Is Genetic Background Important in Lung Cancer Survival?

BACKGROUND:In lung cancer, a patient's survival is poor with a wide variation in survival within the stage of disease. The aim of this study was to investigate the familial concordance in lung cancer survival by means of analyses of pairs with different degrees of familial relationships. METHODS:Our population-based Swedish family database included three million families and over 58,100 lung cancer patients. We modelled the proband (parent, sibling, spouse) survival utilizing a multivariate proportional hazard (Cox) model adjusting for possible confounders of survival. Subsequently, the survival in proband's relative (child, sibling, spouse) was analysed with a Cox model. FINDINGS:By use of Cox modelling with 5 years follow-up, we noted a decreased hazard ratio for death in children with good parental survival (Hazard Ratio [HR] = 0.71, 95% CI = 0.51 to 0.99), compared to those with poor parental survival. Also for siblings, a very strong protective effect was seen (HR = 0.14, 95% CI = 0.030 to 0.65). Finally, in spouses no correlation in survival was found. INTERPRETATION:Our findings suggest that genetic factors are important in lung cancer survival. In a clinical setting, information on prognosis in a relative may be vital in foreseeing the survival in an individual newly diagnosed with lung cancer. Future molecular studies enhancing the understanding of the underlying mechanisms and pathways are needed

CpG Islands Undermethylation in Human Genomic Regions under Selective Pressure

DNA methylation at CpG islands (CGIs) is one of the most intensively studied epigenetic mechanisms. It is fundamental for cellular differentiation and control of transcriptional potential. DNA methylation is involved also in several processes that are central to evolutionary biology, including phenotypic plasticity and evolvability. In this study, we explored the relationship between CpG islands methylation and signatures of selective pressure in Homo Sapiens, using a computational biology approach. By analyzing methylation data of 25 cell lines from the Encyclopedia of DNA Elements (ENCODE) Consortium, we compared the DNA methylation of CpG islands in genomic regions under selective pressure with the methylation of CpG islands in the remaining part of the genome. To define genomic regions under selective pressure, we used three different methods, each oriented to provide distinct information about selective events. Independently of the method and of the cell type used, we found evidences of undermethylation of CGIs in human genomic regions under selective pressure. Additionally, by analyzing SNP frequency in CpG islands, we demonstrated that CpG islands in regions under selective pressure show lower genetic variation. Our findings suggest that the CpG islands in regions under selective pressure seem to be somehow more “protected” from methylation when compared with other regions of the genome

Effects of Common Polymorphisms rs11614913 in miR-196a2 and rs2910164 in miR-146a on Cancer Susceptibility: A Meta-Analysis

BACKGROUND: MicroRNAs regulate gene expression at the post-transcriptional level and involved in diverse biological and pathological processes, including tumorigenesis. Rs11614913 in miR-196a2 and rs2910164 in miR-146a are shown to associate with increased/decreased cancer risk. We performed a meta-analysis to systematically summarize the possible association. METHODOLOGY/PRINCIPAL FINDINGS: We assessed published studies of the association between these microRNA polymorphisms and cancer risk from eleven studies with 16,771 subjects for miR-196a2 and from ten studies with 15,126 subjects for miR-146a. As for rs11614913, the contrast of homozygote (TT vs CC: OR = 0.92, 95% CI = 0.85-0.99, P(heterogeneity) = 0.45), allele (T vs C: OR = 0.96, 95% CI = 0.92-0.99, P(heterogeneity) = 0.61) and recessive model (OR = 0.90, 95% CI = 0.84-0.97, P(heterogeneity) = 0.50) produced statistically association. Subgroup analysis by ethnicity, statistically significantly decreased cancer risks were found among Asians for allele contrast (OR = 0.95, 95% CI = 0.90-0.99, P(heterogeneity) = 0.74) and the recessive genetic model (OR = 0.90, 95% CI = 0.82-0.98, P(heterogeneity) = 0.85). According to subgroup analysis by tumor types, the protective effect of C/T polymorphism was only found in breast cancer under allele contrast (T vs C: OR = 0.94, 95% CI = 0.88-0.99, P(heterogeneity) = 0.26). For rs2910164, no significant associations were found among overall analysis model with relatively large heterogeneity. Through the stratified analysis, heterogeneity decreased significantly. In the subgroup analyses by cancer types, the C allele of rs2910164 was associated with protection from digestive cancer in allele contrast (C vs G: OR = 0.86, 95% CI = 0.77-0.96, P(heterogeneity) = 0.51). CONCLUSIONS/SIGNIFICANCE: Our meta-analysis suggests that the rs11614913 most likely contributes to decreased susceptibility to cancer, especially in Asians and breast cancer. Besides, the C allele of the rs2910164 might be associated with a protection from digestive cancer

Plk1 regulates mitotic Aurora A function through βTrCP-dependent degradation of hBora

Polo-like kinase 1 (Plk1) and Aurora A play key roles in centrosome maturation, spindle assembly, and chromosome segregation during cell division. Here we show that the functions of these kinases during early mitosis are coordinated through Bora, a partner of Aurora A first identified in Drosophila. Depletion of human Bora (hBora) results in spindle defects, accompanied by increased spindle recruitment of Aurora A and its partner TPX2. Conversely, hBora overexpression induces mislocalization of Aurora A and monopolar spindle formation, reminiscent of the phenotype seen in Plk1-depleted cells. Indeed, Plk1 regulates hBora. Following Cdk1-dependent recruitment, Plk1 triggers hBora destruction by phosphorylating a recognition site for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{SCF}}^{{\text{ $ \beta $ - TrCP}}}$$\end{document}. Plk1 depletion or inhibition results in a massive accumulation of hBora, concomitant with displacement of Aurora A from spindle poles and impaired centrosome maturation, but remarkably, co-depletion of hBora partially restores Aurora A localization and bipolar spindle formation. This suggests that Plk1 controls Aurora A localization and function by regulating cellular levels of hBora

A Genotype-First Approach for the Molecular and Clinical Characterization of Uncommon De Novo Microdeletion of 20q13.33

Background: Subtelomeric deletions of the long arm of chromosome 20 are rare, with only 11 described in the literature. Clinical features of individuals with these microdeletions include severe limb malformations, skeletal abnormalities, growth retardation, developmental and speech delay, mental retardation, seizures and mild, non-specific dysmorphic features. Methodology/Principal Findings: We characterized microdeletions at 20q13.33 in six individuals referred for genetic evaluation of developmental delay, mental retardation, and/or congenital anomalies. A comparison to previously reported cases of 20q13.33 microdeletion shows phenotypic overlap, with clinical features that include mental retardation, developmental delay, speech and language deficits, seizures, and behavior problems such as autistic spectrum disorder. There does not appear to be a clinically recognizable constellation of dysmorphic features among individuals with subtelomeric 20q microdeletions. Conclusions/Significance: Based on genotype-phenotype correlation among individuals in this and previous studies, we discuss several possible candidate genes for specific clinical features, including ARFGAP1, CHRNA4 and KCNQ2 and neurodevelopmental deficits. Deletion of this region may play an important role in cognitive development

Using genetic variation and environmental risk factor data to identify individuals at high risk for age-related macular degeneration

A major goal of personalized medicine is to pre-symptomatically identify individuals at high risk for disease using knowledge of each individual's particular genetic profile and constellation of environmental risk factors. With the identification of several well-replicated risk factors for age-related macular degeneration (AMD), the leading cause of legal blindness in older adults, this previously unreachable goal is beginning to seem less elusive. However, recently developed algorithms have either been much less accurate than expected, given the strong effects of the identified risk factors, or have not been applied to independent datasets, leaving unknown how well they would perform in the population at large. We sought to increase accuracy by using novel modeling strategies, including multifactor dimensionality reduction (MDR) and grammatical evolution of neural networks (GENN), in addition to the traditional logistic regression approach. Furthermore, we rigorously designed and tested our models in three distinct datasets: a Vanderbilt-Miami (VM) clinic-based case-control dataset, a VM family dataset, and the population-based Age-related Maculopathy Ancillary (ARMA) Study cohort. Using a consensus approach to combine the results from logistic regression and GENN models, our algorithm was successful in differentiating between high- and low-risk groups (sensitivity 77.0%, specificity 74.1%). In the ARMA cohort, the positive and negative predictive values were 63.3% and 70.7%, respectively. We expect that future efforts to refine this algorithm by increasing the sample size available for model building, including novel susceptibility factors as they are discovered, and by calibrating the model for diverse populations will improve accuracy

Polymorphisms in DNA-repair genes in a cohort of prostate cancer patients from different areas in Spain: heterogeneity between populations as a confounding factor in association studies

Background: Differences in the distribution of genotypes between individuals of the same ethnicity are an important confounder factor commonly undervalued in typical association studies conducted in radiogenomics. Objective: To evaluate the genotypic distribution of SNPs in a wide set of Spanish prostate cancer patients for determine the homogeneity of the population and to disclose potential bias. Design, Setting, and Participants: A total of 601 prostate cancer patients from Andalusia, Basque Country, Canary and Catalonia were genotyped for 10 SNPs located in 6 different genes associated to DNA repair: XRCC1 (rs25487, rs25489, rs1799782), ERCC2 (rs13181), ERCC1 (rs11615), LIG4 (rs1805388, rs1805386), ATM (rs17503908, rs1800057) and P53 (rs1042522). The SNP genotyping was made in a Biotrove OpenArrayH NT Cycler. Outcome Measurements and Statistical Analysis: Comparisons of genotypic and allelic frequencies among populations, as well as haplotype analyses were determined using the web-based environment SNPator. Principal component analysis was made using the SnpMatrix and XSnpMatrix classes and methods implemented as an R package. Non-supervised hierarchical cluster of SNP was made using MultiExperiment Viewer. Results and Limitations: We observed that genotype distribution of 4 out 10 SNPs was statistically different among the studied populations, showing the greatest differences between Andalusia and Catalonia. These observations were confirmed in cluster analysis, principal component analysis and in the differential distribution of haplotypes among the populations. Because tumor characteristics have not been taken into account, it is possible that some polymorphisms may influence tumor characteristics in the same way that it may pose a risk factor for other disease characteristics. Conclusion: Differences in distribution of genotypes within different populations of the same ethnicity could be an important confounding factor responsible for the lack of validation of SNPs associated with radiation-induced toxicity, especially when extensive meta-analysis with subjects from different countries are carried out

Inheritance of deleterious mutations at both BRCA1 and BRCA2 in an international sample of 32,295 women

Background: Most $\textit{BRCA1}$ or $\textit{BRCA2}$ mutation carriers have inherited a single (heterozygous) mutation. Transheterozygotes (TH) who have inherited deleterious mutations in both $\textit{BRCA1}$ and $\textit{BRCA2}$ are rare, and the consequences of transheterozygosity are poorly understood. Methods: From 32,295 female $\textit{BRCA1/2}$ mutation carriers, we identified 93 TH (0.3 %). "Cases" were defined as TH, and "controls" were single mutations at $\textit{BRCA1}$ (SH1) or $\textit{BRCA2}$ (SH2). Matched SH1 "controls" carried a BRCA1 mutation found in the TH "case". Matched SH2 "controls" carried a BRCA2 mutation found in the TH "case". After matching the TH carriers with SH1 or SH2, 91 TH were matched to 9316 SH1, and 89 TH were matched to 3370 SH2. Results: The majority of TH (45.2 %) involved the three common Jewish mutations. TH were more likely than SH1 and SH2 women to have been ever diagnosed with breast cancer (BC; $p$ = 0.002). TH were more likely to be diagnosed with ovarian cancer (OC) than SH2 ($p$ = 0.017), but not SH1. Age at BC diagnosis was the same in TH vs. SH1 ($p$ = 0.231), but was on average 4.5 years younger in TH than in SH2 ($p$ < 0.001). BC in TH was more likely to be estrogen receptor (ER) positive ($p$ = 0.010) or progesterone receptor (PR) positive ($p$ = 0.013) than in SH1, but less likely to be ER positive ($p$ < 0.001) or PR positive ($p$ = 0.012) than SH2. Among 15 tumors from TH patients, there was no clear pattern of loss of heterozygosity (LOH) for $\textit{BRCA1}$ or $\textit{BRCA2}$ in either BC or OC. Conclusions: Our observations suggest that clinical TH phenotypes resemble SH1. However, TH breast tumor marker characteristics are phenotypically intermediate to SH1 and SH2.ACA and the CIMBA data management are funded by Cancer Research UK (C12292/A20861 and C12292/A11174). TRR was supported by R01-CA083855, R01-CA102776, and P50-CA083638. KLN, TMF, and SMD are supported by the Basser Research Center at the University of Pennsylvania. BP is supported by R01-CA112520. Cancer Research UK provided financial support for this work. ACA is a Senior Cancer Research UK Cancer Research Fellow. DFE is Cancer Research UK Principal Research Fellow. Tumor analysis was funded by STOP CANCER (to SJR). Study-specific acknowledgements are as provided in the manuscript

An intergenic risk locus containing an enhancer deletion in 2q35 modulates breast cancer risk by deregulating IGFBP5 expression.

Breast cancer is the most diagnosed malignancy and the second leading cause of cancer mortality in females. Previous association studies have identified variants on 2q35 associated with the risk of breast cancer. To identify functional susceptibility loci for breast cancer, we interrogated the 2q35 gene desert for chromatin architecture and functional variation correlated with gene expression. We report a novel intergenic breast cancer risk locus containing an enhancer copy number variation (enCNV; deletion) located approximately 400Kb upstream to IGFBP5, which overlaps an intergenic ERα-bound enhancer that loops to the IGFBP5 promoter. The enCNV is correlated with modified ERα binding and monoallelic-repression of IGFBP5 following estrogen treatment. We investigated the association of enCNV genotype with breast cancer in 1,182 cases and 1,362 controls, and replicate our findings in an independent set of 62,533 cases and 60,966 controls from 41 case control studies and 11 GWAS. We report a dose-dependent inverse association of 2q35 enCNV genotype (percopy OR=0.68 95%CI 0.55-0.83, P=0.0002; replication OR=0.77 95%CI 0.73-0.82, P=2.1x10(-19)) and identify 13 additional linked variants (r(2)>0.8) in the 20Kb linkage block containing the enCNV (P=3.2x10(-15) - 5.6x10(-17)). These associations were independent of previously reported 2q35 variants, rs13387042/rs4442975 and rs16857609, and were stronger for ER-positive than ER-negative disease. Together, these results suggest that 2q35 breast cancer risk loci may be mediating their effect through IGFBP5

An intergenic risk locus containing an enhancer deletion in 2q35 modulates breast cancer risk by deregulating IGFBP5 expression.

Breast cancer is the most diagnosed malignancy and the second leading cause of cancer mortality in females. Previous association studies have identified variants on 2q35 associated with the risk of breast cancer. To identify functional susceptibility loci for breast cancer, we interrogated the 2q35 gene desert for chromatin architecture and functional variation correlated with gene expression. We report a novel intergenic breast cancer risk locus containing an enhancer copy number variation (enCNV; deletion) located approximately 400Kb upstream to IGFBP5, which overlaps an intergenic ERα-bound enhancer that loops to the IGFBP5 promoter. The enCNV is correlated with modified ERα binding and monoallelic-repression of IGFBP5 following estrogen treatment. We investigated the association of enCNV genotype with breast cancer in 1,182 cases and 1,362 controls, and replicate our findings in an independent set of 62,533 cases and 60,966 controls from 41 case control studies and 11 GWAS. We report a dose-dependent inverse association of 2q35 enCNV genotype (percopy OR=0.68 95%CI 0.55-0.83, P=0.0002; replication OR=0.77 95%CI 0.73-0.82, P=2.1x10(-19)) and identify 13 additional linked variants (r(2)>0.8) in the 20Kb linkage block containing the enCNV (P=3.2x10(-15) - 5.6x10(-17)). These associations were independent of previously reported 2q35 variants, rs13387042/rs4442975 and rs16857609, and were stronger for ER-positive than ER-negative disease. Together, these results suggest that 2q35 breast cancer risk loci may be mediating their effect through IGFBP5