Citations

Abstract The 19p13.1 breast cancer susceptibility locus is a modifier of breast cancer risk in BRCA1 mutation carriers and is also associated with the risk of ovarian cancer. Here, we investigated 19p13.1 variation and risk of breast cancer subtypes, defined by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status, using 48,869 breast cancer cases and 49,787 controls from the Breast Cancer Association Consortium (BCAC). Variants from 19p13.1 were not associated with breast cancer overall or with ER-positive breast cancer but were significantly associated with ER-negative breast cancer risk [rs8170 OR, 1.10; 95% confidence interval (CI), 1.05–1.15; P = 3.49 × 10−5] and triple-negative (ER-, PR-, and HER2-negative) breast cancer (rs8170: OR, 1.22; 95% CI, 1.13–1.31; P = 2.22 × 10−7). However, rs8170 was no longer associated with ER-negative breast cancer risk when triple-negative cases were excluded (OR, 0.98; 95% CI, 0.89–1.07; P = 0.62). In addition, a combined analysis of triple-negative cases from BCAC and the Triple Negative Breast Cancer Consortium (TNBCC; N = 3,566) identified a genome-wide significant association between rs8170 and triple-negative breast cancer risk (OR, 1.25; 95% CI, 1.18–1.33; P = 3.31 × 10−13]. Thus, 19p13.1 is the first triple-negative–specific breast cancer risk locus and the first locus specific to a histologic subtype defined by ER, PR, and HER2 to be identified. These findings provide convincing evidence that genetic susceptibility to breast cancer varies by tumor subtype and that triple-negative tumors and other subtypes likely arise through distinct etiologic pathways. Cancer Res; 72(7); 1795–803. ©2012 AACR.

In the bone marrow cavity, adipocyte numbers increase, whereas osteoblast progenitor numbers decrease with aging. Because adipocytes and osteoblasts share a common progenitor, it is possible that this shift is due to an increase in adipocyte-lineage cells at the expense of osteoblast-lineage commitment. Estrogens inhibit adipocyte differentiation, and in both men and women, circulating estrogens correlate with bone loss with aging. In bone cells, estrogens stimulate expression of TGF-β and suppress mesenchymal cell adipogenesis. Using a tripotential mesenchymal cell line, we have examined whether estradiol suppression of adipocyte differentiation is due to stimulation of TGF-β and the mechanism by which TGF-β suppresses adipogenesis. We observed that estradiol-mediated suppression of adipogenic gene expression required at least 48 h treatment. TGF-β expression increased within 24 h of estradiol treatment, and TGF-β inhibition reversed estradiol influences on adipogenesis and adipocyte gene expression. Connective tissue growth factor (CTGF) mediates TGF-β suppression of adipogenesis in mouse 3T3-L1 cells. CTGF expression was induced within 24 h of TGF-β treatment, whereas estradiol-mediated induction required 48 h treatment. Moreover, estradiol-mediated induction of CTGF was abrogated by TGF-β inhibition. These data support that estradiol effects on adipogenesis involves TGF-β induction, which then induces CTGF to suppress adipogenesis.

Abstract Background: The single-nucleotide polymorphism (SNP) 5p12-rs10941679 has been found to be associated with risk of breast cancer, particularly estrogen receptor (ER)-positive disease. We aimed to further explore this association overall, and by tumor histopathology, in the Breast Cancer Association Consortium. Methods: Data were combined from 37 studies, including 40,972 invasive cases, 1,398 cases of ductal carcinoma in situ (DCIS), and 46,334 controls, all of white European ancestry, as well as 3,007 invasive cases and 2,337 controls of Asian ancestry. Associations overall and by tumor invasiveness and histopathology were assessed using logistic regression. Results: For white Europeans, the per-allele OR associated with 5p12-rs10941679 was 1.11 (95% CI = 1.08–1.14, P = 7 × 10−18) for invasive breast cancer and 1.10 (95% CI = 1.01–1.21, P = 0.03) for DCIS. For Asian women, the estimated OR for invasive disease was similar (OR = 1.07, 95%CI = 0.99–1.15, P = 0.09). Further analyses suggested that the association in white Europeans was largely limited to progesterone receptor (PR)-positive disease (per-allele OR = 1.16, 95% CI = 1.12–1.20, P = 1 × 10−18 vs. OR = 1.03, 95% CI = 0.99–1.07, P = 0.2 for PR-negative disease; Pheterogeneity = 2 × 10−7); heterogeneity by ER status was not observed (P = 0.2) once PR status was accounted for. The association was also stronger for lower grade tumors [per-allele OR (95% CI) = 1.20 (1.14–1.25), 1.13 (1.09–1.16), and 1.04 (0.99–1.08) for grade 1, 2, and 3/4, respectively; Ptrend = 5 × 10−7]. Conclusion: 5p12 is a breast cancer susceptibility locus for PR-positive, lower grade breast cancer. Impact: Multicenter fine-mapping studies of this region are needed as a first step to identifying the causal variant or variants. Cancer Epidemiol Biomarkers Prev; 20(10); 2222–31. ©2011 AACR.

X chromosome inactivation (XCI) is the most dramatic example of epigenetic silencing in eukaryotes. Once established, the inactivated X chromosome (Xi) remains silenced throughout subsequent cell divisions. Though the initiation of XCI has been studied extensively, the protein factors involved in Xi silencing and maintenance are largely unknown. Here we report the discovery of a diverse set of 32 proteins involved in maintenance of Xi silencing through a genome-wide RNAi screen. In addition, we describe the mechanistic roles of two proteins—origin recognition complex 2 (Orc2) and heterochromatin protein 1 (HP1α)—in Xi silencing. Immunofluorescence studies indicate that Orc2 and HP1α localize on Xi in mouse cells. Depletion of Orc2 by shRNA leads to the loss of both Orc2 and HP1α localization on Xi. Furthermore, the silencing of genes on Xi is disrupted in both Orc2- and HP1α-depleted cells. Finally, we show, using ChIP assay, that the localization of HP1α and Orc2 to the promoter regions of Xi-silenced genes is interdependent. These findings reveal a diverse set of proteins involved in Xi silencing, show how Orc2 and HP1α impact Xi silencing, and provide a basis for future studies on the maintenance of Xi silencing.

Abstract Purpose: The categorical definition of response assessed via the Response Evaluation Criteria in Solid Tumors has documented limitations. We sought to identify alternative metrics for tumor response that improve prediction of overall survival. Experimental Design: Individual patient data from three North Central Cancer Treatment Group trials (N0026, n = 117; N9741, n = 1,109; and N9841, n = 332) were used. Continuous metrics of tumor size based on longitudinal tumor measurements were considered in addition to a trichotomized response [TriTR: response (complete or partial) vs. stable disease vs. progression). Cox proportional hazards models, adjusted for treatment arm and baseline tumor burden, were used to assess the impact of the metrics on subsequent overall survival, using a landmark analysis approach at 12, 16, and 24 weeks postbaseline. Model discrimination was evaluated by the concordance (c) index. Results: The overall best response rates for the three trials were 26%, 45%, and 25%, respectively. Although nearly all metrics were statistically significantly associated with overall survival at the different landmark time points, the concordance indices (c-index) for the traditional response metrics ranged from 0.59 to 0.65; for the continuous metrics from 0.60 to 0.66; and for the TriTR metrics from 0.64 to 0.69. The c-indices for TriTR at 12 weeks were comparable with those at 16 and 24 weeks. Conclusions: Continuous tumor measurement–based metrics provided no predictive improvement over traditional response–based metrics or TriTR; TriTR had better predictive ability than best TriTR or confirmed response. If confirmed, TriTR represents a promising endpoint for future phase II trials. Clin Cancer Res; 17(20); 6592–9. ©2011 AACR.

Background—Current clinical diagnosis of long-QT syndrome (LQTS) includes genetic testing of family members of mutation-positive patients. The present study was designed to assess the clinical course of individuals who are found negative for the LQTS-causing mutation in their families.Methods and Results—Multivariate Cox proportional hazards model was used to assess the risk for cardiac events (comprising syncope, aborted cardiac arrest [ACA], or sudden cardiac death [SCD]) from birth through age 40 years among 1828 subjects from the LQTS Registry who were found negative for their family LQTS-causing mutation. The median QTc of study subjects was 423 ms (interquartile range, 402–442 ms). The cumulative probability of a first syncope through age 40 years was 15%. However, only 2 patients (0.1%) had ACA, and none died suddenly during follow-up. Independent risk factors for syncope in genotype-negative subjects included female sex (hazard ratio [HR], 1.60;P=0.002), prolonged QTc (HR=1.63 per 100 ms increment,P=0.02), family history of ACA or SCD (HR=1.89,P=0.002), and LQT2 versus LQT1 family mutation (HR=1.41,P=0.03). Subgroup analysis showed that the presence of theK897Tpolymorphism in the LQT2 gene in an affected family was associated with an 11-fold (P=0.001) increase in the risk of recurrent syncope in genotype-negative subjects.Conclusions—Our findings suggest that cardiac events among genotype-negative family members of LQTS patients are dominated by nonfatal syncopal episodes without occurrence of sudden cardiac death. The risk for nonfatal events in this population may be mediated by the presence of common polymorphisms in LQTS genes.

Adenosine monophosphate–activated protein kinase (AMPK) is a major energy sensor that maintains cellular energy homeostasis. Huntington’s disease (HD) is a neurodegenerative disorder caused by the expansion of CAG repeats in the huntingtin (Htt) gene. In this paper, we report that activation of the α1 isoform of AMPK (AMPK-α1) occurred in striatal neurons of humans and mice with HD. Overactivation of AMPK in the striatum caused brain atrophy, facilitated neuronal loss, and increased formation of Htt aggregates in a transgenic mouse model (R6/2) of HD. Such nuclear accumulation of AMPK-α1 was activity dependent. Prevention of nuclear translocation or inactivation of AMPK-α1 ameliorated cell death and down-regulation of Bcl2 caused by mutant Htt (mHtt). Conversely, enhanced expression of Bcl2 protected striatal cells from the toxicity evoked by mHtt and AMPK overactivation. These data demonstrate that aberrant activation of AMPK-α1 in the nuclei of striatal cells represents a new toxic pathway induced by mHtt.

Abstract Background: Genetic susceptibility for cancer can differ substantially among families. We use trait-related covariates to identify a genetically homogeneous subset of families with the best evidence for linkage in the presence of heterogeneity. Methods: We performed a genome-wide linkage screen in 93 families. Samples and data were collected by the familial lung cancer recruitment sites of the Genetic Epidemiology of Lung Cancer Consortium. We estimated linkage scores for each family by the Markov chain Monte Carlo procedure using SimWalk2 software. We used ordered subset analysis (OSA) to identify genetically homogenous families by ordering families based on a disease-associated covariate. We performed permutation tests to determine the relationship between the trait-related covariate and the evidence for linkage. Results: A genome-wide screen for lung cancer loci identified strong evidence for linkage to 6q23–25 and suggestive evidence for linkage to 12q24 using OSA, with peak logarithm of odds (LOD) scores of 4.19 and 2.79, respectively. We found other chromosomes also suggestive for linkages, including 5q31–q33, 14q11, and 16q24. Conclusions: Our OSA results support 6q as a lung cancer susceptibility locus and provide evidence for disease linkage on 12q24. This study further increased our understanding of the inheritability for lung cancer. Validation studies using larger sample size are needed to verify the presence of several other chromosomal regions suggestive of an increased risk for lung cancer and/or other cancers. Impact: OSA can reduce genetic heterogeneity in linkage study and may assist in revealing novel susceptibility loci. Cancer Epidemiol Biomarkers Prev; 19(12); 3157–66. ©2010 AACR.