Pathologic gene network rewiring implicates PPP1R3A as a central regulator in pressure overload heart failure.

Heart failure is a leading cause of mortality, yet our understanding of the genetic interactions underlying this disease remains incomplete. Here, we harvest 1352 healthy and failing human hearts directly from transplant center operating rooms, and obtain genome-wide genotyping and gene expression measurements for a subset of 313. We build failing and non-failing cardiac regulatory gene networks, revealing important regulators and cardiac expression quantitative trait loci (eQTLs). PPP1R3A emerges as a regulator whose network connectivity changes significantly between health and disease. RNA sequencing after PPP1R3A knockdown validates network-based predictions, and highlights metabolic pathway regulation associated with increased cardiomyocyte size and perturbed respiratory metabolism. Mice lacking PPP1R3A are protected against pressure-overload heart failure. We present a global gene interaction map of the human heart failure transition, identify previously unreported cardiac eQTLs, and demonstrate the discovery potential of disease-specific networks through the description of PPP1R3A as a central regulator in heart failure.

Physical activity, sleep and cardiovascular health data for 50,000 individuals from the MyHeart Counts Study.

Studies have established the importance of physical activity and fitness for long-term cardiovascular health, yet limited data exist on the association between objective, real-world large-scale physical activity patterns, fitness, sleep, and cardiovascular health primarily due to difficulties in collecting such datasets. We present data from the MyHeart Counts Cardiovascular Health Study, wherein participants contributed data via an iPhone application built using Apple's ResearchKit framework and consented to make this data available freely for further research applications. In this smartphone-based study of cardiovascular health, participants recorded daily physical activity, completed health questionnaires, and performed a 6-minute walk fitness test. Data from English-speaking participants aged 18 years or older with a US-registered iPhone who agreed to share their data broadly and who enrolled between the study's launch and the time of the data freeze for this data release (March 10 2015-October 28 2015) are now available for further research. It is anticipated that releasing this large-scale collection of real-world physical activity, fitness, sleep, and cardiovascular health data will enable the research community to work collaboratively towards improving our understanding of the relationship between cardiovascular indicators, lifestyle, and overall health, as well as inform mobile health research best practices.

Extracutaneous manifestations in phacomatosis cesioflammea and cesiomarmorata: Case series and literature review.

Phacomatosis pigmentovascularis (PPV) comprises a family of rare conditions that feature vascular abnormalities and melanocytic lesions that can be solely cutaneous or multisystem in nature. Recently published work has demonstrated that both vascular and melanocytic abnormalities in PPV of the cesioflammea and cesiomarmorata subtypes can result from identical somatic mosaic activating mutations in the genes GNAQ and GNA11. Here, we present three new cases of PPV with features of the cesioflammea and/or cesiomarmorata subtypes and mosaic mutations in GNAQ or GNA11. To better understand the risk of potentially occult complications faced by such patients we additionally reviewed 176 cases published in the literature. We report the frequency of clinical findings, their patterns of co-occurrence as well as published recommendations for surveillance after diagnosis. Features assessed include: capillary malformation; dermal and ocular melanocytosis; glaucoma; limb asymmetry; venous malformations; and central nervous system (CNS) anomalies, such as ventriculomegaly and calcifications. We found that ocular findings are common in patients with phacomatosis cesioflammea and cesiomarmorata. Facial vascular involvement correlates with a higher risk of seizures (p = .0066). Our genetic results confirm the role of mosaic somatic mutations in GNAQ and GNA11 in phacomatosis cesioflammea and cesiomarmorata. Their clinical and molecular findings place these conditions on a clinical spectrum encompassing other GNAQ and GNA11 related disorders and inform recommendations for their management.

BPG: Seamless, automated and interactive visualization of scientific data.

BACKGROUND: We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. RESULTS: This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines. CONCLUSION: BPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general.

The effect of digital physical activity interventions on daily step count: a randomised controlled crossover substudy of the MyHeart Counts Cardiovascular Health Study.

BACKGROUND: Smartphone apps might enable interventions to increase physical activity, but few randomised trials testing this hypothesis have been done. The MyHeart Counts Cardiovascular Health Study is a longitudinal smartphone-based study with the aim of elucidating the determinants of cardiovascular health. We aimed to investigate the effect of four different physical activity coaching interventions on daily step count in a substudy of the MyHeart Counts Study. METHODS: In this randomised, controlled crossover trial, we recruited adults (aged ≥18 years) in the USA with access to an iPhone smartphone (Apple, Cupertino, CA, USA; version 5S or newer) who had downloaded the MyHeart Counts app (version 2.0). After completion of a 1 week baseline period of interaction with the MyHeart Counts app, participants were randomly assigned to receive one of 24 permutations (four combinations of four 7 day interventions) in a crossover design using a random number generator built into the app. Interventions consisted of either daily prompts to complete 10 000 steps, hourly prompts to stand following 1 h of sitting, instructions to read the guidelines from the American Heart Association website, or e-coaching based upon the individual's personal activity patterns from the baseline week of data collection. Participants completed the trial in a free-living setting. Due to the nature of the interventions, participants could not be masked from the intervention. Investigators were not masked to intervention allocation. The primary outcome was change in mean daily step count from baseline for each of the four interventions, assessed in the modified intention-to-treat analysis set, which included all participants who had completed 7 days of baseline monitoring and at least 1 day of one of the four interventions. This trial is registered with ClinicalTrials.gov, NCT03090321. FINDINGS: Between Dec 12, 2016, and June 6, 2018, 2783 participants consented to enrol in the coaching study, of whom 1075 completed 7 days of baseline monitoring and at least 1 day of one of the four interventions and thus were included in the modified intention-to-treat analysis set. 493 individuals completed the full set of assigned interventions. All four interventions significantly increased mean daily step count from baseline (mean daily step count 2914 [SE 74]): mean step count increased by 319 steps (75) for participants in the American Heart Association website prompt group (p<0·0001), 267 steps (74) for participants in the hourly stand prompt group (p=0·0003), 254 steps (74) for participants in the cluster-specific prompts group (p=0·0006), and by 226 steps (75) for participants in the 10 000 daily step prompt group (p=0·0026 vs baseline). INTERPRETATION: Four smartphone-based physical activity coaching interventions significantly increased daily physical activity. These findings suggests that digital interventions delivered via a mobile app have the ability to increase short-term physical activity levels in a free-living cohort. FUNDING: Stanford Data Science Initiative.

Biological Insights Into Muscular Strength: Genetic Findings in the UK Biobank.

We performed a large genome-wide association study to discover genetic variation associated with muscular strength, and to evaluate shared genetic aetiology with and causal effects of muscular strength on several health indicators. In our discovery analysis of 223,315 individuals, we identified 101 loci associated with grip strength (P <5 × 10-8). Of these, 64 were associated (P < 0.01 and consistent direction) also in the replication dataset (N = 111,610). eQTL analyses highlighted several genes known to play a role in neuro-developmental disorders or brain function, and the results from meta-analysis showed a significant enrichment of gene expression of brain-related transcripts. Further, we observed inverse genetic correlations of grip strength with cardiometabolic traits, and positive correlation with parents' age of death and education. We also showed that grip strength had shared biological pathways with indicators of frailty, including cognitive performance scores. By use of Mendelian randomization, we provide evidence that higher grip strength is protective of both coronary heart disease (OR = 0.69, 95% CI 0.60-0.79, P < 0.0001) and atrial fibrillation (OR = 0.75, 95% CI 0.62-0.90, P = 0.003). In conclusion, our results show shared genetic aetiology between grip strength, and cardiometabolic and cognitive health; and suggest that maintaining muscular strength could prevent future cardiovascular events.

Biallelic Mutations in ATP5F1D, which Encodes a Subunit of ATP Synthase, Cause a Metabolic Disorder.

ATP synthase, H+ transporting, mitochondrial F1 complex, δ subunit (ATP5F1D; formerly ATP5D) is a subunit of mitochondrial ATP synthase and plays an important role in coupling proton translocation and ATP production. Here, we describe two individuals, each with homozygous missense variants in ATP5F1D, who presented with episodic lethargy, metabolic acidosis, 3-methylglutaconic aciduria, and hyperammonemia. Subject 1, homozygous for c.245C>T (p.Pro82Leu), presented with recurrent metabolic decompensation starting in the neonatal period, and subject 2, homozygous for c.317T>G (p.Val106Gly), presented with acute encephalopathy in childhood. Cultured skin fibroblasts from these individuals exhibited impaired assembly of F1FO ATP synthase and subsequent reduced complex V activity. Cells from subject 1 also exhibited a significant decrease in mitochondrial cristae. Knockdown of Drosophila ATPsynδ, the ATP5F1D homolog, in developing eyes and brains caused a near complete loss of the fly head, a phenotype that was fully rescued by wild-type human ATP5F1D. In contrast, expression of the ATP5F1D c.245C>T and c.317T>G variants rescued the head-size phenotype but recapitulated the eye and antennae defects seen in other genetic models of mitochondrial oxidative phosphorylation deficiency. Our data establish c.245C>T (p.Pro82Leu) and c.317T>G (p.Val106Gly) in ATP5F1D as pathogenic variants leading to a Mendelian mitochondrial disease featuring episodic metabolic decompensation.

Long-read genome sequencing identifies causal structural variation in a Mendelian disease.

PurposeCurrent clinical genomics assays primarily utilize short-read sequencing (SRS), but SRS has limited ability to evaluate repetitive regions and structural variants. Long-read sequencing (LRS) has complementary strengths, and we aimed to determine whether LRS could offer a means to identify overlooked genetic variation in patients undiagnosed by SRS.MethodsWe performed low-coverage genome LRS to identify structural variants in a patient who presented with multiple neoplasia and cardiac myxomata, in whom the results of targeted clinical testing and genome SRS were negative.ResultsThis LRS approach yielded 6,971 deletions and 6,821 insertions > 50 bp. Filtering for variants that are absent in an unrelated control and overlap a disease gene coding exon identified three deletions and three insertions. One of these, a heterozygous 2,184 bp deletion, overlaps the first coding exon of PRKAR1A, which is implicated in autosomal dominant Carney complex. RNA sequencing demonstrated decreased PRKAR1A expression. The deletion was classified as pathogenic based on guidelines for interpretation of sequence variants.ConclusionThis first successful application of genome LRS to identify a pathogenic variant in a patient suggests that LRS has significant potential for the identification of disease-causing structural variation. Larger studies will ultimately be required to evaluate the potential clinical utility of LRS.

Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort.

The ability to measure physical activity through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown. The aim of this work is to assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework. We evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 ± 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination. Devices reported the lowest error for cycling and the highest for walking. Device error was higher for males, greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest. In conclusion, most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).

Exome sequencing identifies de novo pathogenic variants in FBN1 and TRPS1 in a patient with a complex connective tissue phenotype.

Here we describe a patient who presented with a history of congenital diaphragmatic hernia, inguinal hernia, and recurrent umbilical hernia. She also has joint laxity, hypotonia, and dysmorphic features. A unifying diagnosis was not identified based on her clinical phenotype. As part of her evaluation through the Undiagnosed Diseases Network, trio whole-exome sequencing was performed. Pathogenic variants in FBN1 and TRPS1 were identified as causing two distinct autosomal dominant conditions, each with de novo inheritance. Fibrillin 1 (FBN1) mutations are associated with Marfan syndrome and a spectrum of similar phenotypes. TRPS1 mutations are associated with trichorhinophalangeal syndrome types I and III. Features of both conditions are evident in the patient reported here. Discrepant features of the conditions (e.g., stature) and the young age of the patient may have made a clinical diagnosis more difficult in the absence of exome-wide genetic testing.

Erratum to: A bedr way of genomic interval processing.

[This corrects the article DOI: 10.1186/s13029-016-0059-5.].

A bedr way of genomic interval processing.

BACKGROUND: Next-generation sequencing is making it critical to robustly and rapidly handle genomic ranges within standard pipelines. Standard use-cases include annotating sequence ranges with gene or other genomic annotation, merging multiple experiments together and subsequently quantifying and visualizing the overlap. The most widely-used tools for these tasks work at the command-line (e.g. BEDTools) and the small number of available R packages are either slow or have distinct semantics and features from command-line interfaces. RESULTS: To provide a robust R-based interface to standard command-line tools for genomic coordinate manipulation, we created bedr. This open-source R package can use either BEDTools or BEDOPS as a back-end and performs data-manipulation extremely quickly, creating R data structures that can be readily interfaced with existing computational pipelines. It includes data-visualization capabilities and a number of data-access functions that interface with standard databases like UCSC and COSMIC. CONCLUSIONS: bedr package provides an open source solution to enable genomic interval data manipulation and restructuring in R programming language which is commonly used in bioinformatics, and therefore would be useful to bioinformaticians and genomic researchers.

A genome-wide association study of non-HPV-related head and neck squamous cell carcinoma identifies prognostic genetic sequence variants in the MAP-kinase and hormone pathways.

BACKGROUND: Carcinomas of the oral cavity, pharynx and larynx are referred to as head and neck cancers (HNC); together they account for 2-3% of all newly diagnosed cancers in North America. Between 40-50% of HNC are early diagnosed at stages I-II. The 5-year and 10-year relative survival rates are 61% and 50%, respectively. Germline genetic sequence variants (GSV) have become increasingly found to have prognostic implications in a variety of cancers. Identifying these variants may have important clinical and biological implications. METHODS: We conducted a genome-wide association study (GWAS) in 531 Stage I-II radiation-treated HNC patients (originally recruited for α-tocopherol/ß-carotene placebo-controlled secondary prevention study) and used a replication cohort of 566 HNC patients of all stages, of mostly non-HPV-related cancers. Survival rates were estimated by the Kaplan-Meier method. Cox proportional hazards models adjusted for potential clinical factors and principal components were used to test for associations between the GSV and overall survival (OS) in these tumors. RESULTS: The median follow-up time for OS was 9.21 years (GWAS cohort) and 2.37 years (replication cohort). In both cohorts, CACNA2D1:rs2299187, ESRRG:rs946465 and ESRRG:rs1416612 were each individually significantly associated with survival. In silico analysis of ESRRG:rs946465 identifies that it produces a splice variant in ESRRG. Variant alleles of CACNA2D1:rs2299187 and ESRRG:rs946465 were associated with higher expression of the corresponding protein. CONCLUSIONS: Putatively functional polymorphisms in the MAP-Kinase and estrogen pathways, identified through GWAS and replicated in an independent dataset were associated with the survival of HNC patients.

De Novo and Rare Variants at Multiple Loci Support the Oligogenic Origins of Atrioventricular Septal Heart Defects.

Congenital heart disease (CHD) has a complex genetic etiology, and recent studies suggest that high penetrance de novo mutations may account for only a small fraction of disease. In a multi-institutional cohort surveyed by exome sequencing, combining analysis of 987 individuals (discovery cohort of 59 affected trios and 59 control trios, and a replication cohort of 100 affected singletons and 533 unaffected singletons) we observe variation at novel and known loci related to a specific cardiac malformation the atrioventricular septal defect (AVSD). In a primary analysis, by combining developmental coexpression networks with inheritance modeling, we identify a de novo mutation in the DNA binding domain of NR1D2 (p.R175W). We show that p.R175W changes the transcriptional activity of Nr1d2 using an in vitro transactivation model in HUVEC cells. Finally, we demonstrate previously unrecognized cardiovascular malformations in the Nr1d2tm1-Dgen knockout mouse. In secondary analyses we map genetic variation to protein-interaction networks suggesting a role for two collagen genes in AVSD, which we corroborate by burden testing in a second replication cohort of 100 AVSDs and 533 controls (p = 8.37e-08). Finally, we apply a rare-disease inheritance model to identify variation in genes previously associated with CHD (ZFPM2, NSD1, NOTCH1, VCAN, and MYH6), cardiac malformations in mouse models (ADAM17, CHRD, IFT140, PTPRJ, RYR1 and ATE1), and hypomorphic alleles of genes causing syndromic CHD (EHMT1, SRCAP, BBS2, NOTCH2, and KMT2D) in 14 of 59 trios, greatly exceeding variation in control trios without CHD (p = 9.60e-06). In total, 32% of trios carried at least one putatively disease-associated variant across 19 loci,suggesting that inherited and de novo variation across a heterogeneous group of loci may contribute to disease risk.

Medical implications of technical accuracy in genome sequencing.

BACKGROUND: As whole exome sequencing (WES) and whole genome sequencing (WGS) transition from research tools to clinical diagnostic tests, it is increasingly critical for sequencing methods and analysis pipelines to be technically accurate. The Genome in a Bottle Consortium has recently published a set of benchmark SNV, indel, and homozygous reference genotypes for the pilot whole genome NIST Reference Material based on the NA12878 genome. METHODS: We examine the relationship between human genome complexity and genes/variants reported to be associated with human disease. Specifically, we map regions of medical relevance to benchmark regions of high or low confidence. We use benchmark data to assess the sensitivity and positive predictive value of two representative sequencing pipelines for specific classes of variation. RESULTS: We observe that the accuracy of a variant call depends on the genomic region, variant type, and read depth, and varies by analytical pipeline. We find that most false negative WGS calls result from filtering while most false negative WES variants relate to poor coverage. We find that only 74.6% of the exonic bases in ClinVar and OMIM genes and 82.1% of the exonic bases in ACMG-reportable genes are found in high-confidence regions. Only 990 genes in the genome are found entirely within high-confidence regions while 593 of 3,300 ClinVar/OMIM genes have less than 50% of their total exonic base pairs in high-confidence regions. We find greater than 77 % of the pathogenic or likely pathogenic SNVs currently in ClinVar fall within high-confidence regions. We identify sites that are prone to sequencing errors, including thousands present in publicly available variant databases. Finally, we examine the clinical impact of mandatory reporting of secondary findings, highlighting a false positive variant found in BRCA2. CONCLUSIONS: Together, these data illustrate the importance of appropriate use and continued improvement of technical benchmarks to ensure accurate and judicious interpretation of next-generation DNA sequencing results in the clinical setting.

Sports genetics moving forward: lessons learned from medical research.

Sports genetics can take advantage of lessons learned from human disease genetics. By righting past mistakes and increasing scientific rigor, we can magnify the breadth and depth of knowledge in the field. We present an outline of challenges facing sports genetics in the light of experiences from medical research. Sports performance is complex, resulting from a combination of a wide variety of different traits and attributes. Improving sports genetics will foremost require analyses based on detailed phenotyping. To find widely valid, reproducible common variants associated with athletic phenotypes, study sample sizes must be dramatically increased. One paradox is that in order to confirm relevance, replications in specific populations must be undertaken. Family studies of athletes may facilitate the discovery of rare variants with large effects on athletic phenotypes. The complexity of the human genome, combined with the complexity of athletic phenotypes, will require additional metadata and biological validation to identify a comprehensive set of genes involved. Analysis of personal genetic and multiomic profiles contribute to our conceptualization of precision medicine; the same will be the case in precision sports science. In the refinement of sports genetics it is essential to evaluate similarities and differences between sexes and among ethnicities. Sports genetics to date have been hampered by small sample sizes and biased methodology, which can lead to erroneous associations and overestimation of effect sizes. Consequently, currently available genetic tests based on these inherently limited data cannot predict athletic performance with any accuracy.

Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data.

High throughput sequencing has facilitated a precipitous drop in the cost of genomic sequencing, prompting predictions of a revolution in medicine via genetic personalization of diagnostic and therapeutic strategies. There are significant barriers to realizing this goal that are related to the difficult task of interpreting personal genetic variation. A comprehensive, widely accessible application for interpretation of whole genome sequence data is needed. Here, we present a series of methods for identification of genetic variants and genotypes with clinical associations, phasing genetic data and using Mendelian inheritance for quality control, and providing predictive genetic information about risk for rare disease phenotypes and response to pharmacological therapy in single individuals and father-mother-child trios. We demonstrate application of these methods for disease and drug response prognostication in whole genome sequence data from twelve unrelated adults, and for disease gene discovery in one father-mother-child trio with apparently simplex congenital ventricular arrhythmia. In doing so we identify clinically actionable inherited disease risk and drug response genotypes in pre-symptomatic individuals. We also nominate a new candidate gene in congenital arrhythmia, ATP2B4, and provide experimental evidence of a regulatory role for variants discovered using this framework.

Spatial genomic heterogeneity within localized, multifocal prostate cancer.

Herein we provide a detailed molecular analysis of the spatial heterogeneity of clinically localized, multifocal prostate cancer to delineate new oncogenes or tumor suppressors. We initially determined the copy number aberration (CNA) profiles of 74 patients with index tumors of Gleason score 7. Of these, 5 patients were subjected to whole-genome sequencing using DNA quantities achievable in diagnostic biopsies, with detailed spatial sampling of 23 distinct tumor regions to assess intraprostatic heterogeneity in focal genomics. Multifocal tumors are highly heterogeneous for single-nucleotide variants (SNVs), CNAs and genomic rearrangements. We identified and validated a new recurrent amplification of MYCL, which is associated with TP53 deletion and unique profiles of DNA damage and transcriptional dysregulation. Moreover, we demonstrate divergent tumor evolution in multifocal cancer and, in some cases, tumors of independent clonal origin. These data represent the first systematic relation of intraprostatic genomic heterogeneity to predicted clinical outcome and inform the development of novel biomarkers that reflect individual prognosis.

Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection.

The detection of somatic mutations from cancer genome sequences is key to understanding the genetic basis of disease progression, patient survival and response to therapy. Benchmarking is needed for tool assessment and improvement but is complicated by a lack of gold standards, by extensive resource requirements and by difficulties in sharing personal genomic information. To resolve these issues, we launched the ICGC-TCGA DREAM Somatic Mutation Calling Challenge, a crowdsourced benchmark of somatic mutation detection algorithms. Here we report the BAMSurgeon tool for simulating cancer genomes and the results of 248 analyses of three in silico tumors created with it. Different algorithms exhibit characteristic error profiles, and, intriguingly, false positives show a trinucleotide profile very similar to one found in human tumors. Although the three simulated tumors differ in sequence contamination (deviation from normal cell sequence) and in subclonality, an ensemble of pipelines outperforms the best individual pipeline in all cases. BAMSurgeon is available at https://github.com/adamewing/bamsurgeon/.

Developing a prognostic micro-RNA signature for human cervical carcinoma.

Cervical cancer remains the third most frequently diagnosed and fourth leading cause of cancer death in women worldwide. We sought to develop a micro-RNA signature that was prognostic for disease-free survival, which could potentially allow tailoring of treatment for cervical cancer patients. A candidate prognostic 9-micro-RNA signature set was identified in the training set of 79 frozen specimens. However, three different approaches to validate this signature in an independent cohort of 87 patients with formalin-fixed paraffin-embedded (FFPE) specimens, were unsuccessful. There are several challenges and considerations associated with developing a prognostic micro-RNA signature for cervical cancer, namely: tumour heterogeneity, lack of concordance between frozen and FFPE specimens, and platform selection for global micro-RNA expression profiling in this disease. Our observations provide an important cautionary tale for future miRNA signature studies for cervical cancer, which can also be potentially applicable to miRNA profiling studies involving other types of human malignancies.