Systematic Bias in Genomic Classification Due to Contaminating Non-neoplastic Tissue in Breast Tumor Samples

Abstract Background Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification. Methods To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors. Results Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability. Conclusions Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor

RNAi-Mediated Knock-Down of Arylamine N-acetyltransferase-1 Expression Induces E-cadherin Up-Regulation and Cell-Cell Contact Growth Inhibition

Arylamine N-acetyltransferase-1 (NAT1) is an enzyme that catalyzes the biotransformation of arylamine and hydrazine substrates. It also has a role in the catabolism of the folate metabolite p-aminobenzoyl glutamate. Recent bioinformatics studies have correlated NAT1 expression with various cancer subtypes. However, a direct role for NAT1 in cell biology has not been established. In this study, we have knocked down NAT1 in the colon adenocarcinoma cell-line HT-29 and found a marked change in cell morphology that was accompanied by an increase in cell-cell contact growth inhibition and a loss of cell viability at confluence. NAT1 knock-down also led to attenuation in anchorage independent growth in soft agar. Loss of NAT1 led to the up-regulation of E-cadherin mRNA and protein levels. This change in E-cadherin was not attributed to RNAi off-target effects and was also observed in the prostate cancer cell-line 22Rv1. In vivo, NAT1 knock-down cells grew with a longer doubling time compared to cells stably transfected with a scrambled RNAi or to parental HT-29 cells. This study has shown that NAT1 affects cell growth and morphology. In addition, it suggests that NAT1 may be a novel drug target for cancer therapeutics

Expression signatures of TP53 mutations in serous ovarian cancers

<p>Abstract</p> <p>Background</p> <p>Mutations in the <it>TP53 </it>gene are extremely common and occur very early in the progression of serous ovarian cancers. Gene expression patterns that relate to mutational status may provide insight into the etiology and biology of the disease.</p> <p>Methods</p> <p>The <it>TP53 </it>coding region was sequenced in 89 frozen serous ovarian cancers, 40 early stage (I/II) and 49 advanced stage (III/IV). Affymetrix U133A expression data was used to define gene expression patterns by mutation, type of mutation, and cancer stage.</p> <p>Results</p> <p>Missense or chain terminating (null) mutations in <it>TP53 </it>were found in 59/89 (66%) ovarian cancers. Early stage cancers had a significantly higher rate of null mutations than late stage disease (38% vs. 8%, p < 0.03). In advanced stage cases, mutations were more prevalent in short term survivors than long term survivors (81% vs. 30%, p = 0.0004). Gene expression patterns had a robust ability to predict <it>TP53 </it>status within training data. By using early versus late stage disease for out of sample predictions, the signature derived from early stage cancers could accurately (86%) predict mutation status of late stage cancers.</p> <p>Conclusions</p> <p>This represents the first attempt to define a genomic signature of <it>TP53 </it>mutation in ovarian cancer. Patterns of gene expression characteristic of <it>TP53 </it>mutation could be discerned and included several genes that are known p53 targets or have been described in the context of expression signatures of <it>TP53 </it>mutation in breast cancer.</p

Mutations in the nuclear localization sequence of the Aristaless related homeobox; sequestration of mutant ARX with IPO13 disrupts normal subcellular distribution of the transcription factor and retards cell division

The electronic version of this article is the complete one and can be found online at: http://www.pathogeneticsjournal.com/content/3/1/1Background: Aristaless related homeobox (ARX) is a paired-type homeobox gene. ARX function is frequently affected by naturally occurring mutations. Nonsense mutations, polyalanine tract expansions and missense mutations in ARX cause a range of intellectual disability and epilepsy phenotypes with or without additional features including hand dystonia, lissencephaly, autism or dysarthria. Severe malformation phenotypes, such as X-linked lissencephaly with ambiguous genitalia (XLAG), are frequently observed in individuals with protein truncating or missense mutations clustered in the highly conserved paired-type homeodomain. Results: We have identified two novel point mutations in the R379 residue of the ARX homeodomain; c.1135C>A, p.R379S in a patient with infantile spasms and intellectual disability and c.1136G>T, p.R379L in a patient with XLAG. We investigated these and other missense mutations (R332P, R332H, R332C, T333N: associated with XLAG and Proud syndrome) predicted to affect the nuclear localisation sequences (NLS) flanking either end of the ARX homeodomain. The NLS regions are required for correct nuclear import facilitated by Importin 13 (IPO13). We demonstrate that missense mutations in either the N- or C-terminal NLS regions of the homeodomain cause significant disruption to nuclear localisation of the ARX protein in vitro. Surprisingly, none of these mutations abolished the binding of ARX to IPO13. This was confirmed by co-immunoprecipitation and immmuno fluorescence studies. Instead, tagged and endogenous IPO13 remained bound to the mutant ARX proteins, even in the RanGTP rich nuclear environment. We also identify the microtubule protein TUBA1A as a novel interacting protein for ARX and show cells expressing mutant ARX protein accumulate in mitosis, indicating normal cell division may be disrupted. Conclusions: We show that the most likely, common pathogenic mechanism of the missense mutations in NLS regions of the ARX homeodomain is inadequate accumulation and distribution of the ARX transcription factor within the nucleus due to sequestration of ARX with IPO13.Cheryl Shoubridge, May Huey Tan, Tod Fullston, Desiree Cloosterman, David Coman, George McGillivray, Grazia M Mancini, Tjitske Kleefstra and Jozef Géc

TBC1D24 genotype-phenotype correlation: Epilepsies and other neurologic features

Objective: To evaluate the phenotypic spectrum associated with mutations in TBC1D24. Methods: We acquired new clinical, EEG, and neuroimaging data of 11 previously unreported and 37 published patients. TBC1D24 mutations, identified through various sequencing methods, can be found online (http://lovd.nl/TBC1D24). Results: Forty-eight patients were included (28 men, 20 women, average age 21 years) from 30 independent families. Eighteen patients (38%) had myoclonic epilepsies. The other patients carried diagnoses of focal (25%), multifocal (2%), generalized (4%), and unclassified epilepsy (6%), and early-onset epileptic encephalopathy (25%). Most patients had drug-resistant epilepsy. We detail EEG, neuroimaging, developmental, and cognitive features, treatment responsiveness, and physical examination. In silico evaluation revealed 7 different highly conserved motifs, with the most common pathogenic mutation located in the first. Neuronal outgrowth assays showed that some TBC1D24 mutations, associated with the most severe TBC1D24-associated disorders, are not necessarily the most disruptive to this gene function. Conclusions: TBC1D24-related epilepsy syndromes show marked phenotypic pleiotropy, with multisystem involvement and severity spectrum ranging from isolated deafness (not studied here), benign myoclonic epilepsy restricted to childhood with complete seizure control and normal intellect, to early-onset epileptic encephalopathy with severe developmental delay and early death. There is no distinct correlation with mutation type or location yet, but patterns are emerging. Given the phenotypic breadth observed, TBC1D24 mutation screening is indicated in a wide variety of epilepsies. A TBC1D24 consortium was formed to develop further research on this gene and its associated phenotypes

Signaling pathways in breast cancer metastasis - novel insights from functional genomics

The advent of genomic profiling technology has brought about revolutionary changes in our understanding of breast cancer metastasis. Gene expression analyses of primary tumors have been used to predict metastatic propensity with high accuracy. Animal models of metastasis additionally offer a platform to experimentally dissect components of the metastasis genetic program. Recent integrated studies have synergized clinical bioinformatic analyses with advanced experimental methodology and begun to uncover the identities and dynamics of signaling programs driving breast cancer metastasis. Such functional genomics studies hold great promise for understanding the genetic basis of metastasis and improving therapeutics for advanced diseases

A network analysis to identify mediators of germline-driven differences in breast cancer prognosis.

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis

Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium.

BACKGROUND: Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions. METHODS: Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions. RESULTS: Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth. CONCLUSIONS: Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors

A case–control analysis of oral contraceptive use and breast cancer subtypes in the African American Breast Cancer Epidemiology and Risk Consortium

Abstract Introduction Recent oral contraceptive (OC) use has been consistently associated with increased risk of breast cancer, but evidence on specific breast cancer subtypes is sparse. Methods We investigated recency and duration of OC use in relation to molecular subtypes of breast cancer in a pooled analysis of data from the African American Breast Cancer Epidemiology and Risk Consortium. The study included 1,848 women with estrogen receptor-positive (ER+) breast cancer, 1,043 with ER-negative (ER-) breast cancer (including 494 triple negative (TN) tumors, which do not have receptors for estrogen, progesterone, and human epidermal growth factor 2), and 10,044 controls. Multivariable polytomous logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for exposure categories relative to never use, controlling for potential confounding variables. Results OC use within the previous 5 years was associated with increased risk of ER+ (OR 1.46, 95% CI 1.18 to 1.81), ER- (OR 1.57, 95% CI 1.22 to 1.43), and TN (OR 1.78, 95% CI 1.25 to 2.53) breast cancer. The risk declined after cessation of use but was apparent for ER+ cancer for 15 to 19 years after cessation and for ER- breast cancer for an even longer interval after cessation. Long duration of use was also associated with increased risk of each subtype, particularly ER-. Conclusions Our results suggest that OC use, particularly recent use of long duration, is associated with an increased risk of ER+, ER-, and TN breast cancer in African American women. Research into mechanisms that explain these findings, especially the association with ER- breast cancer, is needed