42 research outputs found
Protein kinase Cδ expression in breast cancer as measured by real-time PCR, western blotting and ELISA
The protein kinase C (PKC) family of genes encode serine/threonine kinases that regulate proliferation, apoptosis, cell survival and migration. Multiple isoforms of PKC have been described, one of which is PKCδ. Currently, it is unclear whether PKCδ is involved in promoting or inhibiting cancer formation/progression. The aim of this study was therefore to investigate the expression of PKCδ in human breast cancer and relate its levels to multiple parameters of tumour progression. Protein kinase Cδ expression at the mRNA level was measured using real-time PCR (n=208) and at protein level by both immunoblotting (n=94) and ELISA (n=98). Following immunoblotting, two proteins were identified, migrating with molecular masses of 78 and 160 kDa. The 78 kDa protein is likely to be the mature form of PKCδ but the identity of the 160 kDa form is unknown. Levels of both these proteins correlated weakly but significantly with PKCδ concentrations determined by ELISA (for the 78 kDa form, r=0.444, P<0.005, n=91 and for the 160 kDa form, r=0.237, P=0.023, n=91) and with PKCδ mRNA levels (for the 78 kDa form, r=0.351, P=0.001, n=94 and for the 160 kDa form, r=0.216, P=0.037, n=94). Protein kinase Cδ mRNA expression was significantly higher in oestrogen receptor (ER)-positive compared with ER-negative tumours (P=0.007, Mann–Whitney U-test). Increasing concentrations of PKCδ mRNA were associated with reduced overall patient survival (P=0.004). Our results are consistent with a role for PKCδ in breast cancer progression
Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment
BACKGROUND: Given the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients. METHODS: We performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP < 0.15). RESULTS: Evidence of associations with breast cancer-specific survival was observed in three patient subgroups, with variant rs5934618 in patients with grade 3 tumors (15-year-hazard ratio (HR) [95% confidence interval (CI)] 1.32 [1.20, 1.45], P = 1.4E-08, BFDP = 0.01, per G allele); variant rs4679741 in patients with ER-positive tumors treated with endocrine therapy (15-year-HR [95% CI] 1.18 [1.11, 1.26], P = 1.6E-07, BFDP = 0.09, per G allele); variants rs1106333 (15-year-HR [95% CI] 1.68 [1.39,2.03], P = 5.6E-08, BFDP = 0.12, per A allele) and rs78754389 (5-year-HR [95% CI] 1.79 [1.46,2.20], P = 1.7E-08, BFDP = 0.07, per A allele), in patients with ER-negative tumors treated with chemotherapy. CONCLUSIONS: We found evidence of four loci associated with breast cancer-specific survival within three patient subgroups. There was limited evidence for the existence of associations in other patient subgroups. However, the power for many subgroups is limited due to the low number of events. Even so, our results suggest that the impact of common germline genetic variants on breast cancer-specific survival might be limited
Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer.
Previous genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine-mapping study across 2.06 Mb (chr8:127,561,724-129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium was conducted. Three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93-0.97, conditional p = 5.8 × 10(-6) ), rs7815245 (OR = 0.94, 95% CI = 0.91-0.96, conditional p = 1.1 × 10(-6) ) and rs2033101 (OR = 1.05, 95% CI = 1.02-1.07, conditional p = 1.1 × 10(-4) ) were found. Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r(2) = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry.CRUK, NIH, fp7
Numerous funders. Details can be found within the financial support section of the manuscript
Recommended from our members
Copy number variants as modifiers of breast cancer risk for BRCA1/BRCA2 pathogenic variant carriers.
The contribution of germline copy number variants (CNVs) to risk of developing cancer in individuals with pathogenic BRCA1 or BRCA2 variants remains relatively unknown. We conducted the largest genome-wide analysis of CNVs in 15,342 BRCA1 and 10,740 BRCA2 pathogenic variant carriers. We used these results to prioritise a candidate breast cancer risk-modifier gene for laboratory analysis and biological validation. Notably, the HR for deletions in BRCA1 suggested an elevated breast cancer risk estimate (hazard ratio (HR) = 1.21), 95% confidence interval (95% CI = 1.09-1.35) compared with non-CNV pathogenic variants. In contrast, deletions overlapping SULT1A1 suggested a decreased breast cancer risk (HR = 0.73, 95% CI 0.59-0.91) in BRCA1 pathogenic variant carriers. Functional analyses of SULT1A1 showed that reduced mRNA expression in pathogenic BRCA1 variant cells was associated with reduced cellular proliferation and reduced DNA damage after treatment with DNA damaging agents. These data provide evidence that deleterious variants in BRCA1 plus SULT1A1 deletions contribute to variable breast cancer risk in BRCA1 carriers
Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.
Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs
Characterizing the invasion of different breast cancer cell lines with distinct E-cadherin status in 3D using a microfluidic system
\u3cp\u3eE-cadherin is a cell-cell adhesion protein that plays a prominent role in cancer invasion. Inactivation of E-cadherin in breast cancer can arise from gene promoter hypermethylation or genetic mutation. Depending on their E-cadherin status, breast cancer cells adopt different morphologies with distinct invasion modes. The tumor microenvironment (TME) can also affect the cell morphology and invasion mode. In this paper, we used a previously developed microfluidic system to quantify the three-dimensional invasion of breast cancer cells with different E-cadherin status, namely MCF-7, CAMA-1 and MDA-MB-231 with wild type, mutated and promoter hypermethylated E-cadherin, respectively. The cells migrated into a stable and reproducible microfibrous polycaprolactone mesh in the chip under a programmed stable chemotactic gradient. We observed that the MDA-MB-231 cells invaded the most, as single cells. MCF-7 cells collectively invaded into the matrix more than CAMA-1 cells, maintaining their E-cadherin expression. The CAMA-1 cells exhibited multicellular multifocal infiltration into the matrix. These results are consistent with what is seen in vivo in the cancer biology literature. In addition, comparison between complete serum and serum gradient conditions showed that the MDA-MB-231 cells invaded more under the serum gradient after one day, however this behavior was inverted after 3 days. The results showcase that the microfluidic system can be used to quantitatively assess the invasion behavior of cancer cells with different E-cadherin expression, for a longer period than conventional invasion models. In the future, it can be used to quantitatively investigate effects of matrix structure and cell treatments on cancer invasion.\u3c/p\u3