Distinct Splice Variants and Pathway Enrichment in the Cell Line Models of Aggressive Human Breast Cancer Subtypes.
ABSTRACT This study was conducted as a part of the Chromosome-Centric Human Proteome Project (C-HPP) of the Human Proteome Organization. The United States team of C-HPP is focused on characterizing the protein-coding genes in chromosome 17. Despite its small size, chromosome 17 is rich in protein-coding genes, it contains many cancer-associated genes, including BRCA1, ERBB2 (Her2/neu), and TP53. The goal of this study was to examine the splice variants expressed in three ERBB2 expressed breast cancer cell line models of hormone receptor negative breast cancers by integrating RNA-Seq and proteomic mass spectrometry data. The cell-lines represent distinct phenotypic variations subtype: SKBR3 (ERBB2+ (over-expression)/ ER-/PR-; adenocarcinoma), SUM190 (ERBB2+ (over-expression)/ER-/PR-; inflammatory breast cancer) and SUM149 (ERBB2 (low expression) ER-/PR -; inflammatory breast cancer). We identified more than one splice variant for 1167 genes expressed in at least one of the three cancer cell lines. We found multiple variants of genes that are in the signaling pathways downstream of ERBB2 along with variants specific to one cancer cell line compared to the other two cancer cell lines and to normal mammary cells. The overall transcript profiles based on read counts indicated more similarities between SKBR3 and SUM190. The top-ranking Gene Ontology and BioCarta pathways for the cell-line specific variants pointed to distinct key mechanisms including: amino sugar metabolism, caspase activity, and endocytosis in SKBR3; different aspects of metabolism, especially of lipids in SUM190; cell- to-cell adhesion, integrin and ERK1/ERK2 signaling, and translational control in SUM149. The analyses indicated an enrichment in the electron transport chain processes in the ERBB2 over-expressed cell line models; and an association of nucleotide binding, RNA splicing and translation processes with the IBC models, SUM190 and SUM149. Detailed experimental studies on the distinct variants identified from each of these three breast cancer cell line models may open opportunities for drug target discovery and help unveil their specific roles in cancer progression and metastasis.
SourceAvailable from: PubMed Central[Show abstract] [Hide abstract]
ABSTRACT: One of the major mechanisms of generating mRNA diversity is alternative splicing, a regulated process that allows for the flexibility of producing functionally different proteins from the same genomic sequences. This process is often altered in cancer cells to produce aberrant proteins that drive the progression of cancer. A better understanding of the misregulation of alternative splicing will shed light on the development of novel targets for pharmacological interventions of cancer. In this study, we evaluated three statistical methods, random effects meta-regression, beta regression, and generalized linear mixed effects model, for the analysis of splicing quantitative trait loci (sQTL) using RNA-Seq data. All the three methods use exon-inclusion levels estimated by the PennSeq algorithm, a statistical method that utilizes paired-end reads and accounts for non-uniform sequencing coverage. Using both simulated and real RNA-Seq datasets, we compared these three methods with GLiMMPS, a recently developed method for sQTL analysis. Our results indicate that the most reliable and powerful method was the random effects meta-regression approach, which identified sQTLs at low false discovery rates but higher power when compared to GLiMMPS. We have evaluated three statistical methods for the analysis of sQTLs in RNA-Seq. Results from our study will be instructive for researchers in selecting the appropriate statistical methods for sQTL analysis.Cancer informatics 10/2014; 13(Suppl 4):35-43. DOI:10.4137/CIN.S13971
[Show abstract] [Hide abstract]
ABSTRACT: Searching deep proteome data for 9 NCI-60 cancer cell lines obtained earlier by Moghaddas Gholami, et. al. (Cell Reports, 2013) against a database from cancer genomes returned a variant tryptic peptide fragment 57-72 of molecular chaperone HSC70, in which methionine residue at 61 position is replaced by threonine, or isothreonine (homoserine), residue. However, no traces of the corresponding genetic alteration were found in the cell line genomes reported by Abaan et. al. (Cancer Research, 2013). Studying on the background of this modification led us to conclude that a conversion of methionine into isothreonine resulted from iodoacetamide treatment of the probe during a sample preparation step. We found that up to 10% of methionine containing peptides experienced the above conversion for the datasets under study. The artifact was confirmed by model experiment with bovine albumin, where three of four methionine residues were partly converted to isothreonine by conventional iodoacetamide treatment. This experimental side reaction has to be taken into account when searching for genetically encoded peptide variants in the proteogenomics studies. A lot of effort is currently put into proteogenomics of cancer. Studies detect non-synonymous cancer mutations at protein level by search of high-throughput LC-MS/MS data against customized genomic databases. In such studies, much attention is paid to potential false positive identifications. Here we describe one possible cause of such false identifications, an artifact of sample preparation which mimics methionine to threonine nucleic acid-encoded variant. The methionine to isothreonine conversion should be taken into consideration for correct interpretation of proteogenomic data. Copyright © 2015. Published by Elsevier B.V.Journal of Proteomics 03/2015; 120:169-178. DOI:10.1016/j.jprot.2015.03.003 · 3.93 Impact Factor
[Show abstract] [Hide abstract]
ABSTRACT: During endoplasmic reticulum (ER) stress, the endoribonuclease (RNase) Ire1α initiates removal of a 26 nt region from the mRNA encoding the transcription factor Xbp1 via an unconventional mechanism (atypically within the cytosol). This causes an open reading frame-shift that leads to altered transcriptional regulation of numerous downstream genes in response to ER stress as part of the unfolded protein response (UPR). Strikingly, other examples of targeted, unconventional splicing of short mRNA regions have yet to be reported.PLoS ONE 07/2014; 9(7):e100864. DOI:10.1371/journal.pone.0100864 · 3.53 Impact Factor