Tiezheng Yuan

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.

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.

Abstract 5231: Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer

Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA Androgen deprivation therapy (ADT) for hormone-sensitive prostate cancer (HSPC) and chemotherapy for castration-resistant prostate cancer (CRPC) are considered standard of care. However, there are no clinical tests or factors that can reliably predict treatment responses for the advanced prostate cancer patients. Examination of tumor component in circulation, also known as liquid biopsy, has shown promise for predicting treatment outcomes and survival. To capture the tumor-derived genomic alterations and decrease the surrogacy of using PSA measurements as is currently performed, we propose a Plasma Genomic Abnormality (PGA) score and Treatment Efficacy (TEff) index based on copy number variations as estimated by cell free DNA (cfDNA) in plasma. We first performed whole genome and targeted sequencing (NimbleGen comprehensive cancer panel) to examine plasma cfDNA for tumor-associated genetic and genomic aberrations in 10 HSPC patients receiving ADT and 10 CRPC patients receiving chemotherapy. For each patient, we tested plasma from two time points: pre-treatment and 4 months post-treatment. We then calculated the PGA score by summing the most significant genomic abnormalities with higher PGA score indicating greater tumor DNA content in cfDNA. TEff index was derived from comparison of PGA score difference between treatments with higher TEff index reflecting a better treatment response. The sequencing-based copy number analysis revealed locus-specific gains or losses including those previously reported in prostate cancers, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. We found that overall PGA score was significantly higher in CRPC patients than in HSPC patients (p<0.0005), possibly reflecting increased tumor burden during the disease progression. Patients with low TEff index often demonstrated poor response to treatments, and patients with high initial PGA score or low TEff index tended to have poor overall survival. As examples of the PGA-based TEff associations with outcome we presented three CRPC patients including two with neuro-endocrine origin (small cell carcinoma). Comparison of mutational profiles between pre- and post-treatments showed that treatments caused more diverse gene mutations, in particular, in the genes involving androgen biosynthesis, AR activation, DNA repair and chemotherapy resistance, suggesting subclonal evolution of heterogeneous tumor genomes in response to these treatments. Our results strongly support the feasibility of using non-invasive liquid biopsy as a potential powerful tool to study biological mechanisms underlying therapy-specific resistance and monitor disease progression in the advanced prostate cancer. Further studies are needed to develop and validate the genomics-based PGA score and TEff index for clinical applications. Citation Format: Liang Wang, Shu Xia, Meijun Du, Rachel Ditmar, Tiezheng Yuan, Yongchen Guo, Yuan Wang, Adam Lee, Michael Tschannen, Elizabeth Worthey, Howard Jacobs, Chiang-Ching Huang, Manish Kohli. Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5231. doi:10.1158/1538-7445.AM2015-5231

Exosomal microRNA as prognostic biomarkers in metastatic castrate-resistant prostate cancer (mCRPC).

260 Background: The purpose of this study was to evaluate cell free nucleic acid based biomarkers for prognosis in mCRPC stage. Methods: Uniformly collected blood from mCRPC patients was processed for plasma which was used for exosomal RNA extraction. RNA sequencing was applied to examine microRNA (miRNA) profiles initially in a discovery cohort of 23 mCRPC patients. The sequences from fastq files were mapped to human miRBase (release 19) for known miRNA read counts. A software package (miRDeep2) was used for novel miRNA prediction. Cox regression was used for association of candidate miRNAs with overall survival (OS), defined as time from development of mCRPC to death or last follow up after adjusting for Gleason Score (GS) and time on androgen deprivation (AD) for hormone sensitive disease. miRNAs significantly associated with OS (FDR 10 million mappable reads per ...

Abstract 574: Exosomal miR-1290 and miR-375 as prognostic markers in metastatic castrate resistant prostate cancer

PURPOSE: Cell free circulating microvesicles (in particular, exosomes) contain proteins and nuclei acids that may serve as biomarkers for disease diagnosis and prognosis. The goal of this study was to identify exosomal microRNAs that may predict clinical outcome of patients with castrate resistant prostate cancer (CRPC). EXPERIMENTAL DESIGN: In discovery stage, we performed RNA sequencing using plasma exosomal RNAs derived from 36 patients with CRPC. We mapped the sequence reads to known miRbase (Release 19, 2043 entries) and normalized the miRNA abundance by sequence counts per million mappable reads. We applied Cox regression analysis to identify the miRNAs that were associated with overall survival of CRPC. In validation stage, we first examined an exosomal small RNA sequencing dataset consisting of 192 individuals with various health conditions. We used Normfinder and Bestkeeper to select most stably expressed miRNAs as candidates for normalization references. We then applied real-time qRT-PCR assays to test selected candidate reference miRNAs and survival-related miRNAs in additional 100 CRPC patients. From validated miRNAs, we constructed multivariate models to predict overall survival for this group of patients. RESULTS RNA sequencing generated over 6 million mappable reads per patient in the initial discovery cohort. Among these reads, ∼45% were mapped to known miRNAs for a total of 483 known and 275 novel miRNAs with normalized read counts ≥ 5. The median follow-up time for the 36 CRPC patients was 35.6 months during which 10 patients had died. Cox regression analysis identified four microRNAs (miR-1290, -1246, -375 and a predicted miRNA at chromosome 12) that were associated with overall survival (FDR CONCLUSIONS: Plasma exosomal miRNAs provide an easily accessible resource for biomarker development in prognosis of advanced prostate cancer. Exosomal miR-1290 and miR-375 are associated with overall survival in CRPC patients. miR-30a/e-5p, especially the geometric mean of miR-30a/e-5p, are qualified endogenous references for real-time qPCR. Further confirmation of these findings is needed for prognostic and predictive biomarker in development of CRPC stage. Citation Format: Xiaoyi Huang, Tiezheng Yuan, Meihua Liang, Meijun Du, Shu Xia, Rachel Louise Dittmar, Zhifu Sun, Yan Lu, Stephen N. Thibodeau, Lisa Boardman, Manish Kohli, Liang Wang. Exosomal miR-1290 and miR-375 as prognostic markers in metastatic castrate resistant prostate cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 574. doi:10.1158/1538-7445.AM2014-574