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Multiple Setd2w/f MEF clones display reduced aTubK40me3 protein (A) and relative Setd2 mRNA (B) levels

Loss of the short arm of chromosome 3 (3p) occurs early in >95% of clear cell renal cell carcinoma (ccRCC). Nearly ubiquitous 3p loss in ccRCC suggests haploinsufficiency for 3p tumor suppressors as early drivers of tumorigenesis. We previously reported methyltransferase SETD2, which trimethylates H3 histones on lysine 36 (H3K36me3) and is located in the 3p deletion, to also trimethylate microtubules on lysine 40 (αTubK40me3) during mitosis, with αTubK40me3 required for genomic stability. We now show that monoallelic, Setd2-deficient cells retaining H3K36me3, but not αTubK40me3, exhibit a dramatic increase in mitotic defects and micronuclei count, with increased viability compared with biallelic loss. In SETD2-inactivated human kidney cells, rescue with a pathogenic SETD2 mutant deficient for microtubule (αTubK40me3), but not histone (H3K36me3) methylation, replicated this phenotype. Genomic instability (micronuclei) was also a hallmark of patient-derived cells from ccRCC. These data show that the SETD2 tumor suppressor displays a haploinsufficiency phenotype disproportionately impacting microtubule methylation and serves as an early driver of genomic instability.Significance: Loss of a single allele of a chromatin modifier plays a role in promoting oncogenesis, underscoring the growing relevance of tumor suppressor haploinsufficiency in tumorigenesis. Cancer Res; 78(12); 3135–46. ©2018 AACR.

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Summary Few predictors of response to topical corticosteroid (tCS) treatment have been identified in eosinophilic esophagitis (EoE). We aimed to determine whether baseline gene expression predicts histologic response to tCS treatment for EoE. We analyzed prospectively collected samples from incident EoE cases who were treated with tCS for 8 weeks in a development cohort (prospective study) or in an independent validation cohort (clinical trial). Whole transcriptome RNA expression was determined from a baseline (pre-treatment) RNA-later preserved esophageal biopsy. Baseline expression was compared between histologic responders (

BackgroundThe clinical approvals of KRAS G12C inhibitors has 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.Methods and FindingsBy 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. 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.ConclusionThe 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.

Cutaneous melanoma can be lethal even if detected at an early stage. Epigenetic profiling may facilitate the identification of aggressive primary melanomas with unfavorable outcomes. We performed clustering of whole-genome methylation data to identify subclasses that were then assessed for survival, clinical features, methylation patterns, and biological pathways. Among 89 cutaneous primary invasive melanomas, we identified three methylation subclasses exhibiting low methylation, intermediate methylation, or hypermethylation of CpG islands, known as the CpG island methylator phenotype (CIMP). CIMP melanomas occurred as early as tumor stage 1b and, compared with low-methylation melanomas, were associated with age at diagnosis ≥65 years, lentigo maligna melanoma histologic subtype, presence of ulceration, higher American Joint Committee on Cancer stage and tumor stage, and lower tumor-infiltrating lymphocyte grade (all P0.05). Patients with CIMP melanomas had worse melanoma-specific survival (hazard ratio = 11.84; confidence interval = 4.65‒30.20) than those with low-methylation melanomas, adjusted for age, sex, American Joint Committee on Cancer stage, and tumor-infiltrating lymphocyte grade. Genes hypermethylated in CIMP compared with those in low-methylation melanomas included PTEN, VDR, PD-L1, TET2, and gene sets related to development/differentiation, the extracellular matrix, and immunity. CIMP melanomas exhibited hypermethylation of genes important in melanoma progression and tumor immunity, and although present in some early melanomas, CIMP was associated with worse survival independent of known prognostic factors.

In tumors, extravascular fibrin forms provisional scaffolds for endothelial cell (EC) growth and motility during angiogenesis. We report that fibrin-mediated angiogenesis was inhibited and tumor growth delayed following postnatal deletion of Tgfbr2 in the endothelium of Cdh5-Cre(ERT2) Tgfbr2(fl/fl) mice (Tgfbr2(iECKO) mice). ECs from Tgfbr2(iECKO) mice failed to upregulate the fibrinolysis inhibitor plasminogen activator inhibitor 1 (Serpine1, also known as PAI-1), due in part to uncoupled TGF-β–mediated suppression of miR-30c. Bypassing TGF-β signaling with vascular tropic nanoparticles that deliver miR-30c antagomiRs promoted PAI-1–dependent tumor growth and increased fibrin abundance, whereas miR-30c mimics inhibited tumor growth and promoted vascular-directed fibrinolysis in vivo. Using single-cell RNA-Seq and a NanoString miRNA array, we also found that subtypes of ECs in tumors showed spectrums of Serpine1 and miR-30c expression levels, suggesting functional diversity in ECs at the level of individual cells; indeed, fresh EC isolates from lung and mammary tumor models had differential abilities to degrade fibrin and launch new vessel sprouts, a finding that was linked to their inverse expression patterns of miR-30c and Serpine1 (i.e., miR-30c(hi) Serpine1(lo) ECs were poorly angiogenic and miR-30c(lo) Serpine1(hi) ECs were highly angiogenic). Thus, by balancing Serpine1 expression in ECs downstream of TGF-β, miR-30c functions as a tumor suppressor in the tumor microenvironment through its ability to promote fibrin degradation and inhibit blood vessel formation.

Introduction: Breast cancers differ between genomic and transcriptomic features by ancestry within the TCGA, but current understanding of how gene expression differs across global ancestral populations is extremely limited. We hypothesized that differential expression performed by ancestry and geography may provide insight into population-specific, clinically relevant expression patterns. Objective: To compare differentially expressed protein-coding genes and pathways among primary breast tumors of Nigerian origin versus African- and European-American ancestry in TCGA Methods: We analyzed an integrated dataset of RNA-seq from 93 women in Nigeria, 31 African-ancestry women (TCGA AA), and 39 European-ancestry women from TCGA (TCGA EA) with whole-genome data. Ancestry within TCGA was classified by principal component analysis, with African ancestry as >50% contribution and European ancestry as >90% contribution. RNA was obtained from tumors in Nigeria using Qiagen PAXgene kits. A STAR/HTSeq pipeline generated read counts. To optimize assay-associated batch effects, we performed differential expression within each PAM50 subtype using limma-voom with quantile normalization. Significance was defined as a > 1.5-fold change in gene expression (log2 scale) with a false-discovery-rate-adjusted p-value of 0.05. Pathway analysis was performed via Gene Ontology and the Web-Based Gene Set Analysis Toolkit. We also compared gene expression, claudin-low (30 genes) and VEGF (13 genes) signatures to an additional set of 189 primary breast cancers from Nigeria assayed on the NanoString nCounter System using a custom Nano110 probe set (PAM50 + claudin-low & VEGF genes). RNA for these cancers was isolated from paraffin-embedded tumor using the Roche High Pure paraffin kit. Results: Differential expression was performed pairwise across ancestry groups within PAM50 subtypes (see Table). Fewer genes were differentially expressed, and fold change smaller across shared genes, when comparing Nigerian vs. TCGA AA versus Nigerian vs. TCGA EA comparisons, supporting quantile normalization. The strongest gene ontology pathway associations, seen for all subtypes, were intracellular protein targeting and viral gene expression. The epigenetic regulation pathway was significantly associated with comparisons in Basal-like tumors (padj=1.54e-7 for TCGA EA, padj=0.001 for TCGA AA). The PI3K-Akt pathway was significantly associated with Nigerian vs. TCGA-EA within Luminal A (padj=0.006). The Nanostring cohort shared a similar distribution of PAM50 subtypes (see Table, X2 p=0.21). We found concordance in both Nigerian cohorts of relative claudin-low and VEGF expression signature patterns across subtypes. Of 17 genes with significant differential expression by ancestry in the Nanostring dataset, 9 (ADM, ACTB, BIRC5, CDC6, CENPF, MKI67, MPP1, RAD17, and VEGFA) showed significant differential expression by ancestry in the PAXgene dataset. Discussion: This is one of the first analyses of differential gene expression across tumors from a global population. We identified differential pathways in breast tumors between African and European ancestry populations to target for future work. We also validated several ancestry-specific genes across platforms with potential clinical relevance. Understanding how molecular features differ across global populations will improve precision oncology for all patients. PAM50ClassificationNigerian: PAXgene (n=93)TCGA AA (n=31)TCGA EA (n=39)Nigerian: Nanostring (n=189)Nigerian (PAXgene) vs. TCGA EA ComparisonNigerian (PAXgene) vs. TCGA AAComparisonBasal-like41 (42.8%)23 (74.1%)17 (43.6%)78 (41.3%)4893 genes4687 genesHer2-enriched27 (28.1%)05 (12.8%)31 (16.4%)961 genesN/ALuminal A14 (14.5%)4 (12.9%)8 (20.5%)39 (20.6%)2596 genes480 genesLuminal B11 (11.4%)4 (12.9%)9 (23.1%)25 (13.2%)2112 genes222 genes Citation Format: Padma Sheila Rajagopal, Yi-Hsuan S Tsai, Ashley Hardeman, Ian Hurley, Aminah Sallam, Yonglan Zheng, Toshio Yoshimatsu, Anna Woodard, Dezheng Huo, Guimin Gao, Charles M Perou, Joel S Parker, Mengjie Chen, Olufunmilayo I Olopade. Comparative analysis of differential gene expression by ancestry using primary breast cancers from Nigeria and the cancer genome atlas (TCGA) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS18-12.

Telomerase reverse transcriptase (TERT) promoter mutations are commonly found in malignant melanomas but rare in melanocytic nevi. To assess its potential diagnostic utility for the distinction of melanoma from nevus, we determined the TERT promoter mutation status of 86 primary melanomas, 72 melanocytic nevi, and 40 diagnostically problematic melanocytic proliferations. Of the 86 melanomas, 67 (77.9%) were TERT-positive, defined as harboring a hotspot TERT promoter mutation at positions -124C>T, -124_125CC>TT, -138_139CC>TT, or -146C>T. Of the 72 nevi, only 1 (1.4%) was TERT-positive. Of the 40 diagnostically uncertain melanocytic proliferations, 2 (5.0%) were TERT-positive. TERT positivity as a test for melanoma versus nevus had an accuracy of 87.3% [95% confidence interval (CI), 81.1-92.1], a sensitivity of 77.9% (95% CI, 68.9-85.4), a specificity of 98.6% (95% CI, 95.8-100), a positive predictive value of 98.5% (95% CI, 95.6-100), and a negative predictive value of 78.9% (95% CI, 72.6-85.4). Our results indicate that hotspot TERT promoter mutation status may be a useful ancillary parameter for the diagnosis of melanoma. In particular, the high specificity of these mutations for melanoma indicates the presence of a TERT promoter mutation in a melanocytic neoplasm associated with diagnostic controversy, or uncertainty should increase concern for a melanoma.

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.

Irritable bowel syndrome (IBS) is a functional gastrointestinal (GI) disorder characterized by chronic abdominal pain associated with alterations in bowel function. Given the heterogeneity of the symptoms, multiple pathophysiologic factors are suspected to play a role. We classified women with IBS into four subgroups based on distinct symptom profiles. In-depth shotgun proteomic analysis was carried out to profile the urinary proteomes to identify possible proteins associated with these subgroups. First void urine samples with urine creatinine level ≥ 100 mg/dL were used after excluding samples that tested positive for blood. Urine from ten subjects representing each symptom subgroup was pooled for proteomic analysis. The urine proteome was analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) using a data-independent method known as Precursor Acquisition Independent From Ion Count (PAcIFIC) that allowed extended detectable dynamic range. Differences in protein quantities were determined by peptide spectral counting followed by validation of select proteins with ELISA or a targeted single reaction monitoring (LC-SRM/MS) approach. Four IBS symptom subgroups were selected: 1) Constipation, 2) Diarrhea + Low Pain, 3) Diarrhea + High Pain, and 4) High Pain + High Pychological Distress. A fifth group consisted of Healthy Control subjects. From comparisons of quantitative spectral counting data among the symptom subgroups and controls, a total of 18 proteins that showed quantitative differences in relative abundance and possible physiological relevance to IBS were selected for further investigation. Three of the 18 proteins were chosen for validation by either ELISA or SRM. An elevated expression of gelsolin (GSN) was associated with the high pain groups. Trefoil Factor 3 (TFF3) levels were higher in IBS groups compared to controls. In this study the IBS patients subclassified by predominant symptoms showed differences in urine proteome levels. Proteins showing distinctive changes are involved in homeostasis of intestinal function and inflammatory response. These findings warrant future studies with larger, independent cohorts to enable more extensive assessment and validation of urinary protein markers as a diagnostic tool in adult with IBS.

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.

SummarySplicing dysregulation is one of the molecular hallmarks of cancer. However, the underlying molecular mechanisms remain poorly defined. Here we report that 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 coexpression 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 decreased dramatically in cancer patients, and the RBM4 level correlates positively with improved survival. In addition to providing mechanistic insights of cancer-related splicing dysregulation, this study establishes RBM4 as a tumor suppressor with therapeutic potential and clinical values as a prognostic factor.

Alternative splicing of pre-messenger RNA (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 carboxy-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 (extracellular signal-regulated protein kinase) 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.

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 to function analogously to DNA restriction enzymes. We combine a general RNA cleavage domain with a series of Pumilio/fem-3-binding factor domains that specifically recognize different 8-nucleotide RNA sequences. The resulting artificial site-specific RNA endonucleases specifically recognize RNA substrates and efficiently cleave near their binding sites. The artificial site-specific RNA endonucleases 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 artificial site-specific RNA endonucleases to specifically silence an endogenous gene in Escherichia coli, as well as a mitochondrial-encoded gene in human cells, suggesting that artificial site-specific RNA endonucleases can serve as a gene-silencing tool with designed specificity.

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

In the last two years, because of advances in protein separation and mass spectrometry, top-down mass spectrometry moved from analyzing single proteins to analyzing complex samples and identifying hundreds and even thousands of proteins. However, computational tools for database search of top-down spectra against protein databases are still in their infancy. We describe MS-Align+, a fast algorithm for top-down protein identification based on spectral alignment that enables searches for unexpected post-translational modifications. We also propose a method for evaluating statistical significance of top-down protein identifications and further benchmark various software tools on two top-down data sets from Saccharomyces cerevisiae and Salmonella typhimurium. We demonstrate that MS-Align+ significantly increases the number of identified spectra as compared with MASCOT and OMSSA on both data sets. Although MS-Align+ and ProSightPC have similar performance on the Salmonella typhimurium data set, MS-Align+ outperforms ProSightPC on the (more complex) Saccharomyces cerevisiae data set.