Genetic risk variants associated with in situ breast cancer

INTRODUCTION: Breast cancer in situ (BCIS) diagnoses, a precursor lesion for invasive breast cancer, comprise about 20 % of all breast cancers (BC) in countries with screening programs. Family history of BC is considered one of the strongest risk factors for BCIS. METHODS: To evaluate the association of BC susceptibility loci with BCIS risk, we genotyped 39 single nucleotide polymorphisms (SNPs), associated with risk of invasive BC, in 1317 BCIS cases, 10,645 invasive BC cases, and 14,006 healthy controls in the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3). Using unconditional logistic regression models adjusted for age and study, we estimated the association of SNPs with BCIS using two different comparison groups: healthy controls and invasive BC subjects to investigate whether BCIS and BC share a common genetic profile. RESULTS: We found that five SNPs (CDKN2BAS-rs1011970, FGFR2-rs3750817, FGFR2-rs2981582, TNRC9-rs3803662, 5p12-rs10941679) were significantly associated with BCIS risk (P value adjusted for multiple comparisons <0.0016). Comparing invasive BC and BCIS, the largest difference was for CDKN2BAS-rs1011970, which showed a positive association with BCIS (OR = 1.24, 95 % CI: 1.11-1.38, P = 1.27 x 10(-4)) and no association with invasive BC (OR = 1.03, 95 % CI: 0.99-1.07, P = 0.06), with a P value for case-case comparison of 0.006. Subgroup analyses investigating associations with ductal carcinoma in situ (DCIS) found similar associations, albeit less significant (OR = 1.25, 95 % CI: 1.09-1.42, P = 1.07 x 10(-3)). Additional risk analyses showed significant associations with invasive disease at the 0.05 level for 28 of the alleles and the OR estimates were consistent with those reported by other studies. CONCLUSIONS: Our study adds to the knowledge that several of the known BC susceptibility loci are risk factors for both BCIS and invasive BC, with the possible exception of rs1011970, a putatively functional SNP situated in the CDKN2BAS gene that may be a specific BCIS susceptibility locus

Importance of TP53 codon 72 and intron 3 duplication 16bp polymorphisms in prediction of susceptibility on breast cancer

<p>Abstract</p> <p>Background</p> <p><it>TP53 </it>is one of major tumour suppressor genes being essential in preservation of genome integrity. Two very common polymorphisms have been demonstrated to contribute to cancer susceptibility and tumour behaviour. The purpose of this study was to evaluate the role of <it>Arg72Pro </it>and <it>PIN3 Ins16bp </it>polymorphisms in <it>TP53 </it>gene as genetic susceptibility and predictive markers to breast cancer.</p> <p>Methods</p> <p>We analysed DNA samples from 264 breast cancer patients and 440 controls, for <it>TP53 Arg72Pro </it>and <it>PIN3 Ins16bp </it>polymorphisms using PCR-RFLP.</p> <p>Results</p> <p>We observed that women with <it>A2A2 </it>genotype have increased risk for developing breast cancer, either in women with or without familial history (FH) of the disease (OR = 4.40, 95% CI 1.60–12.0; p = 0.004; OR = 3.88, 95% CI 1.18–12.8; p = 0.026, respectively). In haplotype analysis, statistically significant differences were found between <it>TP53 Arg-A2 </it>haplotype frequencies and familial breast cancer cases and the respective control group (OR = 2.10, 95% CI 1.08–4.06; p = 0.028). Furthermore, both <it>TP53 </it>polymorphisms are associated with higher incidence of lymph node metastases.</p> <p>Conclusion</p> <p>Our findings suggest <it>TP53 PIN3 Ins16bp </it>polymorphism as a real risk modifier in breast cancer disease, either in sporadic and familial breast cancer. Furthermore, both TP53 polymorphisms are associated with higher incidence of lymph node metastases.</p

TNFRSF1B +676 T>G polymorphism predicts survival of non-Small cell lung cancer patients treated with chemoradiotherapy

<p>Abstract</p> <p>Background</p> <p>The dysregulation of gene expression in the TNF-TNFR superfamily has been involved in various human cancers including non-small cell lung cancer (NSCLC). Furthermore, functional polymorphisms in <it>TNF-α </it>and <it>TNFRSF1B </it>genes that alter gene expression are likely to be associated with risk and clinical outcomes of cancers. However, few reported studies have investigated the association between potentially functional SNPs in both <it>TNF-α </it>and <it>TNFRSF1B </it>and prognosis of NSCLC patients treated with chemoradiotherapy.</p> <p>Methods</p> <p>We genotyped five potentially functional polymorphisms of <it>TNF-α </it>and <it>TNFRSF1B </it>genes [<it>TNF-α </it>-308 G>A (rs1800629) and -1031 T>C (rs1799964); <it>TNFRSF1B </it>+676 T>G (rs1061622), -1709A>T(rs652625) and +1663A>G (rs1061624)] in 225 NSCLC patients treated with chemoradiotherapy or radiotherapy alone. Kaplan-Meier survival analysis, log-rank tests and Cox proportional hazard models were used to evaluate associations between these variants and NSCLC overall survival (OS).</p> <p>Results</p> <p>We found that the <it>TNFRSF1B </it>+676 GG genotype was associated with a significantly better OS of NSCLC (GG <it>vs. </it>TT: adjusted HR = 0.38, 95% CI = 0.15-0.94; GG <it>vs. </it>GT/TT: adjusted HR = 0.35, 95% CI = 0.14-0.88). Further stepwise multivariate Cox regression analysis showed that the <it>TNFRSF1B </it>+676 GG was an independent prognosis predictor in this NSCLC cohort (GG <it>vs. </it>GT/TT: HR = 0.35, 95% CI = 0.14-0.85), in the presence of node status (N_2-3<it>vs. </it>N_0-1: HR = 1.60, 95% CI = 1.09-2.35) and tumor stage (T_3-4<it>vs. </it>T_0-2: HR = 1.48, 95% CI = 1.08-2.03).</p> <p>Conclusions</p> <p>Although the exact biological function for this SNP remains to be explored, our findings suggest a possible role of <it>TNFRSF1B </it>+676 T>G (rs1061622) in the prognosis of NSCLC. Further large and functional studies are needed to confirm our findings.</p

Prognostic and predictive value of TOPK stratified by KRAS and BRAF gene alterations in sporadic, hereditary and metastatic colorectal cancer patients

BACKGROUND: Our aim was to investigate the prognostic and predictive value of the oncogenic MAPKK-like protein T-cell-originated protein kinase (TOPK) stratified by KRAS and BRAF mutations in patients with sporadic, hereditary and metastatic colorectal cancer (CRC) treated with anti-EGFR therapy. METHODS: Immunohistochemistry (IHC) for TOPK was performed on four study groups. Group 1 included two subgroups of 543 and 501 sporadic CRC patients used to test the reliability of TOPK expression by IHC. In Group 2, representing an additional 222 sporadic CRCs, the prognostic effect of TOPK stratified by KRAS and BRAF was assessed. The prognostic effect of TOPK was further analysed in Group 3, representing 71 hereditary Lynch syndrome-associated CRC patients. In Group 4, the predictive and prognostic value of TOPK was analysed on 45 metastatic patients treated with cetuximab or panitumumab stratified by KRAS and BRAF gene status. RESULTS: In both sporadic CRC subgroups (Group 1), associations of diffuse TOPK expression with clinicopathological features were reproducible. Molecular analysis of sporadic CRCs in Group 2 showed that diffuse TOPK expression was associated with KRAS and BRAF mutations (p<0.001) and with poor outcome in patients with either mutation in univariate and multivariate analysis (P=0.017). In hereditary patients (Group 3), diffuse TOPK was linked to advanced pT stage. In metastatic patients treated with anti-EGFR therapy (Group 4), diffuse TOPK expression was linked to dismal outcome despite objective response to treatment (P=0.01). CONCLUSIONS: TOPK expression is an unfavourable prognostic indicator in sporadic patients with KRAS or BRAF mutations and also in patients with metastatic disease experiencing a response to anti-EGFR therapies. The inhibition of TOPK, which could benefit 30-40% of CRC patients, may represent a new avenue of investigation for targeted therapy

The association of polymorphisms in hormone metabolism pathway genes, menopausal hormone therapy, and breast cancer risk: a nested case-control study in the California Teachers Study cohort

Abstract Introduction The female sex steroids estrogen and progesterone are important in breast cancer etiology. It therefore seems plausible that variation in genes involved in metabolism of these hormones may affect breast cancer risk, and that these associations may vary depending on menopausal status and use of hormone therapy. Methods We conducted a nested case-control study of breast cancer in the California Teachers Study cohort. We analyzed 317 tagging single nucleotide polymorphisms (SNPs) in 24 hormone pathway genes in 2746 non-Hispanic white women: 1351 cases and 1395 controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated by fitting conditional logistic regression models using all women or subgroups of women defined by menopausal status and hormone therapy use. P values were adjusted for multiple correlated tests (P ACT). Results The strongest associations were observed for SNPs in SLCO1B1, a solute carrier organic anion transporter gene, which transports estradiol-17β-glucuronide and estrone-3-sulfate from the blood into hepatocytes. Ten of 38 tagging SNPs of SLCO1B1 showed significant associations with postmenopausal breast cancer risk; 5 SNPs (rs11045777, rs11045773, rs16923519, rs4149057, rs11045884) remained statistically significant after adjusting for multiple testing within this gene (P ACT = 0.019-0.046). In postmenopausal women who were using combined estrogen-progestin therapy (EPT) at cohort enrollment, the OR of breast cancer was 2.31 (95% CI = 1.47-3.62) per minor allele of rs4149013 in SLCO1B1 (P = 0.0003; within-gene P ACT = 0.002; overall P ACT = 0.023). SNPs in other hormone pathway genes evaluated in this study were not associated with breast cancer risk in premenopausal or postmenopausal women. Conclusions We found evidence that genetic variation in SLCO1B1 is associated with breast cancer risk in postmenopausal women, particularly among those using EPT

Advancing brain barriers RNA sequencing: guidelines from experimental design to publication

Background: RNA sequencing (RNA-Seq) in its varied forms has become an indispensable tool for analyzing differential gene expression and thus characterization of specific tissues. Aiming to understand the brain barriers genetic signature, RNA seq has also been introduced in brain barriers research. This has led to availability of both, bulk and single-cell RNA-Seq datasets over the last few years. If appropriately performed, the RNA-Seq studies provide powerful datasets that allow for significant deepening of knowledge on the molecular mechanisms that establish the brain barriers. However, RNA-Seq studies comprise complex workflows that require to consider many options and variables before, during and after the proper sequencing process.Main body: In the current manuscript, we build on the interdisciplinary experience of the European PhD Training Network BtRAIN (https://www.btrain-2020.eu/) where bioinformaticians and brain barriers researchers collaborated to analyze and establish RNA-Seq datasets on vertebrate brain barriers. The obstacles BtRAIN has identified in this process have been integrated into the present manuscript. It provides guidelines along the entire workflow of brain barriers RNA-Seq studies starting from the overall experimental design to interpretation of results. Focusing on the vertebrate endothelial blood–brain barrier (BBB) and epithelial blood-cerebrospinal-fluid barrier (BCSFB) of the choroid plexus, we provide a step-by-step description of the workflow, highlighting the decisions to be made at each step of the workflow and explaining the strengths and weaknesses of individual choices made. Finally, we propose recommendations for accurate data interpretation and on the information to be included into a publication to ensure appropriate accessibility of the data and reproducibility of the observations by the scientific community.Conclusion: Next generation transcriptomic profiling of the brain barriers provides a novel resource for understanding the development, function and pathology of these barrier cells, which is essential for understanding CNS homeostasis and disease. Continuous advancement and sophistication of RNA-Seq will require interdisciplinary approaches between brain barrier researchers and bioinformaticians as successfully performed in BtRAIN. The present guidelines are built on the BtRAIN interdisciplinary experience and aim to facilitate collaboration of brain barriers researchers with bioinformaticians to advance RNA-Seq study design in the brain barriers community