Deregulation of ribosomal proteins in human cancers

Khoury, Wendy El; Nasr, Zeina

doi:10.1042/bsr20211577

Cited by 60 publications

(41 citation statements)

References 139 publications

(174 reference statements)

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“…The ribosomal protein S6's phosphorylation in response to numerous growth factors has been discovered as a growth regulator, whereas some roles of other ribosomal proteins are not recognized [ 17 , 18 ]. Ribosomal proteins are overexpressed in breast cancer, liver, and colon [ 19 ]. Increased cell proliferation or development does not immediately increase ribosomal protein mRNA [ 20 ] immediately.…”

Section: Introductionmentioning

confidence: 99%

The Current Status of SSRP1 in Cancer: Tribulation and Road Ahead

Jia

Guo

Wang

et al. 2022

Journal of Healthcare Engineering

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Background and Objectives. Owing to the complexity and heterogeneity of tumors, cancer’s early diagnoses and treatment have become a provocation. Structure-specific recognition protein-1 (SSRP1) is a histone (H3-H4 or H2A-H2B) chaperone in chromatin-related processes such as transcription, cell cycle control, and DNA replication, reported in various tumor tissues. It may also be used as a biomarker. This study aimed to highlight the role of SSRP1 in cancer with a focus on the current progress and future perspective. Methods. We search PubMed and Web of Sciences with keywords “SSRP1” and “Cancer.” Only English literature was included, and conference papers and abstract were all excluded. Results. Transcription factors are classified into three groups based on their DNA binding motifs: simple helix-loop-helix (bHLH), classical zinc fingers (ZF-TFs), and homeodomains. The tumor-suppressive miR-497 (microRNA-497) acted as an undesirable regulator of SSRP1 upregulation, which led to tumor growth. The siRNA (small interfering RNA) knockdown of SSRP1 hindered cell proliferation along with incursion and glioma cell migration. Through the AKT (also known as protein kinase B) signaling pathway, SSRP1 silencing affected cancer apoptosis and cell proliferation. Conclusion. The MAPK (mitogen-activated protein kinase) signaling pathway’s phosphorylation was suppressed when SSRP1 was depleted. The effect of curaxins on p53 and NF-B (nuclear factor-κB), and their toxicity to cancer cells, is attributable to the FACT (facilitates chromatin transcription) complex’s chromatin trapping.

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Section: Introductionmentioning

confidence: 99%

The Current Status of SSRP1 in Cancer: Tribulation and Road Ahead

Jia

Guo

Wang

et al. 2022

Journal of Healthcare Engineering

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“…Another study found GLUD2, a potentially relevant gene for HCC (47). In one study, overexpression of RPL39 was reported to be associated with HCC (48). In one study, KDELR2 was identified as a potential gene associated with HBV (49).…”

Section: Discussionmentioning

confidence: 98%

Machine Learning-Based Classification of HBV and HCV-Related Hepatocellular Carcinoma Using Genomic Biomarkers

Akbulut¹,

Küçükakçalı²,

Çolak³

2022

jmed

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Objective: It is crucial to know the underlying causes of hepatocellular carcinoma (HCC) for optimal management. This study aims to classify open access gene expression data of HCC patients who have an HBV or HCV infection using the XGboost method.Material and Methods: This case-control study considered the open-access gene expression data of patients with HBV-related HCC and HCV-related HCC. For this purpose, data from 17 patients with HBV+HCC and 17 patients with HCV+HCC were included. XGboost was constructed for the classification via tenfold cross-validation. Accuracy, balanced accuracy, sensitivity, specificity, the positive predictive value, the negative predictive value, and F1 score performance metrics were evaluated for a model performance.Results: With the feature selection approach, 17 genes were chosen, and modeling was done using these input variables. Accuracy, balanced accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and the F1 score obtained from the XGboost model were 97.1%, 97.1%, 94.1%, 100%, 100%, 94.4%, and 97%, respectively. Based on the variable importance findings from the XGboost, the ALDOC, GLUD2, TRAPPC10, FLJ12998, RPL39, KDELR2, and KIAA0446 genes can be employed as potential biomarkers for HBV-related HCC.

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“…RPLs may be able to induce oncogenesis through their extra-ribosomal functions. Overactivity of ribosome biogenesis is crucial to the initiation and progression of cancer [23].RPLs' pattern of expression varies considerably between tumor types and tissues, suggesting that they can be used as biomarkers for a variety of cancers [24]. The ribosomal protein gene 5 (RPL5) was reported to be signi cantly mutated in glioblastoma, melanoma, and breast cancer samples as a haploinsu cient tumor suppressor [25].…”

Section: Discussionmentioning

confidence: 99%

Identification of genes in patients for predicting ulcerative colitis-associated colorectal cancer

Wei

Yong

Jin

et al. 2022

Preprint

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Aim: Ulcerative colitis (UC) has been considered a risk factor for colorectal cancer (CRC). However, effective biomarkers for predicting UC-associated CRC are lacking. Therefore, it is necessary to screen biomarkers associated with UC-related CRC, which could be used to evaluate UC-associated CRC early, and provide possible mechanisms involved in UC-associated CRC. Efficient bioinformatics analysis could help to explore potential biomarkers. Method: Two public datasets, including 44 UC without CRC samples and 17 UC-associated CRC samples were chosen from Gene Expression Omnibus (GEO) database. Sva package was used to remove batch effects, and then we screened out differentially expressed genes (DEGs) with the limma package. STRING and Cytoscape were used to achieve protein-protein interaction (PPI) network analysis and hub genes. The survival curves between high and low gene expression were performed by a log-rank test based on the cancer genome atlas (TCGA) program. To validate the hub gene expression, we compared their expression between normal and colorectal cancer based on Oncomine. Furthermore, immunohistochemistry was used to validate the expression of selected differentially expressed proteins Results: 405 DEGs were identified, including 256 down-regulated genes and 149 up-regulated genes in UC-associated CRC tissues. 16 hub genes were identified. And among them, RPL6, RPL7, and RPL35 were related to the poor prognosis of patients. Higher expression of RPL6, RPL7, and RPL35 was validated in CRC tissues based on Oncomine. Moreover, higher expression of RPL7 was observed in CRC sample tissues compared to normal colorectal tissues(p=0.004) or UC tissues (p=0.009). However, the expression of RPL6 and RPL35 in CRC tissues was not significantly increased compared to UC tissues or normal tissues. Conclusion: Our study showed that overexpressed RPL7 may be a potential tumor oncogene and could act as a prognostic factor in clinical diagnosis and treatment during UC-associated CRC.

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Deregulation of ribosomal proteins in human cancers

Cited by 60 publications

References 139 publications

The Current Status of SSRP1 in Cancer: Tribulation and Road Ahead

The Current Status of SSRP1 in Cancer: Tribulation and Road Ahead

Machine Learning-Based Classification of HBV and HCV-Related Hepatocellular Carcinoma Using Genomic Biomarkers

Identification of genes in patients for predicting ulcerative colitis-associated colorectal cancer

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