Sequential tumor molecular profiling identifies likely germline variants.

PURPOSE: To identify likely germline DNA variants from sequential tumor profiling data from hematopoietic malignancies (HMs). METHODS: The coefficient of variance was calculated from variant allele frequency of next-generation sequencing assays. Variants' likelihood of being germline was ranked on a 1 to 5 scale. Outcomes were examined in patients with such variants. RESULTS: In a pilot set of 33 genes, 89% of grade 1, 77% of grade 2, 62% of grade 3, 52% of grade 4, and 21% of grade 5 variants were confirmed to be germline. Among those, 22% were pathogenic or likely pathogenic in genes recognized as conferring hereditary HM risk, including BRCA1/2, CHEK2, CSF3R, and DDX41. To determine if this approach identified genes with known autosomal dominant inheritance, we analyzed sequential data from 1336 genes in 1135 HM patients. Among unique variants, 16% occurred in hereditary HM genes, and 15% were deleterious. Patients with grade 1/2 alleles had decreased survival 2 years after initial molecular testing (78% versus 88%, P = .0037) and increased all-cause mortality compared with those without (hazard ratio 2.02, 95% CI 1.18-3.46, P = .019). CONCLUSION: Variant germline status may be predicted using sequential tumor profiling and patients with likely germline variants experience inferior outcomes compared with those without.

Alternating EM algorithm for a bilinear model in isoform quantification from RNA-seq data.

MOTIVATION: Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform read distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide bias correction step(s), which is based on biological considerations-such as GC content-and applied in single samples separately. The main problem is that not all biases are known. RESULTS: We have developed a novel method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xß, where the design matrix X is known and is computed based on the simplifying assumptions. In contrast XAEM considers Xß as a bilinear model with both X and ß unknown. Joint estimation of X and ß is made possible by a simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. We use an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and ß. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes. In a differential-expression analysis of a real single-cell RNA-seq dataset, XAEM achieves substantially better rediscovery rates in independent validation sets. AVAILABILITY AND IMPLEMENTATION: The method and pipeline are implemented as a tool and freely available for use at http://fafner.meb.ki.se/biostatwiki/xaem/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Isoform-level gene expression patterns in single-cell RNA-sequencing data.

Motivation: RNA sequencing of single cells enables characterization of transcriptional heterogeneity in seemingly homogeneous cell populations. Single-cell sequencing has been applied in a wide range of researches fields. However, few studies have focus on characterization of isoform-level expression patterns at the single-cell level. In this study, we propose and apply a novel method, ISOform-Patterns (ISOP), based on mixture modeling, to characterize the expression patterns of isoform pairs from the same gene in single-cell isoform-level expression data. Results: We define six principal patterns of isoform expression relationships and describe a method for differential-pattern analysis. We demonstrate ISOP through analysis of single-cell RNA-sequencing data from a breast cancer cell line, with replication in three independent datasets. We assigned the pattern types to each of 16 562 isoform-pairs from 4929 genes. Among those, 26% of the discovered patterns were significant (P<0.05), while remaining patterns are possibly effects of transcriptional bursting, drop-out and stochastic biological heterogeneity. Furthermore, 32% of genes discovered through differential-pattern analysis were not detected by differential-expression analysis. Finally, the effects of drop-out events and expression levels of isoforms on ISOP's performances were investigated through simulated datasets. To conclude, ISOP provides a novel approach for characterization of isoform-level preference, commitment and heterogeneity in single-cell RNA-sequencing data. Availability and implementation: The ISOP method has been implemented as a R package and is available at https://github.com/nghiavtr/ISOP under a GPL-3 license. Supplementary information: Supplementary data are available at Bioinformatics online.

Metformin pharmacogenomics: a genome-wide association study to identify genetic and epigenetic biomarkers involved in metformin anticancer response using human lymphoblastoid cell lines.

Metformin is currently considered as a promising anticancer agent in addition to its anti-diabetic effect. To better individualize metformin therapy and explore novel molecular mechanisms in cancer treatment, we conducted a pharmacogenomic study using 266 lymphoblastoid cell lines (LCLs). Metformin cytotoxicity assay was performed using the MTS assay. Genome-wide association (GWA) analyses were performed in LCLs using 1.3 million SNPs, 485k DNA methylation probes, 54k mRNA expression probe sets, and metformin cytotoxicity (IC50s). Top candidate genes were functionally validated using siRNA screening, followed by MTS assay in breast cancer cell lines. Further study of one top candidate, STUB1, was performed to elucidate the mechanisms by which STUB1 might contribute to metformin action. GWA analyses in LCLs identified 198 mRNA expression probe sets, 12 SNP loci, and 5 DNA methylation loci associated with metformin IC50 with P-values <10−4 or <10−5. Integrated SNP/methylation loci-expression-IC50 analyses found 3 SNP loci or 5 DNA methylation loci associated with metformin IC50 through trans-regulation of expression of 11 or 26 genes with P-value <10−4. Functional validation of top 61 candidate genes in 4 IPA networks indicated down regulation of 14 genes significantly altered metformin sensitivity in two breast cancer cell lines. Mechanistic studies revealed that the E3 ubiquitin ligase, STUB1, could influence metformin response by facilitating proteasome-mediated degradation of cyclin A. GWAS using a genomic data-enriched LCL model system, together with functional and mechanistic studies using cancer cell lines, help us to identify novel genetic and epigenetic biomarkers involved in metformin anticancer response.

Beta-Poisson model for single-cell RNA-seq data analyses.

MOTIVATION: Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a proportion of non-expressing cells. The standard and the over-dispersed gamma-Poisson models that are commonly used in bulk-cell RNA-sequencing are not able to capture this property. RESULTS: We introduce a beta-Poisson mixture model that can capture the bimodality of the single-cell gene expression distribution. We further integrate the model into the generalized linear model framework in order to perform differential expression analyses. The whole analytical procedure is called BPSC. The results from several real single-cell RNA-seq datasets indicate that ∼90% of the transcripts are well characterized by the beta-Poisson model; the model-fit from BPSC is better than the fit of the standard gamma-Poisson model in > 80% of the transcripts. Moreover, in differential expression analyses of simulated and real datasets, BPSC performs well against edgeR, a conventional method widely used in bulk-cell RNA-sequencing data, and against scde and MAST, two recent methods specifically designed for single-cell RNA-seq data. AVAILABILITY AND IMPLEMENTATION: An R package BPSC for model fitting and differential expression analyses of single-cell RNA-seq data is available under GPL-3 license at https://github.com/nghiavtr/BPSC CONTACT: yudi.pawitan@ki.se or mattias.rantalainen@ki.se SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The eSNV-detect: a computational system to identify expressed single nucleotide variants from transcriptome sequencing data.

Rapid development of next generation sequencing technology has enabled the identification of genomic alterations from short sequencing reads. There are a number of software pipelines available for calling single nucleotide variants from genomic DNA but, no comprehensive pipelines to identify, annotate and prioritize expressed SNVs (eSNVs) from non-directional paired-end RNA-Seq data. We have developed the eSNV-Detect, a novel computational system, which utilizes data from multiple aligners to call, even at low read depths, and rank variants from RNA-Seq. Multi-platform comparisons with the eSNV-Detect variant candidates were performed. The method was first applied to RNA-Seq from a lymphoblastoid cell-line, achieving 99.7% precision and 91.0% sensitivity in the expressed SNPs for the matching HumanOmni2.5 BeadChip data. Comparison of RNA-Seq eSNV candidates from 25 ER+ breast tumors from The Cancer Genome Atlas (TCGA) project with whole exome coding data showed 90.6-96.8% precision and 91.6-95.7% sensitivity. Contrasting single-cell mRNA-Seq variants with matching traditional multicellular RNA-Seq data for the MD-MB231 breast cancer cell-line delineated variant heterogeneity among the single-cells. Further, Sanger sequencing validation was performed for an ER+ breast tumor with paired normal adjacent tissue validating 29 out of 31 candidate eSNVs. The source code and user manuals of the eSNV-Detect pipeline for Sun Grid Engine and virtual machine are available at http://bioinformaticstools.mayo.edu/research/esnv-detect/.

Discovery of genetic biomarkers contributing to variation in drug response of cytidine analogues using human lymphoblastoid cell lines.

BACKGROUND: Two cytidine analogues, gemcitabine and cytosine arabinoside (AraC), are widely used in the treatment of a variety of cancers with a large individual variation in response. To identify potential genetic biomarkers associated with response to these two drugs, we used a human lymphoblastoid cell line (LCL) model system with extensive genomic data, including 1.3 million SNPs and 54,000 basal expression probesets to perform genome-wide association studies (GWAS) with gemcitabine and AraC IC50 values. RESULTS: We identified 11 and 27 SNP loci significantly associated with gemcitabine and AraC IC50 values, respectively. Eleven candidate genes were functionally validated using siRNA knockdown approach in multiple cancer cell lines. We also characterized the potential mechanisms of genes by determining their influence on the activity of 10 cancer-related signaling pathways using reporter gene assays. Most SNPs regulated gene expression in a trans manner, except 7 SNPs in the PIGB gene that were significantly associated with both the expression of PIGB and gemcitabine cytotoxicity. CONCLUSION: These results suggest that genetic variation might contribute to drug response via either cis- or trans- regulation of gene expression. GWAS analysis followed by functional pharmacogenomics studies might help identify novel biomarkers contributing to variation in response to these two drugs and enhance our understanding of underlying mechanisms of drug action.

Radiation pharmacogenomics: a genome-wide association approach to identify radiation response biomarkers using human lymphoblastoid cell lines.

Radiation therapy is used to treat half of all cancer patients. Response to radiation therapy varies widely among patients. Therefore, we performed a genome-wide association study (GWAS) to identify biomarkers to help predict radiation response using 277 ethnically defined human lymphoblastoid cell lines (LCLs). Basal gene expression levels and 1.3 million genome-wide single nucleotide polymorphism (SNP) markers from both Affymetrix and Illumina platforms were assayed for all 277 human LCLs. MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium] assays for radiation cytotoxicity were also performed to obtain area under the curve (AUC) as a radiation response phenotype for use in the association studies. Functional validation of candidate genes, selected from an integrated analysis that used SNP, expression, and AUC data, was performed with multiple cancer cell lines using specific siRNA knockdown, followed by MTS and colony-forming assays. A total of 27 loci, each containing at least two SNPs within 50 kb with P-values less than 10(-4) were associated with radiation AUC. A total of 270 expression probe sets were associated with radiation AUC with P < 10(-3). The integrated analysis identified 50 SNPs in 14 of the 27 loci that were associated with both AUC and the expression of 39 genes, which were also associated with radiation AUC (P < 10(-3)). Functional validation using siRNA knockdown in multiple tumor cell lines showed that C13orf34, MAD2L1, PLK4, TPD52, and DEPDC1B each significantly altered radiation sensitivity in at least two cancer cell lines. Studies performed with LCLs can help to identify novel biomarkers that might contribute to variation in response to radiation therapy and enhance our understanding of mechanisms underlying that variation.

Truncating Variants in RFC1 in Cerebellar Ataxia, Neuropathy, and Vestibular Areflexia Syndrome.

BACKGROUND AND OBJECTIVE: Cerebellar ataxia, neuropathy, and vestibular areflexia syndrome (CANVAS) is an autosomal recessive neurodegenerative disease characterized by adult-onset and slowly progressive sensory neuropathy, cerebellar dysfunction, and vestibular impairment. In most cases, the disease is caused by biallelic (AAGGG)n repeat expansions in the second intron of the replication factor complex subunit 1 (RFC1). However, a small number of cases with typical CANVAS do not carry the common biallelic repeat expansion. The objective of this study was to expand the genotypic spectrum of CANVAS by identifying sequence variants in RFC1-coding region associated with this condition. METHODS: Fifteen individuals diagnosed with CANVAS and carrying only 1 heterozygous (AAGGG)n expansion in RFC1 underwent whole-genome sequencing or whole-exome sequencing to test for the presence of a second variant in RFC1 or other unrelated gene. To assess the effect of truncating variants on RFC1 expression, we tested the level of RFC1 transcript and protein on patients' derived cell lines. RESULTS: We identified 7 patients from 5 unrelated families with clinically defined CANVAS carrying a heterozygous (AAGGG)n expansion together with a second truncating variant in trans in RFC1, which included the following: c.1267C>T (p.Arg423Ter), c.1739_1740del (p.Lys580SerfsTer9), c.2191del (p.Gly731GlufsTer6), and c.2876del (p.Pro959GlnfsTer24). Patient fibroblasts containing the c.1267C>T (p.Arg423Ter) or c.2876del (p.Pro959GlnfsTer24) variants demonstrated nonsense-mediated mRNA decay and reduced RFC1 transcript and protein. DISCUSSION: Our report expands the genotype spectrum of RFC1 disease. Full RFC1 sequencing is recommended in cases affected by typical CANVAS and carrying monoallelic (AAGGG)n expansions. In addition, it sheds further light on the pathogenesis of RFC1 CANVAS because it supports the existence of a loss-of-function mechanism underlying this complex neurodegenerative condition.

Genetic association with overall survival of taxane-treated lung cancer patients - a genome-wide association study in human lymphoblastoid cell lines followed by a clinical association study.

BACKGROUND: Taxane is one of the first line treatments of lung cancer. In order to identify novel single nucleotide polymorphisms (SNPs) that might contribute to taxane response, we performed a genome-wide association study (GWAS) for two taxanes, paclitaxel and docetaxel, using 276 lymphoblastoid cell lines (LCLs), followed by genotyping of top candidate SNPs in 874 lung cancer patient samples treated with paclitaxel. METHODS: GWAS was performed using 1.3 million SNPs and taxane cytotoxicity IC50 values for 276 LCLs. The association of selected SNPs with overall survival in 76 small or 798 non-small cell lung cancer (SCLC, NSCLC) patients were analyzed by Cox regression model, followed by integrated SNP-microRNA-expression association analysis in LCLs and siRNA screening of candidate genes in SCLC (H196) and NSCLC (A549) cell lines. RESULTS: 147 and 180 SNPs were associated with paclitaxel or docetaxel IC50s with p-values <10-4 in the LCLs, respectively. Genotyping of 153 candidate SNPs in 874 lung cancer patient samples identified 8 SNPs (p-value < 0.05) associated with either SCLC or NSCLC patient overall survival. Knockdown of PIP4K2A, CCT5, CMBL, EXO1, KMO and OPN3, genes within 200 kb up-/downstream of the 3 SNPs that were associated with SCLC overall survival (rs1778335, rs2662411 and rs7519667), significantly desensitized H196 to paclitaxel. SNPs rs2662411 and rs1778335 were associated with mRNA expression of CMBL or PIP4K2A through microRNA (miRNA) hsa-miR-584 or hsa-miR-1468. CONCLUSIONS: GWAS in an LCL model system, joined with clinical translational and functional studies, might help us identify genetic variations associated with overall survival of lung cancer patients treated paclitaxel.

Ibrutinib and venetoclax target distinct subpopulations of CLL cells: implication for residual disease eradication.

Ibrutinib inhibits Bruton tyrosine kinase while venetoclax is a specific inhibitor of the anti-apoptotic protein BCL2. Both drugs are highly effective as monotherapy against chronic lymphocytic leukemia (CLL), and clinical trials using the combination therapy have produced remarkable results in terms of rate of complete remission and frequency of undetectable minimal residual disease. However, the laboratory rationale behind the success of the drug combination is still lacking. A better understanding of how these two drugs synergize would eventually help develop other rational combination strategies. Using an ex vivo model that promotes CLL proliferation, we show that modeled ibrutinib proliferative responses, but not viability responses, correlate well with patients' actual clinical responses. Importantly, we demonstrate for the first time that ibrutinib and venetoclax act on distinct CLL subpopulations that have different proliferative capacities. While the dividing subpopulation of CLL responds to ibrutinib, the resting subpopulation preferentially responds to venetoclax. The combination of these targeted therapies effectively reduced both the resting and dividing subpopulations in most cases. Our laboratory findings help explain several clinical observations and contribute to the understanding of tumor dynamics. Additionally, our proliferation model may be used to identify novel drug combinations with the potential of eradicating residual disease.

CDC25B partners with PP2A to induce AMPK activation and tumor suppression in triple negative breast cancer.

Cell division cycle 25 (CDC25) dual specificity phosphatases positively regulate the cell cycle by activating cyclin-dependent kinase/cyclin complexes. Here, we demonstrate that in addition to its role in cell cycle regulation, CDC25B functions as a regulator of protein phosphatase 2A (PP2A), a major cellular Ser/Thr phosphatase, through its direct interaction with PP2A catalytic subunit. Importantly, CDC25B alters the regulation of AMP-activated protein kinase signaling (AMPK) by PP2A, increasing AMPK activity by inhibiting PP2A to dephosphorylate AMPK. CDC25B depletion leads to metformin resistance by inhibiting metformin-induced AMPK activation. Furthermore, dual inhibition of CDC25B and PP2A further inhibits growth of 3D organoids isolated from patient derived xenograft model of breast cancer compared to CDC25B inhibition alone. Our study identifies CDC25B as a regulator of PP2A, and uncovers a mechanism of controlling the activity of a key energy metabolism marker, AMPK.

Next-generation sequencing identifies 2 genomically distinct groups among pyloric gland adenomas.

The molecular alterations identified among pyloric gland adenomas (PGAs) in the published literature are based on polymerase chain reaction of targeted genes, and next-generation sequencing (NGS) has not been performed. In this study, we performed NGS and correlated the molecular alterations with the histologic grade of dysplasia and immunohistochemical findings in a cohort of PGAs. Successful DNA extraction and sequencing were performed in 15 pyloric gland adenomas/adenocarcinoma from 12 patients. Additionally, 4 specimens of autoimmune gastritis were selected to serve as the control group. Ten PGAs with low-grade dysplasia were seen to have mutations in the triad of APC, KRAS, and GNAS genes. Five PGAs with high-grade dysplasia/adenocarcinoma exhibited mutations in several genes including APC, CTNNB1, KRAS, GNAS, TP53, CDKN2A, PIK3CA, and EPHA5 genes but did not exhibit mutations in the triad of APC, KRAS, and GNAS genes. The median tumor mutational burden was higher in PGAs with high-grade dysplasia/adenocarcinoma when compared with PGAs with low-grade dysplasia (5.25 and 4.38, respectively). PGAs with high-grade dysplasia/adenocarcinoma had more chromosomal gains and losses than PGAs with low-grade dysplasia. The molecular findings suggest that there are 2 separate mutator pathways of dysplasia development in PGAs.

Inflammatory Myofibroblastic Tumor of the Uterus: An Immunohistochemical Study of 23 Cases.

Inflammatory myofibroblastic tumors (IMT) of the uterus may be underrecognized as their morphology and immunophenotype may overlap with myxoid variants of uterine smooth muscle tumors and endometrial stromal tumors. Although ALK is a helpful biomarker, not all uterine IMTs are ALK-rearranged, and a small subset of myxoid leiomyosarcomas is ALK-positive. Herein, we evaluated a series of 23 IMTs for the novel endometrial stromal markers interferon-inducible transmembrane protein-1 (IFITM1) and BCOR, the novel myoid marker transgelin, and possible predictive markers p16 and p53 by immunohistochemistry to determine their expression profile and potential prognostic value. Patients' ages ranged from 8 to 59 (mean 39) years and tumors from 2 to 20 (mean 8.2) cm. Follow-up was available for 12/23 (52%) patients; 9/12 (75%) without evidence of disease, 2/12 (17%) alive with disease, and 1/12 (8%) dead from disease. Four IMTs were classified as malignant due to extrauterine disease at diagnosis and/or recurrence. IFITM1 was positive (combined score>2) in 19/23 (83%), BCOR in 8/20 (40%), and transgelin in 22/23 (96%) of tumors. IFITM1 and BCOR were more often expressed in the myxoid component, and transgelin in the compact areas. p16 expression was absent in 5/23 (22%) of IMTs, while p53 was wildtype in all tumors. p16-negative IMTs included all 4 classified as malignant and one where the patient was lost to follow-up. Molecular data were available in 2 malignant IMTs, both of which harbored CDKN2A deletions. We conclude that caution is advised when using IFITM1, BCOR, and transgelin as markers for endometrial and smooth muscle tumors, as these are commonly expressed in IMTs. However, we did identify an association among lack of p16 staining, CKDN2A deletions, and aggressive behavior that merits corroboration by other studies. As a result of this finding, we recommend the use of p16 in the diagnostic work-up of uterine IMTs due to its potential prognostic significance.

Multi-Institutional Evaluation of Interrater Agreement of Variant Classification Based on the 2017 Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer.

This multi-institutional study was undertaken to evaluate interrater reliability of the 2017 Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists guidelines for interpretation and reporting of oncology sequence variants and to assess current practices and perceptions surrounding these guidelines. Fifty-one variants were distributed to 20 participants from 10 institutions for classification using the new guidelines. Agreement was assessed using chance-corrected agreement (Cohen κ). κ was 0.35. To evaluate if data sharing could help resolve disagreements, a summary of variant classifications and additional information about each variant were distributed to all participants. κ improved to 0.7 after the original classifications were revised. Participants were invited to take a web-based survey regarding their perceptions of the guidelines. Only 20% (n = 3) of the survey respondents had prior experience with the guidelines in clinical practice. The main perceived barriers to guideline implementation included the complexity of the guidelines, discordance between clinical actionability and pathobiologic relevance, lack of familiarity with the new classifications, and uncertainty when applying criteria to potential germline variants. This study demonstrates noteworthy discordances between pathologists for variant classification in solid tumors when using the 2017 Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists guidelines. These findings highlight potential areas for clarification/refinement before mainstream clinical adoption.

Targeted mutational analysis of inflammatory bowel disease-associated colorectal cancers.

Inflammatory bowel disease-associated colorectal carcinomas (IBD-CRCs) develop in a background of chronic inflammation, and thus, the molecular landscape of these tumors likely differs from that of sporadic colorectal cancer. To add to emerging data on molecular alterations present in these tumors, we analyzed our institution's cohort of IBD-CRCs. CRCs resected from patients with IBD underwent molecular analysis via a 50-gene hot-spot solid tumor panel (OncoScreen ST2.0). In-house sporadic CRCs and The Cancer Genome Atlas project data were used for comparison. Fifty-five IBD-CRCs from 48 patients were successfully analyzed. Mutations in TP53 were most common and were present in 69% of IBD-CRCs; a similar percentage of TP53 mutations was detected in sporadic colorectal carcinomas (70%). APC and KRAS mutations were significantly less common in IBD-CRCs than in sporadic CRCs (15% versus 53%, P < .001 and 20% versus 38%, P = .02, respectively). Additionally, the potentially targetable IDH1 R132 mutation was present in 7% of IBD-CRCs but only 1% of sporadic CRCs and The Cancer Genome Atlas CRCs; alterations in other genes with potential targeted therapies were very rare. In conclusion, IBD-CRCs exhibit molecular differences when compared to sporadic CRCs, suggesting different pathways of carcinogenesis, although certain alterations are common to both types of tumors. IDH1 mutations are present in a subset of IBD-CRCs, which may expand therapeutic options in the future.

Localization and mutation detection for paroxysmal kinesigenic choreoathetosis.

BACKGROUND: Paroxysmal kinesigenic choreoathetosis (PKC) is an autosomal-dominant movement disorder characterized by attacks of paroxysmal involuntary movements. To date, the causative gene has not been discovered. PURPOSE: The purpose of the study is to localize the causative region and detect the causative mutation. METHODS: A PKC family including 16 subjects (5 cases and 11 controls) in Zhejiang Province was recruited. Nine microsatellite markers on chromosome 16 were selected and genotyped. Two-point LOD scores were calculated. After preliminary localization, CACNG3, IL4R and ABCC11 were selected as candidate genes and were detected by polymerase chain reaction-sequencing or PCR-denaturing high performance liquid chromatography (PCR-DHPLC). RESULTS: The maximal two-point LOD score was obtained in D16S3081 with 1.21, and haplotype analysis revealed almost all of individuals carrying 5-3-8-3-4-2-5-5-6 in D16S3093/D16S685/D16S690/D16S3081/D16S3080 D16S411/D16S3136/D16S3112/D16S3057 were affected by PKC. There were no causative mutation in CACNG3, IL4R and ABCC11 genes. CONCLUSIONS: The culprit gene for PKC was located in approximately 19.34 cM region between 16p12.1-q13, and CACNG3, IL4R and ABCC11 were all ruled out as the cause.

Association between the gamma-aminobutyric acid type B receptor 1 and 2 gene polymorphisms and mesial temporal lobe epilepsy in a Han Chinese population.

An abnormal gamma-aminobutyric acid B receptor composed of gamma-aminobutyric acid type B receptor 1 (GABBR1) and gamma-aminobutyric acid type B receptor 2 (GABBR2) can provoke seizures. This study was designed to assess the contribution of GABBR1 and GABBR2 in mesial temporal lobe epilepsy (MTLE). Two tag single-nucleotide polymorphisms (SNPs) of GABBR1 and four tag SNPs of GABBR2 were selected and genotyped in 318 MTLE patients and 315 non-epileptic individuals. The rs967932 A-allele of GABBR2 increased the risk of MTLE in an additive and a dominant genetic model, respectively (P=0.018, OR=1.305, 95% CI 1.048-1.624 and P=0.003, OR=1.667, 95% CI 1.186-2.343, respectively). rs1999501 and rs944688 of GABBR2, and rs29259 of GABBR1 were thought to be associated with MTLE; however, after a Bonferroni correction, these associations were not observed and only the rs967932 A-allele was found to increase the risk of MTLE in the dominant model (P=0.036). The frequency at which the haplotype G-C-A-C (rs3780428-rs1999501-rs967932-rs944688) occurred in MTLE patients was significantly higher compared to the controls (12.26% vs. 6.51%, P=0.0004) and patients carrying this haplotype exhibited an earlier onset of MTLE (P=0.028). No evidence of significant allelic, genotypic, or haplotypic associations were identified in the tag SNPs of the GABBR1 gene in patients with MTLE, and the polymorphism at G1465A was not observed in our samples. Our results provide the first evidence that common genetic variations in the GABBR2 gene contribute to the risk of MTLE. Moreover, the present results do not support the hypothesis that common variants of GABBR1 contribute substantially to the epileptogenic effect during MTLE in the Han Chinese.

[Single nucleotide polymorphisms of promoter of human leukocyte antigen-DQB1 alleles in Chinese Han patients with Vogt-Koyanagi-Harada syndrome].

OBJECTIVE: To investigate the single nucleotide polymorphism of the promoter of HLA-DQB1(QBP) in Chinese Han patients with Vogt-Koyanagi-Harada syndrome. METHODS: Case-control design was applied. Eighty-eight Chinese Han patients with Vogt-Koyanagi-Harada syndrome and 88 non-Vogt-Koyanagi-Harada syndrome controls were admitted. DNA was extracted from the peripheral white blood cells of the subjects by the phenol-chloroform method. Polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) and clone-sequencing were applied to determine the sequences of the promoter of HLA-DQB1. Chromans and Bioedit software were used to analyze the sequences of the promoter of HLA-DQB1. Chi-square test and Fisher exact test were applied to compare the frequencies of bands of QBPs and SNPs for the two groups. RESULTS: Sixteen band patterns of HLA-QBP were shown by polyacrylamide gel electrophoresis (PAGE). The band frequencies of QBPb (corresponding gene sequence was QBP2.1 + 77C > A, chi2 = 26.01, Pc < 0.001) and QBPl (corresponding gene sequence was QBP3.3, chi2 = 16.99, Pc < 0.001) were significantly higher in patients with Vogt-Koyanagi-Harada syndrome than that in normal controls (Pc < 0.001). However, the frequencies of QBPg (corresponding gene sequence was QBP3.1, chi2 = 12.10, Pc < 0.05) and QBPn (corresponding gene sequence was QBP6.1 + 39G > A, chi2 = 14.64, Pc < 0.05) were significantly lower in patients with Vogt-Koyanagi-Harada syndrome than those of the controls. Twelve SNPs were found in all subjects. The frequency of C allele at position -189C/A in patients with Vogt-Koyanagi-Harada syndrome was significantly higher than that in controls (chi2 = 45.92, P = 0.000). However, the frequency of G allele at position -227G/A in patients with Vogt-Koyanagi-Harada syndrome was significantly lower as compared with that in the normal controls (chi2 = 15.63, P = 0.000). CONCLUSIONS: C allele of -189C/A is a genetically susceptible factor of Vogt-Koyanagi-Harada syndrome and G allele of -227G/A is the protective factor of Vogt-Koyanagi-Harada syndrome.

TSPYL Family Regulates CYP17A1 and CYP3A4 Expression: Potential Mechanism Contributing to Abiraterone Response in Metastatic Castration-Resistant Prostate Cancer.

The testis-specific Y-encoded-like protein (TSPYL) gene family includes TSPYL1 to TSPYL6. We previously reported that TSPYL5 regulates cytochrome P450 (CYP) 19A1 expression. Here we show that TSPYLs, especially TSPYL 1, 2, and 4, can regulate the expression of many CYP genes, including CYP17A1, a key enzyme in androgen biosynthesis, and CYP3A4, an enzyme that catalyzes the metabolism of abiraterone, a CYP17 inhibitor. Furthermore, a common TSPYL1 single nucleotide polymorphism (SNP), rs3828743 (G/A) (Pro62Ser), abolishes TSPYL1's ability to suppress CYP3A4 expression, resulting in reduced abiraterone concentrations and increased cell proliferation. Data from a prospective clinical trial of 87 metastatic castration-resistant prostate cancer patients treated with abiraterone acetate/prednisone showed that the variant SNP genotype (A) was significantly associated with worse response and progression-free survival. In summary, TSPYL genes are novel CYP gene transcription regulators, and genetic alteration within these genes significantly influences response to drug therapy through transcriptional regulation of CYP450 genes.