Transcriptome-wide identification and study of cancer-specific splicing events across multiple tumors

Dysregulation of alternative splicing (AS) is one of the molecular hallmarks of cancer, with splicing alteration of numerous genes in cancer patients. However, studying splicing mis-regulation in cancer is complicated by the large noise generated from tissue-specific splicing. To obtain a global picture of cancer-specific splicing, we analyzed transcriptome sequencing data from 1149 patients in The Cancer Genome Atlas project, producing a core set of AS events significantly altered across multiple cancer types. These cancer-specific AS events are highly conserved, are more likely to maintain protein reading frame, and mainly function in cell cycle, cell adhesion/migration, and insulin signaling pathways. Furthermore, these events can serve as new molecular biomarkers to distinguish cancer from normal tissues, to separate cancer subtypes, and to predict patient survival. We also found that most genes whose expression is closely associated with cancer-specific splicing are key regulators of the cell cycle. This study uncovers a common set of cancer-specific AS events altered across multiple cancers, providing mechanistic insight into how splicing is mis-regulated in cancers

Engineering RNA endonucleases with customized sequence specificities

Specific cleavage of RNAs is critical for in vitro manipulation of RNA and for in vivo gene silencing. Here we engineer artificial site-specific RNA endonucleases (ASREs) to function analogously to DNA restriction enzymes. We combine a general RNA cleavage domain with a series of Pumilio/FBF (PUF) domains that specifically recognize different 8-nt RNA sequences. The resulting ASREs specifically recognize RNA substrates and efficiently cleave near their binding sites. ASREs can be devised to recognize and cleave various RNA target sequences, providing a useful tool to manipulate RNAs in vitro. In addition, we generate designer ASREs to specifically silence an endogenous gene in E. coli, as well as a mitochondrial-encoded gene in human cells, suggesting that ASREs can serve as a gene silencing tool with designed specificity

The Path to Preservation: Using Proteomics to Decipher the Fate of Diatom Proteins During Microbial Degradation

We drew upon recent advances in tandem mass spectrometry-based proteomic analyses in order to examine the proteins that remain after a diatom bloom enters the stationary phase, precipitates out of the photic zone, and is subjected to microbial degradation over a 23-d period within a controlled laboratory environment. Proteins were identified from tandem mass spectra searched against three different protein databases in order to track proteins from Thalassiosira pseudonana and any potential bacterial contributions. A rapid loss of diatom protein was observed over the incubation period; 75% of the proteins initially identified were not detected after 72 h of exposure to a microbial population. By the 23rd day, peptides identified with high confidence correlated with only four T. pseudonana proteins. Five factors may have influenced the preservation of diatom proteins: (1) protection within organelles or structures with multiple membranes, (2) the relative cellular abundance in the photosynthetic apparatus, (3) the number of transmembrane domains in the protein sequence, (4) the presence of glycan modification motifs, and (5) the capability of proteins or peptides to aggregate into supramolecules

Precursor Ion Independent Algorithm for Top-Down Shotgun Proteomics

We present a precursor ion independent top-down algorithm (PIITA) for use in automated assignment of protein identifications from tandem mass spectra of whole proteins. To acquire the data, we utilize data-dependent acquisition to select protein precursor ions eluting from a C4-based HPLC column for collision induced dissociation in the linear ion trap of an LTQ-Orbitrap mass spectrometer. Gas-phase fractionation is used to increase the number of acquired tandem mass spectra, all of which are recorded in the Orbitrap mass analyzer. To identify proteins, the PIITA algorithm compares deconvoluted, deisotoped, observed tandem mass spectra to all possible theoretical tandem mass spectra for each protein in a genomic sequence database without regard for measured parent ion mass. Only after a protein is identified, is any difference in measured and theoretical precursor mass used to identify and locate post-translation modifications. We demonstrate the application of PIITA to data generated via our wet-lab approach on a Salmonella typhimurium outer membrane extract and compare these results to bottom-up analysis. From these data, we identify 154 proteins by top-down analysis, 73 of which were not identified in a parallel bottom-up analysis. We also identify 201 unique isoforms of these 154 proteins at a false discovery rate (FDR) of <1%

The splicing activator DAZAP1 integrates splicing control into MEK/Erk-regulated cell proliferation and migration

Alternative splicing of pre-mRNA is a critical stage of gene regulation in response to environmental stimuli. Here we show that DAZAP1, an RNA binding protein involved in mammalian development and spermatogenesis, promotes inclusion of weak exons through specific recognition of diverse cis-elements. The C-terminal proline-rich domain of DAZAP1 interacts with and neutralizes general splicing inhibitors, and is sufficient to activate splicing when recruited to pre-mRNA. This domain is phosphorylated by the MEK/Erk pathway and this modification is essential for the splicing regulatory activity and the nuclear/cytoplasmic translocation of DAZAP1. Using mRNA-seq we identify endogenous splicing events regulated by DAZAP1, many of which are involved in maintaining cell growth. Knockdown or over-expression of DAZAP1 causes a cell proliferation defect. Taken together, these studies reveal a molecular mechanism that integrates splicing control into MEK/Erk regulated cell proliferation

The Splicing Factor RBM4 Controls Apoptosis, Proliferation, and Migration to Suppress Tumor Progression

Splicing dysregulation is one of the molecular hallmarks of cancer. However, the underlying molecular mechanisms remain poorly defined. Here we report the splicing factor RBM4 suppresses proliferation and migration of various cancer cells by specifically controlling cancer-related splicing. Particularly, RBM4 regulates Bcl-x splicing to induce apoptosis, and co-expression of Bcl-xL partially reverses the RBM4-mediated tumor suppression. Moreover, RBM4 antagonizes an oncogenic splicing factor, SRSF1, to inhibit mTOR activation. Strikingly, RBM4 expression is dramatically decreased in cancer patients, and RBM4 level is positively correlated with improved survival. In addition to providing mechanistic insights of cancer-related splicing dysregulation, this study establishes RBM4 as a tumor suppressor with therapeutic potentials and clinical values as a prognostic factor

Prevalent RNA recognition motif duplication in the human genome

The sequence-specific recognition of RNA by proteins is mediated through various RNA binding domains, with the RNA recognition motif (RRM) being the most frequent and present in >50% of RNA-binding proteins (RBPs). Many RBPs contain multiple RRMs, and it is unclear how each RRM contributes to the binding specificity of the entire protein. We found that RRMs within the same RBP (i.e., sibling RRMs) tend to have significantly higher similarity than expected by chance. Sibling RRM pairs from RBPs shared by multiple species tend to have lower similarity than those found only in a single species, suggesting that multiple RRMs within the same protein might arise from domain duplication followed by divergence through random mutations. This finding is exemplified by a recent RRM domain duplication in DAZ proteins and an ancient duplication in PABP proteins. Additionally, we found that different similarities between sibling RRMs are associated with distinct functions of an RBP and that the RBPs tend to contain repetitive sequences with low complexity. Taken together, this study suggests that the number of RBPs with multiple RRMs has expanded in mammals and that the multiple sibling RRMs may recognize similar target motifs in a cooperative manner

An integrated model for predicting KRAS dependency.

The clinical approvals of KRAS G12C inhibitors have been a revolutionary advance in precision oncology, but response rates are often modest. To improve patient selection, we developed an integrated model to predict KRAS dependency. By integrating molecular profiles of a large panel of cell lines from the DEMETER2 dataset, we built a binary classifier to predict a tumor's KRAS dependency. Monte Carlo cross validation via ElasticNet within the training set was used to compare model performance and to tune parameters α and λ. The final model was then applied to the validation set. We validated the model with genetic depletion assays and an external dataset of lung cancer cells treated with a G12C inhibitor. We then applied the model to several Cancer Genome Atlas (TCGA) datasets. The final "K20" model contains 20 features, including expression of 19 genes and KRAS mutation status. In the validation cohort, K20 had an AUC of 0.94 and accurately predicted KRAS dependency in both mutant and KRAS wild-type cell lines following genetic depletion. It was also highly predictive across an external dataset of lung cancer lines treated with KRAS G12C inhibition. When applied to TCGA datasets, specific subpopulations such as the invasive subtype in colorectal cancer and copy number high pancreatic adenocarcinoma were predicted to have higher KRAS dependency. The K20 model has simple yet robust predictive capabilities that may provide a useful tool to select patients with KRAS mutant tumors that are most likely to respond to direct KRAS inhibitors

Urinary proteomics evaluation in interstitial cystitis/painful bladder syndrome: a pilot study

PURPOSE: Interstitial cystitis/painful bladder syndrome (IC/PBS) is characterized by chronic pain, pressure and discomfort felt in the pelvis or bladder. An in-depth shotgun proteomics study was carried out to profile the urinary proteome of women with IC/PBS to identify possible specific proteins and networks associated with IC/PBS. MATERIALS AND METHODS: Urine samples from ten female IC/PBS patients and ten female asymptomatic, healthy control subjects were analyzed in quadruplicate by liquid chromatography-tandem mass spectrometry (LC-MS/MS) on a hybrid linear ion trap-orbitrap mass spectrometer. Gas-phase fractionation (GPF) was used to enhance protein identification. Differences in protein quantity were determined by peptide spectral counting. RESULTS: a-1B-glycoprotein (A1BG) and orosomucoid-1 (ORM1) were detected in all IC/PBS patients, and = 60% of these patients had elevated expression of these two proteins compared to control subjects. Transthyretin (TTR) and hemopexin (HPX) were detected in all control individuals, but = 60% of the IC/PBS patients had decreased expression levels of these two proteins. Enrichment functional analysis showed cell adhesion and response to stimuli were down-regulated whereas response to inflammation, wounding, and tissue degradation were up-regulated in IC/PBS. Activation of neurophysiological processes in synaptic inhibition, and lack of DNA damage repair may also be key components of IC/PBS. CONCLUSION: There are qualitative and quantitative differences between the urinary proteomes of women with and without IC/PBS. We identified a number of proteins as well as pathways/networks that might contribute to the pathology of IC/PBS or result from perturbations induced by this condition