An automated approach for estimation of breast density

Breast density is a strong risk factor for breast cancer; however, no standard assessment method exists. An automated breast density method was modified and compared with a semi-automated, user-assisted thresholding method (Cumulus method) and the Breast Imaging Reporting and Data System four-category tissue composition measure for their ability to predict future breast cancer risk. The three estimation methods were evaluated in a matched breast cancer case-control (n = 372 and n = 713, respectively) study at the Mayo Clinic using digitized film mammograms. Mammograms from the craniocaudal view of the noncancerous breast were acquired on average 7 years before diagnosis. Two controls with no previous history of breast cancer from the screening practice were matched to each case on age, number of previous screening mammograms, final screening exam date, menopausal status at this date, interval between earliest and latest available mammograms, and residence. Both Pearson linear correlation (R) and Spearman rank correlation (r) coefficients were used for comparing the three methods as appropriate. Conditional logistic regression was used to estimate the risk for breast cancer (odds ratios and 95% confidence intervals) associated with the quartiles of percent breast density (automated breast density method, Cumulus method) or Breast Imaging Reporting and Data System categories. The area under the receiver operator characteristic curve was estimated and used to compare the discriminatory capabilities of each approach. The continuous measures (automated breast density method and Cumulus method) were highly correlated with each other (R = 0.70) but less with Breast Imaging Reporting and Data System (r = 0.49 for automated breast density method and r = 0.57 for Cumulus method). Risk estimates associated with the lowest to highest quartiles of automated breast density method were greater in magnitude [odds ratios: 1.0 (reference), 2.3, 3.0, 5.2; P trend < 0.001] than the corresponding quartiles for the Cumulus method [odds ratios: 1.0 (reference), 1.7, 2.1, and 3.8; P trend < 0.001] and Breast Imaging Reporting and Data System [odds ratios: 1.0 (reference), 1.6, 1.5, 2.6; P trend < 0.001] method. However, all methods similarly discriminated between case and control status; areas under the receiver operator characteristic curve were 0.64, 0.63, and 0.61 for automated breast density method, Cumulus method, and Breast Imaging Reporting and Data System, respectively. The automated breast density method is a viable option for quantitatively assessing breast density from digitized film mammograms.

Validating genetic risk associations for ovarian cancer through the international Ovarian Cancer Association Consortium

The search for genetic variants associated with ovarian cancer risk has focused on pathways including sex steroid hormones, DNA repair, and cell cycle control. The Ovarian Cancer Association Consortium (OCAC) identified 10 single-nucleotide polymorphisms (SNPs) in genes in these pathways, which had been genotyped by Consortium members and a pooled analysis of these data was conducted. Three of the 10 SNPs showed evidence of an association with ovarian cancer at P< or =0.10 in a log-additive model: rs2740574 in CYP3A4 (P=0.011), rs1805386 in LIG4 (P=0.007), and rs3218536 in XRCC2 (P=0.095). Additional genotyping in other OCAC studies was undertaken and only the variant in CYP3A4, rs2740574, continued to show an association in the replication data among homozygous carriers: OR(homozygous(hom))=2.50 (95% CI 0.54-11.57, P=0.24) with 1406 cases and 2827 controls. Overall, in the combined data the odds ratio was 2.81 among carriers of two copies of the minor allele (95% CI 1.20-6.56, P=0.017, p(het) across studies=0.42) with 1969 cases and 3491 controls. There was no association among heterozygous carriers. CYP3A4 encodes a key enzyme in oestrogen metabolism and our finding between rs2740574 and risk of ovarian cancer suggests that this pathway may be involved in ovarian carcinogenesis. Additional follow-up is warranted.

Single nucleotide polymorphisms in DNA repair genes and prostate cancer risk

The specific causes of prostate cancer are not known. However, multiple etiologic factors, including genetic profile, metabolism of steroid hormones, nutrition, chronic inflammation, family history of prostate cancer, and environmental exposures are thought to play significant roles. Variations in exposure to these risk factors may explain interindividual differences in prostate cancer risk. However, regardless of the precise mechanism(s), a robust DNA repair capacity may mitigate any risks conferred by mutations from these risk factors. Numerous single nucleotide polymorphisms (SNPs) in DNA repair genes have been found, and studies of these SNPs and prostate cancer risk are critical to understanding the response of prostate cells to DNA damage. A few SNPs in DNA repair genes are associated with significantly increased risk of prostate cancer; however, in most cases, the effects are moderate and often depend upon interactions among the risk alleles of several genes in a pathway or with other environmental risk factors. This report reviews the published epidemiologic literature on the association of SNPs in genes involved in DNA repair pathways and prostate cancer risk.

Epidemiology of ovarian cancer

Ovarian cancer represents the sixth most commonly diagnosed cancer among women in the world, and causes more deaths per year than any other cancer of the female reproductive system. Despite the high incidence and mortality rates, the etiology of this disease is poorly understood. Established risk factors for ovarian cancer include age and having a family history of the disease, while protective factors include increasing parity, oral contraceptive use, and oophorectomy. Lactation, incomplete pregnancies, and surgeries such as hysterectomy and tubal ligation may confer a weak protective effect against ovarian cancer. Infertility may contribute to ovarian cancer risk among nulliparous women. Other possible risk factors for ovarian cancer include postmenopausal hormone-replacement therapy and lifestyle factors such as cigarette smoking and alcohol consumption. Many of the causes of ovarian cancer are yet to be identified. Additional research is needed to better understand the etiology of this deadly disease.

Systematic review and meta-analysis of ovarian cancers: estimation of microsatellite-high frequency and characterization of mismatch repair deficient tumor histology

PURPOSE

A meta-analytic approach was used to estimate the frequency of: (a) microsatellite instability-high (MSI-H) phenotype in unselected ovarian cancers and (b) various histologic subtypes of mismatch repair (MMR)-deficient epithelial ovarian cancers.

METHODS

A systematic search of the Medline electronic database was conducted to identify articles published between January 1, 1966, and December 31, 2007, that examined MMR deficiency in ovarian cancers. Data were extracted on the study population, sample size, MSI-H frequency, and histology of MMR-deficient ovarian tumors.

RESULTS

The pooled proportion of MSI-H ovarian cancers was 0.12 [95% confidence interval (CI), 0.08-0.17] from 18 studies with 977 cases. The proportion of histologic subtypes in the pooled analysis from 15 studies with 159 cases was serous at 0.32 (95% CI, 0.20-0.44), mucinous at 0.19 (95% CI, 0.12-0.27), endometrioid at 0.29 (95% CI, 0.22-0.36), clear cell at 0.18 (95% CI, 0.09-0.28), and mixed at 0.24 (95% CI, 0.07-0.47). There was significant heterogeneity between studies.

CONCLUSIONS

The frequency of the MSI-H phenotype in unselected ovarian cancers approximates 12%. MMR-deficient ovarian cancers also seem to be characterized by an overrepresentation of nonserous histologic subtypes. Knowledge of histologic subtype may aid clinicians in identifying the relatively large proportion of ovarian cancers due to MMR defects; such knowledge has potential implications for medical management.

Performance of amplified DNA in an Illumina GoldenGate BeadArray assay

Whole genome amplification (WGA) offers a means to enrich DNA quantities for epidemiologic studies. We used an ovarian cancer study of 1,536 single nucleotide polymorphisms (SNPs) and 2,368 samples to assess performance of multiple displacement amplification (MDA) WGA using an Illumina GoldenGate BeadArray. Initial screening revealed successful genotyping for 93.4% of WGA samples and 99.3% of genomic samples, and 93.2% of SNPs for WGA samples and 96.3% of SNPs for genomic samples. SNP failure was predicted by Illumina-provided designability rank, %GC (P < or = 0.002), and for WGA only, distance to telomere and Illumina-provided SNP score (P < or = 0.002). Distance to telomere and %GC were highly correlated; adjustment for %GC removed the association between distance to telomere and SNP failure. Although universally high, per-SNP call rates were related to designability rank, SNP score, %GC, minor allele frequency, distance to telomere (P < or = 0.01), and, for WGA only, Illumina-provided validation class (P < 0.001). We found excellent concordance generally (>99.0%) among 124 WGA:genomic replicates, 15 WGA replicates, 88 replicate aliquots of the same WGA preparation, and 25 genomic replicates. Where there was discordance, it was across WGA:genomic replicates but limited to only a few samples among other replicates suggesting the introduction of error. Designability rank and SNP score correlated with WGA:genomic concordance (P < 0.001). In summary, use of MDA WGA DNA is feasible; however, caution is warranted regarding SNP selection and analysis. We recommend that biological SNP characteristics, notably distance to telomere and GC content (<50% GC recommended), as well as Illumina-provided metrics be considered in the creation of GoldenGate assays using MDA WGA DNA.

Prospective evaluation of trans-fatty acid intake and colorectal cancer risk in the Iowa Women's Health Study

Concerns regarding the safety of dietary trans-fatty acids (tFAs) have generated recent public interest, scientific discussion and legislative action. Although most widely recognized as a risk factor for cardiovascular disease, associations between tFA intake and incident cancer have also been proposed. With respect to colorectal cancer (CRC), existing observational data remain limited and inconclusive. Therefore, we conducted a prospective evaluation of tFA intake and CRC risk, overall and by anatomic subsite, among participants in the Iowa Women's Health Study (IWHS), a population-based cohort of older women (ages 55-69 years at enrollment). Exposure data were collected at baseline using a semiquantitative food-frequency questionnaire. Incident CRC cases were identified through annual linkage to the Iowa Cancer Registry. CRC risks were estimated using Cox proportional hazards regression models. In total, 35,216 women met our inclusion criteria and 1,229 CRC cases (631 proximal, 571 distal, 27 site not specified) were observed through 18 years of follow-up. Adjusting for age and total energy consumption, tFA intake in the 4th versus 1st quartile was not significantly associated with overall CRC risk [relative risk (RR) = 1.12; 95% confidence interval (CI) = 0.96-1.32]. Similarly, risk estimates based on proximal (RR = 1.09; 95% CI = 0.87-1.37) and distal (RR = 1.18; 95% CI = 0.93-1.49) CRC subsites did not differ from unity. Multivariable adjustment yielded slightly attenuated risk estimates, but the observed associations were not meaningfully altered. Given these findings, tFA intake does not appear to be a major CRC risk factor, at least among older women.

Can genes for mammographic density inform cancer aetiology?

Mammographic density (MD) reflects variations in fat, stromal and epithelial tissues that are thought to be regulated by several genes. High MD is an established risk factor for breast cancer; therefore, genes that regulate MD may indirectly influence breast cancer. These genes might also be fewer in number and easier to identify than those for breast cancer risk outside of inherited predisposition syndromes. In this Perspective, we review the limited genetic studies of MD and propose future directions.

Factors associated with breast cancer prevention communication between mothers and daughters

OBJECTIVE

Mother-daughter communication may be a potential pathway between family history and cancer prevention behavior. We examined the degree to which mothers reported providing advice on breast cancer prevention to their daughters, the content of such advice, and correlates of providing such advice.

METHODS

Data were collected via a mailed questionnaire to 1773 women from 355 families in the Minnesota Breast Cancer Family Study. Women were asked whether or not they had provided advice to their daughters on what they should do to prevent breast cancer. An additional open-ended question asked them to describe the types of advice they had provided.

RESULTS

Nine hundred seventy-six (55%) of the women reported providing breast cancer prevention advice to their daughters. The most frequent types of advice were to have a mammogram (51%), perform breast self-examination (BSE) (39%), have a clinical breast examination (CBE) (30%), and maintain a healthy lifestyle (21%). From multivariate logistic regression, older age (p < 0.001), having a personal history of breast cancer (p < 0.001), higher degree of breast cancer worry/concern (p < 0.001), engaging in a higher number of health-promoting behaviors (p < 0.001), and ever performing a BSE (p = 0.04) were factors independently associated with the provision of advice. Analyses accounting for sample nonindependence did not change our results.

CONCLUSIONS

Breast cancer prevention behaviors were associated with providing advice. By better understanding the pathways through which breast cancer family history is associated with screening mammography and other prevention behaviors, researchers can develop more effective, tailored prevention interventions at the family level.

A review of the clinical relevance of mismatch-repair deficiency in ovarian cancer

Ovarian cancer ranks fifth in both cancer incidence and mortality among women in the United States. Defects in the mismatch-repair (MMR) pathway that arise through genetic and/or epigenetic mechanisms may be important etiologically in a reasonable proportion of ovarian cancers. Genetic mechanisms of MMR dysfunction include germline and somatic mutations in the MMR proteins. Germline mutations cause hereditary nonpolyposis colorectal cancer (HNPCC), which is the third most common cause of inherited ovarian cancer after BRCA1 and BRCA2 mutations. An epigenetic mechanism known to cause inactivation of the MMR system is promoter hypermethylation of 1 of the MMR genes, mutL homolog 1 (MLH1). Various laboratory methods, in addition to clinical and histopathologic criteria, can be used to identify MMR-deficient ovarian cancers. Such methods include microsatellite instability analysis, immunohistochemistry, MLH1 promoter hypermethylation testing, and germline mutation analysis. In this review, the authors describe the existing literature regarding the molecular, clinical, and histologic characteristics of MMR-deficient ovarian cancers along with the possible effect on survival and treatment response. By further defining the profile of MMR-deficient ovarian cancers and their associated etiologic mechanisms, there may be a greater potential to distinguish between those of hereditary and sporadic etiology. The ability to make such distinctions may be of diagnostic, prognostic, and therapeutic utility.

Proteomic contributions to personalized cancer care

Cancer impacts each patient and family differently. Our current understanding of the disease is primarily limited to clinical hallmarks of cancer, but many specific molecular mechanisms remain elusive. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies that improve patient prognosis are not widely available for most cancers. Individualized care plans, also described as personalized medicine, still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics holds great promise in contributing to the prevention and cure of cancer because it provides unique tools for discovery of biomarkers and therapeutic targets. As such, proteomics can help translate basic science discoveries into the clinical practice of personalized medicine. Here we describe how biological mass spectrometry and proteome analysis interact with other major patient care and research initiatives and present vignettes illustrating efforts in discovery of diagnostic biomarkers for ovarian cancer, development of treatment strategies in lung cancer, and monitoring prognosis and relapse in multiple myeloma patients.

Association of mammographic density with the pathology of subsequent breast cancer among postmenopausal women

BACKGROUND

Limited studies have examined the associations between mammographic density and subsequent breast tumor characteristics.

METHODS

Eligible women were part of a case-control study of postmenopausal breast cancer, were 40 years or older and had a routine mammogram 4 years or more before their diagnosis. Mammographic density (percent density, dense area, and nondense area) was estimated using a computer-assisted thresholding program. At the time of cancer diagnosis, cases were classified as asymptomatic or symptomatic based on medical record review and breast imaging workup. Pathologic review was done blinded to the density status. Linear regression models and tests for trend examined the association between pathologic characteristics of the breast tumor and the components of density for all participants, and stratified by symptom status at diagnosis.

RESULTS

Of the 286 eligible cases, 77% were 60 years or older and mean percent density was 29.5% (SD, 14.6%). Density was not significantly associated with tumor size (P = 0.22), histologic type (P = 0.77), estrogen receptor (P = 0.11) or progesterone receptor (P = 0.37) status, mitotic activity (P = 0.12), or nuclear pleomorphism (P = 0.09; P values for percent density). An inverse association was suggested between tumor grade and percent density (32.0%, 30.3%, 26.7% for grades 1-3; P = 0.06 for trend). The inverse association with tumor grade and its components (nuclear pleomorphism and tubular differentiation) was only evident among the 97 symptomatic women; positive associations of estrogen receptor (P = 0.009) and progesterone receptor (P = 0.04) were also seen with percent density only in this subgroup.

CONCLUSIONS

The inverse association between tumor grade and percent density in the symptomatic population could inform the biology of the association between mammographic density and breast cancer risk.

Familial and perceived risk of breast cancer in relation to use of complementary medicine

AIM

To examine the use of complementary and alternative medicine (CAM) by women with varying levels of familial and perceived risk of breast cancer with the goal of preventing breast cancer.

METHODS

Cross-sectional data on CAM use were collected on 2,198 women (mean age, 63 years) personally unaffected by breast cancer in the Minnesota Breast Cancer Family Study. CAM use was compared across women at high, moderate, or average risk based on family history, as well as across categories of perceived risk of breast cancer. CAM use was also examined in relation to screening and general health behaviors, worry about breast cancer, and optimism.

RESULTS

Half (49.5%) of the women reported using at least one CAM modality with the intent of preventing breast cancer. Univariate analyses indicated that greater overall CAM use was related to greater perceived risk (P = 0.018), more general health behaviors (P < 0.0001), more breast cancer screening behaviors (P = 0.0002), greater optimism (P = 0.0002), and higher educational attainment (P < 0.0001). Multivariate analysis revealed that general health behaviors (P < 0.0001), education (P = 0.0027), and optimism (P = 0.037) were significant predictors of CAM use when in the same model with perceived risk and breast cancer screening behaviors.

CONCLUSIONS

Many women use CAM with the goal of preventing breast cancer. General health-promoting behaviors, education, and optimism predict CAM use. Evidence-based guidance is needed for the public and health care providers on the potential and limitations of specific CAM approaches to affect cancer risk.

Association of single nucleotide polymorphisms in glycosylation genes with risk of epithelial ovarian cancer

Studies suggest that underglycosylation of the cell membrane mucin MUC1 may be associated with epithelial ovarian cancer. We identified 26 genes involved in glycosylation and examined 93 single nucleotide polymorphisms (SNP) with a minor allele frequency of > or =0.05 in relation to incident ovarian cancer. Cases were ascertained at the Mayo Clinic, Rochester, MN (n = 396) or a 48-county region in North Carolina (Duke University; n = 534). Ovarian cancer-free controls (n = 1,037) were frequency matched to the cases on age, race, and residence. Subjects were interviewed to obtain data on risk factors and a sample of blood for DNA and genotyped using the Illumina GoldenGate assay. We excluded subjects and individual SNPs with genotype call rates of <90%. Data were analyzed using logistic regression, with adjustment for age and residence. We fitted dominant, log additive, and recessive genetic models. Among Caucasians, nine SNPs in eight genes were associated with risk at P < 0.05 under at least one genetic model before adjusting for multiple testing. A SNP in GALNT1 (rs17647532) was the only one that remained statistically significant after Bonferroni adjustment for multiple testing but was not statistically significant in Hardy-Weinberg equilibrium among controls. Haplotype analyses revealed a global association of GALNT1 with risk (P = 0.038, under a recessive genetic model), which largely reflected a decreased risk of one haplotype (0.10 frequency; odds ratio, 0.07; P = 0.01) compared with the most common haplotype (0.39 frequency). These results suggest that genetic polymorphisms in the glycoslyation process may be novel risk factors for ovarian cancer.

Age-specific trends in mammographic density: the Minnesota Breast Cancer Family Study

Mammographic density is a strong risk factor for breast cancer, yet few studies have evaluated density trends, and associated factors, over time. The authors retrieved and digitized mammograms (> or =1 per woman) imaged in 1990-2003 to evaluate percent density (PD) in the Minnesota Breast Cancer Family cohort. Multivariable-adjusted, mixed-effects, repeated-measures models incorporating a natural cubic spline provided estimates of nonlinear trends in PD with age and were used to examine association with covariates. Overall, 5,698 mammograms from 1,689 women with covariate information were digitized. In descriptive analyses, the highest median PD was 33.1% (interquartile range, 21.8%; n = 230) among premenopausal women, 31.0% (interquartile range, 23.2%; n = 175) among women who transitioned from pre- to postmenopause, and 18.7% (interquartile range, 22.2%; n = 1,284) among postmenopausal women. On average, premenopausal compared with postmenopausal women had 1.9% (p = 0.001) higher PD. In repeated-measures analyses, greater declines in PD occurred with menopause and among women with higher baseline PD; current postmenopausal hormone use and higher body mass index modified these declines (p interaction < 0.001). No significant modification of the density change with age was seen with parity/age at first birth, age at menarche, oral contraceptive use, family history of breast or ovarian cancer in a first- or second-degree relative, educational level, smoking status, or alcohol intake were observed. These data suggest that menopause, baseline PD, postmenopausal hormone use, and body mass index predict changes in mammographic density trends during adult life.

Genetic variation in the one-carbon transfer pathway and ovarian cancer risk

Dysfunction in enzymes involved in one-carbon (1-C) metabolism can lead to increased chromosomal strand breaking and abnormal methylation patterns, which are both associated with cancer risk. Availability of 1-C units may modify risk. We investigated the association of single-nucleotide polymorphisms (SNP) in 21 genes in the 1-C transfer pathway among 829 Caucasian cases with primary epithelial ovarian cancer and 941 frequency-matched unaffected controls enrolled at Mayo Clinic (Rochester, MN) and Duke University (Durham, NC) and examined risk modification by multivitamin supplement use. Multivariable-adjusted SNP-specific logistic regression and haplotype analyses were done for 180 SNPs and false positive report probabilities (FPRP) were calculated. Each copy of the minor allele in SHMT1 intron 5 A>G (rs9909104) was associated with epithelial ovarian cancer [odds ratio (OR), 1.2; 95% confidence interval (95% CI), 1.0-1.4; P trend = 0.02; FPRP = 0.16] and a 5-SNP SHMT1 haplotype was associated with decreased risk (P = 0.01; FPRP = 0.09). Three SNPs in DNMT3A were associated with risk among multivitamin supplement users: 3' untranslated region (UTR) C>G (rs13420827: OR, 0.8; 95% CI, 0.6-1.0; P interaction = 0.006; FPRP = 0.54), intron 6 G>A (rs11887120: OR, 0.8; 95% CI, 0.7-1.0; P interaction = 0.007; FPRP = 0.57), and intron 22 A>T (rs11695471: OR, 1.2; 95% CI, 1.0-1.5; P interaction = 0.01; FPRP = 0.66). These data extend previous findings from other cancers of a role for SHMT1 in ovarian cancer, and provide evidence that SNPs in methylation and DNA synthesis reactions are associated with risk of ovarian cancer. Interventions with modifiable factors such as multivitamin intake may reduce risk.

Unpasteurized milk consumption and subsequent risk of cancer

Concerns have been raised regarding the possible adverse health effects of consumption of unpasteurized milk and risk of cancer. We examined the association of self-reported intake of unpasteurized milk with subsequent risk of cancer in a large population-based cohort study. The Iowa Women's Health Study is a prospective cohort study of 55-69 year old women at baseline in 1986. Of the 41,836 women in the cohort at baseline, 22,808 cancer-free women completed the fourth follow-up questionnaire in 1997. Risk ratios (RR) and 95% confidence intervals (CI) were calculated using Cox proportional hazards regression analysis. Reported intake of unpasteurized milk was high: 59.2% consumed only as a child, 2.5% consumed only as an adult, and 16.5% consumed as a child and an adult. A total of 2,379 cancers were identified in the cohort at risk. Overall, the age-adjusted risk of cancer was lower among women who reported consumption of unpasteurized milk only as a child (RR = 0.90, 95% CI: 0.82-0.99) or as a child and an adult (RR = 0.85; 95% CI: 0.75-0.97). Adjustment for confounding factors attenuated these associations (RR = 0.92, 95% CI: 0.83-1.02 for consumption only as a child, and RR = 0.91; 95% CI: 0.79-1.04 for consumption as a child and an adult). These data suggest that consumption of unpasteurized milk does not increase risk of cancer.

Mammographic density, breast cancer risk and risk prediction

In this review, we examine the evidence for mammographic density as an independent risk factor for breast cancer, describe the risk prediction models that have incorporated density, and discuss the current and future implications of using mammographic density in clinical practice. Mammographic density is a consistent and strong risk factor for breast cancer in several populations and across age at mammogram. Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models may replace the existing Gail model for clinical risk assessment. However, absolute risk estimates resulting from these improved models are still limited in their ability to characterize an individual's probability of developing cancer. Promising new measures of mammographic density, including volumetric density, which can be standardized using full-field digital mammography, will likely result in a stronger risk factor and improve accuracy of risk prediction models.

Population-based case-control study of diabetes and breast cancer risk in Hispanic and non-Hispanic White women living in US southwestern states

Diabetes mellitus has been associated with breast cancer, although no studies appear to have adequately assessed the association in Hispanic women, a population with a high prevalence of diabetes. The authors investigated this association in a population-based case-control study of Hispanic and non-Hispanic White women living in the southwestern United States. Breast cancer cases diagnosed in 1999-2004 were identified through state cancer registries (1,526 non-Hispanic Whites, 798 Hispanics). Age- and ethnicity-matched controls (1,599 non-Hispanic Whites, 924 Hispanics) were selected from commercial mailing lists and driver's license and Social Security records. Diabetes history was assessed through interviewer-administered questionnaires. Odds ratios and 95% confidence intervals were calculated using logistic regression, adjusting for age, body mass index at age 15 years, and parity. Having any type of diabetes was not associated with breast cancer overall (odds ratio = 0.94, 95% confidence interval: 0.78, 1.12). Type 2 diabetes was observed among 19% of Hispanics and 9% of non-Hispanic Whites but was not associated with breast cancer in either group. Gestational diabetes was inversely associated with breast cancer in both ethnic groups, especially when first diagnosed at age < or =35 years (odds ratio = 0.54, 95% confidence interval: 0.37, 0.79). In this study, diabetes was not associated with breast cancer overall, although the inverse association with gestational diabetes warrants further investigation.

Relative weight at age 12 and risk of postmenopausal breast cancer

BACKGROUND

Early adolescent weight may affect the risk of postmenopausal breast cancer, and this association may be modified by a family history of breast or ovarian cancer in a first-degree relative, and/or estrogen (ER) and progesterone (PR) receptor status of the disease.

METHODS

Relative weight at age 12 years (above, below, or average weight compared with peers) and family history were ascertained using a mailed questionnaire in 1986, in the Iowa Women's Health Study, a prospective cohort study of postmenopausal women. Incident breast cancer cases (including ER and PR status) were identified using the Iowa Surveillance, Epidemiology, and End Results Cancer Registry. Relative risks (RR) and 95% confidence intervals (95% CI) were estimated using Cox proportional hazards regression, and were adjusted for breast cancer risk factors, including body mass index at age 18 years and body mass index at study baseline.

RESULTS

Through 2003, 2,503 cases of postmenopausal breast cancer were identified among 35,941 women in the analytic cohort. Compared with women with average weight at age 12 years, there was no association of below average weight with risk of breast cancer (RR, 1.02; 95% CI, 0.92-1.13), whereas women with above average weight had a lower risk (RR, 0.85; 95% CI, 0.74-0.98). There was no evidence of an interaction between weight at age 12 years and family history (P = 0.44). The inverse association of above average weight with risk of breast cancer was strongest for PR- tumors (RR, 0.62; 95% CI, 0.43-0.89), intermediate for ER+ (RR, 0.80; 95% CI, 0.67-0.96) and ER- (RR, 0.77; 95% CI, 0.50-1.19) tumors, and weakest for PR+ tumors (RR, 0.90; 95% CI, 0.74-1.09). These associations were not modified by a family history (all P > 0.18). In a joint ER/PR analyses, the strongest inverse association with above average weight at age 12 years was seen for ER+/PR- (RR, 0.49; 95% CI, 0.29-0.85).

CONCLUSION

Above average weight at age 12 years was inversely associated with risk of postmenopausal breast cancer, and was not modified by a family history of the disease. The inverse association was strongest for ER+/PR- tumors.

Progesterone receptor variation and risk of ovarian cancer is limited to the invasive endometrioid subtype: results from the Ovarian Cancer Association Consortium pooled analysis

There is evidence that progesterone plays a role in the aetiology of invasive epithelial ovarian cancer. Therefore, genes involved in pathways that regulate progesterone may be candidates for susceptibility to this disease. Previous studies have suggested that genetic variants in the progesterone receptor gene (PGR) may be associated with ovarian cancer risk, although results have been inconsistent. We have established an international consortium to pool resources and data from many ovarian cancer case–control studies in an effort to identify variants that influence risk. In this study, three PGR single nucleotide polymorphisms (SNPs), for which previous data have suggested they affect ovarian cancer risk, were examined. These were +331 C/T (rs10895068), PROGINS (rs1042838), and a 3′ variant (rs608995). A total of 4788 ovarian cancer cases and 7614 controls from 12 case–control studies were included in this analysis. Unconditional logistic regression was used to model the association between each SNP and ovarian cancer risk and two-sided P-values are reported. Overall, risk of ovarian cancer was not associated with any of the three variants studied. However, in histopathological subtype analyses, we found a statistically significant association between risk of endometrioid ovarian cancer and the PROGINS allele (n=651, OR=1.17, 95% CI=1.01–1.36, P=0.036). We also observed borderline evidence of an association between risk of endometrioid ovarian cancer and the +331C/T variant (n=725 cases; OR=0.80, 95% CI 0.62–1.04, P=0.100). These data suggest that while these three variants in the PGR are not associated with ovarian cancer overall, the PROGINS variant may play a modest role in risk of endometrioid ovarian cancer.