Bioinformatic analysis revealing mitotic spindle assembly regulated NDC80 and MAD2L1 as prognostic biomarkers in non-small cell lung cancer development

Wei, Rong; Wang, Ziyue; Zhang, Yaping; Wang, Bin; Shen, Ningning; E, Li; Li, Xin; Shang, Lifang; Shang, Yangwei; Yan, Wenpeng; Zhang, Xiaoqin; Ma, Wenxia; Wang, Chen

doi:10.1186/s12920-020-00762-5

Cited by 17 publications

(13 citation statements)

References 43 publications

(45 reference statements)

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“…As an SACP, MAD2L1 ensures that the chromosomes are appropriately oriented toward the metaphase plate during cell division [ 49 ]. Lung adenocarcinoma patients have a higher risk of cancer relapse and shorter recovery times, due to the elevated expression of MAD2L1 and CDK1 [ 50 ].…”

Section: Discussionmentioning

confidence: 99%

“…Lung adenocarcinoma patients have a higher risk of cancer relapse and shorter recovery times, due to the elevated expression of MAD2L1 and CDK1 [ 50 ]. It has also been demonstrated that MAD2L1 binds with CDC20 and BUB1B and contributes to the abnormal growth of salivary duct carcinoma, despite its participation in signaling transductions [ 49 ].…”

Section: Discussionmentioning

confidence: 99%

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Differentially Expressed Cell Cycle Genes and STAT1/3-Driven Multiple Cancer Entanglement in Psoriasis, Coupled with Other Comorbidities

Anand

2022

Cells

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Psoriasis is a persistent T-cell-supported inflammatory cutaneous disorder, which is defined by a significant expansion of basal cells in the epidermis. Cell cycle and STAT genes that control cell cycle progression and viral infection have been revealed to be comorbid with the development of certain cancers and other disorders, due to their abnormal or scanty expression. The purpose of this study is to evaluate the expression of certain cell cycle and STAT1/3 genes in psoriasis patients and to determine the types of comorbidities associated with these genes. To do so, we opted to adopt the in silico methodology, since it is a quick and easy way to discover any potential comorbidity risks that may exist in psoriasis patients. With the genes collected from early research groups, protein networks were created in this work using the NetworkAnalyst program. The crucial hub genes were identified by setting the degree parameter, and they were then used in gene ontology and pathway assessments. The transcription factors that control the hub genes were detected by exploring TRRUST, and DGIdb was probed for remedies that target transcription factors and hubs. Using the degree filter, the first protein subnetwork produced seven hub genes, including STAT3, CCNB1, STAT1, CCND1, CDC20, HSPA4, and MAD2L1. The hub genes were shown to be implicated in cell cycle pathways by the gene ontology and Reactome annotations. The former four hubs were found in signaling pathways, including prolactin, FoxO, JAK/STAT, and p53, according to the KEGG annotation. Furthermore, they enhanced several malignancies, including pancreatic cancer, Kaposi’s sarcoma, non-small cell lung cancer, and acute myeloid leukemia. Viral infections, including measles, hepatitis C, Epstein–Barr virus, and HTLV-1 and viral carcinogenesis were among the other susceptible diseases. Diabetes and inflammatory bowel disease were conjointly annotated. In total, 129 medicines were discovered in DGIdb to be effective against the transcription factors BRCA1, RELA, TP53, and MYC, as opposed to 10 medications against the hubs, STAT3 and CCND1, in tandem with 8 common medicines. The study suggests that the annotated medications should be tested in suitable psoriatic cell lines and animal models to optimize the drugs used based on the kind, severity, and related comorbidities of psoriasis. Furthermore, a personalized medicine protocol must be designed for each psoriasis patient that displays different comorbidities.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Differentially Expressed Cell Cycle Genes and STAT1/3-Driven Multiple Cancer Entanglement in Psoriasis, Coupled with Other Comorbidities

Anand

2022

Cells

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“…There are currently no reports of MAD2L1 expression in HCC and its potential prognostic impact in the literature. In a study by Wei et al, bioinformatics analysis was used to demonstrate that NDC80 and MAD2L1 were potential biomarkers for the diagnosis of non-small-cell lung cancer [ 37 ]. Moreover, CDK1 and MAD2L1 were reported by Lu et al as prognostic markers in rhabdomyosarcoma [ 38 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of MAD2L1 as a Potential Biomarker in Hepatocellular Carcinoma via Comprehensive Bioinformatics Analysis

Chen

Yang

Zhang

et al. 2022

BioMed Research International

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Background. Hepatocellular carcinoma (HCC) is widely acknowledged as a malignant tumor with rapid progression, high recurrence rate, and poor prognosis. At present, there is a paucity of reliable biomarkers at the clinical level to guide the management of HCC and improve patient outcomes. Our research is aimed at assessing the prognostic value of MAD2L1 in HCC. Methods. Four datasets, GSE121248, GSE101685, GSE85598, and GSE62232, were selected from the GEO database to analyze differentially expressed genes (DEGs) between HCC and normal liver tissues. After functional analysis, we constructed a protein-protein interaction network (PPI) for DEGs and identified core genes in this network with high connectivity with other genes. We assessed the relationship between core genes and the pathogenesis and prognosis of HCC. Finally, we explored the gene regulatory signaling mechanisms involved in HCC pathogenesis. Results. 145 DEGs were screened from the intersection of the four GEO datasets. MAD2L1 was associated with most genes according to the PPI network and was selected as a candidate gene for further study. Survival analysis suggested that high MAD2L1 expression in HCC correlated with a worse prognosis. In addition, real-time quantitative PCR (RT-qPCR), western blot (WB), and immunohistochemistry (IHC) findings suggested that the expression of MAD2L1 was abnormally increased in HCC tissues and cells compared to paraneoplastic tissues and normal hepatocytes. Conclusion. We found that high MAD2L1 expression in HCC was significantly associated with overall patient survival and clinical features. We also explored the potential biological properties of this gene.

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“…2A-2D). Actually, this phenomenon has been observed in many other cancers [40][41][42], and it's logical considering the biological fact that most function genes are synthesised in nuclear and regulated by various modular factors, the slight change in nuclear protein might result in massive extra nuclear proteins changes.…”

Section: Go/kegg Preliminary Interpretation Of the Oscc Abnormal Expr...mentioning

confidence: 96%

Construction of a SPP1/PLAU dual genes containing signature as prognosis risk indicator in Oropharyngeal squamous cell carcinoma

Gui

Shang

et al. 2023

Preprint

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Background Oropharyngeal squamous cell carcinoma (OSCC) has been a common malignancy in head and neck region. Despite the improved understanding of the cancer development attributing to the revealing of significant epidemiological risk factors, the genetic information of the cancer is still lacking and the patients prognosis remains challenging. The study is to explore the transcriptome data of OSCC and to identify promising cancer development responsible genes thus aiding more precise understanding of the disease and screening promising drug targets for clinical medical therapy. Methods Multiple bioinformatic serves were used to interpret the genetic events in OSCC development. Firstly, based on GEO OSCC transcriptome data, the genes with changed expression in cancer comparing to normal oral tissues were identified, followed by being grouped according to the changing level. Then, GO/KEGG interpretation, protein-protein interaction (PPI) network construction and modules analysis were in succession performed to interpret the multiple gene groups for selecting promising hub gene clusters, which were next step proceeded by risk score assessment, Kaplan-Meier survival and Cox Regression analysis to scale down the cluster of candidate genes and select credible prognosis relating key genes. Further, detailed information of the key genes including their physicochemical properties, predicted cellular locations, the expression in human cancers, association with immune cells infiltration, relation with OSCC clinical pathological features and the probable signaling pathways involved in the gene’s regulation on cancer development were explored. Results A total of 30054 genes were identified to express abnormally in OSCC cancer versus normal oral epithelium. Of the genes, the expression difference of 607/30054 genes were indicated to be over 8-fold, and further module analysis of the 607 genes highlighted a 33-genes containing module which was supported by SurvExpress risk score assessment to be associated with OSCC survival. Moreover, Kaplan-Meier survival and Cox-regression analysis were performed continually to analyze all the 33 genes one by one, and the result revealed SPP1 and PLAU as two independent prognostic indicators in OSCC development. After the validation of changed expression of SPP1 and PLAU in OSCC versus normal tissues using local hospital biobank samples and exploration of the genes’ association with patients clinical pathological features including the relation with HPV infection, detailed information for instance their physicochemical properties, their expression and variation ratio in human cancers, their relation with immune cells infiltration, as well as the probable signaling pathways involved in the genes’ regulation on OSCC development were explored. Conclusions Based on online bioinformatic serves as well as local hospital samples validation, we identified SPP1 and PLAU as two independent prognostic indicators in OSCC and preliminary explored their biological features and clinical significance. Although further experiments and rigorous clinical trials are needed to reveal the genes’ potential drug-target role in clinical medical use, the results shall provide inspiring insights into current understanding of the genetic events in OSCC development and provoke next step deeply exploration of the disease.

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Bioinformatic analysis revealing mitotic spindle assembly regulated NDC80 and MAD2L1 as prognostic biomarkers in non-small cell lung cancer development

Cited by 17 publications

References 43 publications

Differentially Expressed Cell Cycle Genes and STAT1/3-Driven Multiple Cancer Entanglement in Psoriasis, Coupled with Other Comorbidities

Differentially Expressed Cell Cycle Genes and STAT1/3-Driven Multiple Cancer Entanglement in Psoriasis, Coupled with Other Comorbidities

Identification of MAD2L1 as a Potential Biomarker in Hepatocellular Carcinoma via Comprehensive Bioinformatics Analysis

Construction of a SPP1/PLAU dual genes containing signature as prognosis risk indicator in Oropharyngeal squamous cell carcinoma

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