor for breast cancer. We aimed to determine if recently identified common variants associated with small gradients in breast cancer risk are associated with mammographic density. We genotyped 497 monozygotic and 330 dizygotic twin pairs and 634 of their sisters from 903 families for 12 independent variants. Mammographic dense area, percent dense area, and nondense area were measured by three observers using a computer-thresholding technique. Associations with mammographic density measures adjusted for age, BMI, and other determinants were estimated (a) cross-sectionally using a multivariate normal model for pedigree analysis (P(x)), (b) between sibships, and (c) within sibships using orthogonal transformations of outcomes and exposures. A combined test of association (P(c)) was derived using the independent estimates from b and c. We tested if the distributions of P values across variants differed from the uniform distribution (P(u)). For dense area and percent dense area, the distributions of P(c) values were not uniform (both P(u) <0.007). Consistent with their breast cancer associations, rs3817198 (LSP1) and rs13281615 (8q) were associated with dense area and percent dense area (all P(x) and P(c) <0.05), and rs889312 (MAP3K1), rs2107425 (H19), and rs17468277 (CASP8) were marginally associated with dense area (some P(x) or P(c) <0.05). All associations were independent of menopausal status. At least two common breast cancer susceptibility variants are associated with mammographic density measures that predict breast cancer. These findings could help elucidate how those variants and mammographic density measures are associated with breast cancer susceptibility.

Rare, evolutionarily unlikely missense substitutions in ATM confer increased risk of breast cancer.

The susceptibility gene for ataxia telangiectasia, ATM, is also an intermediate-risk breast-cancer-susceptibility gene. However, the spectrum and frequency distribution of ATM mutations that confer increased risk of breast cancer have been controversial. To assess the contribution of rare variants in this gene to risk of breast cancer, we pooled data from seven published ATM case-control mutation-screening studies, including a total of 1544 breast cancer cases and 1224 controls, with data from our own mutation screening of an additional 987 breast cancer cases and 1021 controls. Using an in silico missense-substitution analysis that provides a ranking of missense substitutions from evolutionarily most likely to least likely, we carried out analyses of protein-truncating variants, splice-junction variants, and rare missense variants. We found marginal evidence that the combination of ATM protein-truncating and splice-junction variants contribute to breast cancer risk. There was stronger evidence that a subset of rare, evolutionarily unlikely missense substitutions confer increased risk. On the basis of subset analyses, we hypothesize that rare missense substitutions falling in and around the FAT, kinase, and FATC domains of the protein may be disproportionately responsible for that risk and that a subset of these may confer higher risk than do protein-truncating variants. We conclude that a comparison between the graded distributions of missense substitutions in cases versus controls can complement analyses of truncating variants and help identify susceptibility genes and that this approach will aid interpretation of the data emerging from new sequencing technologies.

Short-term forecasting of emergency inpatient flow.

Hospital managers have to manage resources effectively, while maintaining a high quality of care. For hospitals where admissions from the emergency department to the wards represent a large proportion of admissions, the ability to forecast these admissions and the resultant ward occupancy is especially useful for resource planning purposes. Since emergency admissions often compete with planned elective admissions, modeling emergency demand may result in improved elective planning as well. We compare several models for forecasting daily emergency inpatient admissions and occupancy. The models are applied to three years of daily data. By measuring their mean square error in a cross-validation framework, we find that emergency admissions are largely random, and hence, unpredictable, whereas emergency occupancy can be forecasted using a model combining regression and autoregressive integrated moving average (ARIMA) model, or a seasonal ARIMA model, for up to one week ahead. Faced with variable admissions and occupancy, hospitals must prepare a reserve capacity of beds and staff. Our approach allows estimation of the required reserve capacity.

Predictors of mammographic density: insights gained from a novel regression analysis of a twin study.

Understanding which factors influence mammographically dense and nondense areas is important because percent mammographic density adjusted for age is a strong, continuously distributed risk factor for breast cancer, especially when adjusted for weight or body mass index. Using computer-assisted methods, we measured mammographically dense areas for 571 monozygotic and 380 dizygotic Australian and North American twin pairs ages 40 to 70 years. We used a novel regression modeling approach in which each twin's measure of dense and nondense area was regressed against one or both of the twin's and co-twin's covariates. The nature of changes to regression estimates with the inclusion of the twin and/or co-twin's covariates can be evaluated for consistency with causal and/or other models. By causal, we mean that if it were possible to vary a covariate experimentally then the expected value of the outcome measure would change. After adjusting for the individual's weight, the co-twin associations with weight were attenuated, consistent with a causal effect of weight on mammographic measures, which in absolute log cm(2)/kg was thrice stronger for nondense than dense area. After adjusting for weight, later age at menarche, and greater height were associated with greater dense and lesser nondense areas in a manner inconsistent with causality. The associations of dense and nondense areas with parity are consistent with a causal effect and/or within-person confounding. The associations between mammographic density measures and height are consistent with shared early life environmental factors that predispose to both height and percent mammographic density and possibly breast cancer risk.

Glycosylated hemoglobin and risk of colorectal cancer in men and women, the European prospective investigation into cancer and nutrition.

Although large-scale prospective cohort studies have related hyperglycemia to increased risk of cancer overall, studies specifically on colorectal cancer have been generally small. We investigated the association between prediagnostic levels of glycosylated hemoglobin (HbA1c), a marker for average glucose level in blood, and colorectal cancer risk in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition cohort. One thousand and twenty-six incident colorectal cancer cases (561 men and 465 women) and 1,026 matched controls were eligible for the study. Multivariate conditional logistic regression was used to estimate odds ratios (ORS) adjusted for possible confounders. Increasing HbA1c percentages were statistically significantly associated with a mild increase in colorectal cancer risk in the whole population [OR, 1.10; 95% confidence interval (CI), 1.01,1.19 for a 10% increase in HbA1c]. In women, increasing HbA1c percentages were associated with a statistically significant increase in colorectal cancer risk (OR, 1.16; 95% CI, 1.01, 1.32 for a 10% increase in HbA1c) and with a borderline statistically significant increase in rectum cancer (OR, 1.22; 95% CI, 0.99,1.50 for a 10% increase in HbA1c). No significant association with cancer risk was observed in men. The results of the current study suggest a mild implication of hyperglycemia in colorectal cancer, which seems more important in women than in men, and more for cancer of the rectum than of the colon.

Using mammographic density to improve breast cancer screening outcomes.

It is possible that the performance of mammographic screening would be improved if it is targeted at women at higher risk of breast cancer or who are more likely to have their cancer missed at screening, through more intensive screening or alternative screening modalities. We conducted a case-control study within a population-based Australian mammographic screening program (1,706 invasive breast cancers and 5,637 randomly selected controls). We used logistic regression to examine the effects of breast density, age, and hormone therapy use, all known to influence both breast cancer risk and the sensitivity of mammographic screening, on the risk of small (15 mm) screen-detected and interval breast cancers. The risk of small screen-detected cancers was not associated with density, but the risk of large screen-detected cancers was nearly 3-fold for the second quintile and approximately 4-fold for the four highest density categories (third and fourth quintiles and the two highest deciles) compared with the lowest quintile. The risk of interval cancers increased monotonically across the density categories [highest decile odds ratio (OR), 4.65; 95% confidence interval (95% CI), 2.96-7.31]. The risk of small and large screen-detected cancers, but not interval cancers, increased with age. After adjusting for age and density, hormone therapy use was associated with a moderately elevated risk of interval cancers (OR, 1.43; 95% CI, 1.12-1.81). The effectiveness of the screening program could be improved if density were to be used to identify women most likely to have poor screening outcomes. There would be little additional benefit in targeting screening based on age and hormone therapy use.

Genetic evidence and integration of various data sources for classifying uncertain variants into a single model.

Genetic testing often results in the finding of a variant whose clinical significance is unknown. A number of different approaches have been employed in the attempt to classify such variants. For some variants, case-control, segregation, family history, or other statistical studies can provide strong evidence of direct association with cancer risk. For most variants, other evidence is available that relates to properties of the protein or gene sequence. In this work we propose a Bayesian method for assessing the likelihood that a variant is pathogenic. We discuss the assessment of prior probability, and how to combine the various sources of data into a statistically valid integrated assessment with a posterior probability of pathogenicity. In particular, we propose the use of a two-component mixture model to integrate these various sources of data and to estimate the parameters related to sensitivity and specificity of specific kinds of evidence. Further, we discuss some of the issues involved in this process and the assumptions that underpin many of the methods used in the evaluation process.

In silico analysis of missense substitutions using sequence-alignment based methods.

Genetic testing for mutations in high-risk cancer susceptibility genes often reveals missense substitutions that are not easily classified as pathogenic or neutral. Among the methods that can help in their classification are computational analyses. Predictions of pathogenic vs. neutral, or the probability that a variant is pathogenic, can be made based on: 1) inferences from evolutionary conservation using protein multiple sequence alignments (PMSAs) of the gene of interest for almost any missense sequence variant; and 2) for many variants, structural features of wild-type and variant proteins. These in silico methods have improved considerably in recent years. In this work, we review and/or make suggestions with respect to: 1) the rationale for using in silico methods to help predict the consequences of missense variants; 2) important aspects of creating PMSAs that are informative for classification; 3) specific features of algorithms that have been used for classification of clinically-observed variants; 4) validation studies demonstrating that computational analyses can have predictive values (PVs) of approximately 75 to 95%; 5) current limitations of data sets and algorithms that need to be addressed to improve the computational classifiers; and 6) how in silico algorithms can be a part of the "integrated analysis" of multiple lines of evidence to help classify variants. We conclude that carefully validated computational algorithms, in the context of other evidence, can be an important tool for classification of missense variants.

Classification of rare missense substitutions, using risk surfaces, with genetic- and molecular-epidemiology applications.

Many individually rare missense substitutions are encountered during deep resequencing of candidate susceptibility genes and clinical mutation screening of known susceptibility genes. BRCA1 and BRCA2 are among the most resequenced of all genes, and clinical mutation screening of these genes provides an extensive data set for analysis of rare missense substitutions. Align-GVGD is a mathematically simple missense substitution analysis algorithm, based on the Grantham difference, which has already contributed to classification of missense substitutions in BRCA1, BRCA2, and CHEK2. However, the distribution of genetic risk as a function of Align-GVGD's output variables Grantham variation (GV) and Grantham deviation (GD) has not been well characterized. Here, we used data from the Myriad Genetic Laboratories database of nearly 70,000 full-sequence tests plus two risk estimates, one approximating the odds ratio and the other reflecting strength of selection, to display the distribution of risk in the GV-GD plane as a series of surfaces. We abstracted contours from the surfaces and used the contours to define a sequence of missense substitution grades ordered from greatest risk to least risk. The grades were validated internally using a third, personal and family history-based, measure of risk. The Align-GVGD grades defined here are applicable to both the genetic epidemiology problem of classifying rare missense substitutions observed in known susceptibility genes and the molecular epidemiology problem of analyzing rare missense substitutions observed during case-control mutation screening studies of candidate susceptibility genes.

Are the so-called low penetrance breast cancer genes, ATM, BRIP1, PALB2 and CHEK2, high risk for women with strong family histories?

A woman typically presents for genetic counselling because she has a strong family history and is interested in knowing the probability she will develop disease in the future; that is, her absolute risk. Relative risk for a given factor refers to risk compared with either population average risk (sense a), or risk when not having the factor, with all other factors held constant (sense b). Not understanding that these are three distinct concepts can result in failure to correctly appreciate the consequences of studies on clinical genetic testing. Several studies found that the frequencies of mutations in ATM, BRIP1, PALB2 and CHEK2 were many times greater for cases with a strong family history than for controls. To account for the selected case sampling (ascertainment), a statistical model that assumes that the effect of any measured variant multiplies the effect of unmeasured variants was applied. This multiplicative polygenic model in effect estimated the relative risk in the sense b, not sense a, and found it was in the range of 1.7 to 2.4. The authors concluded that the variants are "low penetrance". They failed to note that their model fits predicted that, for some women, absolute risk may be as high as for BRCA2 mutation carriers. This is because the relative risk multiplies polygenic risk, and the latter is predicted by family history. Therefore, mutation testing of these genes for women with a strong family history, especially if it is of early onset, may be as clinically relevant as it is for BRCA1 and BRCA2.