Factors affecting levels of circulating cell-free fetal DNA in maternal plasma and their implications for noninvasive prenatal testing.

OBJECTIVE: Sufficient fetal DNA in a maternal plasma sample is required for accurate aneuploidy detection via noninvasive prenatal testing, thus highlighting a need to understand the factors affecting fetal fraction. METHOD: The MaterniT21™ PLUS test uses massively parallel sequencing to analyze cell-free fetal DNA in maternal plasma and detect chromosomal abnormalities. We assess the impact of a variety of factors, both maternal and fetal, on the fetal fraction across a large number of samples processed by Sequenom Laboratories. RESULTS: The rate of increase in fetal fraction with increasing gestational age varies across the duration of the testing period and is also influenced by fetal aneuploidy status. Maternal weight trends inversely with fetal fraction, and we find no added benefit from analyzing body mass index or blood volume instead of weight. Strong correlations exist between fetal fractions from aliquots taken from the same patient at the same blood draw and also at different blood draws. CONCLUSION: While a number of factors trend with fetal fraction across the cohort as a whole, they are not the sole determinants of fetal fraction. In this study, the variability for any one patient does not appear large enough to justify postponing testing to a later gestational age.

Determination of fetal DNA fraction from the plasma of pregnant women using sequence read counts.

OBJECTIVE: This study introduces a novel method, referred to as SeqFF, for estimating the fetal DNA fraction in the plasma of pregnant women and to infer the underlying mechanism that allows for such statistical modeling. METHODS: Autosomal regional read counts from whole-genome massively parallel single-end sequencing of circulating cell-free DNA (ccfDNA) from the plasma of 25 312 pregnant women were used to train a multivariate model. The pretrained model was then applied to 505 pregnant samples to assess the performance of SeqFF against known methodologies for fetal DNA fraction calculations. RESULTS: Pearson's correlation between chromosome Y and SeqFF for pregnancies with male fetuses from two independent cohorts ranged from 0.932 to 0.938. Comparison between a single-nucleotide polymorphism-based approach and SeqFF yielded a Pearson's correlation of 0.921. Paired-end sequencing suggests that shorter ccfDNA, that is, less than 150 bp in length, is nonuniformly distributed across the genome. Regions exhibiting an increased proportion of short ccfDNA, which are more likely of fetal origin, tend to provide more information in the SeqFF calculations. CONCLUSION: SeqFF is a robust and direct method to determine fetal DNA fraction. Furthermore, the method is applicable to both male and female pregnancies and can greatly improve the accuracy of noninvasive prenatal testing for fetal copy number variation.

Detection of fetal subchromosomal abnormalities by sequencing circulating cell-free DNA from maternal plasma.

BACKGROUND: The development of sequencing-based noninvasive prenatal testing (NIPT) has been largely focused on whole-chromosome aneuploidies (chromosomes 13, 18, 21, X, and Y). Collectively, they account for only 30% of all live births with a chromosome abnormality. Various structural chromosome changes, such as microdeletion/microduplication (MD) syndromes are more common but more challenging to detect. Recently, several publications have shown results on noninvasive detection of MDs by deep sequencing. These approaches demonstrated the proof of concept but are not economically feasible for large-scale clinical applications. METHODS: We present a novel approach that uses low-coverage whole genome sequencing (approximately 0.2×) to detect MDs genome wide without requiring prior knowledge of the event's location. We developed a normalization method to reduce sequencing noise. We then applied a statistical method to search for consistently increased or decreased regions. A decision tree was used to differentiate whole-chromosome events from MDs. RESULTS: We demonstrated via a simulation study that the sensitivity difference between our method and the theoretical limit was <5% for MDs ≥9 Mb. We tested the performance in a blinded study in which the MDs ranged from 3 to 40 Mb. In this study, our algorithm correctly identified 17 of 18 cases with MDs and 156 of 157 unaffected cases. CONCLUSIONS: The limit of detection for any given MD syndrome is constrained by 4 factors: fetal fraction, MD size, coverage, and biological and technical variability of the event region. Our algorithm takes these factors into account and achieved 94.4% sensitivity and 99.4% specificity.

Non-invasive prenatal chromosomal aneuploidy testing--clinical experience: 100,000 clinical samples.

OBJECTIVE: As the first laboratory to offer massively parallel sequencing-based noninvasive prenatal testing (NIPT) for fetal aneuploidies, Sequenom Laboratories has been able to collect the largest clinical population experience data to date, including >100,000 clinical samples from all 50 U.S. states and 13 other countries. The objective of this study is to give a robust clinical picture of the current laboratory performance of the MaterniT21 PLUS LDT. STUDY DESIGN: The study includes plasma samples collected from patients with high-risk pregnancies in our CLIA-licensed, CAP-accredited laboratory between August 2012 to June 2013. Samples were assessed for trisomies 13, 18, 21 and for the presence of chromosome Y-specific DNA. Sample data and ad hoc outcome information provided by the clinician was compiled and reviewed to determine the characteristics of this patient population, as well as estimate the assay performance in a clinical setting. RESULTS: NIPT patients most commonly undergo testing at an average of 15 weeks, 3 days gestation; and average 35.1 years of age. The average turnaround time is 4.54 business days and an overall 1.3% not reportable rate. The positivity rate for Trisomy 21 was 1.51%, followed by 0.45% and 0.21% rate for Trisomies 18 and 13, respectively. NIPT positivity rates are similar to previous large clinical studies of aneuploidy in women of maternal age ≥ 35 undergoing amniocentesis. In this population 3519 patients had multifetal gestations (3.5%) with 2.61% yielding a positive NIPT result. CONCLUSION: NIPT has been commercially offered for just over 2 years and the clinical use by patients and clinicians has increased significantly. The risks associated with invasive testing have been substantially reduced by providing another assessment of aneuploidy status in high-risk patients. The accuracy and NIPT assay positivity rate are as predicted by clinical validations and the test demonstrates improvement in the current standard of care.

Noninvasive prenatal detection of sex chromosomal aneuploidies by sequencing circulating cell-free DNA from maternal plasma.

OBJECTIVE: Whole-genome sequencing of circulating cell free (ccf) DNA from maternal plasma has enabled noninvasive prenatal testing for common autosomal aneuploidies. The purpose of this study was to extend the detection to include common sex chromosome aneuploidies (SCAs): [47,XXX], [45,X], [47,XXY], and [47,XYY] syndromes. METHOD: Massively parallel sequencing was performed on ccf DNA isolated from the plasma of 1564 pregnant women with known fetal karyotype. A classification algorithm for SCA detection was constructed and trained on this cohort. Another study of 411 maternal samples from women with blinded-to-laboratory fetal karyotypes was then performed to determine the accuracy of the classification algorithm. RESULTS: In the training cohort, the new algorithm had a detection rate (DR) of 100% (95%CI: 82.3%, 100%), a false positive rate (FPR) of 0.1% (95%CI: 0%, 0.3%), and nonreportable rate of 6% (95%CI: 4.9%, 7.4%) for SCA determination. The blinded validation yielded similar results: DR of 96.2% (95%CI: 78.4%, 99.8%), FPR of 0.3% (95%CI: 0%, 1.8%), and nonreportable rate of 5% (95%CI: 3.2%, 7.7%) for SCA determination CONCLUSION: Noninvasive prenatal identification of the most common sex chromosome aneuploidies is possible using ccf DNA and massively parallel sequencing with a high DR and a low FPR.

High-throughput massively parallel sequencing for fetal aneuploidy detection from maternal plasma.

BACKGROUND: Circulating cell-free (ccf) fetal DNA comprises 3-20% of all the cell-free DNA present in maternal plasma. Numerous research and clinical studies have described the analysis of ccf DNA using next generation sequencing for the detection of fetal aneuploidies with high sensitivity and specificity. We sought to extend the utility of this approach by assessing semi-automated library preparation, higher sample multiplexing during sequencing, and improved bioinformatic tools to enable a higher throughput, more efficient assay while maintaining or improving clinical performance. METHODS: Whole blood (10mL) was collected from pregnant female donors and plasma separated using centrifugation. Ccf DNA was extracted using column-based methods. Libraries were prepared using an optimized semi-automated library preparation method and sequenced on an Illumina HiSeq2000 sequencer in a 12-plex format. Z-scores were calculated for affected chromosomes using a robust method after normalization and genomic segment filtering. Classification was based upon a standard normal transformed cutoff value of z = 3 for chromosome 21 and z = 3.95 for chromosomes 18 and 13. RESULTS: Two parallel assay development studies using a total of more than 1900 ccf DNA samples were performed to evaluate the technical feasibility of automating library preparation and increasing the sample multiplexing level. These processes were subsequently combined and a study of 1587 samples was completed to verify the stability of the process-optimized assay. Finally, an unblinded clinical evaluation of 1269 euploid and aneuploid samples utilizing this high-throughput assay coupled to improved bioinformatic procedures was performed. We were able to correctly detect all aneuploid cases with extremely low false positive rates of 0.09%, <0.01%, and 0.08% for trisomies 21, 18, and 13, respectively. CONCLUSIONS: These data suggest that the developed laboratory methods in concert with improved bioinformatic approaches enable higher sample throughput while maintaining high classification accuracy.

Inclusion of genotype with fundus phenotype improves accuracy of predicting choroidal neovascularization and geographic atrophy.

PURPOSE: The accuracy of predicting conversion from early-stage age-related macular degeneration (AMD) to the advanced stages of choroidal neovascularization (CNV) or geographic atrophy (GA) was evaluated to determine whether inclusion of clinically relevant genetic markers improved accuracy beyond prediction using phenotypic risk factors alone. DESIGN: Cohort study. PARTICIPANTS: White, non-Hispanic subjects participating in the Age-Related Eye Disease Study (AREDS) sponsored by the National Eye Institute consented to provide a genetic specimen. Of 2415 DNA specimens available, 940 were from disease-free subjects and 1475 were from subjects with early or intermediate AMD. METHODS: DNA specimens from study subjects were genotyped for 14 single nucleotide polymorphisms (SNPs) in genes shown previously to associate with CNV: ARMS2, CFH, C3, C2, FB, CFHR4, CFHR5, and F13B. Clinical demographics and established disease associations, including age, sex, smoking status, body mass index (BMI), AREDS treatment category, and educational level, were evaluated. Four multivariate logistic models (phenotype; genotype; phenotype + genotype; and phenotype + genotype + demographic + environmental factors) were tested using 2 end points (CNV, GA). Models were fitted using Cox proportional hazards regression to use time-to-disease onset data. MAIN OUTCOME MEASURES: Brier score (measure of accuracy) was used to identify the model with the lowest prediction error in the training set. The most accurate model was subjected to independent statistical validation, and final model performance was described using area under the receiver operator curve (AUC) or C-statistic. RESULTS: The CNV prediction models that combined genotype with phenotype with or without age and smoking revealed superior performance (C-statistic = 0.96) compared with the phenotype model based on the simplified severity scale and the presence of CNV in the nonstudy eye (C-statistic = 0.89; P<0.01). For GA, the model that combined genotype with phenotype demonstrated the highest performance (AUC = 0.94). Smoking status and ARMS2 genotype had less of an impact on the prediction of GA compared with CNV. CONCLUSIONS: Inclusion of genotype assessment improves CNV prediction beyond that achievable with phenotype alone and may improve patient management. Separate assessments should be used to predict progression to CNV and GA because genetic markers and smoking status do not equally predict both end points. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Two algorithms for biospecimen comparison and differentiation using SNP genotypes.

AIMS: Biobanks are frequently required to verify specimen relationships. We present two algorithms to compare SNP genotype patterns that provide an objective, high-throughput tool for verification. METHODS: The first algorithm allows for comparison of all holdings within a biobank, and is well suited to construct sample relationships de novo for comparison with assumed relationships. The second algorithm is tailored to oncology, and allows one to confirm that paired DNAs from malignant and normal tissues are from the same individual in the presence of copy number variations. To evaluate both algorithms, we used an internal training data set (n = 1504) and an external validation data set (n = 1457). RESULTS: In comparison with the results from manual review and a priori knowledge of patient relationships, we identified no errors in interpreting sample relationships within our validation data set. CONCLUSION: We provide an efficient and objective method of automated data analysis that is currently lacking for establishing and verifying specimen relationships in biobanks.

Multiplex protein detection with DNA readout via mass spectrometry.

Multiplex protein quantification has been constrained by issues of assay specificity, sensitivity and throughput. This research presents a novel approach that overcomes these limitations using antibody-oligonucleotide conjugates for immuno-polymerase chain reaction (immuno-PCR) or proximity ligation, coupled with competitive PCR and MALDI-TOF mass spectrometry. Employing these combinations of technologies, we demonstrate multiplex detection and quantification of up to eight proteins, spanning wide dynamic ranges from femtomolar concentrations, using only microliter sample volumes.

Clinical validation of a genetic model to estimate the risk of developing choroidal neovascular age-related macular degeneration.

Predictive tests for estimating the risk of developing late-stage neovascular age-related macular degeneration (AMD) are subject to unique challenges. AMD prevalence increases with age, clinical phenotypes are heterogeneous and control collections are prone to high false-negative rates, as many control subjects are likely to develop disease with advancing age. Risk prediction tests have been presented previously, using up to ten genetic markers and a range of self-reported non-genetic variables such as body mass index (BMI) and smoking history. In order to maximise the accuracy of prediction for mainstream genetic testing, we sought to derive a test comparable in performance to earlier testing models but based purely on genetic markers, which are static through life and not subject to misreporting. We report a multicentre assessment of a larger panel of single nucleotide polymorphisms (SNPs) than previously analysed, to improve further the classification performance of a predictive test to estimate the risk of developing choroidal neovascular (CNV) disease. We developed a predictive model based solely on genetic markers and avoided inclusion of self-reported variables (eg smoking history) or non-static factors (BMI, education status) that might otherwise introduce inaccuracies in calculating individual risk estimates. We describe the performance of a test panel comprising 13 SNPs genotyped across a consolidated collection of four patient cohorts obtained from academic centres deemed appropriate for pooling. We report on predictive effect sizes and their classification performance. By incorporating multiple cohorts of homogeneous ethnic origin, we obtained >80 per cent power to detect differences in genetic variants observed between cases and controls. We focused our study on CNV, a subtype of advanced AMD associated with a severe and potentially treatable form of the disease. Lastly, we followed a two-stage strategy involving both test model development and test model validation to present estimates of classification performance anticipated in the larger clinical setting. The model contained nine SNPs tagging variants in the regulators of complement activation (RCA) locus spanning the complement factor H (CFH), complement factor H-related 4 (CFHR4), complement factor H-related 5 (CFHR5) and coagulation factor XIII B subunit (F13B) genes; the four remaining SNPs targeted polymorphisms in the complement component 2 (C2), complement factor B (CFB), complement component 3 (C3) and age-related maculopathy susceptibility protein 2 (ARMS2) genes. The pooled sample size (1,132 CNV cases, 822 controls) allowed for both model development and model validation to confirm the accuracy of risk prediction. At the validation stage, our test model yielded 82 per cent sensitivity and 63 per cent specificity, comparable with metrics reported with earlier testing models that included environmental risk factors. Our test had an area under the curve of 0.80, reflecting a modest improvement compared with tests reported with fewer SNPs.

Fetal RHD genotype detection from circulating cell-free fetal DNA in maternal plasma in non-sensitized RhD negative women.

OBJECTIVE: To examine the performance of the SensiGene Fetal RHD Genotyping Laboratory Developed Test (RHD Genotyping LDT) using circulating cell-free fetal DNA (ccff DNA) extracted from maternal plasma. METHODS: ccff DNA was extracted from maternal blood from non-sensitized women with singleton pregnancies in two cohorts, one with a serotype reference (11-13 weeks' gestation) and one with the reference source (6-30 weeks' gestation). The presence of three RHD exon sequences (exons 4, 5, 7), the psi-pseudogene, three Y-chromosome sequences (SRY, DBY and TTTY2), and the X/Y-chromosome TGIF gene control were determined using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry-the RHD Genotyping LDT. RESULTS: The cohort with a serotype RhD reference showed correct classification in 201 of 207 patients, a test accuracy of 97.1%, with a sensitivity and specificity for prediction of RhD serotype of 97.2 and 96.8%, respectively. The cohort with a genotype RHD reference showed correct classification in 198 of 199 patients, indicating a test accuracy of 99.5% with a sensitivity and specificity for prediction of RHD genotype of 100.0 and 98.3%, respectively. CONCLUSION: Fetal RHD genotyping can accurately be determined using ccff DNA in the first and second trimesters of pregnancy.

Restriction enzyme-mediated enhanced detection of circulating cell-free fetal DNA in maternal plasma.

A universal method confirming the presence of circulating cell-free fetal (ccff) DNA in maternal plasma is important in the field of noninvasive prenatal diagnostics. Restriction endonuclease digestion of one allele of a single-nucleotide polymorphism (SNP) was used to allow detection of paternal alleles in maternal plasma DNA. Multiplexed genotyping of 92 panethnic high-frequency SNPs predicted >0.99 probability of detecting at least four informative loci per sample. Child-maternal paired DNA samples were used to confirm detection of 2% child's heterozygous DNA in a background of maternal DNA homozygous for the digestible allele. By restriction endonuclease digestion of DNA in a PCR cocktail before thermal cycling, 10 genomic copies of a paternal SNP allele were detectable in a background of 990 maternal SNP alleles. A comparison of 154 pregnant and nonpregnant female plasma DNA samples demonstrated enhanced detection of nondigestible SNP alleles in maternal plasma. Receiver operating characteristic curve analysis showed an optimal detection threshold of four nondigestible SNP alleles in plasma for the confirmation of ccff DNA and 98% sensitivity and 96% specificity at a 95% confidence level. Our study demonstrates the ability of this technique to confirm the presence of paternal alleles from ccff DNA in maternal plasma.

Noninvasive detection of fetal trisomy 21 by sequencing of DNA in maternal blood: a study in a clinical setting.

OBJECTIVE: We sought to evaluate a multiplexed massively parallel shotgun sequencing assay for noninvasive trisomy 21 detection using circulating cell-free fetal DNA. STUDY DESIGN: Sample multiplexing and cost-optimized reagents were evaluated as improvements to a noninvasive fetal trisomy 21 detection assay. A total of 480 plasma samples from high-risk pregnant women were employed. RESULTS: In all, 480 prospectively collected samples were obtained from our third-party storage site; 13 of these were removed due to insufficient quantity or quality. Eighteen samples failed prespecified assay quality control parameters. In all, 449 samples remained: 39 trisomy 21 samples were correctly classified; 1 sample was misclassified as trisomy 21. The overall classification showed 100% sensitivity (95% confidence interval, 89-100%) and 99.7% specificity (95% confidence interval, 98.5-99.9%). CONCLUSION: Extending the scope of previous reports, this study demonstrates that plasma DNA sequencing is a viable method for noninvasive detection of fetal trisomy 21 and warrants clinical validation in a larger multicenter study.

Multiplexed analysis of circulating cell-free fetal nucleic acids for noninvasive prenatal diagnostic RHD testing.

OBJECTIVE: The objective of the study was the evaluation of a novel multiplex assay to detect fetal Rh blood group D-antigen gene (RHD) loci in maternal plasma from RhD-negative, pregnant women. STUDY DESIGN: An RHD genotyping assay was designed to detect exons 4, 5, 7, and 10 and RHDΨ (pseudogene) of the RHD gene along with a Y chromosome-specific assay and a generic polymerase chain reaction amplification control. Plasma samples from 150 RhD-negative pregnant women were assayed for fetal RHD genotype using the MassARRAY system. RESULTS: The fetal RHD status of 148 of 150 samples (98.7%) was correctly classified; 86 (57.3%) and 62 (41.3%) were positive and negative, respectively. CONCLUSION: This study demonstrates that noninvasive prenatal diagnostics with a single-reaction multiplexed assay is a viable path toward routine characterization of fetal RHD genotypes using circulating cell-free fetal DNA in maternal plasma on the MassARRAY system and is perhaps preferable to serologic testing as currently used clinically.

Transcript profiling of candidate genes in testis of pigs exhibiting large differences in androstenone levels.

BACKGROUND: Boar taint is an unpleasant odor and flavor of the meat and occurs in a high proportion of uncastrated male pigs. Androstenone, a steroid produced in testis and acting as a sex pheromone regulating reproductive function in female pigs, is one of the main compounds responsible for boar taint. The primary goal of the present investigation was to determine the differential gene expression of selected candidate genes related to levels of androstenone in pigs. RESULTS: Altogether 2560 boars from the Norwegian Landrace and Duroc populations were included in this study. Testicle samples from the 192 boars with most extreme high or low levels of androstenone in fat were used for RNA extraction, and 15 candidate genes were selected and analyzed by real-competitive PCR analysis. The genes Cytochrome P450 c17 (CYP17A1), Steroidogenic acute regulatory protein (STAR), Aldo-keto reductase family 1 member C4 (AKR1C4), Short-chain dehydrogenase/reductase family member 4 (DHRS4), Ferritin light polypeptide (FTL), Sulfotransferase family 2A, dehydroepiandrosterone-preferring member 1 (SULT2A1), Cytochrome P450 subfamily XIA polypeptide 1 (CYP11A1), Cytochrome b5 (CYB5A), and 17-beta-Hydroxysteroid dehydrogenase IV (HSD17B4) were all found to be significantly (P < 0.05) up-regulated in high androstenone boars in both Duroc and Landrace. Furthermore, Cytochrome P450 c19A2 (CYP19A2) was down-regulated and progesterone receptor membrane component 1 (PGRMC1) was up-regulated in high-androstenone Duroc boars only, while CYP21 was significantly down-regulated (2.5) in high-androstenone Landrace only. The genes Nuclear Receptor co-activator 4 (NCOA4), Sphingomyrlin phosphodiesterase 1 (SMPD1) and 3beta-hydroxysteroid dehydrogenase (HSD3B) were not significantly differentially expressed in any breeds. Additionally, association studies were performed for the genes with one or more detected SNPs. Association between SNP and androstenone level was observed in CYB5A only, suggesting cis-regulation of the differential transcription in this gene. CONCLUSION: A large pig material of highly extreme androstenone levels is investigated. The current study contributes to the knowledge about which genes that is differentially expressed regard to the levels of androstenone in pigs. Results in this paper suggest that several genes are important in the regulation of androstenone level in boars and warrant further evaluation of the above mentioned candidate genes, including analyses in different breeds, identification of causal mutations and possible gene interactions.

Qualitative and quantitative genotyping using single base primer extension coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MassARRAY).

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) has developed over the past decade into a versatile tool for the analysis of nucleic acids and especially as a reliable genotyping platform. This chapter summarizes its use in the context of the most widely used MALDI-TOF MS genomics platform, the Sequenom MassARRAY system. MassARRAY genotyping is based upon region-specific PCR followed by allele-specific single base primer extension reactions which are then desalted, dispensed onto a silica array preloaded with matrix, and the genotyping products are resolved on the basis of mass using MALDI-TOF MS. The platform is versatile in that it can resolve multiplexed reactions (40+ separate loci per reaction), acquires and interprets data quickly, gives a quantitative output which reflects the amount of product generated for each allele within an assay for multiplexed reactions, and is highly sensitive. These characteristics coupled with integrated software for sequence annotation, assay design, data interpretation, and data storage have lead to its wide adoption and use for multiple nucleic acid analysis applications in both the realm of genomics research and molecular diagnostics.

Development and evaluation of a PCR and mass spectroscopy (PCR-MS)-based method for quantitative, type-specific detection of human papillomavirus.

Knowledge of the central role of high-risk human papillomavirus (HPV) in cervical carcinogenesis, coupled with an emerging need to monitor the efficacy of newly introduced HPV vaccines, warrant development and evaluation of type-specific, quantitative HPV detection methods. In the present study, a prototype PCR and mass spectroscopy (PCR-MS)-based method to detect and quantitate 13 high-risk HPV types is compared to the Hybrid Capture 2 High-Risk HPV DNA test (HC2; Digene Corp., Gaithersburg, MD) in 199 cervical scraping samples and to DNA sequencing in 77 cervical tumor samples. High-risk HPV types were detected in 76/77 (98.7%) cervical tumor samples by PCR-MS. Degenerate and type-specific sequencing confirmed the types detected by PCR-MS. In 199 cervical scraping samples, all 13 HPV types were detected by PCR-MS. Eighteen (14.5%) of 124 cervical scraping samples that were positive for high-risk HPV by HC2 were negative by PCR-MS. In all these cases, degenerate DNA sequencing failed to detect any of the 13 high-risk HPV types. Nearly half (46.7%) of the 75 cervical scraping samples that were negative for high-risk HPV by the HC2 assay were positive by PCR-MS. Type-specific sequencing in a subset of these samples confirmed the HPV type detected by PCR-MS. Quantitative PCR-MS results demonstrated that 11/75 (14.7%) samples contained as much HPV copies/cell as HC2-positive samples. These findings suggest that this prototype PCR-MS assay performs at least as well as HC2 for HPV detection, while offering the additional, unique advantages of type-specific identification and quantitation. Further validation work is underway to define clinically meaningful HPV detection thresholds and to evaluate the potential clinical application of future generations of the PCR-MS assay.

Cytosine methylation profiles as a molecular marker in non-small cell lung cancer.

Aberrant promoter methylation is frequently observed in different types of lung cancer. Epigenetic modifications are believed to occur before the clinical onset of the disease and hence hold a great promise as early detection markers. Extensive analysis of DNA methylation has been impeded by methods that are either too labor intensive to allow large-scale studies or not sufficiently quantitative to measure subtle changes in the degree of methylation. We used a novel quantitative DNA methylation analysis technology to complete a large-scale cytosine methylation profiling study involving 47 gene promoter regions in 96 lung cancer patients. Each individual contributed a lung cancer specimen and corresponding adjacent normal tissue. The study identified six genes with statistically significant differences in methylation between normal and tumor tissue (P < 10(-6)). We explored the quantitative methylation data using an unsupervised hierarchical clustering algorithm. The data analysis revealed that methylation patterns differentiate normal from tumor tissue. For validation of our approach, we divided the samples to train a classifier and test its performance. We were able to distinguish normal from lung cancer tissue with >95% sensitivity and specificity. These results show that quantitative cytosine methylation profiling can be used to identify molecular classification markers in lung cancer.

A single nucleotide polymorphism based approach for the identification and characterization of gene expression modulation using MassARRAY.

Single nucleotide polymorphisms (SNPs) are the most common form of genetic variation. Their abundance and the ease with which they can be assayed have lead to their use in applications beyond simple genotyping. One such application is the quantitative determination of transcript levels associated with distinct alleles or haplotypes found in promoters and coding regions of genes. These changes in expression due to allelic variation are often associated with additional genomic or transcript modifications such as DNA methylation or RNA editing. Here, we describe the use of an integrated genetic analysis platform, based on matrix-assisted laser desorption/ionisation-time-of-flight (MALDI-TOF) to first, discover coding SNPs (cSNPs); second, use these cSNPs to identify and analyze allele-specific expression; and third, from this knowledge to further analyze methylation patterns as a putative cause for the allele-specific expression. An established model involving allele-specific expression profiles of the human tumor protein 73 (TP73) gene is presented as an example to outline and validate data obtained from the MassARRAY platform. The availability of a single integrated platform to assay stable and dynamic variation at the genomic and transcript level greatly simplifies complex functional genomic studies.

Role of ICAM1 in invasion of human breast cancer cells.

We identified previously a region on chromosome 19p13.2 spanning the genes encoding the intercellular adhesion molecules (ICAM), ICAM1, ICAM4 and ICAM5 as a breast cancer susceptibility locus. Genetic variants in this region were also associated with indicators of disease severity, including higher rates of metastases to other organs. Based on this association, we set out to explore the role of ICAM1 in proliferation and invasion of human breast cancer cells. We observed that ICAM1 downregulation at the mRNA and protein levels led to a strong suppression of human breast cell invasion through a matrigel matrix. Under the same conditions, no significant effect on cell proliferation in vitro was seen. Incubation of cells with an antibody against ICAM1 blocked invasion of the highly metastatic MDA-MB-435 cell line in a dose-dependent manner without affecting cell migration. We also demonstrated that the level of ICAM1 protein expression on the cell surface positively correlated with metastatic potential of five human breast cancer cell lines and that ICAM1 mRNA levels were elevated in breast tumor compared with adjacent normal tissue. These results corroborate our previous genetic finding that variations in the ICAM region are associated with the occurrence of metastases and establish a causal role of ICAM1 in invasion of metastatic human breast carcinoma cell lines.