In mammals, most physiology and behavior are subject to well-controlled daily oscillations. Thus, sleep-wake cycles, heartbeat frequency, blood pressure, body temperature, renal activity, liver metabolism, and the secretion of many hormones are controlled by an endogenous time measuring system called the circadian clock (Portaluppi et

Mammalian circadian rhythms are generated by a feedback loop in which BMAL1 and CLOCK, players of the positive limb, activate transcription of the cryptochrome and period genes, components of the negative limb. Bmal1 and Per transcription cycles display nearly opposite phases and are thus governed by different mechanisms. Here, we identify the orphan nuclear receptor REV-ERBalpha as the major regulator of cyclic Bmal1 transcription. Circadian Rev-erbalpha expression is controlled by components of the general feedback loop. Thus, REV-ERBalpha constitutes a molecular link through which components of the negative limb drive antiphasic expression of components of the positive limb. While REV-ERBalpha influences the period length and affects the phase-shifting properties of the clock, it is not required for circadian rhythm generation.

The treatment of cultured rat-1 fibroblasts or H35 hepatoma cells with high concentrations of serum induces the circadian expression of various genes whose transcription also oscillates in living animals. Oscillating genes include rper1 and rper2 (rat homologs of the Drosophila clock gene period), and the genes encoding the transcription factors Rev-Erb alpha, DBP, and TEF. In rat-1 fibroblasts, up to three consecutive daily oscillations with an average period length of 22.5 hr could be recorded. The temporal sequence of the various mRNA accumulation cycles is the same in cultured cells and in vivo. The serum shock of rat-1 fibroblasts also results in a transient stimulation of c-fos and rper expression and thus mimics light-induced immediate-early gene expression in the suprachiasmatic nucleus.

TERT-locus single nucleotide polymorphisms (SNPs) and leucocyte telomere measures are reportedly associated with risks of multiple cancers. Using the iCOGs chip, we analysed ~480 TERT-locus SNPs in breast (n=103,991), ovarian (n=39,774) and BRCA1 mutation carrier (11,705) cancer cases and controls. 53,724 participants have leucocyte telomere measures. Most associations cluster into three independent peaks. Peak 1 SNP rs2736108 minor allele associates with longer telomeres (P=5.8×10 −7 ), reduced estrogen receptor negative (ER-negative) (P=1.0×10 −8 ) and BRCA1 mutation carrier (P=1.1×10 −5 ) breast cancer risks, and altered promoter-assay signal. Peak 2 SNP rs7705526 minor allele associates with longer telomeres (P=2.3×10 −14 ), increased low malignant potential ovarian cancer risk (P=1.3×10 −15 ) and increased promoter activity. Peak 3 SNPs rs10069690 and rs2242652 minor alleles increase ER-negative (P=1.2×10 −12 ) and BRCA1 mutation carrier (P=1.6×10 −14 ) breast and invasive ovarian (P=1.3×10 −11 ) cancer risks, but not via altered telomere length. The cancer-risk alleles of rs2242652 and rs10069690 respectively increase silencing and generate a truncated TERT splicevariant.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3, 9q31.1) and one for endometrioid EOC (5q12.3). We then meta-analysed the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified an additional three loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a novel susceptibility gene for low grade/borderline serous EOC.

IMPORTANCE Limited information about the relationship between specific mutations in BRCA1 or BRCA2 (BRCA1/2) and cancer risk exists. OBJECTIVE To identify mutation-specific cancer risks for carriers of BRCA1/2. DESIGN, SETTING, AND PARTICIPANTS Observational study of women who were ascertained between 1937 and 2011 (median, 1999) and found to carry disease-associated BRCA1 or BRCA2 mutations. The international sample comprised 19 581 carriers of BRCA1 mutations and 11 900 carriers of BRCA2 mutations from 55 centers in 33 countries on 6 continents. We estimated hazard ratios for breast and ovarian cancer based on mutation type, function, and nucleotide position. We also estimated RHR, the ratio of breast vs ovarian cancer hazard ratios. A value of RHR greater than 1 indicated elevated breast cancer risk; a value of RHR less than 1 indicated elevated ovarian cancer risk. EXPOSURES Mutations of BRCA1 or BRCA2. MAIN OUTCOMES AND MEASURES Breast and ovarian cancer risks. RESULTS Among BRCA1 mutation carriers, 9052 women (46%) were diagnosed with breast cancer, 2317 (12%) with ovarian cancer, 1041 (5%) with breast and ovarian cancer, and 7171 (37%) without cancer. Among BRCA2 mutation carriers, 6180 women (52%) were diagnosed with breast cancer, 682 (6%) with ovarian cancer, 272 (2%) with breast and ovarian cancer, and 4766 (40%) without cancer. In BRCA1, we identified 3 breast cancer cluster regions (BCCRs) located at c.179 to c.505 (BCCR1; RHR = 1.46; 95% CI, 1.22–1.74; P = 2 × 10−6), c.4328 to c.4945 (BCCR2; RHR = 1.34; 95% CI, 1.01–1.78; P = .04), and c. 5261 to c.5563 (BCCR23, RHR = 1.38; 95% CI, 1.22–1.55; P = 6 × 10−9). We also identified an ovarian cancer cluster region (OCCR) from c.1380 to c.4062 (approximately exon 11) with RHR = 0.62 (95% CI, 0.56–0.70; P = 9 × 10−17). In BRCA2, we observed multiple BCCRs spanning c.1 to c.596 (BCCR1; RHR = 1.71; 95% CI, 1.06–2.78; P = .03), c.772 to c.1806 (BCCR13; RHR = 1.63; 95% CI, 1.10–2.40; P = .01), and c.7394 to c.8904 (BCCR2; RHR = 2.31; 95% CI, 1.69–3.16; P = .00002). We also identified 3 OCCRs: the first (OCCR1) spanned c.3249 to c.5681 that was adjacent to c.5946delT (6174delT; RHR = 0.51; 95% CI, 0.44–0.60; P = 6 × 10−17). The second OCCR spanned c.6645 to c.7471 (OCCR2; RHR = 0.57; 95% CI, 0.41–0.80; P = .001). Mutations conferring nonsense-mediated decay were associated with differential breast or ovarian cancer risks and an earlier age of breast cancer diagnosis for both BRCA1 and BRCA2 mutation carriers. CONCLUSIONS AND RELEVANCE Breast and ovarian cancer risks varied by type and location of BRCA1/2 mutations. With appropriate validation, these data may have implications for risk assessment and cancer prevention decision making for carriers of BRCA1 and BRCA2 mutations.

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease1. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10−8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 14% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

contributed equally to this workThe circadian timing system in mammals is composed of a master pacemaker in the suprachiasmatic nucleus (SCN) of the hypothalamus and slave clocks in most peripheral cell types. The phase of peripheral clocks can be completely uncoupled from the SCN pacemaker by restricted feeding. Thus, feeding time, while not affecting the phase of the SCN pacemaker, is a dominant Zeitgeber for peripheral circadian oscillators. Here we show that the phase resetting in peripheral clocks of nocturnal mice is slow when feeding time is changed from night to day and rapid when switched back from day to night. Unexpectedly, the inertia in daytime feeding-induced phase resetting of circadian gene expression in liver and kidney is not an intrinsic property of peripheral oscillators, but is caused by glucocorticoid signaling. Thus, glucocorticoid hormones inhibit the uncoupling of peripheral and central circadian oscillators by altered feeding time.