Whole genome exon arrays identify differential expression of alternatively spliced, cancer-related genes in lung cancer

Prognostic Model for High-Grade Neuroendocrine Carcinoma of the Lung Incorporating Genomic Profiling and Poly (ADP-ribose) Polymerase-1 Expression

PURPOSE

High-grade neuroendocrine carcinoma (HGNEC) of the lung is an aggressive cancer with a complex biology. We aimed to explore the prognostic value of genetic aberrations and poly(ADP-ribose) polymerase-1 (PARP1) expression in HGNEC and to establish a novel prognostic model.

MATERIALS AND METHODS

We retrospectively enrolled 191 patients with histologically confirmed HGNEC of the lung. Tumor tissues were analyzed using PARP1 immunohistochemistry (IHC; N = 191) and comprehensive cancer panel sequencing (n = 102). Clinical and genetic data were used to develop an integrated Cox hazards model.

RESULTS

Strong PARP1 IHC expression (intensity 3) was observed in 153 of 191 (80.1%) patients, and the mean PARP1 H-score was 285 (range, 5-300). To develop an integrated Cox hazard model, our data set included information from 357 gene mutations and 19 clinical profiles. When the targeted mutation profiles were combined with clinical profiles, 12 genes (ATRX, CCND2, EXT2, FGFR2, FOXO1, IL21R, MAF, TGM7, TNFAIP3, TP53, TSHR, and DDR2) were identified as prognostic factors for survival. The integrated Cox hazard model, which combines mutation profiles with a baseline model, outperformed the baseline model (incremental area under the curve 0.84 v 0.78; P = 8.79e-12). The integrated model stratified patients into high- and low-risk groups with significantly different disease-free and overall survival (integrated model: hazard ratio, 7.14 [95% CI, 4.07 to 12.54]; P < .01; baseline model: 4.38 [2.56 to 7.51]; P < .01).

CONCLUSION

We introduced a new prognostic model for HGNEC that combines genetic and clinical data. The integrated Cox hazard model outperformed the baseline model in predicting the survival of patients with HGNEC.

Analysis of cancer omics data: a selective review of statistical techniques

Cancer is an omics disease. The development in high-throughput profiling has fundamentally changed cancer research and clinical practice. Compared with clinical, demographic and environmental data, the analysis of omics data-which has higher dimensionality, weaker signals and more complex distributional properties-is much more challenging. Developments in the literature are often 'scattered', with individual studies focused on one or a few closely related methods. The goal of this review is to assist cancer researchers with limited statistical expertise in establishing the 'overall framework' of cancer omics data analysis. To facilitate understanding, we mainly focus on intuition, concepts and key steps, and refer readers to the original publications for mathematical details. This review broadly covers unsupervised and supervised analysis, as well as individual-gene-based, gene-set-based and gene-network-based analysis. We also briefly discuss 'special topics' including interaction analysis, multi-datasets analysis and multi-omics analysis.

USP15 and USP4 facilitate lung cancer cell proliferation by regulating the alternative splicing of SRSF1

The deubiquitinating enzyme USP15 is implicated in several human cancers by regulating different cellular processes, including splicing regulation. However, the underlying molecular mechanisms of its functional relevance and the successive roles in enhanced tumorigenesis remain ambiguous. Here, we found that USP15 and its close paralog USP4 are overexpressed and facilitate lung cancer cell proliferation by regulating the alternative splicing of SRSF1. Depletion of USP15 and USP4 impair SRSF1 splicing characterized by the replacement of exon 4 with non-coding intron sequences retained at its C-terminus, resulting in an alternative isoform SRSF1-3. We observed an increased endogenous expression of SRSF1 in lung cancer cells as well, and its overexpression significantly enhanced cancer cell phenotype and rescued the depletion effect of USP15 and USP4. However, the alternatively spliced isoform SRSF1-3 was deficient in such aspects for its premature degradation through nonsense-mediated mRNA decay. The increased USP15 expression contributes to the lung adenocarcinoma (LUAD) development and shows significantly lower disease-specific survival of patients with USP15 alteration. In short, we identified USP15 and USP4 as key regulators of SRSF1 alternative splicing with altered functions, which may represent the novel prognostic biomarker as well as a potential target for LUAD.

Splicing reprogramming of TRAIL/DISC-components sensitizes lung cancer cells to TRAIL-mediated apoptosis

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) selective killing of cancer cells underlines its anticancer potential. However, poor tolerability and resistance underscores the need to identify cancer-selective TRAIL-sensitizing agents. Apigenin, a dietary flavonoid, sensitizes lung cancer cell lines to TRAIL. It remains unknown, however, whether apigenin sensitizes primary lung cancer cells to TRAIL and its underlying mechanisms. Here we show that apigenin reprograms alternative splicing of key TRAIL/death-inducing-signaling-complex (DISC) components: TRAIL Death Receptor 5 (DR5) and cellular-FLICE-inhibitory-protein (c-FLIP) by interacting with the RNA-binding proteins hnRNPA2 and MSI2, resulting in increased DR5 and decreased c-FLIP_S protein levels, enhancing TRAIL-induced apoptosis of primary lung cancer cells. In addition, apigenin directly bound heat shock protein 70 (Hsp70), promoting TRAIL/DISC assembly and triggering apoptosis. Our findings reveal that apigenin directs alternative splicing and inhibits Hsp70 enhancing TRAIL anticancer activity. These findings underscore impactful synergies between diet and cancer treatments opening new avenues for improved cancer treatments.

The HNRNPA2B1-MST1R-Akt axis contributes to epithelial-to-mesenchymal transition in head and neck cancer

The deregulation of splicing factors and alternative splicing are increasingly viewed as major contributory factors in tumorigenesis. In this study, we report overexpression of a key splicing factor, heterogeneous nuclear ribonucleoprotein A2B1 (HNRNPA2B1), and thereby misregulation of alternative splicing, which is associated with the poor prognosis of head and neck cancer (HNC). The role of HNRNPA2B1 in HNC tumorigenesis via deregulation of alternative splicing is not well understood. Here, we found that the CRISPR/Cas9-mediated knockout of HNRNPA2B1 results in inhibition of HNC cells growth via the misregulation of alternative splicing of MST1R, WWOX, and CFLAR. We investigated the mechanism of HNRNPA2B1-mediated HNC cells growth and found that HNRNPA2B1 plays an important role in the alternative splicing of a proto-oncogene, macrophage stimulating 1 receptor (MST1R), which encodes for the recepteur d'origine nantais (RON), a receptor tyrosine kinase. Our results indicate that HNRNPA2B1 mediates the exclusion of cassette exon 11 from MST1R, resulting in the generation of RON∆165 isoform, which was found to be associated with the activation of Akt/PKB signaling in HNC cells. Using the MST1R-minigene model, we validated the role of HNRNPA2B1 in the generation of RON∆165 isoform. The depletion of HNRNPA2B1 results in the inclusion of exon 11, thereby reduction of RON∆165 isoform. The decrease of RON∆165 isoform causes inhibition of Akt/PKB signaling, which results in the upregulation of E-cadherin and downregulation of vimentin leading to the reduced epithelial-to-mesenchymal transition. The overexpression of HNRNPA2B1 in HNRNPA2B1 knockout cells rescues the expression of the RON∆165 isoform and leads to activation of Akt/PKB signaling and induces epithelial-to-mesenchymal transition in HNC cells. In summary, our study identifies HNRNPA2B1 as a putative oncogene in HNC that promotes Akt/PKB signaling via upregulation of RON∆165 isoform and promotes epithelial to mesenchymal transition in head and neck cancer cells.

Preclinical Characterization of the Radioimmunoconjugate 111In or 90Y-FF-21101 Against a P-Cadherin-Expressing Tumor in a Mouse Xenograft Model and a Nonhuman Primate

P-cadherin is overexpressed in various cancers and can be a target for radioimmunotherapy. We investigated the preclinical pharmacokinetics and pharmacology of FF-21101, an ¹¹¹In- or ⁹⁰Y-conjugated monoclonal antibody against P-cadherin, to evaluate its clinical applications. Methods: The radiochemical purity, binding affinity, and in vitro serum stability of ¹¹¹In or ⁹⁰Y-labeled FF-21101 were evaluated. The pharmacokinetics of ¹¹¹In or ⁹⁰Y-FF-21101 were compared in normal mice. Tumor accumulation after ¹¹¹In-FF-21101 administration was investigated in mice bearing subcutaneous tumors with high (NCI-H1373), moderate (EBC-1), or no (A549) P-cadherin expression. The tumor suppression effect after a single intravenous injection of ⁹⁰Y-FF-21101 was assessed in NCI-H1373 and EBC-1 mouse xenograft models. The relationship between antibody dose and tumor accumulation was investigated in the NCI-H1373 mouse xenograft model. The absorbed radiation dose in humans after injection of ⁹⁰Y-FF-21101 was estimated using γ-camera images of cynomolgus monkeys. Results: The radiochemical purities of ¹¹¹In- and ⁹⁰Y-FF-21101 were 98.2% ± 2.5% (n = 9) and 99.3% ± 0.6% (n = 5), respectively. The dissociation constants were 1.083 nM for ¹¹¹In-FF-21101 and 1.367 nM for ⁹⁰Y-FF-21101. Both ¹¹¹In- and ⁹⁰Y-FF-21101 were stable in human serum after 96 h of incubation and exhibited similar pharmacokinetics in normal mice. The tumor accumulation of ¹¹¹In-FF-21101 was closely related to the intensity of P-cadherin expression in the cells. ⁹⁰Y-FF-21101 showed significant tumor growth inhibition, indicating that NCI-H1373 and EBC-1 recurrence was not observed after intravenous administration of 3.7 and 7.4 MBq, respectively of ⁹⁰Y-FF-21101 per animal. Tumor uptake in the mouse xenograft model and estimated absorbed radiation doses in the spleen of monkeys decreased with increasing antibody doses of ¹¹¹In-FF-21101. Conversely, the estimated absorbed radiation dose in the red marrow increased with increasing antibody dose. An antibody dose of 4.8 mg/m² was considered appropriate for humans, on the basis of efficacy and safety. The maximum tolerated administered activity of ⁹⁰Y-FF-21101 was estimated to be 2,886 MBq/human. Conclusion: FF-21101 radioimmunotherapy exhibited high antitumor affinity and antitumor efficacy in mouse xenograft models. Extrapolation of the pharmacokinetics in monkeys to humans suggests the potential for clinical application of FF-21101 for treating P-cadherin–expressing tumor.

Predictability of human differential gene expression

The identification of genes that are differentially expressed provides a molecular foothold onto biological questions of interest. Whether some genes are more likely to be differentially expressed than others, and to what degree, has never been assessed on a global scale. Here, we reanalyze more than 600 studies and find that knowledge of a gene’s prior probability of differential expression (DE) allows for accurate prediction of DE hit lists, regardless of the biological question. This result suggests redundancy in transcriptomics experiments that both informs gene set interpretation and highlights room for growth within the field.

Differential expression (DE) is commonly used to explore molecular mechanisms of biological conditions. While many studies report significant results between their groups of interest, the degree to which results are specific to the question at hand is not generally assessed, potentially leading to inaccurate interpretation. This could be particularly problematic for metaanalysis where replicability across datasets is taken as strong evidence for the existence of a specific, biologically relevant signal, but which instead may arise from recurrence of generic processes. To address this, we developed an approach to predict DE based on an analysis of over 600 studies. A predictor based on empirical prior probability of DE performs very well at this task (mean area under the receiver operating characteristic curve, ∼0.8), indicating that a large fraction of DE hit lists are nonspecific. In contrast, predictors based on attributes such as gene function, mutation rates, or network features perform poorly. Genes associated with sex, the extracellular matrix, the immune system, and stress responses are prominent within the “DE prior.” In a series of control studies, we show that these patterns reflect shared biology rather than technical artifacts or ascertainment biases. Finally, we demonstrate the application of the DE prior to data interpretation in three use cases: (i) breast cancer subtyping, (ii) single-cell genomics of pancreatic islet cells, and (iii) metaanalysis of lung adenocarcinoma and renal transplant rejection transcriptomics. In all cases, we find hallmarks of generic DE, highlighting the need for nuanced interpretation of gene phenotypic associations.

Identification of nine microRNAs as potential biomarkers for lung adenocarcinoma

Lung cancer is a leading global cause of cancer‐related death, and lung adenocarcinoma (LUAD) accounts for ~ 50% of lung cancer. Here, we screened for novel and specific biomarkers of LUAD by searching for differentially expressed mRNAs (DEmRNAs) and microRNAs (DEmiRNAs) in LUAD patient expression data within The Cancer Genome Atlas (TCGA). The identified optimal diagnostic miRNA biomarkers were used to establish classification models (including support vector machine, decision tree, and random forest) to distinguish between LUAD and adjacent tissues. We then predicted the targets of identified optimal diagnostic miRNA biomarkers, functionally annotated these target genes, and performed receiver operating characteristic curve analysis of the respective DEmiRNA biomarkers, their target DEmRNAs, and combinations of DEmiRNA biomarkers. We validated the expression of selected DEmiRNA biomarkers by quantitative real‐time PCR (qRT‐PCR). In all, we identified a total of 13 DEmiRNAs, 2301 DEmRNAs and 232 DEmiRNA–target DEmRNA pairs between LUAD and adjacent tissues and selected nine DEmiRNAs (hsa‐mir‐486‐1, hsa‐mir‐486‐2, hsa‐mir‐153, hsa‐mir‐210, hsa‐mir‐9‐1, hsa‐mir‐9‐2, hsa‐mir‐9‐3, hsa‐mir‐577, and hsa‐mir‐4732) as optimal LUAD‐specific biomarkers with great diagnostic value. The predicted targets of these nine DEmiRNAs were significantly enriched in transcriptional misregulation in cancer and central carbon metabolism. Our qRT‐PCR results were generally consistent with our integrated analysis. In summary, our study identified nine DEmiRNAs that may serve as potential diagnostic biomarkers of LUAD. Functional annotation of their target DEmRNAs may provide information on their roles in LUAD.

Revealing potential long non-coding RNA biomarkers in lung adenocarcinoma using long non-coding RNA-mediated competitive endogenous RNA network

In our study, we aimed to reveal potential long non-coding RNAs (lncRNA) biomarkers in lung adenocarcinoma (LAD) using lncRNA-mediated competing endogenous RNAs (ceRNAs) network (LMCN). Competing lncRNA-mRNA interactions were identified using the hypergeometric test. Co-expression analysis for the competing lncRNA-mRNA interactions was implemented, and relying on the weight value >0.8, a highly competitive LMCN was further constructed. Degree distribution, betweenness and closeness for LMCN were carried out to analyze the network structure. Functional analyses of mRNAs in LMCN were carried out to further explore the biological functions of lncRNAs. Biclique algorithm was utilized to extract competing modules from the LMCN. Finally, we verified our findings in an independent sample set using qRT-PCR. Based on degrees >60, we identified 4 hubs, including DLEU2, SNHG12, HCP5, and LINC00472. Furthermore, 2 competing modules were identified, and LINC00472 in module 1 functioned as a hub in both LMCN and module. Functional implications of lncRNAs demonstrated that lncRNAs were related to histone modification, negative regulation of cell cycle, neuroactive ligand-receptor interaction, and regulation of actin cytoskeleton. qRT-PCR results demonstrated that lncRNAs LINC00472, and HCP5 were down-regulated in LAD tissues, while the expression level of SNHG12 was up-regulated in LAD tissues. Our study sheds novel light on the roles of lncRNA-related ceRNA network in LAD and facilitates the detection of potential lncRNA biomarkers for LAD diagnosis and treatment. Remarkably, in our study, LINC00472, HCP5, and SNHG12 might be potential biomarkers for LAD management.

Splice variants as novel targets in pancreatic ductal adenocarcinoma

Despite a wealth of genomic information, a comprehensive alternative splicing (AS) analysis of pancreatic ductal adenocarcinoma (PDAC) has not been performed yet. In the present study, we assessed whole exome-based transcriptome and AS profiles of 43 pancreas tissues using Affymetrix exon array. The AS analysis of PDAC indicated on average two AS probe-sets (ranging from 1-28) in 1,354 significantly identified protein-coding genes, with skipped exon and alternative first exon being the most frequently utilised. In addition to overrepresented extracellular matrix (ECM)-receptor interaction and focal adhesion that were also seen in transcriptome differential expression (DE) analysis, Fc gamma receptor-mediated phagocytosis and axon guidance AS genes were also highly represented. Of note, the highest numbers of AS probe-sets were found in collagen genes, which encode the characteristically abundant stroma seen in PDAC. We also describe a set of 37 'hypersensitive' genes which were frequently targeted by somatic mutations, copy number alterations, DE and AS, indicating their propensity for multidimensional regulation. We provide the most comprehensive overview of the AS landscape in PDAC with underlying changes in the spliceosomal machinery. We also collate a set of AS and DE genes encoding cell surface proteins, which present promising diagnostic and therapeutic targets in PDAC.

Methods to increase reproducibility in differential gene expression via meta-analysis

Findings from clinical and biological studies are often not reproducible when tested in independent cohorts. Due to the testing of a large number of hypotheses and relatively small sample sizes, results from whole-genome expression studies in particular are often not reproducible. Compared to single-study analysis, gene expression meta-analysis can improve reproducibility by integrating data from multiple studies. However, there are multiple choices in designing and carrying out a meta-analysis. Yet, clear guidelines on best practices are scarce. Here, we hypothesized that studying subsets of very large meta-analyses would allow for systematic identification of best practices to improve reproducibility. We therefore constructed three very large gene expression meta-analyses from clinical samples, and then examined meta-analyses of subsets of the datasets (all combinations of datasets with up to N/2 samples and K/2 datasets) compared to a ‘silver standard’ of differentially expressed genes found in the entire cohort. We tested three random-effects meta-analysis models using this procedure. We showed relatively greater reproducibility with more-stringent effect size thresholds with relaxed significance thresholds; relatively lower reproducibility when imposing extraneous constraints on residual heterogeneity; and an underestimation of actual false positive rate by Benjamini–Hochberg correction. In addition, multivariate regression showed that the accuracy of a meta-analysis increased significantly with more included datasets even when controlling for sample size.

Serine-arginine protein kinase 1 promotes a cancer stem cell-like phenotype through activation of Wnt/β-catenin signalling in NSCLC

Cancer stem cells (CSCs) are commonly associated with cancer recurrence and metastasis that occurs in up to 30-55% of non-small-cell lung carcinoma (NSCLC) patients. Herein, we showed that serine-arginine protein kinase 1 (SRPK1) was highly expressed at both the mRNA and the protein levels in human NCSLC. SRPK1 was associated with the clinical features of human NSCLC, including clinical stage (p < 0.001) and T (p = 0.001), N (p = 0.007), and M (p = 0.001) classifications. Ectopic overexpression of SRPK1 promoted the acquisition of a stem cell-like phenotype in human NSCLC cell lines cultured in vitro. Overexpression of SRPK1 increased sphere formation and the proportion of side-population cells that exclude Hoechst dye. Conversely, SRPK1 silencing reduced the number of spheres and the proportion of side-population cells. Mouse studies indicated that SRPK1 promoted NSCLC cell line tumour growth and SRPK1 overexpression reduced the number of tumour cells required to initiate tumourigenesis in vivo. Mechanistically, gene set enrichment analysis showed that Wnt/β-catenin signalling correlated with SRPK1 mRNA levels and this signalling pathway was hyperactivated by ectopic SRPK1 expression in NSCLC cell lines. Immunofluorescence demonstrated that SRPK1 enhanced β-catenin accumulation in the nuclei of NSCLC cell lines, and inhibition of β-catenin signalling abrogated the SRPK1-induced stem cell-like phenotype. Together, our findings suggest that SRPK1 promotes a stem cell-like phenotype in NSCLC via Wnt/β-catenin signalling. Moreover, SRPK1 may represent a novel target for human NSCLC diagnosis and therapy. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Triple-layer dissection of the lung adenocarcinoma transcriptome: regulation at the gene, transcript, and exon levels

Lung adenocarcinoma is one of the most deadly human diseases. However, the molecular mechanisms underlying this disease, particularly RNA splicing, have remained underexplored. Here, we report a triple-level (gene-, transcript-, and exon-level) analysis of lung adenocarcinoma transcriptomes from 77 paired tumor and normal tissues, as well as an analysis pipeline to overcome genetic variability for accurate differentiation between tumor and normal tissues. We report three major results. First, more than 5,000 differentially expressed transcripts/exonic regions occur repeatedly in lung adenocarcinoma patients. These transcripts/exonic regions are enriched in nicotine metabolism and ribosomal functions in addition to the pathways enriched for differentially expressed genes (cell cycle, extracellular matrix receptor interaction, and axon guidance). Second, classification models based on rationally selected transcripts or exonic regions can reach accuracies of 0.93 to 1.00 in differentiating tumor from normal tissues. Of the 28 selected exonic regions, 26 regions correspond to alternative exons located in such regulators as tumor suppressor (GDF10), signal receptor (LYVE1), vascular-specific regulator (RASIP1), ubiquitination mediator (RNF5), and transcriptional repressor (TRIM27). Third, classification systems based on 13 to 14 differentially expressed genes yield accuracies near 100%. Genes selected by both detection methods include C16orf59, DAP3, ETV4, GABARAPL1, PPAR, RADIL, RSPO1, SERTM1, SRPK1, ST6GALNAC6, and TNXB. Our findings imply a multilayered lung adenocarcinoma regulome in which transcript-/exon-level regulation may be dissociated from gene-level regulation. Our described method may be used to identify potentially important genes/transcripts/exonic regions for the tumorigenesis of lung adenocarcinoma and to construct accurate tumor vs. normal classification systems for this disease.

A large-scale analysis of alternative splicing reveals a key role of QKI in lung cancer

Increasing interest has been devoted in recent years to the understanding of alternative splicing in cancer. In this study, we performed a genome-wide analysis to identify cancer-associated splice variants in non-small cell lung cancer. We discovered and validated novel differences in the splicing of genes known to be relevant to lung cancer biology, such as NFIB, ENAH or SPAG9. Gene enrichment analyses revealed an important contribution of alternative splicing to cancer-related molecular functions, especially those involved in cytoskeletal dynamics. Interestingly, a substantial fraction of the altered genes found in our analysis were targets of the protein quaking (QKI), pointing to this factor as one of the most relevant regulators of alternative splicing in non-small cell lung cancer. We also found that ESYT2, one of the QKI targets, is involved in cytoskeletal organization. ESYT2-short variant inhibition in lung cancer cells resulted in a cortical distribution of actin whereas inhibition of the long variant caused an increase of endocytosis, suggesting that the cancer-associated splicing pattern of ESYT2 has a profound impact in the biology of cancer cells. Finally, we show that low nuclear QKI expression in non-small cell lung cancer is an independent prognostic factor for disease-free survival (HR = 2.47; 95% CI = 1.11-5.46, P = 0.026). In conclusion, we identified several splicing variants with functional relevance in lung cancer largely regulated by the splicing factor QKI, a tumor suppressor associated with prognosis in lung cancer.

MYCN controls an alternative RNA splicing program in high-risk metastatic neuroblastoma

The molecular mechanisms underlying the aggressive behavior of MYCN driven neuroblastoma (NBL) is under intense investigation; however, little is known about the impact of this family of transcription factors on the splicing program. Here we used high-throughput RNA sequencing to systematically study the expression of RNA isoforms in stage 4 MYCN-amplified NBL, an aggressive subtype of metastatic NBL. We show that MYCN-amplified NBL tumors display a distinct gene splicing pattern affecting multiple cancer hallmark functions. Six splicing factors displayed unique differential expression patterns in MYCN-amplified tumors and cell lines, and the binding motifs for some of these splicing factors are significantly enriched in differentially-spliced genes. Direct binding of MYCN to promoter regions of the splicing factors PTBP1 and HNRNPA1 detected by ChIP-seq demonstrates that MYCN controls the splicing pattern by direct regulation of the expression of these key splicing factors. Furthermore, high expression of PTBP1 and HNRNPA1 was significantly associated with poor overall survival of stage4 NBL patients (p ≤ 0.05). Knocking down PTBP1, HNRNPA1 and their downstream target PKM2, an isoform of pro-tumor-growth, result in repressed growth of NBL cells. Therefore, our study reveals a novel role of MYCN in controlling global splicing program through regulation of splicing factors in addition to its well-known role in the transcription program. These findings suggest a therapeutically potential to target the key splicing factors or gene isoforms in high-risk NBL with MYCN-amplification.

Novel long non-coding RNAs are specific diagnostic and prognostic markers for prostate cancer

Current prostate cancer (PCa) biomarkers such as PSA are not optimal in distinguishing cancer from benign prostate diseases and predicting disease outcome. To discover additional biomarkers, we investigated PCa-specific expression of novel unannotated transcripts. Using the unique probe design of Affymetrix Human Exon Arrays, we identified 334 candidates (EPCATs), of which 15 were validated by RT-PCR. Combined into a diagnostic panel, 11 EPCATs classified 80% of PCa samples correctly, while maintaining 100% specificity. High specificity was confirmed by in situ hybridization for EPCAT4R966 and EPCAT2F176 (SChLAP1) on extensive tissue microarrays. Besides being diagnostic, EPCAT2F176 and EPCAT4R966 showed significant association with pT-stage and were present in PIN lesions. We also found EPCAT2F176 and EPCAT2R709 to be associated with development of metastases and PCa-related death, and EPCAT2F176 to be enriched in lymph node metastases. Functional significance of expression of 9 EPCATs was investigated by siRNA transfection, revealing that knockdown of 5 different EPCATs impaired growth of LNCaP and 22RV1 PCa cells. Only the minority of EPCATs appear to be controlled by androgen receptor or ERG. Although the underlying transcriptional regulation is not fully understood, the novel PCa-associated transcripts are new diagnostic and prognostic markers with functional relevance to prostate cancer growth.

TOX3 protein expression is correlated with pathological characteristics in breast cancer

TOX3 is a newly identified gene that has been observed to correlate with breast cancer by genome-wide association studies (GWAS) in recent years. In addition, it has been noted that single-nucleotide polymorphisms (SNPs) in the TOX3 gene have a strong correlation with estrogen receptor (ER)-positive tumors. However, the role of TOX3 in breast carcinoma development is still unclear. There are limited studies on the subject of TOX3 mRNA expression in breast tumors and little information on the variation of TOX3 protein expression in relation to the clinical pathological features in breast cancer and healthy tissues. In this study, we characterize the protein expression of TOX3 in breast tumors with respect to various clinical and pathological characteristics and explore the correlation between TOX3 protein expression and ER-positive tumors. A breast cancer tissue microarray containing 267 human breast tumors and 25 healthy controls, breast cancer cell lines (ZR-75-1, MDA-MB-231, MCF-7 and Bcap-37) with positive or negative ER expression, tumor tissues and matched controls were used to analyze the protein expression levels of TOX3 by immunohistochemistry, western blot analysis and quantitative polymerase chain reaction. Among the 267 breast tumor specimens, ER expression was detected in 66 tumor tissues. The expression levels of TOX3 increased in breast carcinoma tissue compared with controls, and were higher in advanced carcinoma (T3 and T4), lymph node metastases tissues (N2) and stage III tissues. Furthermore, TOX3 protein expression was more intense in ER-positive tumors, but did not demonstrate a statistical significance. However, it was significantly increased in ER-positive breast cancer cell lines (ZR-75-1, MCF-7 and Bcap-37) compared with the MDA-MB-231 cell line, which had ER-negative expression. Our findings provide support to the hypothesis that TOX3 has a strong correlation with the development of breast cancer. The current study is likely to assist in investigating the mechanisms involved in breast cancer development.

Aberrant RNA splicing in cancer; expression changes and driver mutations of splicing factor genes

Alternative splicing is a widespread process contributing to structural transcript variation and proteome diversity. In cancer, the splicing process is commonly disrupted, resulting in both functional and non-functional end-products. Cancer-specific splicing events are known to contribute to disease progression; however, the dysregulated splicing patterns found on a genome-wide scale have until recently been less well-studied. In this review, we provide an overview of aberrant RNA splicing and its regulation in cancer. We then focus on the executors of the splicing process. Based on a comprehensive catalog of splicing factor encoding genes and analyses of available gene expression and somatic mutation data, we identify cancer-associated patterns of dysregulation. Splicing factor genes are shown to be significantly differentially expressed between cancer and corresponding normal samples, and to have reduced inter-individual expression variation in cancer. Furthermore, we identify enrichment of predicted cancer-critical genes among the splicing factors. In addition to previously described oncogenic splicing factor genes, we propose 24 novel cancer-critical splicing factors predicted from somatic mutations.

Regulation of CD44E by DARPP-32-dependent activation of SRp20 splicing factor in gastric tumorigenesis

Objective

CD44E is a frequently overexpressed variant of CD44 in gastric cancer. Mechanisms that regulate CD44 splicing and expression in gastric cancer remain unknown. Herein, we investigated the role of DARPP-32 (dopamine and cAMP-regulated phosphoprotein, Mr 32000) in promoting tumor growth through regulation of CD44 splicing.

Design

Quantitative luciferase reporter, quantitative real-time RT-PCR (qRT-PCR), Western blot, co-immunoprecipitation, ubiquitination, and tumor xenograft experiments were performed.

Results

Western blot and qRT-PCR results indicated that knockdown of endogenous DARPP-32 markedly reduces expression of CD44 V8-V10 (CD44E). Using a quantitative splicing luciferase reporter system, we detected a significant increase in the reporter activity following DARPP-32 overexpression (p < 0.001). Conversely, knocking down endogenous DARPP-32 significantly attenuated the splicing activity (p < 0.001). Further experiments showed that DARPP-32 regulates the expression of SRp20 splicing factor and co-exists with it in the same protein complex. Inhibition of alternative splicing with digitoxin followed by immunoprecipitation and immunoblotting indicated that DARPP-32 plays an important role in regulating SRp20 protein stability. The knockdown of endogenous DARPP-32 confirmed that DARPP-32 regulates the SRp20-dependent CD44E splicing. Using tumor xenograft mouse model, knocking down endogenous DARPP-32 markedly reduced SRp20 and CD44E protein levels with a decreased tumor growth. The reconstitution of SRp20 expression in these cells rescued tumor growth. In addition, we also demonstrated frequent co-overexpression and positive correlation of DARPP-32, SRp20 and CD44E expression levels in human gastric primary tumors.

Conclusion

Our novel findings establish for the first time the role of DARPP-32 in regulating splicing factors in gastric cancer cells. The DARPP-32–SRp20 axis plays a key role in regulating the CD44E splice variant that promotes gastric tumorigenesis.

Molecular histology of lung cancer: from targets to treatments

Lung cancer is the leading cause of cancer-related death worldwide with a 5-year survival rate of less than 15%, despite significant advances in both diagnostic and therapeutic approaches. Combined genomic and transcriptomic sequencing studies have identified numerous genetic driver mutations that are responsible for the development of lung cancer. In addition, molecular profiling studies identify gene products and their mutations which predict tumour responses to targeted therapies such as protein tyrosine kinase inhibitors and also can offer explanation for drug resistance mechanisms. The profiling of circulating micro-RNAs has also provided an ability to discriminate patients in terms of prognosis/diagnosis and high-throughput DNA sequencing strategies are beginning to elucidate cell signalling pathway mutations associated with oncogenesis, including potential stem cell associated pathways, offering the promise that future therapies may target this sub-population, preventing disease relapse post treatment and improving patient survival. This review provides an assessment of molecular profiling within lung cancer concerning molecular mechanisms, treatment options and disease-progression. Current areas of development within lung cancer profiling are discussed (i.e. profiling of circulating tumour cells) and future challenges for lung cancer treatment addressed such as detection of micro-metastases and cancer stem cells.

Evaluation of copy number variation and gene expression in neurofibromatosis type-1-associated malignant peripheral nerve sheath tumours

BACKGROUND

Neurofibromatosis type-1 (NF1) is a complex neurogenetic disorder characterised by the development of benign and malignant tumours of the peripheral nerve sheath (MPNSTs). Whilst biallelic NF1 gene inactivation contributes to benign tumour formation, additional cellular changes in gene structure and/or expression are required to induce malignant transformation. Although few molecular profiling studies have been performed on the process of progression of pre-existing plexiform neurofibromas to MPNSTs, the integrated analysis of copy number alterations (CNAs) and gene expression is likely to be key to understanding the molecular mechanisms underlying NF1-MPNST tumorigenesis. In a pilot study, we employed this approach to identify genes differentially expressed between benign and malignant NF1 tumours.

RESULTS

SPP1 (osteopontin) was the most differentially expressed gene (85-fold increase in expression), compared to benign plexiform neurofibromas. Short hairpin RNA (shRNA) knockdown of SPP1 in NF1-MPNST cells reduced tumour spheroid size, wound healing and invasion in four different MPNST cell lines. Seventy-six genes were found to exhibit concordance between CNA and gene expression level.

CONCLUSIONS

Pathway analysis of these genes suggested that glutathione metabolism and Wnt signalling may be specifically involved in NF1-MPNST development. SPP1 is associated with malignant transformation in NF1-associated MPNSTs and could prove to be an important target for therapeutic intervention.

Integrated exon level expression analysis of driver genes explain their role in colorectal cancer

Integrated analysis of genomic and transcriptomic level changes holds promise for a better understanding of colorectal cancer (CRC) biology. There is a pertinent need to explain the functional effect of genome level changes by integrating the information at the transcript level. Using high resolution cytogenetics array, we had earlier identified driver genes by ‘Genomic Identification of Significant Targets In Cancer (GISTIC)’ analysis of paired tumour-normal samples from colorectal cancer patients. In this study, we analyze these driver genes at three levels using exon array data – gene, exon and network. Gene level analysis revealed a small subset to experience differential expression. These results were reinforced by carrying out separate differential expression analyses (SAM and LIMMA). ATP8B1 was found to be the novel gene associated with CRC that shows changes at cytogenetic, gene and exon levels. Splice index of 29 exons corresponding to 13 genes was found to be significantly altered in tumour samples. Driver genes were used to construct regulatory networks for tumour and normal groups. There were rearrangements in transcription factor genes suggesting the presence of regulatory switching. The regulatory pattern of AHR gene was found to have the most significant alteration. Our results integrate data with focus on driver genes resulting in highly enriched novel molecules that need further studies to establish their role in CRC.

Transcriptome sequencing reveals altered long intergenic non-coding RNAs in lung cancer

BACKGROUND

Long intergenic non-coding RNAs (lncRNAs) represent an emerging and under-studied class of transcripts that play a significant role in human cancers. Due to the tissue- and cancer-specific expression patterns observed for many lncRNAs it is believed that they could serve as ideal diagnostic biomarkers. However, until each tumor type is examined more closely, many of these lncRNAs will remain elusive.

RESULTS

Here we characterize the lncRNA landscape in lung cancer using publicly available transcriptome sequencing data from a cohort of 567 adenocarcinoma and squamous cell carcinoma tumors. Through this compendium we identify over 3,000 unannotated intergenic transcripts representing novel lncRNAs. Through comparison of both adenocarcinoma and squamous cell carcinomas with matched controls we discover 111 differentially expressed lncRNAs, which we term lung cancer-associated lncRNAs (LCALs). A pan-cancer analysis of 324 additional tumor and adjacent normal pairs enable us to identify a subset of lncRNAs that display enriched expression specific to lung cancer as well as a subset that appear to be broadly deregulated across human cancers. Integration of exome sequencing data reveals that expression levels of many LCALs have significant associations with the mutational status of key oncogenes in lung cancer. Functional validation, using both knockdown and overexpression, shows that the most differentially expressed lncRNA, LCAL1, plays a role in cellular proliferation.

CONCLUSIONS

Our systematic characterization of publicly available transcriptome data provides the foundation for future efforts to understand the role of LCALs, develop novel biomarkers, and improve knowledge of lung tumor biology.

Transcriptome sequencing reveals altered long intergenic non-coding RNAs in lung cancer

Background

Long intergenic non-coding RNAs (lncRNAs) represent an emerging and under-studied class of transcripts that play a significant role in human cancers. Due to the tissue- and cancer-specific expression patterns observed for many lncRNAs it is believed that they could serve as ideal diagnostic biomarkers. However, until each tumor type is examined more closely, many of these lncRNAs will remain elusive.

Results

Here we characterize the lncRNA landscape in lung cancer using publicly available transcriptome sequencing data from a cohort of 567 adenocarcinoma and squamous cell carcinoma tumors. Through this compendium we identify over 3,000 unannotated intergenic transcripts representing novel lncRNAs. Through comparison of both adenocarcinoma and squamous cell carcinomas with matched controls we discover 111 differentially expressed lncRNAs, which we term lung cancer-associated lncRNAs (LCALs). A pan-cancer analysis of 324 additional tumor and adjacent normal pairs enable us to identify a subset of lncRNAs that display enriched expression specific to lung cancer as well as a subset that appear to be broadly deregulated across human cancers. Integration of exome sequencing data reveals that expression levels of many LCALs have significant associations with the mutational status of key oncogenes in lung cancer. Functional validation, using both knockdown and overexpression, shows that the most differentially expressed lncRNA, LCAL1, plays a role in cellular proliferation.

Conclusions

Our systematic characterization of publicly available transcriptome data provides the foundation for future efforts to understand the role of LCALs, develop novel biomarkers, and improve knowledge of lung tumor biology.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0429-8) contains supplementary material, which is available to authorized users.

Transcriptome instability as a molecular pan-cancer characteristic of carcinomas

BACKGROUND

We have previously proposed transcriptome instability as a genome-wide, pre-mRNA splicing-related characteristic of colorectal cancer. Here, we explore the hypothesis of transcriptome instability being a general characteristic of cancer.

RESULTS

Exon-level microarray expression data from ten cancer datasets were analyzed, including breast cancer, cervical cancer, colorectal cancer, gastric cancer, lung cancer, neuroblastoma, and prostate cancer (555 samples), as well as paired normal tissue samples from the colon, lung, prostate, and stomach (93 samples). Based on alternative splicing scores across the genomes, we calculated sample-wise relative amounts of aberrant exon skipping and inclusion. Strong and non-random (P < 0.001) correlations between these estimates and the expression levels of splicing factor genes (n = 280) were found in most cancer types analyzed (breast-, cervical-, colorectal-, lung- and prostate cancer). This suggests a biological explanation for the splicing variation. Surprisingly, these associations prevailed in pan-cancer analyses. This is in contrast to the tissue and cancer specific patterns observed in comparisons across healthy tissue samples from the colon, lung, prostate, and stomach, and between paired cancer-normal samples from the same four tissue types.

CONCLUSION

Based on exon-level expression profiling and computational analyses of alternative splicing, we propose transcriptome instability as a molecular pan-cancer characteristic. The affected cancers show strong and non-random associations between low expression levels of splicing factor genes, and high amounts of aberrant exon skipping and inclusion, and vice versa, on a genome-wide scale.

SigFuge: single gene clustering of RNA-seq reveals differential isoform usage among cancer samples

High-throughput sequencing technologies, including RNA-seq, have made it possible to move beyond gene expression analysis to study transcriptional events including alternative splicing and gene fusions. Furthermore, recent studies in cancer have suggested the importance of identifying transcriptionally altered loci as biomarkers for improved prognosis and therapy. While many statistical methods have been proposed for identifying novel transcriptional events with RNA-seq, nearly all rely on contrasting known classes of samples, such as tumor and normal. Few tools exist for the unsupervised discovery of such events without class labels. In this paper, we present SigFuge for identifying genomic loci exhibiting differential transcription patterns across many RNA-seq samples. SigFuge combines clustering with hypothesis testing to identify genes exhibiting alternative splicing, or differences in isoform expression. We apply SigFuge to RNA-seq cohorts of 177 lung and 279 head and neck squamous cell carcinoma samples from the Cancer Genome Atlas, and identify several cases of differential isoform usage including CDKN2A, a tumor suppressor gene known to be inactivated in a majority of lung squamous cell tumors. By not restricting attention to known sample stratifications, SigFuge offers a novel approach to unsupervised screening of genetic loci across RNA-seq cohorts. SigFuge is available as an R package through Bioconductor.

The evolution of the coding exome of the Arabidopsis species--the influences of DNA methylation, relative exon position, and exon length

Background

The evolution of the coding exome is a major driving force of functional divergence both between species and between protein isoforms. Exons at different positions in the transcript or in different transcript isoforms may (1) mutate at different rates due to variations in DNA methylation level; and (2) serve distinct biological roles, and thus be differentially targeted by natural selection. Furthermore, intrinsic exonic features, such as exon length, may also affect the evolution of individual exons. Importantly, the evolutionary effects of these intrinsic/extrinsic features may differ significantly between animals and plants. Such inter-lineage differences, however, have not been systematically examined.

Results

Here we examine how DNA methylation at CpG dinucleotides (CpG methylation), in the context of intrinsic exonic features (exon length and relative exon position in the transcript), influences the evolution of coding exons of Arabidopsis thaliana. We observed fairly different evolutionary patterns in A. thaliana as compared with those reported for animals. Firstly, the mutagenic effect of CpG methylation is the strongest for internal exons and the weakest for first exons despite the stringent selective constraints on the former group. Secondly, the mutagenic effect of CpG methylation increases significantly with length in first exons but not in the other two exon groups. Thirdly, CpG methylation level is correlated with evolutionary rates (d_S, d_N, and the d_N/d_S ratio) with markedly different patterns among the three exon groups. The correlations are generally positive, negative, and mixed for first, last, and internal exons, respectively. Fourthly, exon length is a CpG methylation-independent indicator of evolutionary rates, particularly for d_N and the d_N/d_S ratio in last and internal exons. Finally, the evolutionary patterns of coding exons with regard to CpG methylation differ significantly between Arabidopsis species and mammals.

Conclusions

Our results suggest that intrinsic features, including relative exonic position in the transcript and exon length, play an important role in the evolution of A. thaliana coding exons. Furthermore, CpG methylation is correlated with exonic evolutionary rates differentially between A. thaliana and animals, and may have served different biological roles in the two lineages.

'N-of-1-pathways' unveils personal deregulated mechanisms from a single pair of RNA-Seq samples: towards precision medicine

Background

The emergence of precision medicine allowed the incorporation of individual molecular data into patient care. Indeed, DNA sequencing predicts somatic mutations in individual patients. However, these genetic features overlook dynamic epigenetic and phenotypic response to therapy. Meanwhile, accurate personal transcriptome interpretation remains an unmet challenge. Further, N-of-1 (single-subject) efficacy trials are increasingly pursued, but are underpowered for molecular marker discovery.

Method

‘N-of-1-pathways’ is a global framework relying on three principles: (i) the statistical universe is a single patient; (ii) significance is derived from geneset/biomodules powered by paired samples from the same patient; and (iii) similarity between genesets/biomodules assesses commonality and differences, within-study and cross-studies. Thus, patient gene-level profiles are transformed into deregulated pathways. From RNA-Seq of 55 lung adenocarcinoma patients, N-of-1-pathways predicts the deregulated pathways of each patient.

Results

Cross-patient N-of-1-pathways obtains comparable results with conventional genesets enrichment analysis (GSEA) and differentially expressed gene (DEG) enrichment, validated in three external evaluations. Moreover, heatmap and star plots highlight both individual and shared mechanisms ranging from molecular to organ-systems levels (eg, DNA repair, signaling, immune response). Patients were ranked based on the similarity of their deregulated mechanisms to those of an independent gold standard, generating unsupervised clusters of diametric extreme survival phenotypes (p=0.03).

Conclusions

The N-of-1-pathways framework provides a robust statistical and relevant biological interpretation of individual disease-free survival that is often overlooked in conventional cross-patient studies. It enables mechanism-level classifiers with smaller cohorts as well as N-of-1 studies.

Software

http://lussierlab.org/publications/N-of-1-pathways

The RNA-binding protein QKI suppresses cancer-associated aberrant splicing

Lung cancer is the leading cause of cancer-related death worldwide. Aberrant splicing has been implicated in lung tumorigenesis. However, the functional links between splicing regulation and lung cancer are not well understood. Here we identify the RNA-binding protein QKI as a key regulator of alternative splicing in lung cancer. We show that QKI is frequently down-regulated in lung cancer, and its down-regulation is significantly associated with a poorer prognosis. QKI-5 inhibits the proliferation and transformation of lung cancer cells both in vitro and in vivo. Our results demonstrate that QKI-5 regulates the alternative splicing of NUMB via binding to two RNA elements in its pre-mRNA, which in turn suppresses cell proliferation and prevents the activation of the Notch signaling pathway. We further show that QKI-5 inhibits splicing by selectively competing with a core splicing factor SF1 for binding to the branchpoint sequence. Taken together, our data reveal QKI as a critical regulator of splicing in lung cancer and suggest a novel tumor suppression mechanism involving QKI-mediated regulation of the Notch signaling pathway.

Splicing factor hnRNP A2 activates the Ras-MAPK-ERK pathway by controlling A-Raf splicing in hepatocellular carcinoma development

In recent years, it has become clear that splicing factors play a direct role in cancer development. We showed previously that splicing factors SRSF1, SRSF6, and hnRNP A2/B1 are up-regulated in several cancers and can act as oncogenes when up-regulated. Here we examined the role of splicing factors hnRNP A1/A1b and hnRNP A2/B1 in hepatocellular carcinoma (HCC). We show that the splicing factors hnRNP A1 and hnRNP A2 are up-regulated in HCC tumors derived from inflammation-induced liver cancer mouse model. Overexpression of hnRNP A1 or hnRNP A2, but not the splicing isoform hnRNP B1, induced tumor formation of immortalized liver progenitor cells, while knockdown of these proteins inhibited anchorage-independent growth and tumor growth of human liver cancer cell lines. In addition, we found that cells overexpressing hnRNP A2 showed constitutive activation of the Ras-MAPK-ERK pathway. In contrast, knockdown of hnRNP A2 inhibited the Ras-MAPK-ERK pathway and prevented ERK1/2 activation by EGF. Moreover, we found that hnRNP A2 regulates the splicing of A-Raf, reducing the production of a short dominant-negative isoform of A-Raf and elevating the full-length A-Raf transcript. Taken together, our data suggest that hnRNP A2 up-regulation in HCC induces an alternative splicing switch that down-regulates a dominant-negative isoform of A-Raf, leading to activation of the Raf-MEK-ERK pathway and cellular transformation.

Expression microarray analysis reveals alternative splicing of LAMA3 and DST genes in head and neck squamous cell carcinoma

Purpose

Prior studies have demonstrated tumor-specific alternative splicing events in various solid tumor types. The role of alternative splicing in the development and progression of head and neck squamous cell carcinoma (HNSCC) is unclear. Our study queried exon-level expression to implicate splice variants in HNSCC tumors.

Experimental Design

We performed a comparative genome-wide analysis of 44 HNSCC tumors and 25 uvulopalatopharyngoplasty (UPPP) tissue samples at an exon expression level. In our comparison we ranked genes based upon a novel score—the Maximum-Minimum Exon Score (MMES) – designed to predict the likelihood of an alternative splicing event occurring. We validated predicted alternative splicing events using quantitative RT-PCR on an independent cohort.

Results

After MMES scoring of 17,422 genes, the top 900 genes with the highest scores underwent additional manual inspection of expression patterns in a graphical analysis. The genes LAMA3, DST, VEGFC, SDHA, RASIP1, and TP63 were selected for further validation studies because of a high frequency of alternative splicing suggested in our graphical analysis, and literature review showing their biological relevance and known splicing patterns. We confirmed TP63 as having dominant expression of the short DeltaNp63 isoform in HNSCC tumor samples, consistent with prior reports. Two of the six genes (LAMA3 and DST) validated by quantitative RT-PCR for tumor-specific alternative splicing events (Student's t test, P<0.001).

Conclusion

Alternative splicing events of oncologically relevant proteins occur in HNSCC. The number of genes expressing tumor-specific splice variants needs further elucidation, as does the functional significance of selective isoform expression.

Molecular profiling of premalignant lesions in lung squamous cell carcinomas identifies mechanisms involved in stepwise carcinogenesis

Lung squamous cell carcinoma (SCC) is thought to arise from premalignant lesions in the airway epithelium; therefore, studying these lesions is critical for understanding lung carcinogenesis. Previous microarray and sequencing studies designed to discover early biomarkers and therapeutic targets for lung SCC had limited success identifying key driver events in lung carcinogenesis, mostly due to the cellular heterogeneity of patient samples examined and the interindividual variability associated with difficult to obtain airway premalignant lesions and appropriate normal control samples within the same patient. We performed RNA sequencing on laser-microdissected representative cell populations along the SCC pathologic continuum of patient-matched normal basal cells, premalignant lesions, and tumor cells. We discovered transcriptomic changes and identified genomic pathways altered with initiation and progression of SCC within individual patients. We used immunofluorescent staining to confirm gene expression changes in premalignant lesions and tumor cells, including increased expression of SLC2A1, CEACAM5, and PTBP3 at the protein level and increased activation of MYC via nuclear translocation. Cytoband enrichment analysis revealed coordinated loss and gain of expression in chromosome 3p and 3q regions, respectively, during carcinogenesis. This is the first gene expression profiling study of airway premalignant lesions with patient-matched SCC tumor samples. Our results provide much needed information about the biology of premalignant lesions and the molecular changes that occur during stepwise carcinogenesis of SCC, and it highlights a novel approach for identifying some of the earliest molecular changes associated with initiation and progression of lung carcinogenesis within individual patients.

A genome-wide aberrant RNA splicing in patients with acute myeloid leukemia identifies novel potential disease markers and therapeutic targets

PURPOSE

Despite new treatments, acute myeloid leukemia (AML) remains an incurable disease. More effective drug design requires an expanded view of the molecular complexity that underlies AML. Alternative splicing of RNA is used by normal cells to generate protein diversity. Growing evidence indicates that aberrant splicing of genes plays a key role in cancer. We investigated genome-wide splicing abnormalities in AML and based on these abnormalities, we aimed to identify novel potential biomarkers and therapeutic targets.

EXPERIMENTAL DESIGN

We used genome-wide alternative splicing screening to investigate alternative splicing abnormalities in two independent AML patient cohorts [Dana-Farber Cancer Institute (DFCI) (Boston, MA) and University Hospital de Nantes (UHN) (Nantes, France)] and normal donors. Selected splicing events were confirmed through cloning and sequencing analysis, and than validated in 193 patients with AML.

RESULTS

Our results show that approximately 29% of expressed genes genome-wide were differentially and recurrently spliced in patients with AML compared with normal donors bone marrow CD34(+) cells. Results were reproducible in two independent AML cohorts. In both cohorts, annotation analyses indicated similar proportions of differentially spliced genes encoding several oncogenes, tumor suppressor proteins, splicing factors, and heterogeneous-nuclear-ribonucleoproteins, proteins involved in apoptosis, cell proliferation, and spliceosome assembly. Our findings are consistent with reports for other malignances and indicate that AML-specific aberrations in splicing mechanisms are a hallmark of AML pathogenesis.

CONCLUSIONS

Overall, our results suggest that aberrant splicing is a common characteristic for AML. Our findings also suggest that splice variant transcripts that are the result of splicing aberrations create novel disease markers and provide potential targets for small molecules or antibody therapeutics for this disease.

MicroRNA 4423 is a primate-specific regulator of airway epithelial cell differentiation and lung carcinogenesis

Smoking is a significant risk factor for lung cancer, the leading cause of cancer-related deaths worldwide. Although microRNAs are regulators of many airway gene-expression changes induced by smoking, their role in modulating changes associated with lung cancer in these cells remains unknown. Here, we use next-generation sequencing of small RNAs in the airway to identify microRNA 4423 (miR-4423) as a primate-specific microRNA associated with lung cancer and expressed primarily in mucociliary epithelium. The endogenous expression of miR-4423 increases as bronchial epithelial cells undergo differentiation into mucociliary epithelium in vitro, and its overexpression during this process causes an increase in the number of ciliated cells. Furthermore, expression of miR-4423 is reduced in most lung tumors and in cytologically normal epithelium of the mainstem bronchus of smokers with lung cancer. In addition, ectopic expression of miR-4423 in a subset of lung cancer cell lines reduces their anchorage-independent growth and significantly decreases the size of the tumors formed in a mouse xenograft model. Consistent with these phenotypes, overexpression of miR-4423 induces a differentiated-like pattern of airway epithelium gene expression and reverses the expression of many genes that are altered in lung cancer. Together, our results indicate that miR-4423 is a regulator of airway epithelium differentiation and that the abrogation of its function contributes to lung carcinogenesis.

Analysis of the transcriptome in molecular epidemiology studies

The human transcriptome is complex, comprising multiple transcript types, mostly in the form of non-coding RNA (ncRNA). The majority of ncRNA is of the long form (lncRNA, ≥ 200 bp), which plays an important role in gene regulation through multiple mechanisms including epigenetics, chromatin modification, control of transcription factor binding, and regulation of alternative splicing. Both mRNA and ncRNA exhibit additional variability in the form of alternative splicing and RNA editing. All aspects of the human transcriptome can potentially be dysregulated by environmental exposures. Next-generation RNA sequencing (RNA-Seq) is the best available methodology to measure this although it has limitations, including experimental bias. The third phase of the MicroArray Quality Control Consortium project (MAQC-III), also called Sequencing Quality Control (SeQC), aims to address these limitations through standardization of experimental and bioinformatic methodologies. A limited number of toxicogenomic studies have been conducted to date using RNA-Seq. This review describes the complexity of the human transcriptome, the application of transcriptomics by RNA-Seq or microarray in molecular epidemiology studies, and limitations of these approaches including the type of cell or tissue analyzed, experimental variation, and confounding. By using good study designs with precise, individual exposure measurements, sufficient power and incorporation of phenotypic anchors, studies in human populations can identify biomarkers of exposure and/or early effect and elucidate mechanisms of action underlying associated diseases, even at low doses. Analysis of datasets at the pathway level can compensate for some of the limitations of RNA-Seq and, as more datasets become available, will increasingly elucidate the exposure-disease continuum.

CTEN prolongs signaling by EGFR through reducing its ligand-induced degradation

Activation of EGF receptor (EGFR) triggers signaling pathways regulating various cellular events that contribute to tissue development and function. Aberrant activation of EGFR contributes to tumor progression as well as therapeutic resistance in patients with cancer. C-terminal tensin-like (CTEN; TNS4) is a focal adhesion molecule that is a member of the tensin family. Its expression is upregulated by EGF and elevated CTEN mediates EGF-induced cell migration. In the presence of CTEN, we found that EGF treatment elevated the level of EGFR protein but not mRNA. The extended half-life of activated EGFR sustained its signaling cascades. CTEN reduced ligand-induced EGFR degradation by binding to the E3 ubiquitin ligase c-Cbl and decreasing the ubiquitination of EGFR. The Src homology 2 domain of CTEN is not only required for binding to the phosphorylated tyrosine residue at codon 774 of c-Cbl, but is also essential for the tumorigenicity observed in the presence of CTEN. Public database analyses indicated that CTEN mRNA levels are elevated in breast, colon, lung, and pancreas cancers, but not correlated with EGFR mRNA levels in these cancers. In contrast, immunohistochemistry analyses of lung cancer specimens showed that CTEN and EGFR protein levels were positively associated, in support of our finding that CTEN regulates EGFR protein levels through a posttranslational mechanism. Overall, this work defines a function for CTEN in prolonging signaling from EGFR by reducing its ligand-induced degradation.

Antitumor impact of p14ARF on gefitinib-resistant non-small cell lung cancers

Activation of the epidermal growth factor receptor (EGFR) has been observed in many malignant tumors and its constitutive signal transduction facilitates the proliferation of tumors. EGFR-tyrosine kinase inhibitors, such as gefitinib, are widely used as a molecular-targeting agent for the inactivation of EGFR signaling and show considerable therapeutic effect in non-small cell lung cancers harboring activating EGFR mutations. However, prolonged treatment inevitably produces tumors with additional gefitinib-resistant mutations in EGFR, which is a critical issue for current therapeutics. We aimed to characterize the distinct molecular response to gefitinib between the drug-resistant and drug-sensitive lung adenocarcinoma cells in order to learn about therapeutics based on the molecular information. From the quantitative PCR analysis, we found a specific increase in p14(ARF) expression in gefitinib-sensitive lung adenocarcinoma clones, which was absent in gefitinib-resistant clones. Moreover, mitochondria-targeted p14(ARF) triggered the most augmented apoptosis in both clones. We identified the amino acid residues spanning from 38 to 65 as a functional core of mitochondrial p14(ARF) (p14 38-65 a.a.), which reduced the mitochondrial membrane potential and caused caspase-9 activation. The synthesized peptide covering the p14 38-65 a.a. induced growth suppression of the gefitinib-resistant clones without affecting nonneoplastic cells. Notably, transduction of the minimized dose of the p14 38-65 peptide restored the response to gefitinib like that in the sensitive clones. These findings suggest that the region of p14(ARF) 38-65 a.a. is critical in the pharmacologic action of gefitinib against EGFR-mutated lung adenocarcinoma cells and has potential utility in the therapeutics of gefitinib-resistant cancers.

Alternative splicing for diseases, cancers, drugs, and databases

Alternative splicing is a major diversification mechanism in the human transcriptome and proteome. Several diseases, including cancers, have been associated with dysregulation of alternative splicing. Thus, correcting alternative splicing may restore normal cell physiology in patients with these diseases. This paper summarizes several alternative splicing-related diseases, including cancers and their target genes. Since new cancer drugs often target spliceosomes, several clinical drugs and natural products or their synthesized derivatives were analyzed to determine their effects on alternative splicing. Other agents known to have modulating effects on alternative splicing during therapeutic treatment of cancer are also discussed. Several commonly used bioinformatics resources are also summarized.

SRp20: an overview of its role in human diseases

Alternative splicing in mRNA maturation has emerged as a major field of study also because of its implications in various diseases. The SR proteins play an important role in the regulation of this process. Evidence indicates that SRp20 (SFSR3), the smallest member of the SR protein family, is involved in numerous biological processes. Here we review the state-of-the-art of knowledge about the SR proteins, in particular SRp20, in terms of its function and misregulation in human diseases including cancer also in view of its potential as a therapeutic target.

DiffSplice: the genome-wide detection of differential splicing events with RNA-seq

The RNA transcriptome varies in response to cellular differentiation as well as environmental factors, and can be characterized by the diversity and abundance of transcript isoforms. Differential transcription analysis, the detection of differences between the transcriptomes of different cells, may improve understanding of cell differentiation and development and enable the identification of biomarkers that classify disease types. The availability of high-throughput short-read RNA sequencing technologies provides in-depth sampling of the transcriptome, making it possible to accurately detect the differences between transcriptomes. In this article, we present a new method for the detection and visualization of differential transcription. Our approach does not depend on transcript or gene annotations. It also circumvents the need for full transcript inference and quantification, which is a challenging problem because of short read lengths, as well as various sampling biases. Instead, our method takes a divide-and-conquer approach to localize the difference between transcriptomes in the form of alternative splicing modules (ASMs), where transcript isoforms diverge. Our approach starts with the identification of ASMs from the splice graph, constructed directly from the exons and introns predicted from RNA-seq read alignments. The abundance of alternative splicing isoforms residing in each ASM is estimated for each sample and is compared across sample groups. A non-parametric statistical test is applied to each ASM to detect significant differential transcription with a controlled false discovery rate. The sensitivity and specificity of the method have been assessed using simulated data sets and compared with other state-of-the-art approaches. Experimental validation using qRT-PCR confirmed a selected set of genes that are differentially expressed in a lung differentiation study and a breast cancer data set, demonstrating the utility of the approach applied on experimental biological data sets. The software of DiffSplice is available at http://www.netlab.uky.edu/p/bioinfo/DiffSplice.

Abnormal expression of the pre-mRNA splicing regulators SRSF1, SRSF2, SRPK1 and SRPK2 in non small cell lung carcinoma

Splicing abnormalities frequently occur in cancer. A key role as splice site choice regulator is played by the members of the SR (Ser/Arg-rich) family of proteins. We recently demonstrated that SRSF2 is involved in cisplatin-mediated apoptosis of human lung carcinoma cell lines. In this study, by using immunohistochemistry, we demonstrate that the SR proteins SRSF1 and SRSF2 are overexpressed in 63% and 65% of lung adenocarcinoma (ADC) as well as in 68% and 91% of squamous cell lung carcinoma (SCC), respectively, compared to normal lung epithelial cells. In addition, we show that SRSF2 overexpression correlates with high level of phosphorylated SRSF2 in both ADC (p<0.0001) and SCC (p = 0.02), indicating that SRSF2 mostly accumulates under a phosphorylated form in lung tumors. Consistently, we further show that the SR-phosphorylating kinases SRPK1 and SRPK2 are upregulated in 92% and 94% of ADC as well as in 72% and 68% of SCC, respectively. P-SRSF2 and SRPK2 scores are correlated in ADC (p = 0.01). Using lung adenocarcinoma cell lines, we demonstrate that SRSF1 overexpression leads to a more invasive phenotype, evidenced by activation of PI3K/AKT and p42/44MAPK signaling pathways, increased growth capacity in soft agar, acquisition of mesenchymal markers such as E cadherin loss, vimentin and fibronectin gain, and increased resistance to chemotherapies. Finally, we provide evidence that high levels of SRSF1 and P-SRSF2 proteins are associated with extensive stage (III–IV) in ADC. Taken together, these results indicate that a global deregulation of pre-mRNA splicing regulators occurs during lung tumorigenesis and does not predict same outcome in both Non Small Cell Lung Carcinoma histological sub-types, likely contributing to a more aggressive phenotype in adenocarcinoma.

Noncoder: a web interface for exon array-based detection of long non-coding RNAs

Due to recent technical developments, a high number of long non-coding RNAs (lncRNAs) have been discovered in mammals. Although it has been shown that lncRNAs are regulated differently among tissues and disease statuses, functions of these transcripts are still unknown in most cases. GeneChip Exon 1.0 ST Arrays (exon arrays) from Affymetrix, Inc. have been used widely to profile genome-wide expression changes and alternative splicing of protein-coding genes. Here, we demonstrate that re-annotation of exon array probes can be used to profile expressions of tens of thousands of lncRNAs. With this annotation, a detailed inspection of lncRNAs and their isoforms is possible. To allow for a general usage to the research community, we developed a user-friendly web interface called ‘noncoder’. By uploading CEL files from exon arrays and with a few mouse clicks and parameter settings, exon array data will be normalized and analysed to identify differentially expressed lncRNAs. Noncoder provides the detailed annotation information of lncRNAs and is equipped with unique features to allow for an efficient search for interesting lncRNAs to be studied further. The web interface is available at http://noncoder.mpi-bn.mpg.de.

Identification of novel deregulated RNA metabolism-related genes in non-small cell lung cancer

Lung cancer is a leading cause of cancer death worldwide. Several alterations in RNA metabolism have been found in lung cancer cells; this suggests that RNA metabolism-related molecules are involved in the development of this pathology. In this study, we searched for RNA metabolism-related genes that exhibit different expression levels between normal and tumor lung tissues. We identified eight genes differentially expressed in lung adenocarcinoma microarray datasets. Of these, seven were up-regulated whereas one was down-regulated. Interestingly, most of these genes had not previously been associated with lung cancer. These genes play diverse roles in mRNA metabolism: three are associated with the spliceosome (ASCL3L1, SNRPB and SNRPE), whereas others participate in RNA-related processes such as translation (MARS and MRPL3), mRNA stability (PCBPC1), mRNA transport (RAE), or mRNA editing (ADAR2, also known as ADARB1). Moreover, we found a high incidence of loss of heterozygosity at chromosome 21q22.3, where the ADAR2 locus is located, in NSCLC cell lines and primary tissues, suggesting that the downregulation of ADAR2 in lung cancer is associated with specific genetic losses. Finally, in a series of adenocarcinoma patients, the expression of five of the deregulated genes (ADAR2, MARS, RAE, SNRPB and SNRPE) correlated with prognosis. Taken together, these results support the hypothesis that changes in RNA metabolism are involved in the pathogenesis of lung cancer, and identify new potential targets for the treatment of this disease.

SplicerEX: a tool for the automated detection and classification of mRNA changes from conventional and splice-sensitive microarray expression data

The key postulate that one gene encodes one protein has been overhauled with the discovery that one gene can generate multiple RNA transcripts through alternative mRNA processing. In this study, we describe SplicerEX, a novel and uniquely motivated algorithm designed for experimental biologists that (1) detects widespread changes in mRNA isoforms from both conventional and splice sensitive microarray data, (2) automatically categorizes mechanistic changes in mRNA processing, and (3) mitigates known technological artifacts of exon array-based detection of alternative splicing resulting from 5' and 3' signal attenuation, background detection limits, and saturation of probe set signal intensity. In this study, we used SplicerEX to compare conventional and exon-based Affymetrix microarray data in a model of EBV transformation of primary human B cells. We demonstrated superior detection of 3'-located changes in mRNA processing by the Affymetrix U133 GeneChip relative to the Human Exon Array. SplicerEX-identified exon-level changes in the EBV infection model were confirmed by RT-PCR and revealed a novel set of EBV-regulated mRNA isoform changes in caspases 6, 7, and 8. Finally, SplicerEX as compared with MiDAS analysis of publicly available microarray data provided more efficiently categorized mRNA isoform changes with a significantly higher proportion of hits supported by previously annotated alternative processing events. Therefore, SplicerEX provides an important tool for the biologist interested in studying changes in mRNA isoform usage from conventional or splice-sensitive microarray platforms, especially considering the expansive amount of archival microarray data generated over the past decade. SplicerEX is freely available upon request.

Downregulation of splicing factor SRSF3 induces p53β, an alternatively spliced isoform of p53 that promotes cellular senescence

Most human pre-mRNA transcripts are alternatively spliced, but the significance and fine-tuning of alternative splicing in different biological processes is only starting to be understood. SRSF3 (SRp20) is a member of a highly conserved family of splicing factors that have critical roles in key biological processes, including tumor progression. Here, we show that SRSF3 regulates cellular senescence, a p53-mediated process to suppress tumorigenesis, through TP53 alternative splicing. Downregulation of SRSF3 was observed in normal human fibroblasts undergoing replicative senescence, and was associated with the upregulation of p53β, an alternatively spliced isoform of p53 that promotes p53-mediated senescence. Knockdown of SRSF3 by short interfering RNA (siRNA) in early-passage fibroblasts induced senescence, which was associated with elevated expression of p53β at mRNA and protein levels. Knockdown of p53 partially rescued SRSF3-knockdown-induced senescence, suggesting that SRSF3 acts on p53-mediated cellular senescence. RNA pulldown assays demonstrated that SRSF3 binds to an alternatively spliced exon uniquely included in p53β mRNA through the consensus SRSF3-binding sequences. RNA crosslinking and immunoprecipitation assays (CLIP) also showed that SRSF3 in vivo binds to endogenous p53 pre-mRNA at the region containing the p53β-unique exon. Splicing assays using a transfected TP53 minigene in combination with siRNA knockdown of SRSF3 showed that SRSF3 functions to inhibit the inclusion of the p53β-unique exon in splicing of p53 pre-mRNA. These data suggest that downregulation of SRSF3 represents an endogenous mechanism for cellular senescence that directly regulates the TP53 alternative splicing to generate p53β. This study uncovers the role for general splicing machinery in tumorigenesis, and suggests that SRSF3 is a direct regulator of p53.