Meijun Du

Characterization of human plasma-derived exosomal RNAs by deep sequencing

BackgroundExosomes, endosome-derived membrane microvesicles, contain specific RNA transcripts that are thought to be involved in cell-cell communication. These RNA transcripts have great potential as disease biomarkers. To characterize exosomal RNA profiles systemically, we performed RNA sequencing analysis using three human plasma samples and evaluated the efficacies of small RNA library preparation protocols from three manufacturers. In all we evaluated 14 libraries (7 replicates).ResultsFrom the 14 size-selected sequencing libraries, we obtained a total of 101.8 million raw single-end reads, an average of about 7.27 million reads per library. Sequence analysis showed that there was a diverse collection of the exosomal RNA species among which microRNAs (miRNAs) were the most abundant, making up over 42.32% of all raw reads and 76.20% of all mappable reads. At the current read depth, 593 miRNAs were detectable. The five most common miRNAs (miR-99a-5p, miR-128, miR-124-3p, miR-22-3p, and miR-99b-5p) collectively accounted for 48.99% of all mappable miRNA sequences. MiRNA target gene enrichment analysis suggested that the highly abundant miRNAs may play an important role in biological functions such as protein phosphorylation, RNA splicing, chromosomal abnormality, and angiogenesis. From the unknown RNA sequences, we predicted 185 potential miRNA candidates. Furthermore, we detected significant fractions of other RNA species including ribosomal RNA (9.16% of all mappable counts), long non-coding RNA (3.36%), piwi-interacting RNA (1.31%), transfer RNA (1.24%), small nuclear RNA (0.18%), and small nucleolar RNA (0.01%); fragments of coding sequence (1.36%), 5′ untranslated region (0.21%), and 3′ untranslated region (0.54%) were also present. In addition to the RNA composition of the libraries, we found that the three tested commercial kits generated a sufficient number of DNA fragments for sequencing but each had significant bias toward capturing specific RNAs.ConclusionsThis study demonstrated that a wide variety of RNA species are embedded in the circulating vesicles. To our knowledge, this is the first report that applied deep sequencing to discover and characterize profiles of plasma-derived exosomal RNAs. Further characterization of these extracellular RNAs in diverse human populations will provide reference profiles and open new doors for the development of blood-based biomarkers for human diseases.

Exosomal miR-1290 and miR-375 as Prognostic Markers in Castration-resistant Prostate Cancer

BACKGROUND Extracellular microRNAs (miRNAs) embedded in circulating exosomes may serves as prognostic biomarkers in cancer. OBJECTIVE To identify and evaluate plasma exosomal miRNAs for prognosis in castration-resistant prostate cancer (CRPC). DESIGN, SETTING, AND PARTICIPANTS RNA sequencing was performed to identify candidate exosomal miRNAs associated with overall survival in a screening cohort of 23 CRPC patients. Candidate miRNAs were further evaluated for prognosis using quantitative real-time polymerase chain reaction in a follow-up cohort of 100 CRPC patients. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Cox regression and Kaplan-Meier survival analyses were used to evaluate survival association using candidate miRNAs along with clinical prognostic factors. RESULTS AND LIMITATIONS RNA sequencing in screening cohort generated approximately 6.80 million mappable reads per patient. Of those with normalized read counts ≥ 5, 43% were mapped to miRNAs for a total of 375 known and 57 novel miRNAs. Cox regression analysis identified an association of miR-1290, -1246, and -375 with overall survival (false discover rate < 0.05). Of those, higher levels of miR-1290 and -375 were significantly associated with poor overall survival (p < 0.004) in the follow-up cohort. Incorporation of miR-1290/-375 into putative clinical prognostic factors-based models in CRPC stage significantly improved predictive performance with a time-dependent area under the curve increase from 0.66 to 0.73 (p = 6.57 × 10(-6)). CONCLUSIONS Plasma exosomal miR-1290 and miR-375 are promising prognostic biomarkers for CRPC patients. Prospective validation is needed for further evaluation of these candidate miRNAs. PATIENT SUMMARY In this study, we evaluated whether small RNAs circulating in blood could be used to predict clinical outcomes in late-stage prostate cancer patients. We identified two blood-based small RNAs whose levels showed significant association with survival. Our results warrant further investigation because the noninvasive blood-based test has great potential in the management of late-stage prostate cancer.

Plasma extracellular RNA profiles in healthy and cancer patients.

Extracellular vesicles are selectively enriched in RNA that has potential as disease biomarkers. To systemically characterize circulating extracellular RNA (exRNA) profiles, we performed RNA sequencing analysis on plasma extracellular vesicles derived from 50 healthy individuals and 142 cancer patients. Of ~12.6 million raw reads for each individual, the number of mappable reads aligned to RNA references was ~5.4 million including miRNAs (~40.4%), piwiRNAs (~40.0%), pseudo-genes (~3.7%), lncRNAs (~2.4%), tRNAs (~2.1%), and mRNAs (~2.1%). By expression stability testing, we identified a set of miRNAs showing relatively consistent expression, which may serve as reference control for exRNA quantification. By performing multivariate analysis of covariance, we identified significant associations of these exRNAs with age, sex and different types of cancers. In particular, down-regulation of miR-125a-5p and miR-1343-3p showed an association with all cancer types tested (false discovery rate <0.05). We developed multivariate statistical models to predict cancer status with an area under the curve from 0.68 to 0.92 depending cancer type and staging. This is the largest RNA-seq study to date for profiling exRNA species, which has not only provided a baseline reference profile for circulating exRNA, but also revealed a set of RNA candidates for reference controls and disease biomarkers.

Prostate cancer risk locus at 8q24 as a regulatory hub by physical interactions with multiple genomic loci across the genome

Chromosome 8q24 locus contains regulatory variants that modulate genetic risk to various cancers including prostate cancer (PC). However, the biological mechanism underlying this regulation is not well understood. Here, we developed a chromosome conformation capture (3C)-based multi-target sequencing technology and systematically examined three PC risk regions at the 8q24 locus and their potential regulatory targets across human genome in six cell lines. We observed frequent physical contacts of this risk locus with multiple genomic regions, in particular, inter-chromosomal interaction with CD96 at 3q13 and intra-chromosomal interaction with MYC at 8q24. We identified at least five interaction hot spots within the predicted functional regulatory elements at the 8q24 risk locus. We also found intra-chromosomal interaction genes PVT1, FAM84B and GSDMC and inter-chromosomal interaction gene CXorf36 in most of the six cell lines. Other gene regions appeared to be cell line-specific, such as RRP12 in LNCaP, USP14 in DU-145 and SMIN3 in lymphoblastoid cell line. We further found that the 8q24 functional domains more likely interacted with genomic regions containing genes enriched in critical pathways such as Wnt signaling and promoter motifs such as E2F1 and TCF3. This result suggests that the risk locus may function as a regulatory hub by physical interactions with multiple genes important for prostate carcinogenesis. Further understanding genetic effect and biological mechanism of these chromatin interactions will shed light on the newly discovered regulatory role of the risk locus in PC etiology and progression.

Copy number variations in urine cell free DNA as biomarkers in advanced prostate cancer

Genetic profiling of urine cell free DNA (cfDNA) has not been evaluated in advanced prostate cancer. We performed whole genome sequencing of urine cfDNAs to identify tumor-associated copy number variations in urine before and after initiating androgen deprivation therapy in HSPC stage and docetaxel chemotherapy in CRPC stage. A log2 ratio-based copy number analysis detected common genomic abnormalities in prostate cancer including AR amplification in 5/10 CRPC patients. Other abnormalities identified included TMPRSS2-ERG fusion, PTEN gene deletion, NOTCH1 locus amplification along with genomic amplifications at 8q24.3, 9q34.3, 11p15.5 and 14q11.2, and deletions at 4q35.2, 5q31.3, 7q36.3, 12q24.33, and 16p11.2. By comparing copy number between pre- and post-treatment, we found significant copy number changes in 34 genomic loci. To estimate the somatic tumor DNA fraction in urine cfDNAs, we developed a Urine Genomic Abnormality (UGA) score algorithm that summed the top ten most significant segments with copy number changes. The UGA scores correlated with tumor burden and the change in UGA score after stage-specific therapies reflected disease progression status and overall survival. The study demonstrates the potential clinical utility of urine cfDNAs in predicting treatment response and monitoring disease progression.

miR-375 induces docetaxel resistance in prostate cancer by targeting SEC23A and YAP1

BackgroundTreatment options for metastatic castrate-resistant prostate cancer (mCRPC) are limited and typically are centered on docetaxel-based chemotherapy. We previously reported that elevated miR-375 levels were significantly associated with poor overall survival of mCRPC patients. In this study, we evaluated if miR-375 induced chemo-resistance to docetaxel through regulating target genes associated with drug resistance.MethodsWe first compared miR-375 expression level between prostate cancer tissues and normal prostate tissues using data from The Cancer Genome Atlas (TCGA). To examine the role of miR-375 in docetaxel resistance, we transfected miR-375 using a pre-miRNA lentiviral vector and examined the effects of exogenously overexpressed miR-375 on cell growth in two prostate cancer cell lines, DU145 and PC-3. To determine the effect of overexpressed miR-375 on tumor growth and chemo-resistance in vivo, we injected prostate cancer cells overexpressing miR-375 into nude mice subcutaneously and evaluated tumor growth rate during docetaxel treatment. Lastly, we utilized qRT-PCR and Western blot assay to examine two miR-375 target genes, SEC23A and YAP1, for their expression changes after miR-375 transfection.ResultsBy examining 495 tumor tissues and 52 normal tissues from TCGA data, we found that compared to normal prostate, miR-375 was significantly overexpressed in prostate cancer tissues (8.45-fold increase, p value = 1.98E-23). Docetaxel treatment induced higher expression of miR-375 with 5.83- and 3.02-fold increases in DU145 and PC-3 cells, respectively. Interestingly, miR-375 appeared to play a dual role in prostate cancer proliferation. While miR-375 overexpression caused cell growth inhibition and cell apoptosis, elevated miR-375 also significantly reduced cell sensitivity to docetaxel treatment in vitro, as evidenced by decreased apoptotic cells. In vivo xenograft mouse study showed that tumors with increased miR-375 expression were more tolerant to docetaxel treatment, demonstrated by greater tumor weight and less apoptotic cells in miR-375 transfected group when compared to empty vector control group. In addition, we examined expression levels of the two miR-375 target genes (SEC23A and YAP1) and observed significant reduction in the expression at both protein and mRNA levels in miR-375 transfected prostate cancer cell lines. TCGA dataset analysis further confirmed the negative correlations between miR-375 and the two target genes (r = −0.62 and −0.56 for SEC23A and YAP1, respectively; p < 0.0001).ConclusionsmiR-375 is involved in development of chemo-resistance to docetaxel through regulating SEC23A and YAP1 expression. Our results suggest that miR-375 or its target genes, SEC23A or YAP1, might serve as potential predictive biomarkers to docetaxel-based chemotherapy and/or therapeutic targets to overcome chemo-resistance in mCRPC stage.

Genomic variations in plasma cell free DNA differentiate early stage lung cancers from normal controls.

OBJECTIVES Cell free tumor DNA (cfDNA) circulating in blood has a great potential as biomarker for cancer clinical management. The objective of this study is to evaluate if cfDNA in blood plasma is detectable in early stage lung cancer patients. MATERIALS AND METHODS We extracted cfDNAs and tumor tissue DNAs from 8 lung adenocarcinoma patients. We also extracted cfDNAs from 8 normal controls. To evaluate copy number variations (CNV) and identify potential mutations, we performed low pass whole genome sequencing and targeted sequencing of 50 cancer genes. To accurately reflect the tumor-associated genomic abnormality burden in plasma, we developed a new scoring algorithm, plasma genomic abnormality (PGA) score, by summarizing absolute log2 ratios in most variable genomic regions. We performed digital PCR and allele-specific PCR to validate mutations detected by targeted sequencing. RESULTS AND CONCLUSIONS The median yield of cfDNA in 400 ul plasma was 4.9 ng (range 2.25-26.98 ng) in patients and 2.32 ng (range 1.30-2.81 ng) in controls (p=0.003). The whole genome sequencing generated approximately 20 million mappable sequence reads per subject and 5303 read counts per 1Mb genomic region. Log2 ratio-based CNV analysis showed significant chromosomal abnormality in cancer tissue DNAs and subtle but detectable differences in cfDNAs between patients and controls. Genomic abnormality analysis showed that median PGA score was 9.28 (7.38-11.08) in the 8 controls and 19.50 (5.89-64.47) in the 8 patients (p=0.01). Targeted deep sequencing in tumor tissues derived from the 8 patients identified 14 mutations in 12 different genes. The PCR-based assay confirmed 3 of 6 selected mutations in cfDNAs. These results demonstrated that the PGA score and cfDNA mutational analysis could be useful tool for the early detection of lung cancer. These blood-based genomic and genetic assays are noninvasive and may sensitively distinguish early stage disease when combined with other existing screening strategies including low-dose CT scanning.

eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing

BackgroundRNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers.ResultsWe developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification” includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module “mRNA identification” includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module “Target screening” provides expression profiling analyses and graphic visualization. The module “Self-testing” offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program’s functionality.ConclusionseRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory.

Chromatin interactions and candidate genes at ten prostate cancer risk loci

Genome-wide association studies have identified more than 100 common single nucleotide polymorphisms (SNPs) that are associated with prostate cancer risk. However, the vast majority of these SNPs lie in noncoding regions of the genome. To test whether these risk SNPs regulate their target genes through long-range chromatin interactions, we applied capture-based 3C sequencing technology to investigate possible cis-interactions at ten prostate cancer risk loci in six cell lines. We identified significant physical interactions between risk regions and their potential target genes including CAPG at 2p11.2, C2orf43 at 2p24.1, RFX6 at 6q22.1, NFASC at 1q32.1, MYC at 8q24.1 and AGAP7P at 10q11.23. Most of the interaction peaks were co-localized to regions of active histone modification and transcription factor binding sites. Expression quantitative trait locus (eQTL) analysis showed suggestive eQTL signals at rs1446669, rs699664 and rs1078004 for CAPG (p < 0.004), rs13394027 for C2orf43 (p = 2.25E-27), rs10993994 and rs4631830 for AGAP7P (p < 8.02E-5). Further analysis revealed an enhancer activity at genomic region surrounding rs4631830 which was expected to disrupt HOXB-like DNA binding affinity. This study identifies a set of candidate genes and their potential regulatory variants, and provides additional evidence showing the role of long-range chromatin interactions in prostate cancer etiology.

Cell‐free DNA copy number variations in plasma from colorectal cancer patients

To evaluate the clinical utility of cell‐free DNA (cfDNA), we performed whole‐genome sequencing to systematically examine plasma cfDNA copy number variations (CNVs) in a cohort of patients with colorectal cancer (CRC, n = 80), polyps (n = 20), and healthy controls (n = 35). We initially compared cfDNA yield in 20 paired serum–plasma samples and observed significantly higher cfDNA concentration in serum (median = 81.20 ng, range 7.18–500 ng·mL−1) than in plasma (median = 5.09 ng, range 3.76–62.8 ng·mL−1) (P < 0.0001). However, tumor‐derived cfDNA content was significantly lower in serum than in matched plasma samples tested. With ~10 million reads per sample, the sequencing‐based copy number analysis showed common CNVs in multiple chromosomal regions, including amplifications on 1q, 8q, and 5q and deletions on 1p, 4q, 8p, 17p, 18q, and 22q. Copy number changes were also evident in genes critical to the cell cycle, DNA repair, and WNT signaling pathways. To evaluate whether cumulative copy number changes were associated with tumor stages, we calculated plasma genomic abnormality in colon cancer (PGA‐C) score by summing the most significant CNVs. The PGA‐C score showed predictive performance with an area under the curve from 0.54 to 0.84 for CRC stages I‐IV. Locus‐specific copy number analysis identified nine genomic regions where CNVs were significantly associated with survival in stage III‐IV CRC patients. A multivariate model using six of nine genomic regions demonstrated a significant association of high‐risk score with shorter survival (HR = 5.33, 95% CI = 6.76–94.44, P < 0.0001). Our study demonstrates the importance of using plasma (rather than serum) to test tumor‐related genomic variations. Plasma cfDNA‐based tests can capture tumor‐specific genetic changes and may provide a measurable classifier for assessing clinical outcomes in advanced CRC patients.