Evaluation of the mirn23a Cluster through an iTRAQ-based Quantitative Proteomic Approach

MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression that are implicated in a number of disease states. MiRNAs can exist as individual entities, or may be clustered and transcribed as a single polycistron. The mirn23a cluster consists of three miRNAs, miR-23a, miR-24-2, and miR-27a. While these miRNAs are transcribed together, they often exist at varying levels in the cell. Despite the fact that the mirn23a cluster is known to play a role in a number of diseases and developmental processes, few direct targets have been identified. In this study, we examined the effects of miR-23a, miR-24-2, miR-27a, or the mirn23a cluster overexpression on the proteome of 70Z/3 pre-B lymphoblast cells. Quantitative mass spectrometry using isobaric tags for relative and absolute quantification (iTRAQ) allowed for global profiling of cell lines after miRNA overexpression. We identified a number of targets of each miRNA that contained predicted miRNA seed sequences and are likely direct targets. In addition, we discovered a cohort of shared miRNA targets and cluster targets, demonstrating the importance of studying miRNA clusters in their entirety

Systems-wide RNAi analysis of CASP8AP2/FLASH shows transcriptional deregulation of the replication-dependent histone genes and extensive effects on the transcriptome of colorectal cancer cells

<p>Abstract</p> <p>Background</p> <p>Colorectal carcinomas (CRC) carry massive genetic and transcriptional alterations that influence multiple cellular pathways. The study of proteins whose loss-of-function (LOF) alters the growth of CRC cells can be used to further understand the cellular processes cancer cells depend upon for survival.</p> <p>Results</p> <p>A small-scale RNAi screen of ~400 genes conducted in SW480 CRC cells identified several candidate genes as required for the viability of CRC cells, most prominently <it>CASP8AP2</it>/<it>FLASH</it>. To understand the function of this gene in maintaining the viability of CRC cells in an unbiased manner, we generated gene specific expression profiles following RNAi. Silencing of <it>CASP8AP2</it>/<it>FLASH </it>resulted in altered expression of over 2500 genes enriched for genes associated with cellular growth and proliferation. Loss of CASP8AP2/FLASH function was significantly associated with altered transcription of the genes encoding the replication-dependent histone proteins as a result of the expression of the non-canonical polyA variants of these transcripts. Silencing of <it>CASP8AP2</it>/<it>FLASH </it>also mediated enrichment of changes in the expression of targets of the NFκB and MYC transcription factors. These findings were confirmed by whole transcriptome analysis of <it>CASP8AP2</it>/<it>FLASH </it>silenced cells at multiple time points. Finally, we identified and validated that CASP8AP2/FLASH LOF increases the expression of neurofilament heavy polypeptide (NEFH), a protein recently linked to regulation of the AKT1/ß-catenin pathway.</p> <p>Conclusions</p> <p>We have used unbiased RNAi based approaches to identify and characterize the function of CASP8AP2/FLASH, a protein not previously reported as required for cell survival. This study further defines the role CASP8AP2/FLASH plays in the regulating expression of the replication-dependent histones and shows that its LOF results in broad and reproducible effects on the transcriptome of colorectal cancer cells including the induction of expression of the recently described tumor suppressor gene <it>NEFH</it>.</p

ColoType: a forty gene signature for consensus molecular subtyping of colorectal cancer tumors using whole-genome assay or targeted RNA-sequencing

Colorectal cancer (CRC) tumors can be partitioned into four biologically distinct consensus molecular subtypes (CMS1-4) using gene expression. Evidence is accumulating that tumors in different subtypes are likely to respond differently to treatments. However, to date, there is no clinical diagnostic test for CMS subtyping. In this study, we used novel methodology in a multi-cohort training domain (n = 1,214) to develop the ColoType scores and classifier to predict CMS1-4 based on expression of 40 genes. In three validation cohorts (n = 1,744, in total) representing three distinct gene-expression measurement technologies, ColoType predicted gold-standard CMS subtypes with accuracies 0.90, 0.91, 0.88, respectively. To accommodate for potential intratumoral heterogeneity and tumors of mixed subtypes, ColoType was designed to report continuous scores measuring the prevalence of each of CMS1–4 in a tumor, in addition to specifying the most prevalent subtype. For analysis of clinical specimens, ColoType was also implemented with targeted RNA-sequencing (Illumina AmpliSeq). In a series of formalin-fixed, paraffin-embedded CRC samples (n = 49), ColoType by targeted RNA-sequencing agreed with subtypes predicted by two independent methods with accuracies 0.92, 0.82, respectively. With further validation, ColoType by targeted RNA-sequencing, may enable clinical application of CMS subtyping with widely-available and cost-effective technology

From Prohormones to Neuropeptides: Mass Spectrometric and Bioinformatic Approaches

212 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.To test the predictive models on a larger dataset, another organism was studied. The genome of the western honey bee, Apis mellifera, is being sequenced. After deducing the neuropeptide genes through bioinformatic and mass spectrometric approaches, the neuropeptides are predicted with the Aplysia-based algorithms. To verify all predictions, the peptide sequences are confirmed by electrospray quadrupole mass spectrometry (ESI-Q) TOF-MS. Employing information from additional species will help to test our current prediction schemes and develop more accurate algorithms.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

From Prohormones to Neuropeptides: Mass Spectrometric and Bioinformatic Approaches

212 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.To test the predictive models on a larger dataset, another organism was studied. The genome of the western honey bee, Apis mellifera, is being sequenced. After deducing the neuropeptide genes through bioinformatic and mass spectrometric approaches, the neuropeptides are predicted with the Aplysia-based algorithms. To verify all predictions, the peptide sequences are confirmed by electrospray quadrupole mass spectrometry (ESI-Q) TOF-MS. Employing information from additional species will help to test our current prediction schemes and develop more accurate algorithms.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Proteomic Challenges: Sample Preparation Techniques for Microgram-Quantity Protein Analysis from Biological Samples

Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed

Lipidomic Comparison of 2D and 3D Colon Cancer Cell Culture Models

Altered lipid metabolism is one of the hallmarks of cancer. Cellular proliferation and de novo synthesis of lipids are related to cancer progression. In this study, we evaluated the lipidomic profile of two-dimensional (2D) monolayer and multicellular tumor spheroids from the HCT 116 colon carcinoma cell line. We utilized serial trypsinization on the spheroid samples to generate three cellular populations representing the proliferative, quiescent, and necrotic regions of the spheroid. This analysis enabled a comprehensive identification and quantification of lipids produced in each of the spheroid layer and 2D cultures. We show that lipid subclasses associated with lipid droplets form in oxygen-restricted and acidic regions of spheroids and are produced at higher levels than in 2D cultures. Additionally, sphingolipid production, which is implicated in cell death and survival pathways, is higher in spheroids relative to 2D cells. Finally, we show that increased numbers of lipids comprised of polyunsaturated fatty acids (PUFAs) are produced in the quiescent and necrotic regions of the spheroid. The lipidomic signature for each region and cell culture type highlights the importance of understanding the spatial aspects of cancer biology. These results provide additional lipid biomarkers in the tumor microenvironment that can be further studied to target pivotal lipid production pathways

Mass Spectrometry Imaging of Therapeutics from Animal Models to Three-Dimensional Cell Cultures

This find is registered at Portable Antiquities of the Netherlands with number PAN-0002085

Quantification of Irinotecan in Single Spheroids Using Internal Standards by MALDI Mass Spectrometry Imaging

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been used to visualize molecular distributions in various biological samples. While it has succeeded in localizing molecules ranging from metabolites to peptides, quantitative MSI (qMSI) has remained challenging, especially in small biological samples like spheroids. Spheroids are a three-dimensional cellular model system that replicate the chemical microenvironments of tumors. This cellular model has played an important role in evaluating the penetration of drugs to better understand the efficacy of clinical chemotherapy. Therefore, we aim to optimize a method to quantify the distribution of therapeutics in a single spheroid using MALDI-MSI. Studies were performed with the therapeutic irinotecan (IR). The calibration curve showed a linear relationship with a limit of detection (LOD) of 0.058 ng/mm2 and R2 value at 0.9643. Spheroids treated with IR for different lengths of time were imaged using the optimized method to quantify the drug concentration during the penetration process. With a dosing concentration of 20.6 μM, the concentration of IR at 48 h of treatment was 16.90 μM within a single spheroid. Furthermore, spheroids were divided into different layers by spatial segmentation to be quantified separately. This MALDI-qMSI method is amenable to a wide range of drugs as well as their metabolites. The quantification results show great potential to extend this method to other small biological samples such as organoids for patient derived therapies