Detecting copy number status and uncovering subclonal markers in heterogeneous tumor biopsies

HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data

Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.

Integrated exome sequencing and microarray analyses detected genetic defects and underlying pathways of hepatocellular carcinoma

We performed whole exome sequencing (WES) and microarray analysis to detect somatic variants and copy number alterations (CNAs) for underlying mechanisms in a case series of hepatocellular carcinoma (HCC) with paired DNA samples from tumor and adjacent nontumor tissues. Clinicopathologic findings based on Edmondson-Steiner (E-S) grading, Barcelona-Clinic Liver Cancer (BCLC) stages, recurrence, and survival status and their associations with tumor mutation burden (TMB) and CNA burden (CNAB) were evaluated. WES from 36 cases detected variants in the TP53, AXIN1, CTNNB1, and SMARCA4 genes, amplifications of the AKT3, MYC, and TERT genes, and deletions of the CDH1, TP53, IRF2, RB1, RPL5, and PTEN genes. These genetic defects affecting the p53/cell cycle control, PI3K/Ras, and β-catenin pathways were observed in approximately 80% of cases. A germline variant in the ALDH2 gene was detected in 52% of the cases. Significantly higher CNAB in patients with poor prognosis by E-S grade III, BCLC stage C, and recurrence than patients with good prognosis by grade III, stage A, grade III and nonrecurrence was noted. Further analysis on a large case series to correlate genomic profiling with clinicopathologic classifications could provide evidence for diagnostic interpretation, prognostic prediction, and target intervention on involved genes and pathways.

Oncogenic role and drug sensitivity of ETV4 in human tumors: a pan-cancer analysis

Background

Increasing evidence supports a relationship between E twenty-six variant transcription factor 4 (ETV4) and several cancers, but no pan-cancer analysis has been reported.

Methods

The present study surveyed the effects of ETV4 on cancer using RNA sequencing data obtained from The Cancer Genome Atlas and GTEx, and further explored its role in drug sensitivity using data from Cellminer. Differential expression analyses were conducted for multiple cancers using R software. Cox regression and survival analysis were employed to calculate correlations between ETV4 levels and survival outcomes in multiple cancers using the online tool Sangerbox. ETV4 expression was also compared with immunity, heterogeneity, stemness, mismatch repair genes, and DNA methylation among different cancers.

Results

ETV4 was found to be significantly upregulated in 28 tumors. Upregulation of ETV4 was associated with poor overall survival, progression free interval, disease-free-interval, and disease specific survival in several cancer types. Expression of ETV4 was also remarkably correlated with immune cell infiltration, tumor heterogeneity, mismatch repair gene expression, DNA methylation, and tumor stemness. Furthermore, ETV4 expression seemed to affect sensitivity to a number of anticancer drugs.

Conclusions

These results suggest that ETV4 may be useful as a prognostic factor and therapeutic target.

Mitochondrion-Targeted NIR Therapeutic Agent Suppresses Melanoma by Inducing Apoptosis and Cell Cycle Arrest via E2F/Cyclin/CDK Pathway

Malignant melanoma is the most fatal form of skin cancer worldwide, and earlier diagnosis and more effective therapies are required to improve prognosis. As a possible solution, near-infrared fluorescent heptamethine cyanine dyes have been shown to be useful for tumor diagnosis and treatment. Here, we synthesized a novel theranostic agent, IR-817, a multifunctional bioactive small-molecule that has near-infrared emission, targets mitochondria in cancer cells, and has selective anti-cancer effects. In in vitro experiments, IR-817 preferentially accumulated in melanoma cells through organic anion transporting polypeptide transporters but also selectively inhibited the growth of tumor cells by inducing mitochondrial-dependent intrinsic apoptosis. Mechanistically, IR-817 caused G0/G1 cell cycle arrest by targeting the E2F/Cyclin/CDK pathway. Finally, IR-817 significantly suppressed the growth of xenograft tumors in zebrafish and mice. Immunohistochemical staining and hematoxylin and eosin staining revealed that IR-817 induced apoptosis and inhibited tumor cell proliferation without notable side effects. Therefore, mitochondrial-targeting theranostic agent IR-817 may be promising for accurate tumor diagnosis, real-time monitoring, and safe anti-cancer treatments.

MicroRNA-1-3p affects lung adenocarcinoma progression through E2F8 and regulating NF-кB pathway

E2F8 can modulate development and progression of various cancers including cervical cancer, breast cancer and hepatocellular carcinoma. But its mechanism in lung adenocarcinoma (LUAD) remains underexplored. In this study, we conducted a series of experiments including qRT-PCR, western blot, CCK-8, scratch healing assay, Transwell, and flow cytometry. Through these assays, we confirmed the notable overexpression of E2F8 in LUAD and its promoting effects on LUAD cell proliferation, migration and invasion. Subsequently, microRNA-1-3p that was negatively associated with E2F8 expression was identified through bioinformatics analysis. qRT-PCR was then carried out for quantification of microRNA-1-3p expression, which displayed low microRNA-1-3p expression in LUAD cells. In addition, dual-luciferase reporter gene assay was utilized for validating the targeted relationship between microRNA-1-3p and E2F8. The results denoted that microRNA-1-3p could bind to the promoter region of E2F8. Finally, the results of rescue experiment revealed that microRNA-1-3p negatively modulated E2F8 level. It regulated NF-κB pathway to repress LUAD cell proliferative, migratory, and invasive properties, lead to cell cycle arrest in G0/G1 phase, and enhance cell apoptosis level. This study unraveled that microRNA-1-3p/E2F8 constrained LUAD malignant progression through NF-κB pathway, which may provide possible targets for LUAD diagnosis and treatment.

Correlating genomic copy number alterations with clinicopathologic findings in 75 cases of hepatocellular carcinoma

BACKGROUND

Oligonucleotide array comparative genomic hybridization (aCGH) analysis has been used for detecting somatic copy number alterations (CNAs) in various types of tumors. This study aimed to assess the clinical utility of aCGH for cases of hepatocellular carcinoma (HCC) and to evaluate the correlation between CNAs and clinicopathologic findings.

METHODS

aCGH was performed on 75 HCC cases with paired DNA samples from tumor and adjacent nontumor tissues. Survival outcomes from these cases were analyzed based on Barcelona-Clinic Liver Cancer Stage (BCLC), Edmondson-Steiner grade (E-S), and recurrence status. Correlation of CNAs with clinicopathologic findings was analyzed by Wilcoxon rank test and clustering vs. K means.

RESULTS

The survival outcomes indicated that BCLC stages and recurrence status could be predictors and E-S grades could be a modifier for HCC. The most common CNAs involved gains of 1q and 8q and a loss of 16q (50%), losses of 4q and 17p and a gain of 5p (40%), and losses of 8p and 13q (30%). Analyses of genomic profiles and clusters identified that losses of 4q13.2q35.2 and 10q22.3q26.13 seen in cases of stage A, grade III and nonrecurrence were likely correlated with good survival, while loss of 1p36.31p22.1 and gains of 2q11.2q21.2 and 20p13p11.1 seen in cases of stage C, grade III and recurrence were possibly correlated with worst prognosis.

CONCLUSIONS

These results indicated that aCGH analysis could be used to detect recurrent CNAs and involved key genes and pathways in patients with HCC. Further analysis on a large case series to validate the correlation of CNAs with clinicopathologic findings of HCC could provide information to interpret CNAs and predict prognosis.

Cytogenomic Abnormalities in 19 Cases of Salivary Gland Tumors of Parotid Gland Origin

Salivary gland tumors (SGTs) of parotid origin are a group of diverse neoplasms which are difficult to classify due to their rarity and similar morphologic patterns. Chromosome analysis can detect clonal abnormalities, and array comparative genomic hybridization (aCGH) analysis can define copy number alterations (CNAs) from tumor specimens. Of the 19 cases of various types of SGTs submitted for cytogenomic analyses, an abnormal clone was detected in nine cases (47%), and CNAs were detected in 14 cases (74%). Recurrent rearrangements involving the PLAG1 gene at 8q12, recurrent CNAs including deletions of 6q, 9p (CDKN2A), and 17p (TP53), loss of Y chromosome, and gain of chromosome 7 were defined from these cases. Combined karyotyping and aCGH analyses could improve diagnostic yield. Future study for more precisive correlation of SGT classification with cytogenomic abnormalities will facilitate better diagnosis and treatment.

The Oncogenic Potential of the Centromeric Border Protein FAM84B of the 8q24.21 Gene Desert

FAM84B is a risk gene in breast and prostate cancers. Its upregulation is associated with poor prognosis of prostate cancer, breast cancer, and esophageal squamous cell carcinoma. FAM84B facilitates cancer cell proliferation and invasion in vitro, and xenograft growth in vivo. The FAM84B and Myc genes border a 1.2 Mb gene desert at 8q24.21. Co-amplification of both occurs in 20 cancer types. Mice deficient of a 430 Kb fragment within the 1.2 Mb gene desert have downregulated FAM84B and Myc expressions concurrent with reduced breast cancer growth. Intriguingly, Myc works in partnership with other oncogenes, including Ras. FAM84B shares similarities with the H-Ras-like suppressor (HRASLS) family over their typical LRAT (lecithin:retinal acyltransferase) domain. This domain contains a catalytic triad, H23, H35, and C113, which constitutes the phospholipase A_1/2 and O-acyltransferase activities of HRASLS1-5. These enzymatic activities underlie their suppression of Ras. FAM84B conserves H23 and H35 but not C113 with both histidine residues residing within a highly conserved motif that FAM84B shares with HRASLS1-5. Deletion of this motif abolishes FAM84B oncogenic activities. These properties suggest a collaboration of FAM84B with Myc, consistent with the role of the gene desert in strengthening Myc functions. Here, we will discuss recent research on FAM84B-derived oncogenic potential.

E2F8 regulates the proliferation and invasion through epithelial-mesenchymal transition in cervical cancer

The transcription factor E2F is an important modulator of the cell cycle, and the unrestricted activation of E2F-dependent transcription is considered to be an important driver of tumor formation and progression. E2F8 is known to play an important role in embryonic development and cell cycle control by inhibiting E2F1. However, it is not yet known whether E2F8 is involved in the progression of cervical cancer. In this study, the functional consequences of E2F8 knockdown in vitro and in vivo were explored. To demonstrate the function of E2F8 in cell proliferation, migration and invasion, we knocked down E2F8 in cervical cancer cell lines; in vitro and in vivo experiments using this knockdown showed that E2F8 potently induced the expression of epithelial-mesenchymal transition (EMT) markers. Finally, clinical data confirmed that E2F8 was a significant predictive factor for progression-free survival, and that patients with cervical cancer who exhibited high expression of E2F8 showed high FIGO stages and frequent recurrence rates compared to patients with low E2F8 expression. In conclusion, our study suggests that E2F8 is highly correlated with the progression-free survival of cervical cancer patients.

Upregulation of E2F8 promotes cell proliferation and tumorigenicity in breast cancer by modulating G1/S phase transition

E2F transcription factors are involved in cell cycle regulation and synthesis of DNA in mammalian cells, and simultaneously play important roles in the development and progression of cancer when dysregulated. E2F8, a novel identified E2F family member, was found to be associated with the progression of several human cancers; however, the biological role and clinical significance of E2F8 in breast cancer remain to be further elucidated. Herein, we report that E2F8 is robustly elevated in breast cancer cell lines and clinical breast cancer tissue samples, respectively. The high expression level of E2F8 significantly correlates with clinical progression (P = 0.001), poor patient survival (P < 0.001) and a high Ki67 staining index (P = 0.008) in 187 human breast cancer specimens. Furthermore, we find that overexpressing E2F8 promotes, whereas silencing E2F8 suppresses, the proliferation and tumorigenicity of breast cancer cells both in vitro and in vivo. We further demonstrate that E2F8 transcriptionally upregulates CCNE1 and CCNE2 via directly interacting with their respective gene promoter, which accelerates the transition of G1 to S phase of breast cancer cells. Taken together, these findings uncover a novel biologic role and regulatory mechanism of E2F8 responsible for the progression of breast cancer, indicating E2F8 may represent a novel prognostic biomarker and therapeutic target against breast cancer.

Fluorescence In situ Hybridization: Cell-Based Genetic Diagnostic and Research Applications

Fluorescence in situ hybridization (FISH) is a macromolecule recognition technology based on the complementary nature of DNA or DNA/RNA double strands. Selected DNA strands incorporated with fluorophore-coupled nucleotides can be used as probes to hybridize onto the complementary sequences in tested cells and tissues and then visualized through a fluorescence microscope or an imaging system. This technology was initially developed as a physical mapping tool to delineate genes within chromosomes. Its high analytical resolution to a single gene level and high sensitivity and specificity enabled an immediate application for genetic diagnosis of constitutional common aneuploidies, microdeletion/microduplication syndromes, and subtelomeric rearrangements. FISH tests using panels of gene-specific probes for somatic recurrent losses, gains, and translocations have been routinely applied for hematologic and solid tumors and are one of the fastest-growing areas in cancer diagnosis. FISH has also been used to detect infectious microbias and parasites like malaria in human blood cells. Recent advances in FISH technology involve various methods for improving probe labeling efficiency and the use of super resolution imaging systems for direct visualization of intra-nuclear chromosomal organization and profiling of RNA transcription in single cells. Cas9-mediated FISH (CASFISH) allowed in situ labeling of repetitive sequences and single-copy sequences without the disruption of nuclear genomic organization in fixed or living cells. Using oligopaint-FISH and super-resolution imaging enabled in situ visualization of chromosome haplotypes from differentially specified single-nucleotide polymorphism loci. Single molecule RNA FISH (smRNA-FISH) using combinatorial labeling or sequential barcoding by multiple round of hybridization were applied to measure mRNA expression of multiple genes within single cells. Research applications of these single molecule single cells DNA and RNA FISH techniques have visualized intra-nuclear genomic structure and sub-cellular transcriptional dynamics of many genes and revealed their functions in various biological processes.

E2F8 as a Novel Therapeutic Target for Lung Cancer

BACKGROUND

The E2F members have been divided into transcription activators (E2F1-E2F3) and repressors (E2F4-E2F8). E2F8 with E2F7 has been known to play an important physiologic role in embryonic development and cell cycle regulation by repressing E2F1. However, the function of E2F8 in cancer cells is unknown.

METHODS

E2F8 expression was assessed by immunoblotting or immunofluorescence staining in human lung cancer (LC) cells and tissues from LC patients (n = 45). Cell proliferation, colony formation, and invasion analysis were performed to evaluate the role of E2F8 in LC. Microarray analysis was used to determine the target genes of E2F8. The regulation of E2F8 on the expression of ubiquitin-like PHD and RING domain-containing 1 (UHRF1), one of E2F8 target genes, was determined using chromatin immunoprecipitation and promoter activity assays. Human LC xenograft models were used to determine the effects of inhibiting E2F8 by siRNAs (n = 7 per group) or antisense morpholino (n = 8 per group) on tumor growth. Survival was analyzed using the Kaplan-Meier method and group differences by the Student's t test. All statistical tests were two-sided.

RESULTS

LC tumors overexpressed E2F8 compared with normal lung tissues. Depletion of E2F8 inhibited cell proliferation and tumor growth. E2F8 knockdown statistically significantly reduced the expression of UHRF1 (~60%-70%, P < .001), and the direct binding of E2F8 on the promoter of UHRF1 was identified. Kaplan-Meier analysis with a public database showed prognostic significance of aberrant E2F8 expression in LC (HR = 1.91 95% CI = 1.21 to 3.01 in chemo-naïve patients, P = .0047).

CONCLUSIONS

We demonstrated that E2F8 is overexpressed in LC and is required for the growth of LC cells. These findings implicate E2F8 as a novel therapeutic target for LC treatment.

A droplet digital PCR detection method for rare L1 insertions in tumors

Background

The active human mobile element, long interspersed element 1 (L1) currently populates human genomes in excess of 500,000 copies per haploid genome. Through its mobility via a process called target primed reverse transcription (TPRT), L1 mobilization has resulted in over 100 de novo cases of human disease and has recently been associated with various cancer types. Large advances in high-throughput sequencing (HTS) technology have allowed for an increased understanding of the role of L1 in human cancer; however, researchers are still limited by the ability to validate potentially rare L1 insertion events detected by HTS that may occur in only a small fraction of tumor cells. Additionally, HTS detection of rare events varies greatly as a function of read depth, and new tools for de novo element discovery are needed to fill in gaps created by HTS.

Results

We have employed droplet digital PCR (ddPCR) to detect rare L1 loci in mosaic human genomes. Our assay allows for the detection of L1 insertions as rare as one cell in every 10,000.

Conclusions

ddPCR represents a robust method to be used alongside HTS techniques for detecting, validating and quantitating rare L1 insertion events in tumors and other tissues.

Electronic supplementary material

The online version of this article (doi:10.1186/s13100-014-0030-4) contains supplementary material, which is available to authorized users.

8q24 amplified segments involve novel fusion genes between NSMCE2 and long noncoding RNAs in acute myelogenous leukemia

The pathogenetic roles of 8q24 amplified segments in leukemic cells with double minute chromosomes remain to be verified. Through comprehensive molecular analyses of 8q24 amplicons in leukemic cells from an acute myelogenous leukemia (AML) patient and AML-derived cell line HL60 cells, we identified two novel fusion genes between NSMCE2 and long noncoding RNAs (lncRNAs), namely, PVT1-NSMCE2 and BF104016-NSMCE2. Our study suggests that 8q24 amplicons are associated with the emergence of aberrant chimeric genes between NSMCE2 and oncogenic lncRNAs, and also implicate that the chimeric genes involving lncRNAs potentially possess as-yet-unknown oncogenic functional roles.

Application of SNP microarrays to the genome-wide analysis of chromosomal instability in premalignant airway lesions

Chromosomal instability is central to the process of carcinogenesis. The genome-wide detection of somatic chromosomal alterations (SCA) in small premalignant lesions remains challenging because sample heterogeneity dilutes the aberrant cell information. To overcome this hurdle, we focused on the B allele frequency data from single-nucleotide polymorphism microarrays (SNP arrays). The difference of allelic fractions between paired tumor and normal samples from the same patient (delta-θ) provides a simple but sensitive detection of SCA in the affected tissue. We applied the delta-θ approach to small, heterogeneous clinical specimens, including endobronchial biopsies and brushings. Regions identified by delta-θ were validated by FISH and quantitative PCR in heterogeneous samples. Distinctive genomic variations were successfully detected across the whole genome in all invasive cancer cases (6 of 6), carcinoma in situ (3 of 3), and high-grade dysplasia (severe or moderate; 3 of 11). Not only well-described SCAs in lung squamous cell carcinoma, but also several novel chromosomal alterations were frequently found across the preinvasive dysplastic cases. Within these novel regions, losses of putative tumor suppressors (RNF20 and SSBP2) and an amplification of RASGRP3 gene with oncogenic activity were observed. Widespread sampling of the airway during bronchoscopy demonstrated that field cancerization reflected by SCAs at multiple sites was detectable. SNP arrays combined with delta-θ analysis can detect SCAs in heterogeneous clinical sample and expand our ability to assess genomic instability in the airway epithelium as a biomarker of lung cancer risk.

THetA: inferring intra-tumor heterogeneity from high-throughput DNA sequencing data

Tumor samples are typically heterogeneous, containing admixture by normal, non-cancerous cells and one or more subpopulations of cancerous cells. Whole-genome sequencing of a tumor sample yields reads from this mixture, but does not directly reveal the cell of origin for each read. We introduce THetA (Tumor Heterogeneity Analysis), an algorithm that infers the most likely collection of genomes and their proportions in a sample, for the case where copy number aberrations distinguish subpopulations. THetA successfully estimates normal admixture and recovers clonal and subclonal copy number aberrations in real and simulated sequencing data. THetA is available at http://compbio.cs.brown.edu/software/.

TrAp: a tree approach for fingerprinting subclonal tumor composition

Revealing the clonal composition of a single tumor is essential for identifying cell subpopulations with metastatic potential in primary tumors or with resistance to therapies in metastatic tumors. Sequencing technologies provide only an overview of the aggregate of numerous cells. Computational approaches to de-mix a collective signal composed of the aberrations of a mixed cell population of a tumor sample into its individual components are not available. We propose an evolutionary framework for deconvolving data from a single genome-wide experiment to infer the composition, abundance and evolutionary paths of the underlying cell subpopulations of a tumor. We have developed an algorithm (TrAp) for solving this mixture problem. In silico analyses show that TrAp correctly deconvolves mixed subpopulations when the number of subpopulations and the measurement errors are moderate. We demonstrate the applicability of the method using tumor karyotypes and somatic hypermutation data sets. We applied TrAp to Exome-Seq experiment of a renal cell carcinoma tumor sample and compared the mutational profile of the inferred subpopulations to the mutational profiles of single cells of the same tumor. Finally, we deconvolve sequencing data from eight acute myeloid leukemia patients and three distinct metastases of one melanoma patient to exhibit the evolutionary relationships of their subpopulations.

Bivariate segmentation of SNP-array data for allele-specific copy number analysis in tumour samples

Background

SNP arrays output two signals that reflect the total genomic copy number (LRR) and the allelic ratio (BAF), which in combination allow the characterisation of allele-specific copy numbers (ASCNs). While methods based on hidden Markov models (HMMs) have been extended from array comparative genomic hybridisation (aCGH) to jointly handle the two signals, only one method based on change-point detection, ASCAT, performs bivariate segmentation.

Results

In the present work, we introduce a generic framework for bivariate segmentation of SNP array data for ASCN analysis. For the matter, we discuss the characteristics of the typically applied BAF transformation and how they affect segmentation, introduce concepts of multivariate time series analysis that are of concern in this field and discuss the appropriate formulation of the problem. The framework is implemented in a method named CnaStruct, the bivariate form of the structural change model (SCM), which has been successfully applied to transcriptome mapping and aCGH.

Conclusions

On a comprehensive synthetic dataset, we show that CnaStruct outperforms the segmentation of existing ASCN analysis methods. Furthermore, CnaStruct can be integrated into the workflows of several ASCN analysis tools in order to improve their performance, specially on tumour samples highly contaminated by normal cells.

Integrated analysis of tumor samples sheds light on tumor heterogeneity

The heterogeneity of tumor samples is a major challenge in the analysis of high-throughput profiling of tumor biopsies and cell lines. The measured aggregate signals of multigenerational progenies often represent an average of several tumor subclones with varying genomic aberrations and different gene expression levels. The goal of the present study was to integrate copy number analyses from SNP-arrays and karyotyping, gene expression profiling, and pathway analyses to detect heterogeneity, identify driver mutations, and explore possible mechanisms of tumor evolution. We showed the heterogeneity of the studied samples, characterized the global copy number alteration profiles, and identified genes whose copy number status and expression levels were aberrant. In particular, we identified a recurrent association between two BRAF(V600E) and BRAF(V600K) mutations and changes in DKK1 gene expression levels, which might indicate an association between the BRAF and WNT pathways. These findings show that the integrated approaches used in the present study can robustly address the challenging issue of tumor heterogeneity in high-throughput profiling.

Comparison of methods to detect copy number alterations in cancer using simulated and real genotyping data

Background

The detection of genomic copy number alterations (CNA) in cancer based on SNP arrays requires methods that take into account tumour specific factors such as normal cell contamination and tumour heterogeneity. A number of tools have been recently developed but their performance needs yet to be thoroughly assessed. To this aim, a comprehensive model that integrates the factors of normal cell contamination and intra-tumour heterogeneity and that can be translated to synthetic data on which to perform benchmarks is indispensable.

Results

We propose such model and implement it in an R package called CnaGen to synthetically generate a wide range of alterations under different normal cell contamination levels. Six recently published methods for CNA and loss of heterozygosity (LOH) detection on tumour samples were assessed on this synthetic data and on a dilution series of a breast cancer cell-line: ASCAT, GAP, GenoCNA, GPHMM, MixHMM and OncoSNP. We report the recall rates in terms of normal cell contamination levels and alteration characteristics: length, copy number and LOH state, as well as the false discovery rate distribution for each copy number under different normal cell contamination levels.

Assessed methods are in general better at detecting alterations with low copy number and under a little normal cell contamination levels. All methods except GPHMM, which failed to recognize the alteration pattern in the cell-line samples, provided similar results for the synthetic and cell-line sample sets. MixHMM and GenoCNA are the poorliest performing methods, while GAP generally performed better. This supports the viability of approaches other than the common hidden Markov model (HMM)-based.

Conclusions

We devised and implemented a comprehensive model to generate data that simulate tumoural samples genotyped using SNP arrays. The validity of the model is supported by the similarity of the results obtained with synthetic and real data. Based on these results and on the software implementation of the methods, we recommend GAP for advanced users and GPHMM for a fully driven analysis.

RNA-Seq and human complex diseases: recent accomplishments and future perspectives

The availability of the human genome sequence has allowed identification of disease-causing mutations in many Mendelian disorders, and detection of significant associations of nucleotide polymorphisms to complex diseases and traits. Despite these progresses, finding the causative variations for most of the common diseases remains a complex task. Several studies have shown gene expression analyses provide a quite unbiased way to investigate complex traits and common disorders' pathogenesis. Therefore, whole-transcriptome analysis is increasingly acquiring a key role in the knowledge of mechanisms responsible for complex diseases. Hybridization- and tag-based technologies have elucidated the involvement of multiple genes and pathways in pathological conditions, providing insights into the expression of thousand of coding and noncoding RNAs, such as microRNAs. However, the introduction of Next-Generation Sequencing, particularly of RNA-Seq, has overcome some drawbacks of previously used technologies. Identifying, in a single experiment, potentially novel genes/exons and splice isoforms, RNA editing, fusion transcripts and allele-specific expression are some of its advantages. RNA-Seq has been fruitfully applied to study cancer and host-pathogens interactions, and it is taking first steps for studying neurodegenerative diseases (ND) as well as neuropsychiatric diseases. In addition, it is emerging as a very powerful tool to study quantitative trait loci associated with gene expression in complex diseases. This paper provides an overview on gene expression profiling of complex diseases, with emphasis on RNA-Seq, its advantages over conventional technologies for studying cancer and ND, and for linking nucleotide variations to gene expression changes, also discussing its limitations.

High throughput investigative Dermatology in 2012 and beyond: A new era beckons

High throughput molecular biology began around the mid-1990s with the introduction of microarrays - a technology that enabled investigators to quantify the cellular expression levels of tens of thousands of mRNA transcripts simultaneously. To date, a large number of microarray experiments have been performed in the investigation of RNA expression signatures in normal and pathological tissues. This review focuses on a next generation tool in high throughput investigation: RNA sequencing or RNA-Seq, highlighting its advantages over traditional microarray investigation and discussing its utility in investigative dermatology. In contrast with the results obtained from microarray experiments, RNA-Seq generates mRNA abundance counts, can identify novel transcripts and splice variants, and provides sequence resolution at the level of single base-pairs. Implementing RNA-Seq in the investigation of skin disease will yield novel insights into the pathogenesis of disease, will facilitate the discovery of new diseases and new mechanisms of disease, and will allow researchers to probe genetic disease in high resolution and with unprecedented efficiency.