Integrative genomics analysis of genes with biallelic loss and its relation to the expression of mRNA and micro-RNA in esophageal squamous cell carcinoma.

BACKGROUND: Genomic instability plays an important role in human cancers. We previously characterized genomic instability in esophageal squamous cell carcinomas (ESCC) in terms of loss of heterozygosity (LOH) and copy number (CN) changes in tumors. In the current study we focus on biallelic loss and its relation to expression of mRNA and miRNA in ESCC using results from 500 K SNP, mRNA, and miRNA arrays in 30 cases from a high-risk region of China. RESULTS: (i) Biallelic loss was uncommon but when it occurred it exhibited a consistent pattern: only 77 genes (<0.5%) showed biallelic loss in at least 10% of ESCC samples, but nearly all of these genes were concentrated on just four chromosomal arms (i.e., 42 genes on 3p, 14 genes on 9p, 10 genes on 5q, and seven genes on 4p). (ii) Biallelic loss was associated with lower mRNA expression: 52 of the 77 genes also had RNA expression data, and 41 (79%) showed lower expression levels in cases with biallelic loss compared to those without. (iii) The relation of biallelic loss to miRNA expression was less clear but appeared to favor higher miRNA levels: of 60 miRNA-target gene pairs, 34 pairs (57%) had higher miRNA expression with biallelic loss than without, while 26 pairs (43%) had lower miRNA expression. (iv) Finally, the effect of biallelic loss on the relation between miRNA and mRNA expression was complex. Biallelic loss was most commonly associated with a pattern of elevated miRNA and reduced mRNA (43%), but a pattern of both reduced miRNA and mRNA was also common (35%). CONCLUSION: Our results indicate that biallelic loss in ESCC is uncommon, but when it occurs it is localized to a few specific chromosome regions and is associated with reduced mRNA expression of affected genes. The effect of biallelic loss on miRNA expression and on the relation between miRNA and mRNA expressions was complex.

An integrated genomic approach identifies persistent tumor suppressive effects of transforming growth factor-ß in human breast cancer.

INTRODUCTION: Transforming growth factor-ßs (TGF-ßs) play a dual role in breast cancer, with context-dependent tumor-suppressive or pro-oncogenic effects. TGF-ß antagonists are showing promise in early-phase clinical oncology trials to neutralize the pro-oncogenic effects. However, there is currently no way to determine whether the tumor-suppressive effects of TGF-ß are still active in human breast tumors at the time of surgery and treatment, a situation that could lead to adverse therapeutic responses. METHODS: Using a breast cancer progression model that exemplifies the dual role of TGF-ß, promoter-wide chromatin immunoprecipitation and transcriptomic approaches were applied to identify a core set of TGF-ß-regulated genes that specifically reflect only the tumor-suppressor arm of the pathway. The clinical significance of this signature and the underlying biology were investigated using bioinformatic analyses in clinical breast cancer datasets, and knockdown validation approaches in tumor xenografts. RESULTS: TGF-ß-driven tumor suppression was highly dependent on Smad3, and Smad3 target genes that were specifically enriched for involvement in tumor suppression were identified. Patterns of Smad3 binding reflected the preexisting active chromatin landscape, and target genes were frequently regulated in opposite directions in vitro and in vivo, highlighting the strong contextuality of TGF-ß action. An in vivo-weighted TGF-ß/Smad3 tumor-suppressor signature was associated with good outcome in estrogen receptor-positive breast cancer cohorts. TGF-ß/Smad3 effects on cell proliferation, differentiation and ephrin signaling contributed to the observed tumor suppression. CONCLUSIONS: Tumor-suppressive effects of TGF-ß persist in some breast cancer patients at the time of surgery and affect clinical outcome. Carefully tailored in vitro/in vivo genomic approaches can identify such patients for exclusion from treatment with TGF-ß antagonists.

Genome-wide transcriptional sequencing identifies novel mutations in metabolic genes in human hepatocellular carcinoma.

We report on next-generation transcriptome sequencing results of three human hepatocellular carcinoma tumor/tumor-adjacent pairs. This analysis robustly examined ∼12,000 genes for both expression differences and molecular alterations. We observed 4,513 and 1,182 genes demonstrating 2-fold or greater increase or decrease in expression relative to their normal, respectively. Network analysis of expression data identified the Aurora B signaling, FOXM1 transcription factor network and Wnt signaling pathways pairs being altered in HCC. We validated as differential gene expression findings in a large data set containing of 434 liver normal/tumor sample pairs. In addition to known driver mutations in TP53 and CTNNB1, our mutation analysis identified non-synonymous mutations in genes implicated in metabolic diseases, i.e. diabetes and obesity: IRS1, HMGCS1, ATP8B1, PRMT6 and CLU, suggesting a common molecular etiology for HCC of alternative pathogenic origin.

MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set.

PURPOSE: To conduct a comprehensive analysis of radiologist-made assessments of glioblastoma (GBM) tumor size and composition by using a community-developed controlled terminology of magnetic resonance (MR) imaging visual features as they relate to genetic alterations, gene expression class, and patient survival. MATERIALS AND METHODS: Because all study patients had been previously deidentified by the Cancer Genome Atlas (TCGA), a publicly available data set that contains no linkage to patient identifiers and that is HIPAA compliant, no institutional review board approval was required. Presurgical MR images of 75 patients with GBM with genetic data in the TCGA portal were rated by three neuroradiologists for size, location, and tumor morphology by using a standardized feature set. Interrater agreements were analyzed by using the Krippendorff α statistic and intraclass correlation coefficient. Associations between survival, tumor size, and morphology were determined by using multivariate Cox regression models; associations between imaging features and genomics were studied by using the Fisher exact test. RESULTS: Interrater analysis showed significant agreement in terms of contrast material enhancement, nonenhancement, necrosis, edema, and size variables. Contrast-enhanced tumor volume and longest axis length of tumor were strongly associated with poor survival (respectively, hazard ratio: 8.84, P = .0253, and hazard ratio: 1.02, P = .00973), even after adjusting for Karnofsky performance score (P = .0208). Proneural class GBM had significantly lower levels of contrast enhancement (P = .02) than other subtypes, while mesenchymal GBM showed lower levels of nonenhanced tumor (P < .01). CONCLUSION: This analysis demonstrates a method for consistent image feature annotation capable of reproducibly characterizing brain tumors; this study shows that radiologists' estimations of macroscopic imaging features can be combined with genetic alterations and gene expression subtypes to provide deeper insight to the underlying biologic properties of GBM subsets.

Novel pathway analysis of genomic polymorphism-cancer risk interaction in the Breast Cancer Prevention Trial.

PURPOSE: Tamoxifen was approved for breast cancer risk reduction in high-risk women based on the National Surgical Adjuvant Breast and Bowel Project's Breast Cancer Prevention Trial (P-1:BCPT), which showed 50% fewer breast cancers with tamoxifen versus placebo, supporting tamoxifen's efficacy in preventing breast cancer. Poor metabolizing CYP2D6 variants are currently the subject of intensive scrutiny regarding their impact on clinical outcomes in the adjuvant setting. Our study extends to variants in a wider spectrum of tamoxifen-metabolizing genes and applies to the prevention setting. METHODS: Our case-only study, nested within P-1:BCPT, explored associations of polymorphisms in estrogen/tamoxifen-metabolizing genes with responsiveness to preventive tamoxifen. Thirty-nine candidate polymorphisms in 17 candidate genes were genotyped in 249 P-1:BCPT cases. RESULTS: CVP2D6_C1111T, individually and within a CYP2D6 haplotype, showed borderline significant association with treatment arm. Path analysis of the entire tamoxifen pathway gene network showed that the tamoxifen pathway model was consistent with the pattern of observed genotype variability within the placebo-arm dataset. However, correlation of variations in genes in the tamoxifen arm differed significantly from the predictions of the tamoxifen pathway model. Strong correlations between allelic variation in the tamoxifen pathway at CYP1A1-CYP3A4, CYP3A4-CYP2C9, and CYP2C9-SULT1A2, in addition to CYP2D6 and its adjacent genes, were seen in the placebo-arm but not the tamoxifen-arm. In conclusion, beyond reinforcing a role for CYP2D6 in tamoxifen response, our pathway analysis strongly suggests that specific combinations of allelic variants in other genes make major contributions to the tamoxifen-resistance phenotype.

Genetic variations at loci involved in the immune response are risk factors for hepatocellular carcinoma.

UNLABELLED: Primary liver cancer is the third most common cause of cancer-related death worldwide, with a rising incidence in Western countries. Little is known about the genetic etiology of this disease. To identify genetic factors associated with hepatocellular carcinoma (HCC) and liver cirrhosis (LC), we conducted a comprehensive, genome-wide variation analysis in a population of unrelated Asian individuals. Copy number variation (CNV) and single nucleotide polymorphisms (SNPs) were assayed in peripheral blood with the high-density Affymetrix SNP6.0 microarray platform. We used a two-stage discovery and replication design to control for overfitting and to validate observed results. We identified a strong association with CNV at the T-cell receptor gamma and alpha loci (P < 1 × 10(-15)) in HCC cases when contrasted with controls. This variation appears to be somatic in origin, reflecting differences between T-cell receptor processing in lymphocytes from individuals with liver disease and healthy individuals that is not attributable to chronic hepatitis virus infection. Analysis of constitutional variation identified three susceptibility loci including the class II MHC complex, whose protein products present antigen to T-cell receptors and mediate immune surveillance. Statistical analysis of biologic networks identified variation in the "antigen presentation and processing" pathway as being highly significantly associated with HCC (P = 1 × 10(-11)). SNP analysis identified two variants whose allele frequencies differ significantly between HCC and LC. One of these (P = 1.74 × 10(-12)) lies in the PTEN homolog TPTE2. CONCLUSION: Combined analysis of CNV, individual SNPs, and pathways suggest that HCC susceptibility is mediated by germline factors affecting the immune response and differences in T-cell receptor processing.

Genome wide analysis of DNA copy number neutral loss of heterozygosity (CNNLOH) and its relation to gene expression in esophageal squamous cell carcinoma.

BACKGROUND: Genomic instability plays an important role in human cancers. We previously characterized genomic instability in esophageal squamous cell carcinomas (ESCC) in terms of loss of heterozygosity (LOH) and copy number (CN) changes in tumors using the Affymetrix GeneChip Human Mapping 500K array in 30 cases from a high-risk region of China. In the current study we focused on copy number neutral (CN = 2) LOH (CNNLOH) and its relation to gene expression in ESCC. RESULTS: Overall we found that 70% of all LOH observed was CNNLOH. Ninety percent of ESCCs showed CNNLOH (median frequency in cases = 60%) and this was the most common type of LOH in two-thirds of cases. CNNLOH occurred on all 39 autosomal chromosome arms, with highest frequencies on 19p (100%), 5p (96%), 2p (95%), and 20q (95%). In contrast, LOH with CN loss represented 19% of all LOH, occurred in just half of ESCCs (median frequency in cases = 0%), and was most frequent on 3p (56%), 5q (47%), and 21q (41%). LOH with CN gain was 11% of all LOH, occurred in 93% of ESCCs (median frequency in cases = 13%), and was most common on 20p (82%), 8q (74%), and 3q (42%). To examine the effect of genomic instability on gene expression, we evaluated RNA profiles from 17 pairs of matched normal and tumor samples (a subset of the 30 ESCCs) using Affymetrix U133A 2.0 arrays. In CN neutral regions, expression of 168 genes (containing 1976 SNPs) differed significantly in tumors with LOH versus tumors without LOH, including 101 genes that were up-regulated and 67 that were down-regulated. CONCLUSION: Our results indicate that CNNLOH has a profound impact on gene expression in ESCC, which in turn may affect tumor development.

Novel functions for TAF7, a regulator of TAF1-independent transcription.

The transcription factor TFIID components TAF7 and TAF1 regulate eukaryotic transcription initiation. TAF7 regulates transcription initiation of TAF1-dependent genes by binding to the acetyltransferase (AT) domain of TAF1 and inhibiting the enzymatic activity that is essential for transcription. TAF7 is released from the TAF1-TFIID complex upon completion of preinitiation complex assembly, allowing transcription to initiate. However, not all transcription is TAF1-dependent, and the role of TAF7 in regulating TAF1-independent transcription has not been defined. The IFNγ-induced transcriptional co-activator CIITA activates MHC class I and II genes, which are vital for immune responses, in a TAF1-independent manner. Activation by CIITA depends on its intrinsic AT activity. We now show that TAF7 binds to CIITA and inhibits its AT activity, thereby repressing activated transcription. Consistent with this TAF7 function, siRNA-mediated depletion of TAF7 resulted in increased CIITA-dependent transcription. A more global role for TAF7 as a regulator of transcription was revealed by expression profiling analysis: expression of 30-40% of genes affected by TAF7 depletion was independent of either TAF1 or CIITA. Surprisingly, although TAF1-dependent transcripts were largely down-regulated by TAF7 depletion, TAF1-independent transcripts were predominantly up-regulated. We conclude that TAF7, until now considered only a TFIID component and regulator of TAF1-dependent transcription, also regulates TAF1-independent transcription.

Delineating genetic alterations for tumor progression in the MCF10A series of breast cancer cell lines.

To gain insight into the role of genomic alterations in breast cancer progression, we conducted a comprehensive genetic characterization of a series of four cell lines derived from MCF10A. MCF10A is an immortalized mammary epithelial cell line (MEC); MCF10AT is a premalignant cell line generated from MCF10A by transformation with an activated HRAS gene; MCF10CA1h and MCF10CA1a, both derived from MCF10AT xenografts, form well-differentiated and poorly-differentiated malignant tumors in the xenograft models, respectively. We analyzed DNA copy number variation using the Affymetrix 500 K SNP arrays with the goal of identifying gene-specific amplification and deletion events. In addition to a previously noted deletion in the CDKN2A locus, our studies identified MYC amplification in all four cell lines. Additionally, we found intragenic deletions in several genes, including LRP1B in MCF10CA1h and MCF10CA1a, FHIT and CDH13 in MCF10CA1h, and RUNX1 in MCF10CA1a. We confirmed the deletion of RUNX1 in MCF10CA1a by DNA and RNA analyses, as well as the absence of the RUNX1 protein in that cell line. Furthermore, we found that RUNX1 expression was reduced in high-grade primary breast tumors compared to low/mid-grade tumors. Mutational analysis identified an activating PIK3CA mutation, H1047R, in MCF10CA1h and MCF10CA1a, which correlates with an increase of AKT1 phosphorylation at Ser473 and Thr308. Furthermore, we showed increased expression levels for genes located in the genomic regions with copy number gain. Thus, our genetic analyses have uncovered sequential molecular events that delineate breast tumor progression. These events include CDKN2A deletion and MYC amplification in immortalization, HRAS activation in transformation, PIK3CA activation in the formation of malignant tumors, and RUNX1 deletion associated with poorly-differentiated malignant tumors.

JAK mutations in high-risk childhood acute lymphoblastic leukemia.

Pediatric acute lymphoblastic leukemia (ALL) is a heterogeneous disease consisting of distinct clinical and biological subtypes that are characterized by specific chromosomal abnormalities or gene mutations. Mutation of genes encoding tyrosine kinases is uncommon in ALL, with the exception of Philadelphia chromosome-positive ALL, where the t(9,22)(q34;q11) translocation encodes the constitutively active BCR-ABL1 tyrosine kinase. We recently identified a poor prognostic subgroup of pediatric BCR-ABL1-negative ALL patients characterized by deletion of IKZF1 (encoding the lymphoid transcription factor IKAROS) and a gene expression signature similar to BCR-ABL1-positive ALL, raising the possibility of activated tyrosine kinase signaling within this leukemia subtype. Here, we report activating mutations in the Janus kinases JAK1 (n = 3), JAK2 (n = 16), and JAK3 (n = 1) in 20 (10.7%) of 187 BCR-ABL1-negative, high-risk pediatric ALL cases. The JAK1 and JAK2 mutations involved highly conserved residues in the kinase and pseudokinase domains and resulted in constitutive JAK-STAT activation and growth factor independence of Ba/F3-EpoR cells. The presence of JAK mutations was significantly associated with alteration of IKZF1 (70% of all JAK-mutated cases and 87.5% of cases with JAK2 mutations; P = 0.001) and deletion of CDKN2A/B (70% of all JAK-mutated cases and 68.9% of JAK2-mutated cases). The JAK-mutated cases had a gene expression signature similar to BCR-ABL1 pediatric ALL, and they had a poor outcome. These results suggest that inhibition of JAK signaling is a logical target for therapeutic intervention in JAK mutated ALL.

Deletion of IKZF1 and prognosis in acute lymphoblastic leukemia.

BACKGROUND: Despite best current therapy, up to 20% of pediatric patients with acute lymphoblastic leukemia (ALL) have a relapse. Recent genomewide analyses have identified a high frequency of DNA copy-number abnormalities in ALL, but the prognostic implications of these abnormalities have not been defined. METHODS: We studied a cohort of 221 children with high-risk B-cell-progenitor ALL with the use of single-nucleotide-polymorphism microarrays, transcriptional profiling, and resequencing of samples obtained at diagnosis. Children with known very-high-risk ALL subtypes (i.e., BCR-ABL1-positive ALL, hypodiploid ALL, and ALL in infants) were excluded from this cohort. A copy-number abnormality was identified as a predictor of poor outcome, and it was then tested in an independent validation cohort of 258 patients with B-cell-progenitor ALL. RESULTS: More than 50 recurring copy-number abnormalities were identified, most commonly involving genes that encode regulators of B-cell development (in 66.8% of patients in the original cohort); PAX5 was involved in 31.7% and IKZF1 in 28.6% of patients. Using copy-number abnormalities, we identified a predictor of poor outcome that was validated in the independent validation cohort. This predictor was strongly associated with alteration of IKZF1, a gene that encodes the lymphoid transcription factor IKAROS. The gene-expression signature of the group of patients with a poor outcome revealed increased expression of hematopoietic stem-cell genes and reduced expression of B-cell-lineage genes, and it was similar to the signature of BCR-ABL1-positive ALL, another high-risk subtype of ALL with a high frequency of IKZF1 deletion. CONCLUSIONS: Genetic alteration of IKZF1 is associated with a very poor outcome in B-cell-progenitor ALL.

Bioinformatics tools for single nucleotide polymorphism discovery and analysis.

Single nucleotide polymorphisms (SNPs) are a valuable resource for investigating the genetic basis of disease. These variants can serve as markers for fine-scale genetic mapping experiments and genome-wide association studies. Certain of these nucleotide polymorphisms may predispose individuals to illnesses such as diabetes, hypertension, or cancer, or affect disease progression. Bioinformatics techniques can play an important role in SNP discovery and analysis. We use computational methods to identify SNPs and to predict whether they are likely to be neutral or deleterious. We also use informatics to annotate genes that contain SNPs. To make this information available to the research community, we provide a variety of Internet-accessible tools for data access and display. These tools allow researchers to retrieve data about SNPs based on gene of interest, genetic or physical map location, or expression pattern.

Large-scale analysis of non-synonymous coding region single nucleotide polymorphisms.

MOTIVATION: Single nucleotide polymorphisms (SNPs) are the most common form of genetic variant in humans. SNPs causing amino acid substitutions are of particular interest as candidates for loci affecting susceptibility to complex diseases, such as diabetes and hypertension. To efficiently screen SNPs for disease association, it is important to distinguish neutral variants from deleterious ones. RESULTS: We describe the use of Pfam protein motif models and the HMMER program to predict whether amino acid changes in conserved domains are likely to affect protein function. We find that the magnitude of the change in the HMMER E-value caused by an amino acid substitution is a good predictor of whether it is deleterious. We provide internet-accessible display tools for a genomewide collection of SNPs, including 7391 distinct non-synonymous coding region SNPs in 2683 genes. AVAILABILITY: http://lpgws.nci.nih.gov/cgi-bin/GeneViewer.cgi