RNA Binding Proteins as Drivers and Therapeutic Target Candidates in Pancreatic Ductal Adenocarcinoma

Glaß, Markus; Michl, Patrick; Hüttelmaier, And Stefan

doi:10.3390/ijms21114190

Cited by 18 publications

(14 citation statements)

References 65 publications

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“…Consistent with previous studies, up-regulation of IGF2BP2 promoted liver, colorectal and breast tumorigenesis [34][35][36]. Similarly, studies have also reported the tumorpromoting role of IGF2BP1, IGF2BP3, IGFBP6 and IGFL2 in several cancers such as hepatocellular carcinoma, pancreatic and prostate cancers [37][38][39][40]. The potential association of FGF14 with IGF pathways genes, if validated by additional studies, may serve as a pivotal to understand the existing associations between growth factor pathways that results in pathogenesis of PDAC.…”

Section: Plos Onesupporting

confidence: 81%

Genomic relevance of FGF14 and associated genes on the prognosis of pancreatic cancer

2021

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Background Fibroblast (FGFs) and insulin (IGF) growth factor pathways are among 10 most recurrently altered genomic pathways in pancreatic ductal adenocarcinoma (PDAC). However, the prognostic and therapeutic relevance of FGF and IGF pathways in PDAC is largely unknown. Methods We investigated the relationship between fibroblast and insulin pathway gene expression and clinicopathological features in three independent transcriptomic cohorts of 532 PDAC patients. Furthermore, we have examined the coexpressed genes specific to the prognostic marker identified from these cohorts. Statistical tests including Fisher-exact\Chi-square, Kaplan–Meier, Pearson Correlation and cox regression analyses were performed. Additionally, pathway analysis of gene-specific co-expressed genes was also performed. Results The dysregulation of six genes including FGF9, FGF14, FGFR1, FGFR4, IGF2BP2 and IGF2BP3 were significantly associated with different clinical characteristics (including grade, stage, recurrence and nodes) in PDAC cohorts. 11 genes (including FGF9, FGF13, FGF14, FGF17, FGFR1, FGFRL1, FGFBP3, IGFBP3, IGF2BP2, IGF2BP3 and IGFBPL1) showed association with overall survival in different PDAC cohorts. Interestingly, overexpression of FGF14 was found associated with better overall survival (OS) in all three cohorts. Of note, multivariate analysis also revealed FGF14 as an independent prognostic marker for better OS in all three cohorts. Furthermore, FMN2 and PGR were among the top genes that correlated with FGF14 in all 3 cohorts. Of note, overexpression of FMN2 and PGR was found significantly associated with good overall survival in PDAC patients, suggesting FMN2 and PGR can also act as potential markers for the prediction of prognosis in PDAC patients. Conclusion FGF14 may define a distinct subset of PDAC patients with better prognosis. Moreover, FGF14-based sub-classification of PDAC suggests that FMN2 and PGR can be employed as good prognostic markers in PDAC and this classification may lead to new therapeutic approaches.

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Section: Plos Onesupporting

confidence: 81%

Genomic relevance of FGF14 and associated genes on the prognosis of pancreatic cancer

2021

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“…We have summarized the classical as well as emerging hallmark functions of RBPs in Figure 1. Given their widespread impact on gene expression and signaling networks, mutations or defects in the expression or localization of RBPs can cause a broad range of diseases, e.g., neurodegeneration, obesity, hypertension, and cancer [55,[89][90][91][92][93][94][95][96]. In the next paragraph, we will highlight selected examples of RBPs that have been shown to contribute to the malignancy of oral cancer, especially its metastatic features.…”

Section: General Functions and Mechanisms Of Rna-binding Proteinsmentioning

confidence: 99%

RNA-Binding Proteins as Regulators of Migration, Invasion and Metastasis in Oral Squamous Cell Carcinoma

Weiße

Rosemann

Krauspe

et al. 2020

IJMS

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Nearly 7.5% of all human protein-coding genes have been assigned to the class of RNA-binding proteins (RBPs), and over the past decade, RBPs have been increasingly recognized as important regulators of molecular and cellular homeostasis. RBPs regulate the post-transcriptional processing of their target RNAs, i.e., alternative splicing, polyadenylation, stability and turnover, localization, or translation as well as editing and chemical modification, thereby tuning gene expression programs of diverse cellular processes such as cell survival and malignant spread. Importantly, metastases are the major cause of cancer-associated deaths in general, and particularly in oral cancers, which account for 2% of the global cancer mortality. However, the roles and architecture of RBPs and RBP-controlled expression networks during the diverse steps of the metastatic cascade are only incompletely understood. In this review, we will offer a brief overview about RBPs and their general contribution to post-transcriptional regulation of gene expression. Subsequently, we will highlight selected examples of RBPs that have been shown to play a role in oral cancer cell migration, invasion, and metastasis. Last but not least, we will present targeting strategies that have been developed to interfere with the function of some of these RBPs.

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“…As a member of the OAS protein family, OASL is associated with the innate immune defense against viral infections. Glaß et al (2020) identified OASL to be a candidate oncogenic RNA-binding protein with partially validated target potential in PC. Recently, PLAU has been reported to be an oncogene that activates EMT progression in PAAD (Zhao X. et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Construction and Validation of an Immune-Based Prognostic Model for Pancreatic Adenocarcinoma Based on Public Databases

et al. 2021

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BackgroundPancreatic adenocarcinoma (PAAD) is a highly lethal and aggressive tumor with poor prognoses. The predictive capability of immune-related genes (IRGs) in PAAD has yet to be explored. We aimed to explore prognostic-related immune genes and develop a prediction model for indicating prognosis in PAAD.MethodsThe messenger (m)RNA expression profiles acquired from public databases were comprehensively integrated and differentially expressed genes were identified. Univariate analysis was utilized to identify IRGs that related to overall survival. Whereafter, a multigene signature in the Cancer Genome Atlas cohort was established based on the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Moreover, a transcription factors regulatory network was constructed to reveal potential molecular processes in PAAD. PAAD datasets downloaded from the Gene Expression Omnibus database were applied for the validations. Finally, correlation analysis between the prognostic model and immunocyte infiltration was investigated.ResultsTotally, 446 differentially expressed immune-related genes were screened in PAAD tissues and normal tissues, of which 43 IRGs were significantly related to the overall survival of PAAD patients. An immune-based prognostic model was developed, which contained eight IRGs. Univariate and multivariate Cox regression revealed that the risk score model was an independent prognostic indicator in PAAD (HR > 1, P < 0.001). Besides, the sensitivity of the model was evaluated by the receiver operating characteristic curve analysis. Finally, immunocyte infiltration analysis revealed that the eight-gene signature possibly played a pivotal role in the status of the PAAD immune microenvironment.ConclusionA novel prognostic model based on immune genes may serve to characterize the immune microenvironment and provide a basis for PAAD immunotherapy.

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RNA Binding Proteins as Drivers and Therapeutic Target Candidates in Pancreatic Ductal Adenocarcinoma

Cited by 18 publications

References 65 publications

Genomic relevance of FGF14 and associated genes on the prognosis of pancreatic cancer

Genomic relevance of FGF14 and associated genes on the prognosis of pancreatic cancer

RNA-Binding Proteins as Regulators of Migration, Invasion and Metastasis in Oral Squamous Cell Carcinoma

Construction and Validation of an Immune-Based Prognostic Model for Pancreatic Adenocarcinoma Based on Public Databases

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