Differentially expressed alternatively spliced genes in malignant pleural mesothelioma identified using massively parallel transcriptome sequencing

Prognostic risk assessment model for alternative splicing events and splicing factors in malignant pleural mesothelioma

BACKGROUND

Malignant pleural mesothelioma (MPM) is a rare and highly malignant thoracic tumor. Although alternative splicing (AS) is associated with tumor prognosis, the prognostic significance of AS in MPM is unknown.

METHODS

Transcriptomic data, clinical information, and splicing percentage values for MPM were obtained from The Cancer Genome Atlas (TCGA) and TCGA SpliceSeq databases. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analyses were performed to establish a model affecting the prognosis of MPM. Survival and ROC analyses were used to test the effects of the prognostic model. LASSO/multivariate Cox analysis was used to construct the MPM prognostic splicing factor (SF) model. The SF-AS interaction network was analyzed using Spearman correlation and visualized using Cytoscape. The association between the MPM prognostic SF model and drug sensitivity to chemotherapeutic agents such as cisplatin was analyzed using pRRophetic.R.

RESULTS

The LASSO/multivariate Cox analysis identified 41 AS events and 2 SFs that were mostly associated with survival. Nine prognostic prediction models (i.e., seven types of AS model, total AS model, and SF model) were developed. An MPM prognostic SF-AS regulatory network was subsequently constructed with decreased drug sensitivity in the SF model high-risk group (p = 0.025).

CONCLUSION

This study provides the first comprehensive analysis of the prognostic value of AS events and SFs in MPM. The SF-AS regulatory network established in this study and our drug sensitivity analysis using the SF model may provide novel targets for pharmacological studies of MPM.

Preclinical Models and Resources to Facilitate Basic Science Research on Malignant Mesothelioma - A Review

Malignant mesothelioma is an aggressive cancer with poor prognosis, predominantly caused by human occupational exposure to asbestos. The global incidence of mesothelioma is predicted to increase as a consequence of continued exposure to asbestos from a variety of sources, including construction material produced in the past in developed countries, as well as those currently being produced in developing countries. Mesothelioma typically develops after a long latency period and consequently it is often diagnosed in the clinic at an advanced stage, at which point standard care of treatment, such as chemo- and radio-therapy, are largely ineffective. Much of our current understanding of mesothelioma biology, particularly in relation to disease pathogenesis, diagnosis and treatment, can be attributed to decades of preclinical basic science research. Given the postulated rising incidence in mesothelioma cases and the limitations of current diagnostic and treatment options, continued preclinical research into mesothelioma is urgently needed. The ever-evolving landscape of preclinical models and laboratory technology available to researchers have made it possible to study human disease with greater precision and at an accelerated rate. In this review article we provide an overview of the various resources that can be exploited to facilitate an enhanced understanding of mesothelioma biology and their applications to research aimed to improve the diagnosis and treatment of mesothelioma. These resources include cell lines, animal models, mesothelioma-specific biobanks and modern laboratory techniques/technologies. Given that different preclinical models and laboratory technologies have varying limitations and applications, they must be selected carefully with respect to the intended objectives of the experiments. This review therefore aims to provide a comprehensive overview of the various preclinical models and technologies with respect to their advantages and limitations. Finally, we will detail about a highly valuable preclinical laboratory resource to curate high quality mesothelioma biospecimens for research; the biobank. Collectively, these resources are essential to the continued advancement of precision medicine to curtail the increasing health burden caused by malignant mesothelioma.

Identification of Overexpressed Genes in Malignant Pleural Mesothelioma

Malignant pleural mesothelioma (MPM) is a fatal tumor lacking effective therapies. The characterization of overexpressed genes could constitute a strategy for identifying drivers of tumor progression as targets for novel therapies. Thus, we performed an integrated gene-expression analysis on RNAseq data of 85 MPM patients from TCGA dataset and reference samples from the GEO. The gene list was further refined by using published studies, a functional enrichment analysis, and the correlation between expression and patients' overall survival. Three molecular signatures defined by 15 genes were detected. Seven genes were involved in cell adhesion and extracellular matrix organization, with the others in control of the mitotic cell division or apoptosis inhibition. Using Western blot analyses, we found that ADAMTS1, PODXL, CIT, KIF23, MAD2L1, TNNT1, and TRAF2 were overexpressed in a limited number of cell lines. On the other hand, interestingly, CTHRC1, E-selectin, SPARC, UHRF1, PRSS23, BAG2, and MDK were abundantly expressed in over 50% of the six MPM cell lines analyzed. Thus, these proteins are candidates as drivers for sustaining the tumorigenic process. More studies with small-molecule inhibitors or silencing RNAs are fully justified and need to be undertaken to better evaluate the cancer-driving role of the targets herewith identified.

Malignant Pleural Mesothelioma: Genetic and Microenviromental Heterogeneity as an Unexpected Reading Frame and Therapeutic Challenge

Mesothelioma is a malignancy of serosal membranes including the peritoneum, pleura, pericardium and the tunica vaginalis of the testes. Malignant mesothelioma (MM) is a rare disease with a global incidence in countries like Italy of about 1.15 per 100,000 inhabitants. Malignant Pleural Mesothelioma (MPM) is the most common form of mesothelioma, accounting for approximately 80% of disease. Although rare in the global population, mesothelioma is linked to industrial pollutants and mineral fiber exposure, with approximately 80% of cases linked to asbestos. Due to the persistent asbestos exposure in many countries, a worldwide progressive increase in MPM incidence is expected for the current and coming years. The tumor grows in a loco-regional pattern, spreading from the parietal to the visceral pleura and invading the surrounding structures that induce the clinical picture of pleural effusion, pain and dyspnea. Distant spreading and metastasis are rarely observed, and most patients die from the burden of the primary tumor. Currently, there are no effective treatments for MPM, and the prognosis is invariably poor. Some studies average the prognosis to be roughly one-year after diagnosis. The uniquely poor mutational landscape which characterizes MPM appears to derive from a selective pressure operated by the environment; thus, inflammation and immune response emerge as key players in driving MPM progression and represent promising therapeutic targets. Here we recapitulate current knowledge on MPM with focus on the emerging network between genetic asset and inflammatory microenvironment which characterize the disease as amenable target for novel therapeutic approaches.

Identification of a Combined RNA Prognostic Signature in Adenocarcinoma of the Lung

Background

Adenocarcinoma of the lung is a type of non-small cell lung cancer (NSCLC). Clinical outcome is associated with tumor grade, stage, and subtype. This study aimed to identify RNA expression profiles, including long noncoding RNA (lncRNA), microRNA (miRNA), and mRNA, associated with clinical outcome in adenocarcinoma of the lung using bioinformatics data.

Material/Methods

The miRNA and mRNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database, and lncRNA expression profiles were downloaded from The Atlas of Noncoding RNAs in Cancer (TANRIC) database. The independent dataset, the Gene Expression Omnibus (GEO) accession dataset, GSE81089, was used. RNA expression profiles were used to identify comprehensive prognostic RNA signatures based on patient survival time.

Results

From 7,704 lncRNAs, 787 miRNAs, and 28,937 mRNAs of 449 patients, four joint RNA molecular signatures were identified, including RP11-909N17.2, RP11-14N7.2 (lncRNAs), MIR139 (miRNA), KLHDC8B (mRNA). The random forest (RF) classifier was used to test the prediction ability of patient survival risk and showed a good predictive accuracy of 71% and also showed a significant difference in overall survival (log-rank P=0.0002; HR, 3.54; 95% CI, 1.74–7.19). The combined RNA signature also showed good performance in the identification of patient survival in the validation and independent datasets.

Conclusions

This study identified four RNA sequences as a prognostic molecular signature in adenocarcinoma of the lung, which may also provide an increased understanding of the molecular mechanisms underlying the pathogenesis of this malignancy.

Screening of important lncRNAs associated with the prognosis of lung adenocarcinoma, based on integrated bioinformatics analysis

The study aimed to elucidate the mechanisms underlying the occurrence and development of lung adenocarcinoma, and to reveal long non-coding RNA (lncRNA) prognostic factors to identify patients at high risk of disease recurrence or metastasis. Based on extensive RNA sequencing data and clinical survival prognosis information from patients with lung adenocarcinoma, obtained from The Cancer Genome Atlas and the Gene Expression Omnibus databases, a co-expression network of lncRNAs with different expression levels was built using weighted correlation network analysis and MetaDE.ES. The prognostic lncRNAs were identified using the Cox proportional hazards model and Kaplan-Meier survival curves to construct a risk scoring system. The reliability of the system was confirmed in validation datasets. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed on the genes significantly associated with the prognostic lncRNAs using gene set enrichment analysis. A total of 58 and 1,633 differentially expressed lncRNAs and mRNAs were identified, respectively. Considering the module stability, annotation, correlation between modules and clinical factors, and the differential expression levels of lncRNAs, 32 differentially expressed lncRNAs were selected from the brown, red, blue, green and yellow modules for subsequent survival analysis. A signature-based risk scoring system involving five lncRNAs [DIAPH2 antisense RNA 1, FOXN3 antisense RNA 2, long intergenic non-protein coding RNA 652, maternally expressed 3 and RHPN1 antisense RNA 1 (head to head)] was developed. The system successfully distinguished between low- and high-risk prognostic samples. System effectiveness was further verified using two independent validation datasets. Further KEGG pathway analysis indicated that the target genes of the five prognostic lncRNAs were associated with a number of cellular processes and signaling pathways, including the cell receptor-mediated signaling and cell adhesion pathways. A five-lncRNA signature predicts the prognosis of patients with lung adenocarcinoma. These prognostic lncRNAs may be potential diagnostic markers. The present results may help elucidate the pathogenesis of lung adenocarcinoma.

Genomics and Epigenetics of Malignant Mesothelioma

Malignant mesothelioma is an aggressive and lethal asbestos-related disease. Diagnosis of malignant mesothelioma is particularly challenging and is further complicated by the lack of disease subtype-specific markers. As a result, it is especially difficult to distinguish malignant mesothelioma from benign reactive mesothelial proliferations or reactive fibrosis. Additionally, mesothelioma diagnoses can be confounded by other anatomically related tumors that can invade the pleural or peritoneal cavities, collectively resulting in delayed diagnoses and greatly affecting patient management. High-throughput analyses have uncovered key genomic and epigenomic alterations driving malignant mesothelioma. These molecular features have the potential to better our understanding of malignant mesothelioma biology as well as to improve disease diagnosis and patient prognosis. Genomic approaches have been instrumental in identifying molecular events frequently occurring in mesothelioma. As such, we review the discoveries made using high-throughput technologies, including novel insights obtained from the analysis of the non-coding transcriptome, and the clinical potential of these genetic and epigenetic findings in mesothelioma. Furthermore, we aim to highlight the potential of these technologies in the future clinical applications of the novel molecular features in malignant mesothelioma.

Profiling of the silica-induced molecular events in lung epithelial cells using the RNA-Seq approach

Silicosis is a prolonged, irreversible and incurable occupational disease, and there is a significant number of newly diagnosed cases every year in Hong Kong. Due to the long latency of the disease, the diagnosis can be missed until detailed clinical examination at a later stage. For a better control of this deadly disease, detailing the pro-inflammatory and fibrotic events in the macrophage would be instrumental in understanding the pathogenesis of the disease and essential for the significant biomarkers discovery. In this in vitro study, human cell line model A549 lung epithelial cells were used. The immediate molecular events underneath the activation of quartz silica polymorphs were followed in a time course of 0, 0.5, 2, 8, 16 and 24 h. The transcriptome library was prepared and subjected to RNA-Seq analysis. Data analysis was performed by pathway analysis tools and verified by real-time PCR. The results showed that triggered genes were mainly found in the immune response and inflammatory pathways. An interesting finding was the association of the DNA-binding protein inhibitor (ID) family in the silica exposure to lung cells. The linkage of ID1, ID2 and ID3 to cancer may rationalize themselves to be the markers indicating an early response of silicosis. However, further studies are required to consolidate the roles of these genes in silicosis. Copyright © 2017 John Wiley & Sons, Ltd.

Genetics and epigenetics in small intestinal neuroendocrine tumours

Neuroendocrine tumour of the small intestine (SI-NET), formerly known as midgut carcinoid tumour, is the most common small intestinal malignancy. The incidence is rising, with recent reports of 0.67 per 100 000 in the USA and 1.12 per 100 000 in Sweden. SI-NETs often present a challenge in terms of diagnosis and treatment, as patients often have widespread disease and are beyond cure by surgery. Somatostatin analogues provide the mainstay of medical treatment to control hormonal excess and increase the time to progression. Despite overall favourable prognosis (5-year overall survival of 65%), there is a need to find markers to identify both patients with worse outcome and new targets for therapy. Loss on chromosome 18 has been reported in 60-90% of SI-NETs, but mutated genes on this chromosome have failed detection. Recently, a putative tumour suppressor role has been suggested for TCEB3C occurring at 18q21 (encoding elongin A3), which may undergo epigenetic repression. CDKN1B has recently been revealed as the only recurrently mutated gene in SI-NETs but, with a frequency as low as 8%, its role as a driver in SI-NET development may be questioned. Integrated genomewide analysis including exome and whole-genome sequencing, gene expression, DNA methylation and copy number analysis has identified three novel molecular subtypes of SI-NET with differing clinical outcome. DNA methylation analysis has demonstrated that SI-NETs have significant epigenetic dysregulation in 70-80% of tumours. In this review, we focus on understanding of the genetic, epigenetic and molecular events that lead to development and progression of SI-NETs.

The Genetic Landscape of Malignant Pleural Mesothelioma: Results from Massively Parallel Sequencing

Malignant pleural mesothelioma (MPM) is a rare yet aggressive tumor that is causally associated with-mostly professional-asbestos exposure. Given the long latency between exposure and disease, and because asbestos is still being used, MPM will remain a global health issue for decades to come. Notwithstanding the increasing incidence of MPM and the fact that patients with MPM face a poor prognosis, currently available treatment options are limited. To enable the development of novel targeted therapies, identification of the genetic alterations underlying MPM will be crucial. The first studies reporting on the genomic background of MPM identified recurrent somatic mutations in a number of tumor suppressor genes (i.e., cyclin-dependent kinase inhibitor 2A gene [CDKN2A], neurofibromin 2 (merlin) gene [NF2], and BRCA1 associated protein 1 gene [BAP1]). More recently, massively parallel sequencing strategies have been used and have provided a more genome-wide view on the genetic landscape of MPM. This review summarizes their results, describing alterations that cluster mainly in four pathways: the tumor protein p53/DNA repair, cell cycle, mitogen-activated protein kinase, and phosphoinisitide 3-kinase (PI3K)/AKT pathways. As these pathways are important during tumor development, they provide interesting candidates for targeting with novel drugs.

Comprehensive genomic analysis of malignant pleural mesothelioma identifies recurrent mutations, gene fusions and splicing alterations

We analyzed transcriptomes (n = 211), whole exomes (n = 99) and targeted exomes (n = 103) from 216 malignant pleural mesothelioma (MPM) tumors. Using RNA-seq data, we identified four distinct molecular subtypes: sarcomatoid, epithelioid, biphasic-epithelioid (biphasic-E) and biphasic-sarcomatoid (biphasic-S). Through exome analysis, we found BAP1, NF2, TP53, SETD2, DDX3X, ULK2, RYR2, CFAP45, SETDB1 and DDX51 to be significantly mutated (q-score ≥ 0.8) in MPMs. We identified recurrent mutations in several genes, including SF3B1 (∼2%; 4/216) and TRAF7 (∼2%; 5/216). SF3B1-mutant samples showed a splicing profile distinct from that of wild-type tumors. TRAF7 alterations occurred primarily in the WD40 domain and were, except in one case, mutually exclusive with NF2 alterations. We found recurrent gene fusions and splice alterations to be frequent mechanisms for inactivation of NF2, BAP1 and SETD2. Through integrated analyses, we identified alterations in Hippo, mTOR, histone methylation, RNA helicase and p53 signaling pathways in MPMs.

Molecular Analysis by Gene Expression of Mitochondrial ATPase Subunits in Papillary Thyroid Cancer: Is ATP5E Transcript a Possible Early Tumor Marker?

BACKGROUND

Cancer development involves an "injury" to the respiratory machinery (Warburg effect) due to decreased or impaired mitochondrial function. This circumstance results in a down regulation of some of the ATPase subunits of the malignant tissue. The objective of this work was to assess and compare the relative expression of mRNA of mitochondrial ATPase subunits between samples of thyroid cancer and benign nodules.

MATERIAL AND METHODS

Samples from 31 patients who had an operation for PTC at the General Hospital of Mexico were snap-frozen and stored at -70°C. Thirty-five patients who had an operation for benign tumors were also included in the study. mRNA expression levels of alpha, beta, gamma, and epsilon subunits of F1 and "c12" of subunit Fo were determined by real-time RT-PCR (by duplicate), in order to determine if abnormal expression of these genes could partially explain the Warburg effect in papillary thyroid cancer (PTC).

RESULTS

ATP5E transcript alteration (down-expression) was highly associated to PTC diagnosis OR=11.76 (95% confidence interval, 1.245-237.98; p=0.04).

CONCLUSIONS

Relative down-expression of ATP5E transcript was highly associated with PTC diagnosis. This transcript alteration may be used as a tumoral marker in papillary thyroid cancer.

A platform independent RNA-Seq protocol for the detection of transcriptome complexity

BACKGROUND

Recent studies have demonstrated an unexpected complexity of transcription in eukaryotes. The majority of the genome is transcribed and only a little fraction of these transcripts is annotated as protein coding genes and their splice variants. Indeed, most transcripts are the result of antisense, overlapping and non-coding RNA expression. In this frame, one of the key aims of high throughput transcriptome sequencing is the detection of all RNA species present in the cell and the first crucial step for RNA-seq users is represented by the choice of the strategy for cDNA library construction. The protocols developed so far provide the utilization of the entire library for a single sequencing run with a specific platform.

RESULTS

We set up a unique protocol to generate and amplify a strand-specific cDNA library representative of all RNA species that may be implemented with all major platforms currently available on the market (Roche 454, Illumina, ABI/SOLiD). Our method is reproducible, fast, easy-to-perform and even allows to start from low input total RNA. Furthermore, we provide a suitable bioinformatics tool for the analysis of the sequences produced following this protocol.

CONCLUSION

We tested the efficiency of our strategy, showing that our method is platform-independent, thus allowing the simultaneous analysis of the same sample with different NGS technologies, and providing an accurate quantitative and qualitative portrait of complex whole transcriptomes.

From human genome to cancer genome: the first decade

The realization that cancer progression required the participation of cellular genes provided one of several key rationales, in 1986, for embarking on the human genome project. Only with a reference genome sequence could the full spectrum of somatic changes leading to cancer be understood. Since its completion in 2003, the human reference genome sequence has fulfilled its promise as a foundational tool to illuminate the pathogenesis of cancer. Herein, we review the key historical milestones in cancer genomics since the completion of the genome, and some of the novel discoveries that are shaping our current understanding of cancer.

A review of transcriptome studies combined with data mining reveals novel potential markers of malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM), a cancer of the serosal pleural cavities, is one of the most aggressive human tumors. In order to identify genes crucial for the onset and progression of MPM, we performed an extensive literature review focused on transcriptome studies (RTS). In this kind of studies a great number of transcripts are analyzed without formulating any a priori hypothesis, thus preventing any bias coming from previously established knowledge that could lead to an over-representation of specific genes. Each study was thoroughly analyzed paying particular attention to: (i) the employed microarray platform, (ii) the number and type of samples, (iii) the fold-change, and (iv) the statistical significance of deregulated genes. We also performed data mining (DM) on MPM using three different tools (Coremine, SNPs3D, and GeneProspector). Results from RTS and DM were compared in order to restrict the number of genes potentially deregulated in MPM. Our main requirement for a gene to be a "mesothelioma gene" (MG) is to be reproducibly deregulated among independent studies and confirmed by DM. A list of MGs was thus produced, including PTGS2, BIRC5, ASS1, JUNB, MCM2, AURKA, FGF2, MKI67, CAV1, SFRP1, CCNB1, CDK4, and MSLN that might represent potential novel biomarkers or therapeutic targets for MPM. Moreover, it was found a sub-group of MGs including ASS1, JUNB, PTGS2, EEF2, SULF1, TOP2A, AURKA, BIRC5, CAV1, IFITM1, PCNA, and PKM2 that could explain, at least in part, the mechanisms of resistance to cisplatin, one first-line chemotherapeutic drug used for the disease. Finally, the pathway analysis showed that co-regulation networks related to the cross-talk between MPM and its micro-environment, in particular involving the adhesion molecules, integrins, and cytokines, might have an important role in MPM. Future studies are warranted to better characterize the role played by these genes in MPM.