RNA-Seq mapping and detection of gene fusions with a suffix array algorithm.

High-throughput RNA sequencing enables quantification of transcripts (both known and novel), exon/exon junctions and fusions of exons from different genes. Discovery of gene fusions-particularly those expressed with low abundance- is a challenge with short- and medium-length sequencing reads. To address this challenge, we implemented an RNA-Seq mapping pipeline within the LifeScope software. We introduced new features including filter and junction mapping, annotation-aided pairing rescue and accurate mapping quality values. We combined this pipeline with a Suffix Array Spliced Read (SASR) aligner to detect chimeric transcripts. Performing paired-end RNA-Seq of the breast cancer cell line MCF-7 using the SOLiD system, we called 40 gene fusions among over 120,000 splicing junctions. We validated 36 of these 40 fusions with TaqMan assays, of which 25 were expressed in MCF-7 but not the Human Brain Reference. An intra-chromosomal gene fusion involving the estrogen receptor alpha gene ESR1, and another involving the RPS6KB1 (Ribosomal protein S6 kinase beta-1) were recurrently expressed in a number of breast tumor cell lines and a clinical tumor sample.

mRNA-Seq whole-transcriptome analysis of a single cell.

Next-generation sequencing technology is a powerful tool for transcriptome analysis. However, under certain conditions, only a small amount of material is available, which requires more sensitive techniques that can preferably be used at the single-cell level. Here we describe a single-cell digital gene expression profiling assay. Using our mRNA-Seq assay with only a single mouse blastomere, we detected the expression of 75% (5,270) more genes than microarray techniques and identified 1,753 previously unknown splice junctions called by at least 5 reads. Moreover, 8-19% of the genes with multiple known transcript isoforms expressed at least two isoforms in the same blastomere or oocyte, which unambiguously demonstrated the complexity of the transcript variants at whole-genome scale in individual cells. Finally, for Dicer1(-/-) and Ago2(-/-) (Eif2c2(-/-)) oocytes, we found that 1,696 and 1,553 genes, respectively, were abnormally upregulated compared to wild-type controls, with 619 genes in common.

Oncogene Overlap Analysis of Circulating Cell-free Tumor DNA to Explore the Appropriate Criteria for Defining MET Copy Number-Driven Lung Cancer.

INTRODUCTION: Defining clinically relevant MET amplification levels in non-small cell lung cancer (NSCLC) remains challenging. We hypothesize that oncogene overlap and MET amplicon size decline with increase in MET plasma copy number (pCN), thus enriching for MET-dependent states. PATIENTS AND METHODS: We interrogated cell-free DNA NGS results of 16,782 patients with newly diagnosed advanced NSCLC to identify those with MET amplification as reported using Guardant360. Co-occurring genomic mutations and copy number alterations within each sample were evaluated. An exploratory method of adjusting for tumor fraction was also performed and amplicon size for MET was analyzed when available. RESULTS: MET amplification was detected in 207 (1.2%) of samples. pCN ranged from 2.1 to 52.9. Of these, 43 (20.8%) had an overlapping oncogenic driver, including 23 (11.1%) METex14 skipping or other MET mutations. The degree of (non-MET) oncogene overlap decreased with increases in pCN. Patients with MET pCN ≥ 2.7 had lower rates of overlapping drivers compared to those with MET pCN < 2.7 (6.1% vs. 16.3%, P = .033). None of the 7 patients with pCN > 6.7 had an overlapping driver. After adjusting for tumor fraction, adjusted pCN (ApCN) was also lower for those with overlapping drivers than those without (median ApCN 4.9 vs. 7.3, P =.024). There was an inverse relationship between amplicon size and pCN. CONCLUSIONS: We propose that a high MET pCN and/or ApCN, together with the absence of overlapping oncogenic drivers and small MET amplicon size, will enrich for patients most likely to derive benefit from MET targeted therapy.

Small RNA profiling of Dengue virus-mosquito interactions implicates the PIWI RNA pathway in anti-viral defense.

BACKGROUND: Small RNA (sRNA) regulatory pathways (SRRPs) are important to anti-viral defence in mosquitoes. To identify critical features of the virus infection process in Dengue serotype 2 (DENV2)-infected Ae. aegypti, we deep-sequenced small non-coding RNAs. Triplicate biological replicates were used so that rigorous statistical metrics could be applied. RESULTS: In addition to virus-derived siRNAs (20-23 nts) previously reported for other arbovirus-infected mosquitoes, we show that PIWI pathway sRNAs (piRNAs) (24-30 nts) and unusually small RNAs (usRNAs) (13-19 nts) are produced in DENV-infected mosquitoes. We demonstrate that a major catalytic enzyme of the siRNA pathway, Argonaute 2 (Ago2), co-migrates with a ~1 megadalton complex in adults prior to bloodfeeding. sRNAs were cloned and sequenced from Ago2 immunoprecipitations. Viral sRNA patterns change over the course of infection. Host sRNAs were mapped to the published aedine transcriptome and subjected to analysis using edgeR (Bioconductor). We found that sRNA profiles are altered early in DENV2 infection, and mRNA targets from mitochondrial, transcription/translation, and transport functional categories are affected. Moreover, small non-coding RNAs (ncRNAs), such as tRNAs, spliceosomal U RNAs, and snoRNAs are highly enriched in DENV-infected samples at 2 and 4 dpi. CONCLUSIONS: These data implicate the PIWI pathway in anti-viral defense. Changes to host sRNA profiles indicate that specific cellular processes are affected during DENV infection, such as mitochondrial function and ncRNA levels. Together, these data provide important progress in understanding the DENV2 infection process in Ae. aegypti.

Evaluation of DNA microarray results with quantitative gene expression platforms.

We have evaluated the performance characteristics of three quantitative gene expression technologies and correlated their expression measurements to those of five commercial microarray platforms, based on the MicroArray Quality Control (MAQC) data set. The limit of detection, assay range, precision, accuracy and fold-change correlations were assessed for 997 TaqMan Gene Expression Assays, 205 Standardized RT (Sta)RT-PCR assays and 244 QuantiGene assays. TaqMan is a registered trademark of Roche Molecular Systems, Inc. We observed high correlation between quantitative gene expression values and microarray platform results and found few discordant measurements among all platforms. The main cause of variability was differences in probe sequence and thus target location. A second source of variability was the limited and variable sensitivity of the different microarray platforms for detecting weakly expressed genes, which affected interplatform and intersite reproducibility of differentially expressed genes. From this analysis, we conclude that the MAQC microarray data set has been validated by alternative quantitative gene expression platforms thus supporting the use of microarray platforms for the quantitative characterization of gene expression.

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

Validation of Microsatellite Instability Detection Using a Comprehensive Plasma-Based Genotyping Panel.

PURPOSE: To analytically and clinically validate microsatellite instability (MSI) detection using cell-free DNA (cfDNA) sequencing. EXPERIMENTAL DESIGN: Pan-cancer MSI detection using Guardant360 was analytically validated according to established guidelines and clinically validated using 1,145 cfDNA samples for which tissue MSI status based on standard-of-care tissue testing was available. The landscape of cfDNA-based MSI across solid tumor types was investigated in a cohort of 28,459 clinical plasma samples. Clinical outcomes for 16 patients with cfDNA MSI-H gastric cancer treated with immunotherapy were evaluated. RESULTS: cfDNA MSI evaluation was shown to have high specificity, precision, and sensitivity, with a limit of detection of 0.1% tumor content. In evaluable patients, cfDNA testing accurately detected 87% (71/82) of tissue MSI-H and 99.5% of tissue microsatellite stable (863/867) for an overall accuracy of 98.4% (934/949) and a positive predictive value of 95% (71/75). Concordance of cfDNA MSI with tissue PCR and next-generation sequencing was significantly higher than IHC. Prevalence of cfDNA MSI for major cancer types was consistent with those reported for tissue. Finally, robust clinical activity of immunotherapy treatment was seen in patients with advanced gastric cancer positive for MSI by cfDNA, with 63% (10/16) of patients achieving complete or partial remission with sustained clinical benefit. CONCLUSIONS: cfDNA-based MSI detection using Guardant360 is highly concordant with tissue-based testing, enabling highly accurate detection of MSI status concurrent with comprehensive genomic profiling and expanding access to immunotherapy for patients with advanced cancer for whom current testing practices are inadequate.See related commentary by Wang and Ajani, p. 6887.

The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies.

BACKGROUND: Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists. RESULTS: Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan - the widely regarded "standard" gene expression platform. Our results demonstrate that (1) previously reported discordance between DEG lists could simply result from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion with a non-stringent P-value cutoff filtering, the DEG lists become much more reproducible, especially when fewer genes are selected as differentially expressed, as is the case in most microarray studies; and (3) the instability of short DEG lists solely based on P-value ranking is an expected mathematical consequence of the high variability of the t-values; the more stringent the P-value threshold, the less reproducible the DEG list is. These observations are also consistent with results from extensive simulation calculations. CONCLUSION: We recommend the use of FC-ranking plus a non-stringent P cutoff as a straightforward and baseline practice in order to generate more reproducible DEG lists. Specifically, the P-value cutoff should not be stringent (too small) and FC should be as large as possible. Our results provide practical guidance to choose the appropriate FC and P-value cutoffs when selecting a given number of DEGs. The FC criterion enhances reproducibility, whereas the P criterion balances sensitivity and specificity.

Cystine-glutamate transporter SLC7A11 in cancer chemosensitivity and chemoresistance.

SLC7A11 (xCT), together with SLC3A2 (4F2hc), encodes the heterodimeric amino acid transport system x(c)-, which mediates cystine-glutamate exchange and thereby regulates intracellular glutathione levels. We used microarrays to analyze gene expression of transporters in 60 human cancer cell lines used by the National Cancer Institute for drug screening (NCI-60). The expression of SLC7A11 showed significant correlation with that of SLC3A2 (r = 0.66), which in turn correlated with SLC7A5 (r = 0.68), another known partner for SLC3A2, and with T1A-2 (r = 0.60; all P < 0.0001). Linking expression of SLC7A11 with potency of 1,400 candidate anticancer drugs identified 39 showing positive correlations, e.g., amino acid analogue, L-alanosine, and 296 with negative correlations, e.g., geldanamycin. However, no significant correlation was observed with the geldanamycin analogue 17-allylamino, 17-demethoxygeldanamycin (17-AAG). Inhibition of transport system x(c)- with glutamate or (S)-4-carboxyphenylglycine in lung A549 and HOP-62, and ovarian SK-OV-3 cells, reduced the potency of L-alanosine and lowered intracellular glutathione levels. This further resulted in increased potency of geldanamycin, with no effect on 17-AAG. Down-regulation of SLC7A11 by small interfering RNA affected drug potencies similarly to transport inhibitors. The inhibitor of gamma-glutamylcysteine synthetase, buthionine sulfoximine, also decreased intracellular glutathione levels and enhanced potency of geldanamycin, but did not affect L-alanosine. These results indicate that SLC7A11 mediates cellular uptake of L-alanosine but confers resistance to geldanamycin by supplying cystine for glutathione maintenance. SLC7A11 expression could serve as a predictor of cellular response to L-alanosine and glutathione-mediated resistance to geldanamycin, yielding a potential target for increasing chemosensitivity to multiple drugs.

Rare autosomal trisomies, revealed by maternal plasma DNA sequencing, suggest increased risk of feto-placental disease.

Whole-genome sequencing (WGS) of maternal plasma cell-free DNA (cfDNA) can potentially evaluate all 24 chromosomes to identify abnormalities of the placenta, fetus, or pregnant woman. Current bioinformatics algorithms typically only report on chromosomes 21, 18, 13, X, and Y; sequencing results from other chromosomes may be masked. We hypothesized that by systematically analyzing WGS data from all chromosomes, we could identify rare autosomal trisomies (RATs) to improve understanding of feto-placental biology. We analyzed two independent cohorts from clinical laboratories, both of which used a similar quality control parameter, normalized chromosome denominator quality. The entire data set included 89,817 samples. Samples flagged for analysis and classified as abnormal were 328 of 72,932 (0.45%) and 71 of 16,885 (0.42%) in cohorts 1 and 2, respectively. Clinical outcome data were available for 57 of 71 (80%) of abnormal cases in cohort 2. Visual analysis of WGS data demonstrated RATs, copy number variants, and extensive genome-wide imbalances. Trisomies 7, 15, 16, and 22 were the most frequently observed RATs in both cohorts. Cytogenetic or pregnancy outcome data were available in 52 of 60 (87%) of cases with RATs in cohort 2. Cases with RATs detected were associated with miscarriage, true fetal mosaicism, and confirmed or suspected uniparental disomy. Comparing the trisomic fraction with the fetal fraction allowed estimation of possible mosaicism. Analysis and reporting of aneuploidies in all chromosomes can clarify cases in which cfDNA findings on selected "target" chromosomes (21, 18, and 13) are discordant with the fetal karyotype and may identify pregnancies at risk of miscarriage and other complications.

Effect of various normalization methods on Applied Biosystems expression array system data.

BACKGROUND: DNA microarray technology provides a powerful tool for characterizing gene expression on a genome scale. While the technology has been widely used in discovery-based medical and basic biological research, its direct application in clinical practice and regulatory decision-making has been questioned. A few key issues, including the reproducibility, reliability, compatibility and standardization of microarray analysis and results, must be critically addressed before any routine usage of microarrays in clinical laboratory and regulated areas can occur. In this study we investigate some of these issues for the Applied Biosystems Human Genome Survey Microarrays. RESULTS: We analyzed the gene expression profiles of two samples: brain and universal human reference (UHR), a mixture of RNAs from 10 cancer cell lines, using the Applied Biosystems Human Genome Survey Microarrays. Five technical replicates in three different sites were performed on the same total RNA samples according to manufacturer's standard protocols. Five different methods, quantile, median, scale, VSN and cyclic loess were used to normalize AB microarray data within each site. 1,000 genes spanning a wide dynamic range in gene expression levels were selected for real-time PCR validation. Using the TaqMan assays data set as the reference set, the performance of the five normalization methods was evaluated focusing on the following criteria: (1) Sensitivity and reproducibility in detection of expression; (2) Fold change correlation with real-time PCR data; (3) Sensitivity and specificity in detection of differential expression; (4) Reproducibility of differentially expressed gene lists. CONCLUSION: Our results showed a high level of concordance between these normalization methods. This is true, regardless of whether signal, detection, variation, fold change measurements and reproducibility were interrogated. Furthermore, we used TaqMan assays as a reference, to generate TPR and FDR plots for the various normalization methods across the assay range. Little impact is observed on the TP and FP rates in detection of differentially expressed genes. Additionally, little effect was observed by the various normalization methods on the statistical approaches analyzed which indicates a certain robustness of the analysis methods currently in use in the field, particularly when used in conjunction with the Applied Biosystems Gene Expression System.

Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays.

BACKGROUND: DNA microarrays are rapidly becoming a fundamental tool in discovery-based genomic and biomedical research. However, the reliability of the microarray results is being challenged due to the existence of different technologies and non-standard methods of data analysis and interpretation. In the absence of a "gold standard"/"reference method" for the gene expression measurements, studies evaluating and comparing the performance of various microarray platforms have often yielded subjective and conflicting conclusions. To address this issue we have conducted a large scale TaqMan Gene Expression Assay based real-time PCR experiment and used this data set as the reference to evaluate the performance of two representative commercial microarray platforms. RESULTS: In this study, we analyzed the gene expression profiles of three human tissues: brain, lung, liver and one universal human reference sample (UHR) using two representative commercial long-oligonucleotide microarray platforms: (1) Applied Biosystems Human Genome Survey Microarrays (based on single-color detection); (2) Agilent Whole Human Genome Oligo Microarrays (based on two-color detection). 1,375 genes represented by both microarray platforms and spanning a wide dynamic range in gene expression levels, were selected for TaqMan Gene Expression Assay based real-time PCR validation. For each platform, four technical replicates were performed on the same total RNA samples according to each manufacturer's standard protocols. For Agilent arrays, comparative hybridization was performed using incorporation of Cy5 for brain/lung/liver RNA and Cy3 for UHR RNA (common reference). Using the TaqMan Gene Expression Assay based real-time PCR data set as the reference set, the performance of the two microarray platforms was evaluated focusing on the following criteria: (1) Sensitivity and accuracy in detection of expression; (2) Fold change correlation with real-time PCR data in pair-wise tissues as well as in gene expression profiles determined across all tissues; (3) Sensitivity and accuracy in detection of differential expression. CONCLUSION: Our study provides one of the largest "reference" data set of gene expression measurements using TaqMan Gene Expression Assay based real-time PCR technology. This data set allowed us to use an alternative gene expression technology to evaluate the performance of different microarray platforms. We conclude that microarrays are indeed invaluable discovery tools with acceptable reliability for genome-wide gene expression screening, though validation of putative changes in gene expression remains advisable. Our study also characterizes the limitations of microarrays; understanding these limitations will enable researchers to more effectively evaluate microarray results in a more cautious and appropriate manner.

Membrane transporters and channels: role of the transportome in cancer chemosensitivity and chemoresistance.

Membrane transporters and channels (collectively the transportome) govern cellular influx and efflux of ions, nutrients, and drugs. We used oligonucleotide arrays to analyze gene expression of the transportome in 60 human cancer cell lines used by the National Cancer Institute for drug screening. Correlating gene expression with the potencies of 119 standard anticancer drugs identified known drug-transporter interactions and suggested novel ones. Folate, nucleoside, and amino acid transporters positively correlated with chemosensitivity to their respective drug substrates. We validated the positive correlation between SLC29A1 (nucleoside transporter ENT1) expression and potency of nucleoside analogues, azacytidine and inosine-glycodialdehyde. Application of an inhibitor of SLC29A1, nitrobenzylmercaptopurine ribonucleoside, significantly reduced the potency of these two drugs, indicating that SLC29A1 plays a role in cellular uptake. Three ABC efflux transporters (ABCB1, ABCC3, and ABCB5) showed significant negative correlations with multiple drugs, suggesting a mechanism of drug resistance. ABCB1 expression correlated negatively with potencies of 19 known ABCB1 substrates and with Baker's antifol and geldanamycin. Use of RNA interference reduced ABCB1 mRNA levels and concomitantly increased sensitivity to these two drugs, as expected for ABCB1 substrates. Similarly, specific silencing of ABCB5 by small interfering RNA increased sensitivity to several drugs in melanoma cells, implicating ABCB5 as a novel chemoresistance factor. Ion exchangers, ion channels, and subunits of proton and sodium pumps variably correlated with drug potency. This study identifies numerous potential drug-transporter relationships and supports a prominent role for membrane transport in determining chemosensitivity. Measurement of transporter gene expression may prove useful in predicting anticancer drug response.

CITED1 protein expression suggests Papillary Thyroid Carcinoma in high throughput tissue microarray-based study.

Molecular markers of papillary thyroid carcinoma (PTC) are relatively unknown. Recently, the CITED1 gene was reported to be greatly upregulated in PTC relative to normal thyroid. The CITED1 protein, a 27-kd transcriptional transactivator nuclear protein is expressed in PTC, melanocytes, breast epithelial cells, and several embryonic tissues. However, its expression in other thyroid masses and non-thyroid tumors is not known. We evaluated CITED1 protein expression in tissue microarrays comprising various thyroid and nonthyroid tissues by immunohistochemistry using a polyclonal anti-CITED1 antibody. CITED1 expression was seen in 63 of 68 PTC (93%), 3 of 12 follicular carcinomas (25%), 2 of 7 Hürthle cell carcinomas (28%), 2 of 21 adenomas (10%), 2 of 6 follicular neoplasms of undetermined malignant behavior (33%), and 2 of 24 nodular goiters (8%). Normal thyroids (n = 27), thyrotoxic hyperplasias (n = 14), and anaplastic thyroid carcinomas (n = 5) did not express CITED1. Among nonthyroid tumors, 6 of 23 melanomas (26%), 11 of 65 prostatic carcinomas (17%), 3 of 25 glioblastomas (12%), 4 of 67 breast carcinomas (6%), 1 of 49 lymphomas (2%), 1 of 65 lung carcinomas (2%), 1 of 68 colon carcinomas (2%), and none of 49 ovarian carcinomas (0%) expressed CITED1. The accuracy of CITED1 in differentiating PTC from benign thyroid nodules, other thyroid carcinomas, and nonthyroid carcinomas was 93%, 89%, and 94%, respectively. CITED1 is preferentially expressed in PTC and may be used as a diagnostic marker of it.

Does addition of BRAF V600E mutation testing modify sensitivity or specificity of the Afirma Gene Expression Classifier in cytologically indeterminate thyroid nodules?

OBJECTIVE: The purpose of this study was to determine the frequency of BRAF mutation in cytologically indeterminate thyroid nodules and to investigate whether adding the BRAF test improves diagnostic accuracy of the Afirma Gene Expression Classifier (GEC). DESIGN: BRAF V600E mutational status was determined for DNA extracted from cytologically benign (n = 40), indeterminate (n = 208), and malignant (n = 48) fine-needle aspiration specimens previously categorized by GEC as molecularly Benign or Suspicious. Analytical performance of the BRAF assay was assessed to establish reproducibility and limits of detection. Molecular testing results were correlated with blinded expert histopathological diagnoses. RESULTS: The BRAF assay detected mutations reproducibly to 2.5% mutant allele frequency. The prevalence of BRAF mutations in cytologically benign specimens was 2 of 40 (5.0%, 95% confidence interval [CI], 0-16) and in cytologically malignant specimens was 36 of 48 (75.0%, 95% CI, 60-86). In the cytologically indeterminate category, 10.1% of specimens were BRAF+: 2 of 95 were subcategorized as atypia of undetermined significance or follicular lesion of undetermined significance (2.1%, 95% CI, 0-7); 1 of 70 as follicular neoplasm or suspicious for follicular neoplasm (1.4%, 95% CI, 0-9); and 18 of 43 as suspicious for malignancy (41.9%, 95% CI, 27-58). All BRAF+ specimens were classified as Suspicious by the GEC. CONCLUSIONS: BRAF mutations are uncommon in nodules with atypia of undetermined significance or follicular lesion of undetermined significance or follicular neoplasm or suspicious for follicular neoplasm cytology. Most cytologically indeterminate nodules that proved to be malignant were also BRAF-, and all nodules that were false-negative by GEC were also BRAF-. Similarly, all BRAF+ specimens were also GEC Suspicious. Neither GEC test sensitivity nor specificity was improved by addition of BRAF mutation testing.

Genome and transcriptome sequencing in prospective metastatic triple-negative breast cancer uncovers therapeutic vulnerabilities.

Triple-negative breast cancer (TNBC) is characterized by the absence of expression of estrogen receptor, progesterone receptor, and HER-2. Thirty percent of patients recur after first-line treatment, and metastatic TNBC (mTNBC) has a poor prognosis with median survival of one year. Here, we present initial analyses of whole genome and transcriptome sequencing data from 14 prospective mTNBC. We have cataloged the collection of somatic genomic alterations in these advanced tumors, particularly those that may inform targeted therapies. Genes mutated in multiple tumors included TP53, LRP1B, HERC1, CDH5, RB1, and NF1. Notable genes involved in focal structural events were CTNNA1, PTEN, FBXW7, BRCA2, WT1, FGFR1, KRAS, HRAS, ARAF, BRAF, and PGCP. Homozygous deletion of CTNNA1 was detected in 2 of 6 African Americans. RNA sequencing revealed consistent overexpression of the FOXM1 gene when tumor gene expression was compared with nonmalignant breast samples. Using an outlier analysis of gene expression comparing one cancer with all the others, we detected expression patterns unique to each patient's tumor. Integrative DNA/RNA analysis provided evidence for deregulation of mutated genes, including the monoallelic expression of TP53 mutations. Finally, molecular alterations in several cancers supported targeted therapeutic intervention on clinical trials with known inhibitors, particularly for alterations in the RAS/RAF/MEK/ERK and PI3K/AKT/mTOR pathways. In conclusion, whole genome and transcriptome profiling of mTNBC have provided insights into somatic events occurring in this difficult to treat cancer. These genomic data have guided patients to investigational treatment trials and provide hypotheses for future trials in this irremediable cancer.

Deterministic and stochastic allele specific gene expression in single mouse blastomeres.

Stochastic and deterministic allele specific gene expression (ASE) might influence single cell phenotype, but the extent and nature of the phenomenon at the onset of early mouse development is unknown. Here we performed single cell RNA-Seq analysis of single blastomeres of mouse embryos, which revealed significant changes in the transcriptome. Importantly, over half of the transcripts with detectable genetic polymorphisms exhibit ASE, most notably, individual blastomeres from the same two-cell embryo show similar pattern of ASE. However, about 6% of them exhibit stochastic expression, indicated by altered expression ratio between the two alleles. Thus, we demonstrate that ASE is both deterministic and stochastic in early blastomeres. Furthermore, we also found that 1,718 genes express two isoforms with different lengths of 3'UTRs, with the shorter one on average 5-6 times more abundant in early blastomeres compared to the transcripts in epiblast cells, suggesting that microRNA mediated regulation of gene expression acquires increasing importance as development progresses.

Next-generation sequencing identifies novel microRNAs in peripheral blood of lung cancer patients.

MicroRNAs (miRNAs) are increasingly envisaged as biomarkers for various tumor and non-tumor diseases. MiRNA biomarker identification is, as of now, mostly performed in a candidate approach, limiting discovery to annotated miRNAs and ignoring unknown ones with potential diagnostic value. Here, we applied high-throughput SOLiD transcriptome sequencing of miRNAs expressed in human peripheral blood of patients with lung cancer. We developed a bioinformatics pipeline to generate profiles of miRNA markers and to detect novel miRNAs with diagnostic information. Applying our approach, we detected 76 previously unknown miRNAs and 41 novel mature forms of known precursors. In addition, we identified 32 annotated and seven unknown miRNAs that were significantly altered in cancer patients. These results demonstrate that deep sequencing of small RNAs bears high potential to quantify miRNAs in peripheral blood and to identify previously unknown miRNAs serving as biomarker for lung cancer.

MicroRNAs and their isomiRs function cooperatively to target common biological pathways.

BACKGROUND: Variants of microRNAs (miRNAs), called isomiRs, are commonly reported in deep-sequencing studies; however, the functional significance of these variants remains controversial. Observational studies show that isomiR patterns are non-random, hinting that these molecules could be regulated and therefore functional, although no conclusive biological role has been demonstrated for these molecules. RESULTS: To assess the biological relevance of isomiRs, we have performed ultra-deep miRNA-seq on ten adult human tissues, and created an analysis pipeline called miRNA-MATE to align, annotate, and analyze miRNAs and their isomiRs. We find that isomiRs share sequence and expression characteristics with canonical miRNAs, and are generally strongly correlated with canonical miRNA expression. A large proportion of isomiRs potentially derive from AGO2 cleavage independent of Dicer. We isolated polyribosome-associated mRNA, captured the mRNA-bound miRNAs, and found that isomiRs and canonical miRNAs are equally associated with translational machinery. Finally, we transfected cells with biotinylated RNA duplexes encoding isomiRs or their canonical counterparts and directly assayed their mRNA targets. These studies allow us to experimentally determine genome-wide mRNA targets, and these experiments showed substantial overlap in functional mRNA networks suppressed by both canonical miRNAs and their isomiRs. CONCLUSIONS: Together, these results find isomiRs to be biologically relevant and functionally cooperative partners of canonical miRNAs that act coordinately to target pathways of functionally related genes. This work exposes the complexity of the miRNA-transcriptome, and helps explain a major miRNA paradox: how specific regulation of biological processes can occur when the specificity of miRNA targeting is mediated by only 6 to 11 nucleotides.

Tracing the derivation of embryonic stem cells from the inner cell mass by single-cell RNA-Seq analysis.

During the transition from the inner cell mass (ICM) cells of blastocysts to pluripotent embryonic stem cells (ESCs) in vitro, a normal developmental program is replaced in cells that acquire a capacity for infinite self-renewal and pluripotency. We explored the underlying mechanism of this switch by using RNA-Seq transcriptome analysis at the resolution of single cells. We detected significant molecular transitions and major changes in transcript variants, which include genes for general metabolism. Furthermore, the expression of repressive epigenetic regulators increased with a concomitant decrease in gene activators that might be necessary to sustain the inherent plasticity of ESCs. Furthermore, we detected changes in microRNAs (miRNAs), with one set that targets early differentiation genes while another set targets pluripotency genes to maintain the unique ESC epigenotype. Such genetic and epigenetic events may contribute to a switch from a normal developmental program in adult cells during the formation of diseased tissues, including cancers.