Body fatness and cancer - viewpoint of the IARC working group

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Diabetes mellitus and prostate cancer risk among older men: population-based case–control study

We investigate the relation between diabetes mellitus and risk of prostate cancer among older (age 65–79 years) men in a population-based case–control study of 407 incident histologically confirmed cases registered in the South Carolina Central Cancer Registry between 1999 and 2001 (70.6% response rate); controls were 393 men identified through the Health Care Financing Administration Medicare beneficiary file for South Carolina in 1999 (63.8% response rate). After adjusting for age, race, and prostate cancer screening in the past 5 years, a history of diabetes mellitus was associated with a reduced risk of prostate cancer (adjusted odds ratio (aOR)¼0.64; 95% confidence interval (CI)¼0.45, 0.91). The protective effect was stronger for those with complications associated with diabetes (aOR¼0.61; 95% CI¼0.42, 0.90) and for African-American men (aOR¼0.36; 95% CI¼0.21, 0.62). Additional research is needed to understand the biologic mechanisms by which diabetes may influence prostate cancer risk; genetic factors may play an important role in understanding this association

Genetic risk variants associated with in situ breast cancer

INTRODUCTION: Breast cancer in situ (BCIS) diagnoses, a precursor lesion for invasive breast cancer, comprise about 20 % of all breast cancers (BC) in countries with screening programs. Family history of BC is considered one of the strongest risk factors for BCIS. METHODS: To evaluate the association of BC susceptibility loci with BCIS risk, we genotyped 39 single nucleotide polymorphisms (SNPs), associated with risk of invasive BC, in 1317 BCIS cases, 10,645 invasive BC cases, and 14,006 healthy controls in the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3). Using unconditional logistic regression models adjusted for age and study, we estimated the association of SNPs with BCIS using two different comparison groups: healthy controls and invasive BC subjects to investigate whether BCIS and BC share a common genetic profile. RESULTS: We found that five SNPs (CDKN2BAS-rs1011970, FGFR2-rs3750817, FGFR2-rs2981582, TNRC9-rs3803662, 5p12-rs10941679) were significantly associated with BCIS risk (P value adjusted for multiple comparisons <0.0016). Comparing invasive BC and BCIS, the largest difference was for CDKN2BAS-rs1011970, which showed a positive association with BCIS (OR = 1.24, 95 % CI: 1.11-1.38, P = 1.27 x 10(-4)) and no association with invasive BC (OR = 1.03, 95 % CI: 0.99-1.07, P = 0.06), with a P value for case-case comparison of 0.006. Subgroup analyses investigating associations with ductal carcinoma in situ (DCIS) found similar associations, albeit less significant (OR = 1.25, 95 % CI: 1.09-1.42, P = 1.07 x 10(-3)). Additional risk analyses showed significant associations with invasive disease at the 0.05 level for 28 of the alleles and the OR estimates were consistent with those reported by other studies. CONCLUSIONS: Our study adds to the knowledge that several of the known BC susceptibility loci are risk factors for both BCIS and invasive BC, with the possible exception of rs1011970, a putatively functional SNP situated in the CDKN2BAS gene that may be a specific BCIS susceptibility locus

A network analysis to identify mediators of germline-driven differences in breast cancer prognosis.

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis

Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression

Associations between single nucleotide polymorphisms (SNPs) at 5p15 and multiple cancer types have been reported. We have previously shown evidence for a strong association between prostate cancer (PrCa) risk and rs2242652 at 5p15, intronic in the telomerase reverse transcriptase (TERT) gene that encodes TERT. To comprehensively evaluate the association between genetic variation across this region and PrCa, we performed a fine-mapping analysis by genotyping 134 SNPs using a custom Illumina iSelect array or Sequenom MassArray iPlex, followed by imputation of 1094 SNPs in 22 301 PrCa cases and 22 320 controls in The PRACTICAL consortium. Multiple stepwise logistic regression analysis identified four signals in the promoter or intronic regions of TERT that independently associated with PrCa risk. Gene expression analysis of normal prostate tissue showed evidence that SNPs within one of these regions also associated with TERT expression, providing a potential mechanism for predisposition to disease

Steroid hormone measurements from different types of assays in relation to body mass index and breast cancer risk in postmenopausal women: Reanalysis of eighteen prospective studies

Epidemiological studies have examined breast cancer risk in relation to sex hormone concentrations measured by different methods: "extraction" immunoassays (with prior purification by organic solvent extraction, with or without column chromatography), "direct" immunoassays (no prior extraction or column chromatography), and more recently with mass spectrometry-based assays. We describe the associations of estradiol, estrone and testosterone with both body mass index and breast cancer risk in postmenopausal women according to assay method, using data from a collaborative pooled analysis of 18 prospective studies. In general, hormone concentrations were highest in studies that used direct assays and lowest in studies that used mass spectrometry-based assays. Estradiol and estrone were strongly positively associated with body mass index, regardless of the assay method; testosterone was positively associated with body mass index for direct assays, but less clearly for extraction assays, and there were few data for mass spectrometry assays. The correlations of estradiol with body mass index, estrone and testosterone were lower for direct assays than for extraction and mass spectrometry assays, suggesting that the estimates from the direct assays were less precise. For breast cancer risk, all three hormones were strongly positively associated with risk regardless of assay method (except for testosterone by mass spectrometry where there were few data), with no statistically significant differences in the trends, but differences may emerge as new data accumulate. Future epidemiological and clinical research studies should continue to use the most accurate assays that are feasible within the design characteristics of each study

Body fatness and cancer - viewpoint of the IARC working group

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