Abstract Summary: The development of the Infinium HumanMethylation450 BeadChip enables epigenome-wide association studies at a reduced cost. One observation of the 450K data is that many CpG sites the beadchip interrogates have very large measurement errors. Including these noisy CpGs will decrease the statistical power of detecting relevant associations due to multiple testing correction. We propose to use intra-class correlation coefficient (ICC), which characterizes the relative contribution of the biological variability to the total variability, to filter CpGs when technical replicates are available. We estimate the ICC based on a linear mixed effects model by pooling all the samples instead of using the technical replicates only. An ultra-fast algorithm has been developed to address the computational complexity and CpG filtering can be completed in minutes on a desktop computer for a 450K data set of over 1000 samples. Our method is very flexible and can accommodate any replicate design. Simulations and a real data application demonstrate that our whole-sample ICC method performs better than replicate-sample ICC or variance-based method. Availability and implementation: CpGFilter is implemented in R and publicly available under CRAN via the R package ‘CpGFilter’. Contact: chen.jun2@mayo.edu or xlin@hsph.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Base Resolution Methylome Profiling: Considerations in Platform Selection, Data Preprocessing and Analysis
Abstract Introduction: Pulmonary carcinoid tumors account for up to 5% of all lung malignancies in adults, and comprise 30% of all carcinoid malignancies. They are defined histologically as typical carcinoid (TC) and atypical carcinoid (AC) tumors, and are characterized by neuroendocrine differentiation and the potential to metastasize. Method: We characterized genomic alterations in pulmonary carcinoid tumors using whole genome and exome sequencing in addition to mRNA expression and SNP genotyping from specimens of normal lung, typical and atypical carcinoid, and SCLC. Results: Analysis of the sequencing data identified novel mutations in the pulmonary neuroendocrine tumor spectrum, including KRAS, ABCA9, GALNT10, HSFX1, PTHLH, RANBP2, BRIP1, FXR1, BACE2, NCOR2, DGKI, HERC1, HERC5 and GLI3. Pathway analysis found 45% of the cases to harbor a mutation in genes that are involved in protein-protein interaction with ubiquitin c (UBC) and may therefore play a role in ubiquitin protein degradation pathway. We also identified genes differentially expressed in corresponding regions of copy number variation, 52 of which were linked to ubiquitination pathways in 88% of the samples genotyped. Genes amplified in 15 to 23% of the cases included ITM2A, MAOA, EGR2, HAGH, TSC22D3, NBEA, TCEAL2, and TSPYL2 whereas deleted regions in 15% of the cases implicated CFD, GDI1, IFITM1 and IFITM2. Conclusion: These results suggest that in addition to previously identified pathways, dysregulation of the ubiquitin pathway may contribute to lung carcinoid tumorigenesis and could be exploited for therapeutic purposes. Citation Format: Michael K. Asiedu, Charles L. Thomas, Jie Dong, Prasidda Khadka, Zhifu Sun, Farhad Kosari, Jin Jen, Julian Molina, George Vasmatzis, Marie Christine Aubry, Ping Yang, Dennis Wigle. Genomic alterations modify ubiquitination pathways in pulmonary carcinoid tumors. [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 3895. doi:10.1158/1538-7445.AM2015-3895
DNA Methylation Profiling: Comparison of Genome-Wide Sequencing Methods and the Infinium Human Methylation 450 Bead Chip
Sequence analysis of EBV immune evasion gene BNLF2a in EBV associated tumors and healthy individuals from nasopharyngeal carcinoma endemic and non‐endemic regions of China
Abstract 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<0.05). Of six selected candidate miRNAs, miR-30a/e-5p performed the best in their stability as endogenous references for real-time qRT-PCR. When normalized by these internal controls, we confirmed two of the three known miRs (miR-1290 and -375) showing significant association with overall survival in the validation cohort (p<0.001) with a median follow up time of 12.5 (range: 1-41) months at which time 28 patients had died. The median overall survival for patients with high (N=21) and low (N=40) expression in both miR-1290 and -375 was 7.2 (1-26.7) months and 15.3 (1-41) months, respectively (p<0.05). The miR-1290/-375-based prediction model consistently showed better predictive performance with AUC=72% than clinical variable-based model with AUC=64%. 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
Abstract 5592: Molecular classification of triple negative breast cancer via RNA-sequencing data
Abstract Introduction: Triple negative breast cancers (TNBC) are characterized as lacking estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) expression and TNBC patients have higher rates of recurrence and death compared with other breast cancer subtypes. For TNBC patients who fail standard chemotherapy, there are a lack of novel drug therapies, given the absence of well-defined molecular targets. Recently, a microarray meta-analysis identified 7 triple negative subtypes, including the validation of the luminal androgen receptor (LAR) positive subtype [Lehmann, 2011]. However, microarray technology is dependent on probe-target specificity and the 7 subtypes have yet to be validated using RNA sequencing data, and the presences of recurrent genomic alterations in the 7 subtypes are unknown. METHODS: We obtained 1106 breast cancer RNA-Seq bam files from The Cancer Genome Atlas (TCGA) and aligned with Tophat v1.3. The PAM50 intrinsic gene signature was used to extract a cohort of 128 TNBC samples. Consensus clustering of genes, greater than 75th percentile of variance, was performed using Kmeans clustering in Spearman's correlation space. A nearest centroid prediction model was developed from genes differentially expressed among the clusters. Eighty independent TNBC RNA sequencing samples were obtained (British Colombia; BC) [Shah, 2012] which were calibrated to our TNBC conditional quantile normalized cohort and sub-typed by our model. RESULTS: Using RNA-Seq gene expression count data, we identified 5 clusters, all of which were stable, including the LAR cluster. Signaling pathway impact analysis (SPIA) implicated cytokine-cytokine receptor interaction, leukocyte transendothelial migration, and regulation of actin cytoskeleton pathways commonly altered in the non-LAR TNBC subtypes. In contrast, cell cycle, ECM-receptor interaction, endocrine regulated calcium reabsorption, and insulin signaling pathways were altered in the LAR versus non-LAR subtypes. Neuroactive ligand-receptor interactions were observed to be altered commonly between all sub-types. We then applied our model to the Shah, et al cohort. In this cohort, the LAR subtype was consistent with Shah's classification of ‘other’ TNBC and contained no basal samples by PAM50 intrinsic modeling. Analysis of sub-type specific mutation data from the BC cohort demonstrates an increased mutational load in ECM-related proteins, particularly the myosins, along with increased TP53 clonality in the non-LAR subtypes. CONCLUSIONS: Using TCGA RNASeq data, we have confirmed the presence of 5 major TNBC subtypes, including the LAR; which was negligible in basal composition by PAM50 intrinsic modeling. SPIA pathway analysis indicates a core set of pathways demonstrating altered expression across the TNBC sub-types and the identification of molecular targets within each subtype is ongoing. Citation Format: Kevin J. Thompson, Xiaojia Tang, Zhifu Sun, Jason P. Sinnwell, Hugues Sicotte, Douglas W. Mahoney, Steven Hart, Peter T. Vedell, Poulami Barman, Jeanette E. Eckel Passow, Eric D. Wieben, James N. Ingle, Judy C. Boughey, Liewei Wang, Richard Weinshilboum, Krishna R. Kalari, Matthew P. Goetz. Molecular classification of triple negative breast cancer via RNA-sequencing data. [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 5592. doi:10.1158/1538-7445.AM2014-5592