Pan‐cancer analysis of alternative splicing regulator heterogeneous nuclear ribonucleoproteins (hnRNPs) family and their prognostic potential

Li, Hao; Liu, Jingwei; Shen, Shixuan; Dai, De‐Zai; Cheng, Shitong; Dong, Xinxin; Sun, Liping; Guo, Xiaolin

doi:10.1111/jcmm.15558

Cited by 44 publications

(37 citation statements)

References 33 publications

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“… Xu et al (2020) observed that the expression of ALKBH5 and HNRNPC could predict the outcome of ESCA. In addition, HNRNPA2B1 is a binding protein and member of the hnRNP family ( Li et al, 2020 ). Recently, HNRNPA2B1 was recognized as a nuclear “reader” of m6A sites and was determined to affect alternative splicing patterns ( Alarcón et al, 2015 ).…”

Section: Discussionmentioning

confidence: 99%

HNRNPA2B1 Affects the Prognosis of Esophageal Cancer by Regulating the miR-17-92 Cluster

Chen

Lou

et al. 2021

Front. Cell Dev. Biol.

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N6-methyladenosine (m6A) is the most abundant RNA modification in eukaryotes. Accumulating evidence suggests that dysregulation of m6A modification significantly correlates with tumorigenesis and progression. In this study, we observed an increased expression and positive correlations of all 25 m6A regulators in esophageal cancer (ESCA) data obtained from the TCGA database. Through expression profiling of these regulators, a prognostic score model containing HNRNPA2B1, ALKBH5, and HNRNPG was established, and the high-risk subgroup exhibited strong positive correlations with ESCA progression and outcome. The risk score obtained from this model may represent an independent predictor of ESCA prognosis. Notably, the gene most frequently associated with increased risk was HNRNPA2B1; in ESCA, the increased expression of this gene alone predicted poor prognosis by affecting tumor-promoting signaling pathways through miR-17-92 cluster. An experimental study demonstrated that elevated HNRNPA2B1 expression was positively associated with distant metastasis and lymph node stage, and predicted the poor outcomes of ESCA patients. Knockdown of HNRNPA2B1 significantly decreased the expression of miR-17, miR-18a, miR-20a, miR-93, and miR-106b and inhibited the proliferation of ESCA cells. Therefore, our study indicated that the dynamic changes in 25 m6A regulators were associated with the clinical features and prognosis of patients with ESCA. Importantly, HNRNPA2B1 alone may affect the prognosis of patients with ESCA by regulating the miR-17-92 cluster.

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Section: Discussionmentioning

confidence: 99%

HNRNPA2B1 Affects the Prognosis of Esophageal Cancer by Regulating the miR-17-92 Cluster

Chen

Lou

et al. 2021

Front. Cell Dev. Biol.

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“…The genes HNRNPA1, HNRNPA2B1 and HNRNPC are ubiquitously expressed heterogeneous nuclear ribonucleoproteins (hnRNPs) involved in mRNA metabolism, splicing and regulation of alternative splicing events. Indeed, these genes are associated with carcinogenesis and metastasis with a diverse set of tumor types (66,67). The spliceosomal host machinery is especially important for the high-risk HPV life cycle and transformation in CC.…”

Section: Discussionmentioning

confidence: 99%

Cervical Cancer Stem-Like Cell Transcriptome Profiles Predict Response to Chemoradiotherapy

et al. 2021

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Cervical cancer (CC) represents a major global health issue, particularly impacting women from resource constrained regions worldwide. Treatment refractoriness to standard chemoradiotheraphy has identified cancer stem cells as critical coordinators behind the biological mechanisms of resistance, contributing to CC recurrence. In this work, we evaluated differential gene expression in cervical cancer stem-like cells (CCSC) as biomarkers related to intrinsic chemoradioresistance in CC. A total of 31 patients with locally advanced CC and referred to Mário Penna Institute (Belo Horizonte, Brazil) from August 2017 to May 2018 were recruited for the study. Fluorescence-activated cell sorting was used to enrich CD34+/CD45- CCSC from tumor biopsies. Transcriptome was performed using ultra-low input RNA sequencing and differentially expressed genes (DEGs) using Log2 fold differences and adjusted p-value < 0.05 were determined. The analysis returned 1050 DEGs when comparing the Non-Responder (NR) (n=10) and Responder (R) (n=21) groups to chemoradiotherapy. These included a wide-ranging pattern of underexpressed coding genes in the NR vs. R patients and a panel of lncRNAs and miRNAs with implications for CC tumorigenesis. A panel of biomarkers was selected using the rank-based AUC (Area Under the ROC Curve) and pAUC (partial AUC) measurements for diagnostic sensitivity and specificity. Genes overlapping between the 21 highest AUC and pAUC loci revealed seven genes with a strong capacity for identifying NR vs. R patients (ILF2, RBM22P2, ACO16722.1, AL360175.1 and AC092354.1), of which four also returned significant survival Hazard Ratios. This study identifies DEG signatures that provide potential biomarkers in CC prognosis and treatment outcome, as well as identifies potential alternative targets for cancer therapy.

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“…Selective splicing produces cellular proteins that are selectively expressed in a tissue-specific and time-dependent manner and participate in a variety of regulatory pathways including Abnormal splicing may lead to the production of abnormal mRNA isomers that encode mutant proteins, which have increased or decreased function and participate in cell transformation and the development and metastasis of cancer (21). The functions of spliceosome complexes and splicing modulators have been widely studied in cancer (22). In particular, splicing regulators such as snRNPs, hnRNPs, and SR proteins have been proven to play the role of carcinogenic or tumor suppressor proteins in diverse types of cancer (23,24), including breast (25) and lung cancer (26).…”

Section: Discussionmentioning

confidence: 99%

Identification of heterogeneous nuclear ribonucleoprotein as a candidate biomarker for diagnosis and prognosis of hepatocellular carcinoma

Wang

et al. 2021

J Gastrointest Oncol

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Background: Hepatocellular carcinoma (HCC) is the most common type of liver cancer with a high mortality rate. However, spliceosomal genes are still lacking in the diagnosis and prognosis of HCC.Methods: Identification of differentially expressed genes (DEGs) was performed using the limma package in R software. Modules highly related to HCC were obtained by weighted gene co-expression network analysis (WGCNA), and the module genes were analyzed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. The biomarker for diagnosing HCC was determined by receiver operating characteristic (ROC) curve analysis, and the effect of the biomarker in the diagnosis of HCC was evaluated by performing five-fold cross-validation with logistic regression. HCC specimens from preoperatively treated patients were tested for biomarker by real-time quantitative polymerase chain reaction (RT-qPCR).Kaplan-Meier analysis was used to assess the relationship between biomarker and patient survival. The role of biomarker was evaluated using ESTIMATE analysis in the tumor microenvironment.Results: In this study, 389 DEGs were screened out from three Gene Expression Omnibus (GEO) datasets.We also found that the turquoise module of 123 genes from The Cancer Genome Atlas (TCGA) data was the key module with the highest correlation with HCC traits. Then, 123 genes were analyzed using the KEGG enrichment pathway, and eight genes were found to be most significantly related to the spliceosome pathway. We selected 8 genes and 389 DEGs shared genes, and finally got the only gene, heterogeneous nuclear ribonucleoprotein (hnRNPU). The high expression of hnRNPU was associated with poor prognosis of HCC, and hnRNPU was a biomarker for diagnosing HCC. In the tissues of patients with excellent HCC treatment hnRNPU messenger RNA (mRNA) was lower than in the tissues of patients with poor HCC treatment. High expression of hnRNPU was significantly increased in HCC patients with low stromal (P<0.05), low immune (P<0.05), and low estimation scores (P<0.05), and with high tumor purity (P<0.05) and high malignant progression (P<0.05) of the HCC. Conclusions:The hnRNPU gene identified in this study may become a new biomarker for the diagnosis and prognosis of HCC.

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Pan‐cancer analysis of alternative splicing regulator heterogeneous nuclear ribonucleoproteins (hnRNPs) family and their prognostic potential

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 44 publications

References 33 publications

HNRNPA2B1 Affects the Prognosis of Esophageal Cancer by Regulating the miR-17-92 Cluster

HNRNPA2B1 Affects the Prognosis of Esophageal Cancer by Regulating the miR-17-92 Cluster

Cervical Cancer Stem-Like Cell Transcriptome Profiles Predict Response to Chemoradiotherapy

Identification of heterogeneous nuclear ribonucleoprotein as a candidate biomarker for diagnosis and prognosis of hepatocellular carcinoma

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