Comprehensive Bioinformatic Analysis Genes Associated to the Prognosis of Liposarcoma

Liu, Jianwei; Li, Rong; Liao, Xiwen; Jiang, Weiping

doi:10.12659/msm.913043

Cited by 9 publications

(5 citation statements)

References 32 publications

(34 reference statements)

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“…For the darkorange module of ADC, the most correlated with recurrence-free survival, NIP7 was the highest degree gene. Interestingly, NIP7 has been also identified as the gene among in a three-gene signature significantly associated with RFS in liposarcoma [85].…”

Section: Discussionmentioning

confidence: 99%

Molecular Signature of Subtypes of Non-Small-Cell Lung Cancer by Large-Scale Transcriptional Profiling: Identification of Key Modules and Genes by Weighted Gene Co-Expression Network Analysis (WGCNA)

Niemira

Collin

Szałkowska

et al. 2019

Cancers

212

166

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Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies consisting essentially of adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Although the diagnosis and treatment of ADC and SCC have been greatly improved in recent decades, there is still an urgent need to identify accurate transcriptome profile associated with the histological subtypes of NSCLC. The present study aims to identify the key dysregulated pathways and genes involved in the development of lung ADC and SCC and to relate them with the clinical traits. The transcriptional changes between tumour and normal lung tissues were investigated by RNA-seq. Gene ontology (GO), canonical pathways analysis with the prediction of upstream regulators, and weighted gene co-expression network analysis (WGCNA) to identify co-expressed modules and hub genes were used to explore the biological functions of the identified dysregulated genes. It was indicated that specific gene signatures differed significantly between ADC and SCC related to the distinct pathways. Of identified modules, four and two modules were the most related to clinical features in ADC and SCC, respectively. CTLA4, MZB1, NIP7, and BUB1B in ADC, as well as GNG11 and CCNB2 in SCC, are novel top hub genes in modules associated with tumour size, SUVmax, and recurrence-free survival. Our research provides a more effective understanding of the importance of biological pathways and the relationships between major genes in NSCLC in the perspective of searching for new molecular targets.

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Section: Discussionmentioning

confidence: 99%

Molecular Signature of Subtypes of Non-Small-Cell Lung Cancer by Large-Scale Transcriptional Profiling: Identification of Key Modules and Genes by Weighted Gene Co-Expression Network Analysis (WGCNA)

Niemira

Collin

Szałkowska

et al. 2019

Cancers

212

166

View full text Add to dashboard Cite

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“…Besides, NSA2 may also be involved in the regulation of ribosomal biosynthesis [ 41 ]. In liposarcoma, NIP7, RPL10L, and MCM2 are significantly associated with long-term no recurrence survival rate [ 42 ]. There is a close functional interaction between NIP7 and FTSJ3 during pre-rRNA processing, which indicates that FTSJ3 is involved in ribosome synthesis in human cells [ 43 ].…”

Section: Discussionmentioning

confidence: 99%

Upregulation of GTPBP4 Promotes the Proliferation of Liver Cancer Cells

Chen

Zhang

2021

Journal of Oncology

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Research Background. Liver cancer is a public health issue worldwide and ranks second in cancer-related mortality rates worldwide. In China, the mortality rate of liver cancer ranks second among all cancer types. The five-year survival rate of liver cancer is only 18%, and the five-year survival rate after surgery can exceed 50%, but the recurrence rate after surgery is as high as 70%. Therefore, the research on the occurrence and progression mechanism of liver cancer is still urgent. Research Method. Explore the expression of GTPBP4 in liver cancer patients in GEPIA2, Oncomine, and UALCAN databases. The relationship between GTPBP4 gene expression and the overall survival of liver cancer patients was explored in the Kaplan–Meier plotter database. Through the STRING database, the protein interacting with GTPBP4 was found. Subsequently, the expression of GTPBP4 gene’s mRNA level and protein level in liver cancer cells was verified by fluorescence quantitative PCR and Western blotting experiments. Through the CCK-8 experiment, the effect of GTPBP4 gene’s expression on the growth of liver cancer cells was explored. Through nude mouse tumorigenicity assay, the effect of GTPBP4 expression on tumor growth in vivo was explored. Results. The GTPBP4 has upregulated expression in liver cancer patients ( P < 0.01 ), but there was no difference in its expression in patients with different clinicopathological stages. The expression of GTPBP4 increased with the increase of cancer metastasis in lymph nodes ( P < 0.01 ). Liver cancer patients with upregulated expression of GTPBP4 showed a shorter overall survival rate ( P = 0.02 ). GTPBP4 is closely related to genes such as NIFK, WDR12, and RPF2, and these genes are involved in life processes such as GTP binding and rRNA processing. The upregulated expression of GTPBP4 promotes the proliferation of liver cancer cells and promotes the growth of tumors in mice, while the downregulated expression of GTPBP4 inhibits the proliferation of liver cancer cells and inhibits the growth of tumors in mice. Conclusion. The expression of GTPBP4 is upregulated in liver cancer patients and affects the overall survival rate of patients. The upregulated expression of GTPBP4 promotes the proliferation of liver cancer cells and the growth of tumors.

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“…Targeted therapies for LPS have been developed based on epigenetic deregulation, genetic aberrations, and mechanisms of abnormal adipogenesis in different LPS subtypes. 49–52 A new nomogram including variables such as gene expression or experimental tumor biomarkers may thus open another door to perfect the prognosis system.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a novel prognostic model for long-term overall survival in liposarcoma patients: a population-based study

Cao

Yang

et al. 2020

J Int Med Res

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Objective To construct and validate a clinically accurate and histology-specific nomogram to predict overall survival (OS) among liposarcoma (LPS) patients. Methods We retrospectively screened eligible patients with LPS diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results database. We screened independent predictors for the nomogram using univariate and multivariate analyses. We then evaluated the prognostic accuracy of the nomogram by receiver operating characteristic (ROC) curve analysis and Harrell’s concordance index. The prognostic performances of the nomogram and the American Joint Committee on Cancer (AJCC) seventh edition staging system were compared using integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analyses (DCA). Results A novel nomogram was developed using independent prognostic variables, which exhibited excellent predictive performances for 3- and 5-year OS according to ROC curves. The C-index proved that the proposed nomogram had better prognostic accuracy for LPS than the traditional AJCC system, while the NRI, IDI, and DCA of the nomogram indicated better clinical net benefit. Conclusions The proposed nomogram can predict 3- and 5-year OS of LPS patients with reliable accuracy and may thus help clinicians to develop appropriate clinical therapies and counseling strategies to prolong the life expectancy of these patients.

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Comprehensive Bioinformatic Analysis Genes Associated to the Prognosis of Liposarcoma

Cited by 9 publications

References 32 publications

Molecular Signature of Subtypes of Non-Small-Cell Lung Cancer by Large-Scale Transcriptional Profiling: Identification of Key Modules and Genes by Weighted Gene Co-Expression Network Analysis (WGCNA)

Molecular Signature of Subtypes of Non-Small-Cell Lung Cancer by Large-Scale Transcriptional Profiling: Identification of Key Modules and Genes by Weighted Gene Co-Expression Network Analysis (WGCNA)

Upregulation of GTPBP4 Promotes the Proliferation of Liver Cancer Cells

Development and validation of a novel prognostic model for long-term overall survival in liposarcoma patients: a population-based study

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