Robert C. Wilson

Genotype–phenotype correlation in 1,507 families with congenital adrenal hyperplasia owing to 21-hydroxylase deficiency

Over the last two decades, we have extensively studied the genetics of congenital adrenal hyperplasia caused by 21-hydroxylase deficiency (CAH) and have performed 8,290 DNA analyses of the CYP21A2 gene on members of 4,857 families at risk for CAH—the largest cohort of CAH patients reported to date. Of the families studied, 1,507 had at least one member affected with one of three known forms of CAH, namely salt wasting, simple virilizing, or nonclassical CAH. Here, we report the genotype and phenotype of each affected patient, as well as the ethnic group and country of origin for each patient. We showed that 21 of 45 genotypes yielded a phenotypic correlation in our patient cohort. In particular, contrary to what is generally reported in the literature, we found that certain mutations, for example, the P30L, I2G, and I172N mutations, yielded different CAH phenotypes. In salt wasting and nonclassical CAH, a phenotype can be attributed to a genotype; however, in simple virilizing CAH, we observe wide phenotypic variability, particularly with the exon 4 I172N mutation. Finally, there was a high frequency of homozygous I2G and V281L mutations in Middle Eastern and Ashkenazi Jewish populations, respectively. By identifying the predominant phenotype for a given genotype, these findings should assist physicians in prenatal diagnosis and genetic counseling of parents who are at risk for having a child with CAH.

KAT6A, a Chromatin Modifier from the 8p11-p12 Amplicon is a Candidate Oncogene in Luminal Breast Cancer

The chromosome 8p11-p12 amplicon is present in 12% to 15% of breast cancers, resulting in an increase in copy number and expression of several chromatin modifiers in these tumors, including KAT6A. Previous analyses in SUM-52 breast cancer cells showed amplification and overexpression of KAT6A, and subsequent RNAi screening identified KAT6A as a potential driving oncogene. KAT6A is a histone acetyltransferase previously identified as a fusion partner with CREB binding protein in acute myeloid leukemia. Knockdown of KAT6A in SUM-52 cells, a luminal breast cancer cell line harboring the amplicon, resulted in reduced growth rate compared to non-silencing controls and profound loss of clonogenic capacity both in mono-layer and in soft agar. The normal cell line MCF10A, however, did not exhibit slower growth with knockdown of KAT6A. SUM-52 cells with KAT6A knockdown formed fewer mammospheres in culture compared to controls, suggesting a possible role for KAT6A in self-renewal. Previous data from our laboratory identified FGFR2 as a driving oncogene in SUM-52 cells. The colony forming efficiency of SUM-52 KAT6A knockdown cells in the presence of FGFR inhibition was significantly reduced compared to cells with KAT6A knockdown only. These data suggest that KAT6A may be a novel oncogene in breast cancers bearing the 8p11-p12 amplicon. While there are other putative oncogenes in the amplicon, the identification of KAT6A as a driving oncogene suggests that chromatin-modifying enzymes are a key class of oncogenes in these cancers, and play an important role in the selection of this amplicon in luminal B breast cancers.

FLI1 expression is correlated with breast cancer cellular growth, migration, and invasion and altered gene expression.

ETS factors have been shown to be dysregulated in breast cancer. ETS factors control the expression of genes involved in many biological processes, such as cellular proliferation, differentiation, and apoptosis. FLI1 is an ETS protein aberrantly expressed in retrovirus-induced hematological tumors, but limited attention has been directed towards elucidating the role of FLI1 in epithelial-derived cancers. Using data mining, we show that loss of FLI1 expression is associated with shorter survival and more aggressive phenotypes of breast cancer. Gain and loss of function cellular studies indicate the inhibitory effect of FLI1 expression on cellular growth, migration, and invasion. Using Fli1 mutant mice and both a transgenic murine breast cancer model and an orthotopic injection of syngeneic tumor cells indicates that reduced Fli1 contributes to accelerated tumor growth. Global expression analysis and RNA-Seq data from an invasive human breast cancer cell line with over expression of either FLI1 and another ETS gene, PDEF, shows changes in several cellular pathways associated with cancer, such as the cytokine-cytokine receptor interaction and PI3K-Akt signaling pathways. This study demonstrates a novel role for FLI1 in epithelial cells. In addition, these results reveal that FLI1 down-regulation in breast cancer may promote tumor progression.

Amplification of WHSC1L1 regulates expression and estrogen-independent activation of ERα in SUM-44 breast cancer cells and is associated with ERα over-expression in breast cancer

The 8p11‐p12 amplicon occurs in approximately 15% of breast cancers in aggressive luminal B‐type tumors. Previously, we identified WHSC1L1 as a driving oncogene from this region. Here, we demonstrate that over‐expression of WHSC1L1 is linked to over‐expression of ERα in SUM‐44 breast cancer cells and in primary human breast cancers. Knock‐down of WHSC1L1, particularly WHSC1L1‐short, had a dramatic effect on ESR1 mRNA and ERα protein levels. SUM‐44 cells do not require exogenous estrogen for growth in vitro; however, they are dependent on ERα expression, as ESR1 knock‐down or exposure to the selective estrogen receptor degrader fulvestrant resulted in growth inhibition. ChIP‐Seq experiments utilizing ERα antibodies demonstrated extensive ERα binding to chromatin in SUM‐44 cells under estrogen‐free conditions. ERα bound to ERE and FOXA1 motifs under estrogen‐free conditions and regulated expression of estrogen‐responsive genes. Short‐term treatment with estradiol enhanced binding of ERα to chromatin and influenced expression of many of the same genes to which ERα was bound under estrogen‐free conditions. Finally, knock‐down of WHSC1L1 in SUM‐44 cells resulted in loss of ERα binding to chromatin under estrogen‐free conditions, which was restored upon exposure to estradiol. These results indicate the SUM‐44 cells are a good model of a subset of luminal B breast cancers that have the 8p11‐p12 amplicon, over‐express WHSC1L1, and over‐express ERα, but are independent of estrogen for binding to chromatin and regulation of gene expression. Breast cancers such as these, that are dependent on ERα activity but independent of estradiol, are a major cause of breast cancer mortality.

Oncogenic signaling in amphiregulin and EGFR‐expressing PTEN‐null human breast cancer

A subset of triple negative breast cancer (TNBC) is characterized by overexpression of the epidermal growth factor receptor (EGFR) and loss of PTEN, and patients with these determinants have a poor prognosis. We used cell line models of EGFR‐positive/PTEN null TNBC to elucidate the signaling networks that drive the malignant features of these cells and cause resistance to EGFR inhibitors. In these cells, amphiregulin (AREG)‐mediated activation of EGFR results in up‐regulation of fibronectin (FN1), which is known to be a mediator of invasive capacity via interaction with integrin β1. EGFR activity in this PTEN null background also results in Wnt/beta‐catenin signaling and activation of NF‐κB. In addition, AKT is constitutively phosphorylated in these cells and is resistant to gefitinib. Expression profiling demonstrated that AREG‐activated EGFR regulates gene expression differently than EGF‐activated EGFR, and functional analysis via genome‐scale shRNA screening identified a set of genes, including PLK1 and BIRC5, that are essential for survival of SUM‐149 cells, but are uncoupled from EGFR signaling. Thus, our results demonstrate that in cells with constitutive EGFR activation and PTEN loss, critical survival genes are uncoupled from regulation by EGFR, which likely mediates resistance to EGFR inhibitors.

Molecular genetic analysis in 93 patients and 193 family members with classical congenital adrenal hyperplasia due to 21-hydroxylase deficiency in Croatia.

Congenital adrenal hyperplasia owing to 21-hydroxylase deficiency is caused by mutation in the CYP21A2 gene. The frequency and spectrum of CYP21A2 mutations and genotype-phenotype correlations among different populations are variable. Aim of this study was to define mutation frequency and spectrum of CYP21A2 gene mutations in patients with classical 21-hydroxylase deficiency (21OHD) and their family members in Croatia and study genotype-phenotype correlation. Clinical features and mutations of CYP21A2 gene in 93 unrelated 21OHD patients and 193 family members were examined. In this cohort, 66 patients were affected with salt wasting (SW) form, and 27 were affected with simple virilizing (SV) form of the disease. Mutations were identified in both alleles (67% compound heterozygous and 33% homozygous) in 91 of 93 patients. Deletions and conversions were found in 18.8% and point mutations in 79.6% alleles. Mutations in 3 alleles (1.6%) remained unidentified (in one patient we found only one, while in other no mutations were found at all). The most common point mutations were Intron 2 splice mutation IVS2-13 A/C>G (35.5%) and p.R357W (16.7%). Genotypes were categorized into Groups 0, A, B and C according to the extent of enzyme impairment. Genotype-phenotype concordance was 100%, 85% and 75% for Groups 0, A and B, respectively. Since only classical 21OHD patients were studied, Group C comprised solely p.P31L mutation and had 73% patients with SV and 27% with SW phenotype. Intrafamilial phenotypic variability was found in two families. CYP21A2 genetic analysis in 193 family members showed that 126 parents were heterozygous carriers, 3 were newly discovered patients, 2 fathers were not biological parents, and mutations were not detected in 3. Among 59 siblings, 32 were heterozygous carriers, 15 carried normal alleles, and 12 were patients (4 newly diagnosed). Genotype-phenotype divergence observed in this study suggests caution in preconceptional counseling and prenatal diagnosis of CAH. High frequency of p.R357W mutation was found in Croatian patients with classical 21-OHD. Genotyping of family members discovered new patients and thus avoided pitfalls in genetic counseling when the parents were found to be affected.

Multivariate models from RNA-Seq SNVs yield candidate molecular targets for biomarker discovery: SNV-DA.

BackgroundIt has recently been shown that significant and accurate single nucleotide variants (SNVs) can be reliably called from RNA-Seq data. These may provide another source of features for multivariate predictive modeling of disease phenotype for the prioritization of candidate biomarkers. The continuous nature of SNV allele fraction features allows the concurrent investigation of several genomic phenomena, including allele specific expression, clonal expansion and/or deletion, and copy number variation.ResultsThe proposed software pipeline and package, SNV Discriminant Analysis (SNV-DA), was applied on two RNA-Seq datasets with varying sample sizes sequenced at different depths: a dataset containing primary tumors from twenty patients with different disease outcomes in lung adenocarcinoma and a larger dataset of primary tumors representing two major breast cancer subtypes, estrogen receptor positive and triple negative. Predictive models were generated using the machine learning algorithm, sparse projections to latent structures discriminant analysis. Training sets composed of RNA-Seq SNV features limited to genomic regions of origin (e.g. exonic or intronic) and/or RNA-editing sites were shown to produce models with accurate predictive performances, were discriminant towards true label groupings, and were able to produce SNV rankings significantly different from than univariate tests. Furthermore, the utility of the proposed methodology is supported by its comparable performance to traditional models as well as the enrichment of selected SNVs located in genes previously associated with cancer and genes showing allele-specific expression. As proof of concept, we highlight the discovery of a previously unannotated intergenic locus that is associated with epigenetic regulatory marks in cancer and whose significant allele-specific expression is correlated with ER+ status; hereafter named ER+ associated hotspot (ERPAHS).ConclusionThe use of models from RNA-Seq SNVs to identify and prioritize candidate molecular targets for biomarker discovery is supported by the ability of the proposed method to produce significantly accurate predictive models that are discriminant towards true label groupings. Importantly, the proposed methodology allows investigation of mutations outside of exonic regions and identification of interesting expressed loci not included in traditional gene annotations. An implementation of the proposed methodology is provided that allows the user to specify SNV filtering criteria and cross-validation design during model creation and evaluation.

Predictive modeling of lung cancer recurrence using alternative splicing events versus differential expression data

Lung cancer is the leading cause of cancer-related deaths worldwide. Biomarker discovery has become increasingly important for the effective diagnosis, prognosis and treatment of the disease. The analysis of differential gene expression data has been the primary method for biomarker discovery. Our research demonstrates that alternative splicing events (ASE) can be another source of data for predictive model creation by identifying putative biomarkers that are complementary to those found from traditional gene expression. RNASeq data from 21 patients diagnosed with lung adenocarcinoma, a non-small cell lung carcinoma (11 of which relapsed) were analyzed. After quantifying splice variants and gene expression with a bioinformatics pipeline, we were able to create predictive models, using orthogonal projections to latent structures discriminate analysis (OPLS-DA) that recognize two clinical phenotypes (disease free and relapse); thus distinguishing between more indolent and aggressive disease. Hierarchical clustering of samples pre and post predictive model feature selection showed that clustering based on ASE was more indicative of the relapse phenotype. A novel hybrid multiple objective genetic algorithm combining alternative splicing events with gene expression was used for discriminate feature selection. A post-processing examination of the putative biomarkers found by the genetic algorithm and ranked correlation tests demonstrate that the analysis of alternative splicing events provide complementary and non-redundant predictive power by identifying biologically relevant patterns that do not result in differential gene expression.

Clinical, genetic, and structural basis of apparent mineralocorticoid excess due to 11β-hydroxysteroid dehydrogenase type 2 deficiency

Significance Apparent mineralocorticoid excess, a rare autosomal recessive disorder characterized by low renin hypertension, may display a severe or mild phenotype in patients. The variability in clinical presentation stems from different extents of impairment of the 11β-hydroxysteroid dehydrogenase type 2 (HSD11B2) enzyme arising from distinct mutations in the encoding gene. The computational model of the HSD11B2 protein that we constructed here will be useful in predicting disease severity for newly reported missense mutations in this gene. Mutations in 11β-hydroxysteroid dehydrogenase type 2 gene (HSD11B2) cause an extraordinarily rare autosomal recessive disorder, apparent mineralocorticoid excess (AME). AME is a form of low renin hypertension that is potentially fatal if untreated. Mutations in the HSD11B2 gene result either in severe AME or a milder phenotype (type 2 AME). To date, ∼40 causative mutations have been identified. As part of the International Consortium for Rare Steroid Disorders, we have diagnosed and followed the largest single worldwide cohort of 36 AME patients. Here, we present the genotype and clinical phenotype of these patients, prominently from consanguineous marriages in the Middle East, who display profound hypertension and hypokalemic alkalosis. To correlate mutations with phenotypic severity, we constructed a computational model of the HSD11B2 protein. Having used a similar strategy for the in silico evaluation of 150 mutations of CYP21A2, the disease-causing gene in congenital adrenal hyperplasia, we now provide a full structural explanation for the clinical severity of AME resulting from each known HSD11B2 missense mutation. We find that mutations that allow the formation of an inactive dimer, alter substrate/coenzyme binding, or impair structural stability of HSD11B2 yield severe AME. In contrast, mutations that cause an indirect disruption of substrate binding or mildly alter intramolecular interactions result in type 2 AME. A simple in silico evaluation of novel missense mutations could help predict the often-diverse phenotypes of an extremely rare monogenic disorder.

A novel mutation in HSD11B2 causes apparent mineralocorticoid excess in an Omani kindred.

Apparent mineralocorticoid excess (AME) is a rare autosomal recessive genetic disorder causing severe hypertension in childhood due to a deficiency of 11β‐hydroxysteroid dehydrogenase type 2 (11βHSD2), which is encoded by HSD11B2. Without treatment, chronic hypertension leads to early development of end‐organ damage. Approximately 40 causative mutations in HSD11B2 have been identified in ∼100 AME patients worldwide. We have studied the clinical presentation, biochemical parameters, and molecular genetics in six patients from a consanguineous Omani family with AME. DNA sequence analysis of affected members of this family revealed homozygous c.799A>G mutations within exon 4 of HSD11B2, corresponding to a p.T267A mutation of 11βHSD2. The structural change and predicted consequences owing to the p.T267A mutation have been modeled in silico. We conclude that this novel mutation is responsible for AME in this family.