Comprehensive Analysis of Splicing Factor and Alternative Splicing Event to Construct Subtype-Specific Prognosis-Predicting Models for Breast Cancer.
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ABSTRACT:
SUBMITTER: Zhang H
PROVIDER: S-EPMC8497829 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background:Alternative splicing (AS) is important in the regulation of gene expression and aberrant AS is emerging as a major factor in the pathogenesis of human conditions, including cancer. Triple-negative breast cancer (TNBC) is the most challenging subtype of breast cancer with strong invasion, high rate of metastasis, and poor prognosis. Here we report a systematic profiling of aberrant AS in TNBC. Methods:The percent spliced in (PSI) values for AS events in 151 TNBC patients were obtained from The Cancer Genome Atlas (TCGA) SpliceSeq database. Univariate Cox and stepwise Multivariate Cox regression analyses were conducted to find the best prognostic AS model. Splicing regulatory networks were constructed by prognosis-related spliceosome and aberrant AS events. Additionally, pathway enrichment and gene set enrichment analysis (GSEA) were further employed to reveal the significant pathways for prognosis-related AS genes. Finally, splicing regulatory networks were constructed via Spearman's rank correlation coefficients between prognosis-related AS events and splicing factor expressions. Results:A total of 1,397 prognosis-associated AS events were identified in TNBC. The majority of the parent genes of prognostic AS events exhibited direct interactions to each other in the STRING gene network. Pathways of focal adhesion (p < 0.001), RNA splicing (p = 0.007), homologous recombination (p = 0.042) and ECM-receptor interaction (p = 0.046) were found to be significantly enriched for prognosis-related AS. Additionally, the area under curve (AUC) of the best AS prognostic predictor model reached 0.949, showing a powerful capability to predict outcomes. The Exon Skip (ES) type of AS events displayed more robust and efficient capacity in predicting performance than any other specific AS events type in terms of prognosis. The ES AS signature might confer a strong oncogenic phenotype in the high-risk group with elevated activities in cell cycle and SUMOylating pathways of tumorigenesis, while programmed cell death and metabolism pathways were found to be enriched in the low-risk group of TNBC. The splicing correlation network also revealed a regulatory mode of prognostic splicing factors (SFs) in TNBC. Conclusion:Our analysis of AS events in TNBC could not only contribute to elucidating the tumorigenesis mechanism of AS but also provide clues to uncovering underlying prognostic biomarkers and therapeutic targets for further study.
| S-EPMC7302061 | biostudies-literature
Project description:Emerging evidence suggests that alternative splicing (AS) is modified in cancer and is associated with cancer progression. Systematic analysis of AS signature in glioblastoma (GBM) is lacking and is greatly needed. We profiled genome-wide AS events in 498 GBM patients in TCGA using RNA-seq data, and splicing network and prognostic predictor were built by integrated bioinformatics analysis. Among 45,610 AS events in 10,434 genes, we detected 1,829 AS events in 1,311 genes, and 1,667 AS events in 1,146 genes that were significantly associated with overall survival and disease-free survival of GBM patients, respectively. Five potential feature genes, S100A4, ECE2, CAST, ASPH, and LY6K, were discovered after network mining as well as correlation analysis between AS and gene expression, most of which were related to carcinogenesis and development. Multivariate survival model analysis indicated that these five feature genes could classify the prognosis at AS event and gene expression level. This report opens up a new avenue for exploration of the pathogenesis of GBM through AS, thus more precisely guiding clinical treatment and prognosis judgment.
| S-EPMC6769083 | biostudies-literature
Project description:Emerging evidence suggests that the dysregulation of autophagy-related genes (ARGs) is coupled with the carcinogenesis and progression of breast cancer (BRCA). We constructed three subtype-specific risk models using differentially expressed ARGs. In Luminal, Her-2, and Basal-like BRCA, four- (BIRC5, PARP1, ATG9B, and TP63), three- (ITPR1, CCL2, and GAPDH), and five-gene (PRKN, FOS, BAX, IFNG, and EIF4EBP1) risk models were identified, which all have a receiver operating characteristic > 0.65 in the training and testing dataset. Multivariable Cox analysis showed that those risk models can accurately and independently predict the overall survival of BRCA patients. Comprehensive analysis showed that the 12 identified ARGs were correlated with the overall survival of BRCA patients; six of the ARGs (PARP1, TP63, CCL2, GAPDH, FOS, and EIF4EBP1) were differentially expressed between BRCA and normal breast tissue at the protein level. In addition, the 12 identified ARGs were highly interconnected and displayed high frequency of copy number variation in BRCA samples. Gene set enrichment analysis suggested that the deactivation of the immune system was the important driving force for the progression of Basal-like BRCA. This study demonstrated that the 12 ARG signatures were potential multi-dimensional biomarkers for the diagnosis, prognosis, and treatment of BRCA.
| S-EPMC7377895 | biostudies-literature
Project description:As a key mechanism, alternative splicing (AS) plays a role in the cancer initiation and development. However, in papillary thyroid cancer (PTC), data for the comprehensive AS event profile and its clinical implications are lacking. Herein, a genome-wide AS event profiling using RNA-Seq data and its correlation with matched clinical information was performed using a 389 PTC patient cohort from the project of The Cancer Genome Atlas (TCGA). We identified 1,925 cancer-associated AS events (CASEs) by comparing paired tumors and neighboring healthy tissues. Parent genes with CASEs remarkably enriched in the pathways were linked with carcinogenesis, such as P53, KRAS, IL6-JAK-STAT3, apoptosis, and MYC signaling. The regulatory networks of AS implied an obvious correlation between the expression of splicing factor and CASE. We identified eight CASEs as predictors for overall survival (OS) and disease-free survival (DFS). The established risk score model based on DFS-associated CASEs successfully predicted the prognosis of PTC patients. From the unsupervised clustering analysis results, it is found that different clusters based on AS correlated with prognosis, molecular features, and immune characteristics. Taken together, the comprehensive genome-wide AS landscape analysis in PTC showed new AS events linked with tumorigenesis and prognosis, which provide new insights for clinical monitoring and therapy for PTC.
| S-EPMC8544310 | biostudies-literature
Project description:Alternative splicing (AS) generates extensive transcriptomic and proteomic complexity. However, the functions of species- and lineage-specific splice variants are largely unknown. Here, we show that mammalian-specific skipping of exon 9 of PTBP1 alters its splicing regulatory activities and affects the inclusion levels of numerous exons. During neurogenesis, skipping of exon 9 reduces PTBP1 repressive activity so as to facilitate activation of a brain-specific AS program. Engineered skipping of the orthologous exon in chicken cells induces a large number of mammalian-like AS changes in PTBP1 target exons. These results thus reveal that a single exon skipping event in an RNA binding regulator directs numerous AS changes between species. The results further suggest that these changes contributed to evolutionary differences in the formation of vertebrate nervous systems. This study contains two sets of samples: (Set 1) mRNA profiling of human 293 cells subjected to four different conditions in two biological replicates: non-targetting control siRNA, PTBP1 and PTBP2 siRNA, PTBP1 and PTBP2 siRNA with overexpression of full-length human PTBP1, PTBP1 and PTBP2 siRNA with overexpression of exon-excluded human PTBP1. (Set 2) mRNA profiling of chicken DT40 cells with 3 genotypes in two bioligcal replicates: wildtype cells, cells with PTBP1 exon 8 (orthologous to human PTBP1 exon 9) deleted in one allele, and cells with PTBP1 exon 8 deleted in both alleles.
2015-09-01 | E-GEOD-69656 | biostudies-arrayexpress
Project description:MotivationAdvancements in sequencing technologies have highlighted the role of alternative splicing (AS) in increasing transcriptome complexity. This role of AS, combined with the relation of aberrant splicing to malignant states, motivated two streams of research, experimental and computational. The first involves a myriad of techniques such as RNA-Seq and CLIP-Seq to identify splicing regulators and their putative targets. The second involves probabilistic models, also known as splicing codes, which infer regulatory mechanisms and predict splicing outcome directly from genomic sequence. To date, these models have utilized only expression data. In this work, we address two related challenges: Can we improve on previous models for AS outcome prediction and can we integrate additional sources of data to improve predictions for AS regulatory factors.ResultsWe perform a detailed comparison of two previous modeling approaches, Bayesian and Deep Neural networks, dissecting the confounding effects of datasets and target functions. We then develop a new target function for AS prediction in exon skipping events and show it significantly improves model accuracy. Next, we develop a modeling framework that leverages transfer learning to incorporate CLIP-Seq, knockdown and over expression experiments, which are inherently noisy and suffer from missing values. Using several datasets involving key splice factors in mouse brain, muscle and heart we demonstrate both the prediction improvements and biological insights offered by our new models. Overall, the framework we propose offers a scalable integrative solution to improve splicing code modeling as vast amounts of relevant genomic data become available.Availability and implementationCode and data available at: majiq.biociphers.org/jha_et_al_2017/.Contactyosephb@upenn.edu.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC5870723 | biostudies-literature
Project description:PurposeTriple-negative breast cancer (TNBC) is a type of breast cancer (BC) showing a high recurrence ratio and a low survival probability, which requires novel actionable molecular targets. The involvement of alternative splicing (AS) in TNBC promoted us to study the potential roles of AS events in the survival prognosis of TNBC patients.MethodsA total of 150 TNBC patients from The Cancer Genome Atlas (TCGA) were involved in this work. To study the effects of AS in the recurrence-free survival (RFS) prognosis of TNBC, we performed the analyses as follows. First, univariate Cox regression model was applied to identify RFS-related AS events. Their host genes were analyzed by Metascape to discover the potential functions and involved pathways. Next, least absolute shrinkage and selection operator (LASSO) method was used to select the most informative RFS-related AS events to constitute an AS risk factor for RFS prognosis, which was evaluated by Kaplan-Meier (KM) and receiver operating characteristic (ROC) curves in all the data and also in different clinical subgroups. Furthermore, we analyzed the relationships between splicing factors (SFs) and these RFS-related AS events to seek the possibility that SFs regulated AS events to influence RFS. Then, we evaluated the potential of these RFS-related AS events in the overall survival (OS) prognosis from all the above aspects.ResultsWe identified a total of 546 RFS-related AS events, which were enriched in some splicing and TNBC-associated pathways. Among them, seven RFS-related events were integrated into a risk factor, exhibiting satisfactory RFS prognosis alone and even better performance when combined with clinical tumor-node-metastasis stages. Furthermore, the correlation analysis between SFs and the seven AS events revealed the hypotheses that SRPK3 might upregulate PCYT2_44231_AA to have an effect on RFS prognosis and that three other SFs may work together to downregulate FLAD1_7874_RI to influence RFS prognosis. In addition, the seven RFS-related AS events were validated to be promising in the OS prognosis of TNBC as well.ConclusionThe abnormal AS events regulated by SFs may act as a kind of biomarker for the survival prognosis of TNBC.
| S-EPMC7841428 | biostudies-literature
Project description:Alternative splicing confers the human genome complexity by increasing the diversity of expressed mRNAs. Hundreds or thousands of splicing regions have been identified through differential alternative splicing analysis of high-throughput datasets. However, it is hard to explain the functional impact of each splicing event. Protein domain formation and nonsense-mediated decay are considered the main functional features of splicing. However, other functional features such as miRNA target sites, phosphorylation sites and single-nucleotide variations are directly affected by alternative splicing and affect downstream function. Hence, we established ASpedia: a comprehensive database for human alternative splicing annotation, which encompasses a range of functions, from genomic annotation to isoform-specific function (ASpedia, http://combio.snu.ac.kr/aspedia). The database provides three features: (i) genomic annotation extracted from DNA, RNA and proteins; (ii) transcription and regulation elements analyzed from next-generation sequencing datasets; and (iii) isoform-specific functions collected from known and published datasets. The ASpedia web application includes three components: an annotation database, a retrieval system and a browser specialized in the identification of human alternative splicing events. The retrieval system supports multiple AS event searches resulting from high-throughput analysis and the AS browser comprises genome tracks. Thus, ASpedia facilitates the systemic annotation of the functional impacts of multiple AS events.
| S-EPMC5753336 | biostudies-literature
Project description:Alternative splicing (AS) generates extensive transcriptomic and proteomic complexity. However, the functions of species- and lineage-specific splice variants are largely unknown. Here, we show that mammalian-specific skipping of exon 9 of PTBP1 alters its splicing regulatory activities and affects the inclusion levels of numerous exons. During neurogenesis, skipping of exon 9 reduces PTBP1 repressive activity so as to facilitate activation of a brain-specific AS program. Engineered skipping of the orthologous exon in chicken cells induces a large number of mammalian-like AS changes in PTBP1 target exons. These results thus reveal that a single exon skipping event in an RNA binding regulator directs numerous AS changes between species. The results further suggest that these changes contributed to evolutionary differences in the formation of vertebrate nervous systems.
2015-09-01 | GSE69656 | GEO
Project description:ObjectiveAlternative splicing (AS) is the mechanism by which a few genes encode numerous proteins, and it redefines the concept of gene expression regulation. Recent studies showed that dysregulation of AS was an important cause of tumorigenesis and microenvironment formation. Therefore, we performed a systematic analysis to examine the role of AS in breast cancer (Breast Cancer, BrCa) progression.MethodsThe present study included 993 BrCa patients from The Cancer Genome Atlas (TCGA) database in the genome-wide analysis of AS events. We used differential and prognostic analyses and found differentially expressed alternative splicing (DEAS) events and independent prognostic factors related to patients' overall survival (OS) and disease-free survival (DFS). We divided the patients into two groups based on these AS events and analyzed their clinical features, molecular subtyping and immune characteristics. We also constructed a splicing factor (SF) regulation network for key AS events and verified the existence of AS events in tissue samples using real-time quantitative PCR.ResultsA total of 678 AS events were identified as differentially expressed, of which 13 and 10 AS events were independent prognostic factors of patients' OS and DFS, respectively. Unsupervised clustering analysis based on these prognostic factors indicated that the Cluster 1 group had a better prognosis and more immune cell infiltration. SFs were significantly related to the expression of AS events, and AA-RPS21 was significantly upregulated in tumors.ConclusionAlternative splicing expands the mechanism of breast cancer progression from a new perspective. Notably, alternative splicing may affect the patient's prognosis by affecting the infiltration of immune cells. Our research provides important guidance for subsequent studies of AS in breast cancer.
| S-EPMC8236959 | biostudies-literature