43 research outputs found

    Paclitaxel, Epirubicin and Capecitabine (TEX) as First-Line Treatment for Metastatic Breast Cancer: a Pilot Phase I/II Feasibility Study

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    Thirteen patients with untreated metastatic breast cancer received epirubicin 60 mg/m2, paclitaxel 155 mg/m2 (both day 1) and capecitabine 665 mg/m2 twice daily (days 1–14) every 21 days, with intra-patient dose escalation/reduction. Grade 3/4 events were infrequent. Nine patients (69%) achieved an objective response. Median time to progression and overall survival were 6.6 and 23.5 months, respectively

    Inactivation of promoter 1B of APC causes partial gene silencing: evidence for a significant role of the promoter in regulation and causative of familial adenomatous polyposis

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    Familial adenomatous polyposis (FAP) is caused by germline mutations in the adenomatous polyposis coli (APC) gene. Two promoters, 1A and 1B, have been recognized in APC, and 1B is thought to have a minor role in the regulation of the gene. We have identified a novel deletion encompassing half of this promoter in the largest family (Family 1) of the Swedish Polyposis Registry. The mutation leads to an imbalance in allele-specific expression of APC, and transcription from promoter 1B was highly impaired in both normal colorectal mucosa and blood from mutation carriers. To establish the significance of promoter 1B in normal colorectal mucosa (from controls), expression levels of specific transcripts from each of the promoters, 1A and 1B, were examined, and the expression from 1B was significantly higher compared with 1A. Significant amounts of transcripts generated from promoter 1B were also determined in a panel of 20 various normal tissues examined. In FAP-related tumors, the APC germline mutation is proposed to dictate the second hit. Mutations leaving two or three out of seven 20-amino-acid repeats in the central domain of APC intact seem to be required for tumorigenesis. We examined adenomas from mutation carriers in Family 1 for second hits in the entire gene without any findings, however, loss of the residual expression of the deleterious allele was observed. Three major conclusions of significant importance in relation to the function of APC can be drawn from this study; (i) germline inactivation of promoter 1B is disease causing in FAP; (ii) expression of transcripts from promoter 1B is generated at considerable higher levels compared with 1A, demonstrating a hitherto unknown importance of 1B; (iii) adenoma formation in FAP, caused by impaired function of promoter 1B, does not require homozygous inactivation of APC allowing for alternative genetic models as basis for adenoma formation

    Association of breast cancer risk in BRCA1 and BRCA2 mutation carriers with genetic variants showing differential allelic expression:Identification of a modifier of breast cancer risk at locus 11q22.3

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    Cis-acting regulatory SNPs resulting in differential allelic expression (DAE) may, in part, explain the underlying phenotypic variation associated with many complex diseases. To investigate whether common variants associated with DAE were involved in breast cancer susceptibility among BRCA1 and BRCA2 mutation carriers, a list of 175 genes was developed based of their involvement in cancer-related pathways.Using data from a genome-wide map of SNPs associated with allelic expression, we assessed the association of similar to 320 SNPs located in the vicinity of these genes with breast and ovarian cancer risks in 15,252 BRCA1 and 8211 BRCA2 mutation carriers ascertained from 54 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2.We identified a region on 11q22.3 that is significantly associated with breast cancer risk in BRCA1 mutation carriers (most significant SNP rs228595 p = 7 x 10(-6)). This association was absent in BRCA2 carriers (p = 0.57). The 11q22.3 region notably encompasses genes such as ACAT1, NPAT, and ATM. Expression quantitative trait loci associations were observed in both normal breast and tumors across this region, namely for ACAT1, ATM, and other genes. In silico analysis revealed some overlap between top risk-associated SNPs and relevant biological features in mammary cell data, which suggests potential functional significance.We identified 11q22.3 as a new modifier locus in BRCA1 carriers. Replication in larger studies using estrogen receptor (ER)-negative or triple-negative (i.e., ER-, progesterone receptor-, and HER2-negative) cases could therefore be helpful to confirm the association of this locus with breast cancer risk.</p

    Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus.

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    BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. CONCLUSION: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk.UK funding includes Cancer Research UK and NIH.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s13058-016-0718-

    Association of Type and Location of BRCA1 and BRCA2 Mutations With Risk of Breast and Ovarian Cancer (vol 313, pg 1347, 2015)

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    Heli Nevanlinna ja Kristiina Aittomäki ovat CIMBA Consortium -työryhmän jäseniä.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% Cl, 1.22-1.74; P = 2 x 10(-6)), c.4328 to c.4945 (BCCR2; RH R = 1.34; 95% Cl, 1.01-1.78; P =.04), and c. 5261 to c.5563 (BCCR2', RHR = 1.38; 95% Cl, 1.22-1.55; P = 6 x 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% Cl, 0.56-0.70; P = 9 x 10(-17)). In BRCA2, we observed multiple BCCRs spanning c.1 to c.596 (BCCR1; RHR = 1.71; 95% Cl, 1.06-2.78; P =.03), c.772 to c.1806 (BCCRI; RHR = 1.63; 95% Cl, 1.10-2.40; P =.01), and c.7394 to c.8904 (BCCR2; RHR = 2.31; 95% Cl, 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% Cl, 0.44-0.60; P = 6 x 10(-17)). The second OCCR spanned c.6645 to c.7471 (OCCR2; RHR = 0.57; 95% Cl, 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.Peer reviewe

    Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

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    BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10-8, HR = 1.14, 95% CI: 1.09-1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10-8, HR = 1.27, 95% CI: 1.17-1.38) and 4q32.3 (rs4691139, P = 3.4×10-8, HR = 1.20, 95% CI: 1.17-1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific associat

    Integrative Genomics with Mediation Analysis in a Survival Context

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    DNA copy number aberrations (DCNA) and subsequent altered gene expression profiles may have a major impact on tumor initiation, on development, and eventually on recurrence and cancer-specific mortality. However, most methods employed in integrative genomic analysis of the two biological levels, DNA and RNA, do not consider survival time. In the present note, we propose the adoption of a survival analysis-based framework for the integrative analysis of DCNA and mRNA levels to reveal their implication on patient clinical outcome with the prerequisite that the effect of DCNA on survival is mediated by mRNA levels. The specific aim of the paper is to offer a feasible framework to test the DCNA-mRNA-survival pathway. We provide statistical inference algorithms for mediation based on asymptotic results. Furthermore, we illustrate the applicability of the method in an integrative genomic analysis setting by using a breast cancer data set consisting of 141 invasive breast tumors. In addition, we provide implementation in R
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