Identification of inflammatory response and alternative splicing in acute kidney injury and experimental verification of the involvement of RNA‑binding protein RBFOX1 in this disease

Lin, Fangyou; Xu, Lei; Yuan, Run; Han, Shangting; Xie, Jinna; Jiang, Kun; Li, Bojun; Ye, Weimin; Rao, Ting; Zhou, Xiangjun

doi:10.3892/ijmm.2022.5087

Cited by 15 publications

(9 citation statements)

References 57 publications

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“…The most prominent of these was RBFOX1 and showed 208 "deep intronic" variants. The RBFOX family of RNAbinding proteins is well known to regulate alternative splicing (AS) 23,24 . Recently, RBFOX2 was reported to modulate a metastatic AS signature in pancreatic cancer 25 .…”

Section: Resultsmentioning

confidence: 99%

A single-cell strategy for the identification of intronic variants related to mis-splicing in pancreatic cancer

Duman

Sitte

Conrads

et al. 2023

Preprint

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Most clinical diagnostic and genomic research setups focus almost exclusively on coding regions and essential splice sites, thereby overlooking other non-coding variants. As a result, intronic variants that can promote mis-splicing events across a range of diseases, including cancer, are yet to be systematically investigated. Such investigations would require both genomic and transcriptomic data, but there currently exist very few datasets that satisfy these requirements. We address this by developing a single-nucleus full-length RNA-sequencing approach that allows for the detection of potentially pathogenic intronic variants. We exemplify the potency of our approach by applying to pancreatic cancer tumor and tumor-derived specimens and linking intronic variants to splicing dysregulation. We specifically find that prominent intron retention and pseudo-exon activation events that are shared by the tumors and affect genes encoding key transcriptional regulators. Our work paves the way for the assessment and exploitation of intronic mutations as powerful prognostic markers and potential therapeutic targets in cancer.

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Section: Resultsmentioning

confidence: 99%

A single-cell strategy for the identification of intronic variants related to mis-splicing in pancreatic cancer

Duman

Sitte

Conrads

et al. 2023

Preprint

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“…Musante et al [437], Han et al [438], Zhang et al [439], Sato et al [440], Yang et al [441], El-Aouni et al [442], Perisic et al [443], Chung et al [444], Wilkening et al [445], Kahvecioglu et al [446], Hu et al [447] and Worthmann et al [448] revealed that ALB (albumin), KLF15, ATF3, LPL (lipoprotein lipase), CUBN (cubilin), ILK (integrin linked kinase), PLEKHH2, TNF (tumor necrosis factor), CCR2, SPON2, LRRC55 and IGFBP1 might be the potential targets for FSGS diagnosis and treatment. Alves et al [449], Ma et al [450], Esposito et al [451], Ai et al [452], Lu et al [453], Bui et al [454], Bao et al [455], Zuo et al [456], Su et al [457], Wang et al [458], Šalamon et al [459], Harskamp et al [460], Ćwiklińska et al [461], Hishida et al [462], Gunay-Aygun et al [463], Simpson et al [464], Svenningsen et al [465], Wang et al [466], Rao et al [467], Chen et al [468], Bedin et al [469], Cao et al [470], Jang et al [471], de Frutos et al [472], Lin et al [473], Wang et al [474], Liu and Zhuang [475], Feng et al [476], Yu et al [477], Reed et al [478], Milillo et al [479], Chen et al [74], Chen et al [480], Vieira et al [76], Charlton et al [481], Shi et al [482], Zhou et al [483], Nazari et al [241], Greene et al [484], Lazar et al [485], Jobst-Schwan et al [486], Du et al [487], Liu et al [85], Liu et al [488], Liu et al [489], Lee et al [490], Wen et al [491], Sakai et al [492], Zhang et al [493], Wang et al [494], CD5L Castelblanco et al [251], Chen et al [495], Swanson et al [496], Ksiazek, [497], Li et al [498], Zhang et a...…”

Section: Discussionmentioning

confidence: 99%

Identification of biomarkers and pathways for focal segmental glomerulosclerosis using next generation sequencing data and bioinformatics analysis

Vastrad¹,

Vastrad²

2022

Preprint

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Focal segmental glomerulosclerosis (FSGS) is a renal disease leading threat to human health around the world. Here we aimed to explore novel molecular and potential therapeutic targets in FSGS through adopting integrated bioinformatics tools. Next generation sequencing (NGS) data of GSE197307 was available from Gene Expression Omnibus (GEO) database. Furthermore, differentially expressed genes (DEGs) were screened using the DESeq2 package in R software. Gene ontology (GO) and REACTOME pathway enrichment analyses of DEGs were performed via g:Profiler. Then, the protein-protein interaction (PPI) network, miRNA- hub gene regulatory network and TF-hub gene regulatory network were constructed using the HIPPIE, miRNet and NetworkAnalyst databases. Hub genes were validated using the receiver operating characteristic curve (ROC) analysis. By performing DEGs analysis, 488 up regulated genes and 488 down regulated genes were successfully identified from GSE197307, respectively. And they were mainly enriched in the terms of multicellular organismal process, cell periphery, protein binding, metabolism, immune system process, signaling receptor binding and immune system. Based on the data of protein-protein interaction (PPI), miRNA-hub gene regulatory network and TF-hub gene regulatory network, the top hub genes were ranked, including ILK, DDX5, MATR3, ALB, FOS, MKI67, PLK1, TNF, LCK and GTSE1. Bioinformatics analysis of NGS data identified signaling pathways and hub genes, potentially representing molecular mechanisms for the occurrence, progression, and risk prediction in FSGS.

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“…However, less than 2% of human genes are actually transcribed into mRNAs that encode proteins to transmit genetic information, and most DNA is transcribed as noncoding RNA that does not encode proteins. RNAs that do not have coding functions are considered key factors in the regulation of complex networks related to specific reactions and fates in cells 8 . LncRNAs are a class of noncoding RNAs with a length greater than 200 nucleotides that regulate gene expression at the level of chromatin modification, transcription, and posttranscriptional processing.…”

Section: The Relationship Between Lncrna Autophagy and Akimentioning

confidence: 99%

“…RNAs that do not have coding functions are considered key factors in the regulation of complex networks related to specific reactions and fates in cells. 8 LncRNAs are a class of noncoding RNAs with a length greater than 200 nucleotides that regulate gene expression at the level of chromatin modification, transcription, and posttranscriptional processing. The functions of lncRNAs depends on their location in the nucleus and the cytoplasm.…”

Section: Brief Introduction To Lncrnas Autophagy and Akimentioning

confidence: 99%

The role of LncRNA‐regulated autophagy in AKI

2023

Self Cite

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Acute kidney injury (AKI) is a complex clinical syndrome involving a series of pathophysiological processes regulated by multiple pathways at the molecular and cellular level. Long noncoding RNAs (lncRNAs) play an important role in the regulation of epigenetics, and their regulation of autophagy‐related genes in AKI has attracted increasing attention. However, the role of lncRNA‐regulated autophagy in AKI has not been fully elucidated. Evidence indicated that lncRNAs play regulatory roles in most factors that induce AKI. LncRNAs can regulate autophagy in AKI via a complex network of regulatory pathways to affect the development and prognosis of AKI. This article reviewed and analyzed the pathways of lncRNA regulation of autophagy in AKI in recent years. The results provide new ideas for further study of the pathophysiological process and targeted therapy for AKI.

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Identification of inflammatory response and alternative splicing in acute kidney injury and experimental verification of the involvement of RNA‑binding protein RBFOX1 in this disease

Cited by 15 publications

References 57 publications

A single-cell strategy for the identification of intronic variants related to mis-splicing in pancreatic cancer

A single-cell strategy for the identification of intronic variants related to mis-splicing in pancreatic cancer

Identification of biomarkers and pathways for focal segmental glomerulosclerosis using next generation sequencing data and bioinformatics analysis

The role of LncRNA‐regulated autophagy in AKI

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