Identification of germline alterations of the mad homology 2 domain of SMAD3 and SMAD4 from the Ontario site of the breast cancer family registry (CFR)

Abstract Introduction A common feature of neoplastic cells is that mutations in SMADs can contribute to the loss of sensitivity to the anti-tumor effects of transforming growth factor-β (TGF-β). However, germline mutation analysis of SMAD3 and SMAD4, the principle substrates of the TGF-β signaling pathway, has not yet been conducted in breast cancer. Thus, it is currently unknown whether germline SMAD3 and SMAD4 mutations are involved in breast cancer predisposition. Methods We performed mutation analysis of the highly conserved mad-homology 2 (MH2) domains for both genes in genomic DNA from 408 non-BRCA1/BRCA2 breast cancer cases and 710 population controls recruited by the Ontario site of the breast cancer family registry (CFR) using denaturing high-performance liquid chromatography (DHPLC) and direct DNA sequencing. The results were interpreted in several ways. First, we adapted nucleotide diversity analysis to quantitatively assess whether the frequency of alterations differ between the two genes. Next, in silico tools were used to predict variants' effect on domain function and mRNA splicing. Finally, 37 cases or controls harboring alterations were tested for aberrant splicing using reverse-transcription polymerase chain reaction (PCR) and real-time PCR statistical comparison of germline expressions by non-parametric Mann-Whitney test of independent samples. Results We identified 27 variants including 2 novel SMAD4 coding variants c.1350G > A (p.Gln450Gln), and c.1701A > G (p.Ile525Val). There were no inactivating mutations even though c.1350G > A was predicted to affect exonic splicing enhancers. However, several additional findings were of note: 1) nucleotide diversity estimate for SMAD3 but not SMAD4 indicated that coding variants of the MH2 domain were more infrequent than expected; 2) in breast cancer cases SMAD3 was significantly over-expressed relative to controls (P A was associated with elevated germline expression (> 5-fold); 3) separate analysis using tissue expression data showed statistically significant over-expression of SMAD3 and SMAD4 in breast carcinomas. Conclusions This study shows that inactivating germline alterations in SMAD3 and SMAD4 are rare, suggesting a limited role in driving tumorigenesis. Nevertheless, aberrant germline expressions of SMAD3 and SMAD4 may be more common in breast cancer than previously suspected and offer novel insight into their roles in predisposition and/or progression of breast cancer

NCI60 Cancer Cell Line Panel Data and RNAi Analysis Help Identify EAF2 as a Modulator of Simvastatin and Lovastatin Response in HCT-116 Cells

Simvastatin and lovastatin are statins traditionally used for lowering serum cholesterol levels. However, there exists evidence indicating their potential chemotherapeutic characteristics in cancer. In this study, we used bioinformatic analysis of publicly available data in order to systematically identify the genes involved in resistance to cytotoxic effects of these two drugs in the NCI60 cell line panel. We used the pharmacological data available for all the NCI60 cell lines to classify simvastatin or lovastatin resistant and sensitive cell lines, respectively. Next, we performed whole-genome single marker case-control association tests for the lovastatin and simvastatin resistant and sensitive cells using their publicly available Affymetrix 125K SNP genomic data. The results were then evaluated using RNAi methodology. After correction of the p-values for multiple testing using False Discovery Rate, our results identified three genes (NRP1, COL13A1, MRPS31) and six genes (EAF2, ANK2, AKAP7, STEAP2, LPIN2, PARVB) associated with resistance to simvastatin and lovastatin, respectively. Functional validation using RNAi confirmed that silencing of EAF2 expression modulated the response of HCT-116 colon cancer cells to both statins. In summary, we have successfully utilized the publicly available data on the NCI60 cell lines to perform whole-genome association studies for simvastatin and lovastatin. Our results indicated genes involved in the cellular response to these statins and siRNA studies confirmed the role of the EAF2 in response to these drugs in HCT-116 colon cancer cells

Bioinformatic analyses identifies novel protein-coding pharmacogenomic markers associated with paclitaxel sensitivity in NCI60 cancer cell lines

<p>Abstract</p> <p>Background</p> <p>Paclitaxel is a microtubule-stabilizing drug that has been commonly used in treating cancer. Due to genetic heterogeneity within patient populations, therapeutic response rates often vary. Here we used the NCI60 panel to identify SNPs associated with paclitaxel sensitivity. Using the panel's GI50 response data available from Developmental Therapeutics Program, cell lines were categorized as either sensitive or resistant. PLINK software was used to perform a genome-wide association analysis of the cellular response to paclitaxel with the panel's SNP-genotype data on the Affymetrix 125 k SNP array. FastSNP software helped predict each SNP's potential impact on their gene product. mRNA expression differences between sensitive and resistant cell lines was examined using data from BioGPS. Using Haploview software, we investigated for haplotypes that were more strongly associated with the cellular response to paclitaxel. Ingenuity Pathway Analysis software helped us understand how our identified genes may alter the cellular response to paclitaxel.</p> <p>Results</p> <p>43 SNPs were found significantly associated (FDR < 0.005) with paclitaxel response, with 10 belonging to protein-coding genes (<it>CFTR</it>, <it>ROBO1</it>, <it>PTPRD</it>, <it>BTBD12</it>, <it>DCT</it>, <it>SNTG1</it>, <it>SGCD</it>, <it>LPHN2</it>, <it>GRIK1</it>, <it>ZNF607</it>). SNPs in <it>GRIK1</it>, <it>DCT</it>, <it>SGCD </it>and <it>CFTR </it>were predicted to be intronic enhancers, altering gene expression, while SNPs in <it>ZNF607 </it>and <it>BTBD12 </it>cause conservative missense mutations. mRNA expression analysis supported these findings as <it>GRIK1</it>, <it>DCT</it>, <it>SNTG1</it>, <it>SGCD </it>and <it>CFTR </it>showed significantly (p < 0.05) increased expression among sensitive cell lines. Haplotypes found in <it>GRIK1, SGCD, ROBO1, LPHN2</it>, and <it>PTPRD </it>were more strongly associated with response than their individual SNPs.</p> <p>Conclusions</p> <p>Our study has taken advantage of available genotypic data and its integration with drug response data obtained from the NCI60 panel. We identified 10 SNPs located within protein-coding genes that were not previously shown to be associated with paclitaxel response. As only five genes showed differential mRNA expression, the remainder would not have been detected solely based on expression data. The identified haplotypes highlight the role of utilizing SNP combinations within genomic loci of interest to improve the risk determination associated with drug response. These genetic variants represent promising biomarkers for predicting paclitaxel response and may play a significant role in the cellular response to paclitaxel.</p

ICAR: endoscopic skull‐base surgery

n/

Neutrophil stunning by metoprolol reduces infarct size

The beta 1-adrenergic-receptor (ADRB1) antagonist metoprolol reduces infarct size in acute myocardial infarction (AMI) patients. The prevailing view has been that metoprolol acts mainly on cardiomyocytes. Here, we demonstrate that metoprolol reduces reperfusion injury by targeting the haematopoietic compartment. Metoprolol inhibits neutrophil migration in an ADRB1-dependent manner. Metoprolol acts during early phases of neutrophil recruitment by impairing structural and functional rearrangements needed for productive engagement of circulating platelets, resulting in erratic intravascular dynamics and blunted inflammation. Depletion of neutrophils, ablation of Adrb1 in haematopoietic cells, or blockade of PSGL-1, the receptor involved in neutrophil-platelet interactions, fully abrogated metoprolol's infarct-limiting effects. The association between neutrophil count and microvascular obstruction is abolished in metoprolol-treated AMI patients. Metoprolol inhibits neutrophil-platelet interactions in AMI patients by targeting neutrophils. Identification of the relevant role of ADRB1 in haematopoietic cells during acute injury and the protective role upon its modulation offers potential for developing new therapeutic strategies.European Regional Development Fund (ERDF/FEDER) PI10/02268 PI13/01979 RD12/0042/0054ERDF/FEDER SAF2015-65607-RFundacio La Marato-TV3 120/C/2015-20153032Severo Ochoa Center of Excellence (MINECO) SEV-2015-0505Pro-CNIC FoundationSpanish Ministry of Economy and Competitiveness (MINECO)Fundacion Interhospitalaria de Investigacion Cardiovascular (FIC)12.353 JCR (2017) Q1, 3/64 Multidisciplinary SciencesUE