scholarly journals The SF3b Splicing Complex Regulates DNA Damage Response in Acute Lymphoblastic Leukemia

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1237-1237 ◽  
Author(s):  
Shalini Sankar ◽  
Miriam Guillen Navarro ◽  
Frida Ponthan ◽  
Simon Bomken ◽  
Sirintra Nakjang ◽  
...  

To identify potential regulators of propagation and self-renewal of Acute Lymphoblastic Leukaemia (ALL), we performed an explorative genome-wide RNAi screen followed by CRISPR ex vivo and in vivo validation screens in the t(4;11)-positive ALL cell line SEM. These screens identified the splicing factor PHF5A as a crucial component of the leukemic program. PHF5A is a subunit of the SF3b protein complex, which directs alternative splicing by binding to the branchpoint of pre-mRNA. Mutations in members of this complex including SF3B1 have been implicated in several haematological malignancies. Functional perturbation experiments demonstrated that PHF5A depletion impairs proliferation, viability and clonogenicity in a range of ALL and AML cell lines strongly suggesting that PHF5A is required for leukemic propagation and self-renewal. To identify genetic programs affected by PHF5A inhibition, we performed RNA-seq followed by analysis of differential gene expression and splicing events. We identified 473 genes with differential expression upon PHF5A knockdown. In addition, we performed in-depth analysis of splicing patterns by examining both differential exon/intron usage and exon junction formation. These analyses demonstrated that loss of PHF5A affects splicing of more than 2500 genes with exon skipping and intron retention being the most frequent splicing events. In order to identify processes and pathways affected by PHF5A, we performed gene set enrichment analysis (GSEA) on both differential expression and splicing. While gene sets associated with RNA processing including splicing, turnover and translation were enriched in both data sets, the differential gene expression signature was also linked to DNA repair processes including base excision, mismatch and homologous recombination repair. In line with these findings, knockdown of either PHF5A or its partner protein SF3B1 induced DNA strand breaks as indicated by comet assay and increased y-H2AX levels. Furthermore, both PHF5A and SF3B1 depletion sensitized ALL cells towards the DNA crosslinking agent mitomycin C. Closer inspection of RNA-seq datasets revealed reduced FANCD2 expression and skipping of exon 22 associated with impaired mono-ubiquitination of the FANCD2 protein as a consequence of PHF5A and SF3B1 knockdown. Furthermore, expression of RAD51, a key component of double strand break repair, also decreased upon PHF5A and SF3B1 knockdown. Notably, in vitro pharmacological inhibition of SF3b complex activity using H3B-8800 (or Pladienolide B) showed a very similar effect on FANCD2 expression, and ubiquitination as well as decrease of RAD51 and an increase in y-H2AX levels on a dose and time-dependent manner. This strongly suggests a mechanistic link between impaired RNA splicing and the repair of DNA double-strand breaks. These combined data show that leukemic cells are highly dependent on a functional SF3b splicing complex. Interference with its function results in DNA damage and also sensitizes towards DNA damaging agents pointing towards a possible benefit of the combined application of inhibitors targeting the SF3b complex with more conventional chemotherapy. Disclosures Ponthan: Epistem Ltd: Employment. Zwaan:Sanofi: Consultancy; Incyte: Consultancy; BMS: Research Funding; Roche: Consultancy; Janssen: Consultancy; Daiichi Sankyo: Consultancy; Servier: Consultancy; Jazz Pharmaceuticals: Other: Travel support; Pfizer: Research Funding; Celgene: Consultancy, Research Funding. Vormoor:Abbvie (uncompensated): Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Roche/Genentech: Consultancy, Honoraria, Research Funding; AstraZeneca: Research Funding.

Author(s):  
Dionysios Fanidis ◽  
Panagiotis Moulos

Abstract The study of differential gene expression patterns through RNA-Seq comprises a routine task in the daily lives of molecular bioscientists, who produce vast amounts of data requiring proper management and analysis. Despite widespread use, there are still no widely accepted golden standards for the normalization and statistical analysis of RNA-Seq data, and critical biases, such as gene lengths and problems in the detection of certain types of molecules, remain largely unaddressed. Stimulated by these unmet needs and the lack of in-depth research into the potential of combinatorial methods to enhance the analysis of differential gene expression, we had previously introduced the PANDORA P-value combination algorithm while presenting evidence for PANDORA’s superior performance in optimizing the tradeoff between precision and sensitivity. In this article, we present the next generation of the algorithm along with a more in-depth investigation of its capabilities to effectively analyze RNA-Seq data. In particular, we show that PANDORA-reported lists of differentially expressed genes are unaffected by biases introduced by different normalization methods, while, at the same time, they comprise a reliable input option for downstream pathway analysis. Additionally, PANDORA outperforms other methods in detecting differential expression patterns in certain transcript types, including long non-coding RNAs.


2015 ◽  
Author(s):  
Xiaobei Zhou ◽  
Mark D Robinson

A correspondence with respect to: Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data Rapaport F, Khanin R, Liang Y, Pirun M, Krek A, Zumbo P, Mason CE, Socci ND and Betel D, Genome Biol 2013, 14:R95


2019 ◽  
Vol 12 (1) ◽  
pp. 11-19 ◽  
Author(s):  
Jun-Young Shin ◽  
Sang-Heon Choi ◽  
Da-Woon Choi ◽  
Ye-Jin An ◽  
Jae-Hyuk Seo ◽  
...  

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Saivageethi Nuthikattu ◽  
Dragan Milenkovic ◽  
John Rutledge ◽  
Amparo Villablanca

AbstractHyperlipidemia is a risk factor for dementia, and chronic consumption of a Western Diet (WD) is associated with cognitive impairment. However, the molecular mechanisms underlying the development of microvascular disease in the memory centers of the brain are poorly understood. This pilot study investigated the nutrigenomic pathways by which the WD regulates gene expression in hippocampal brain microvessels of female mice. Five-week-old female low-density lipoprotein receptor deficient (LDL-R−/−) and C57BL/6J wild type (WT) mice were fed a chow or WD for 8 weeks. Metabolics for lipids, glucose and insulin were determined. Differential gene expression, gene networks and pathways, transcription factors, and non-protein coding RNAs were evaluated by genome-wide microarray and bioinformatics analysis of laser captured hippocampal microvessels. The WD resulted in differential expression of 2,412 genes. The majority of differential gene expression was attributable to differential regulation of cell signaling proteins and their transcription factors, approximately 7% was attributable to differential expression of miRNAs, and a lesser proportion was due to other non-protein coding RNAs, primarily long non-coding RNAs (lncRNAs) and small nucleolar RNAs (snoRNAs) not previously described to be modified by the WD in females. Our findings revealed that chronic consumption of the WD resulted in integrated multilevel molecular regulation of the hippocampal microvasculature of female mice and may provide one of the mechanisms underlying vascular dementia.


2019 ◽  
Vol 20 (23) ◽  
pp. 6098 ◽  
Author(s):  
Amarinder Singh Thind ◽  
Kumar Parijat Tripathi ◽  
Mario Rosario Guarracino

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.


2016 ◽  
Vol 236 ◽  
pp. 98-104 ◽  
Author(s):  
E.E. Malandrakis ◽  
O. Dadali ◽  
E. Golomazou ◽  
M. Kavouras ◽  
S. Dailianis ◽  
...  

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