The value of CEP55 gene as a diagnostic biomarker and independent prognostic factor in LUAD and LUSC

Fu, Linhai; Wei, Desheng; Wang, Bin; Zhang, Chu; Zhu, Tian; Ma, Zhifeng; Li, Zhupeng; Wu, Yifan; Yu, Guanzhen

doi:10.1371/journal.pone.0233283

Cited by 24 publications

(18 citation statements)

References 25 publications

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“…22 Both m 6 A and lncRNAs are important regulators of LUAD tumorigenesis. 23 However, studies on the pathological role of m 6 A and lncRNAs in LUAD progression remain limited, and studies on the biological mechanisms and prognostic biomarkers of LUAD concerning m 6 A-related lncRNAs are still lacking. 24,25 In the present study, we were inspired by the function of m 6 A and lncRNAs in LUAD; thus, we attempted to construct an independent model based on m 6 A-related lncRNAs.…”

Section: Discussionmentioning

confidence: 99%

m6A-related lncRNAs are potential biomarkers for predicting prognoses and immune responses in patients with LUAD

Huang

et al. 2021

Molecular Therapy - Nucleic Acids

166

141

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Lung adenocarcinoma (LUAD) is the most frequent subtype of lung cancer worldwide. However, the survival rate of LUAD patients remains low. N6-methyladenosine (m 6 A) and long noncoding RNAs (lncRNAs) play vital roles in the prognostic value and the immunotherapeutic response of LUAD. Thus, discerning lncRNAs associated with m 6 A in LUAD patients is critical. In this study, m 6 A-related lncRNAs were analyzed and obtained by coexpression. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were conducted to construct an m 6 Arelated lncRNA model. Kaplan-Meier analysis, principalcomponent analysis (PCA), functional enrichment annotation, and nomogram were used to analyze the risk model. Finally, the potential immunotherapeutic signatures and drug sensitivity prediction targeting this model were also discussed. The risk model comprising 12 m 6 A-related lncRNAs was identified as an independent predictor of prognoses. By regrouping the patients with this model, we can distinguish between them more effectively in terms of the immunotherapeutic response. Finally, candidate compounds aimed at LUAD subtype differentiation were identified. This risk model based on the m 6 Abased lncRNAs may be promising for the clinical prediction of prognoses and immunotherapeutic responses in LUAD patients.

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Section: Discussionmentioning

confidence: 99%

m6A-related lncRNAs are potential biomarkers for predicting prognoses and immune responses in patients with LUAD

Huang

et al. 2021

Molecular Therapy - Nucleic Acids

166

141

View full text Add to dashboard Cite

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“…Lung adenocarcinoma (LUAD) is the most prevalent subtype among lung cancer patients (>40%) (2). LUAD patients with indistinct early symptoms, extensive metastasis, and chemoresistance often indicate an unfavorable overall survival (OS), and the 5-year survival rate of LUAD is not more than 10% (3)(4)(5). Advances in recent years, such as the identification of oncogenes and immunotherapy treatments, have provided valuable insight to guide the management of LUAD (6,7).…”

Section: Introductionmentioning

confidence: 99%

KIF11 Serves as an Independent Prognostic Factor and Therapeutic Target for Patients With Lung Adenocarcinoma

et al. 2021

Front. Oncol.

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BackgroundLung adenocarcinoma (LUAD) is challenging in clinical practice due to the poor understanding of molecular mechanisms and limited therapeutic targets. Herein, the work aimed to use bioinformatics to identify a promising molecular target for LUAD therapy.MethodsDifferentially expressed genes (DEGs) from the Cancer Genome Atlas (TCGA) dataset were used for a weighted gene co-expression network analysis (WGCNA) to screen the hub gene. After a prognostic estimation with meta-analysis and COX regression analysis, we performed a function analysis on the corresponding gene. The ESTIMATE and CIBERSORT methods were adopted to analyze the association of the hub gene with the tumor microenvironment (TME). A cohort of functional assays was conducted to establish the functional roles of the hub gene in A549 and PC-9 cells.ResultsOur screen identified KIF11 as a prognostic factor, which indicated the poor overall survival and the worse progression-free survival in LUAD patients. Additionally, KIF11 was primarily involved in cell cycle, TME alteration and tumor-infiltrating immune cells proportions. KIF11 knockdown exerted inhibitory effects on cell proliferation, migration, and invasion. Results of the flow cytometry analysis revealed that KIF11 knockdown induced a G2/M phase arrest and improved apoptosis in LUAD cells.ConclusionsKIF11 is essential for LUAD cell proliferation and metastasis, and it may serve as an independent prognostic factor as well as a promising therapeutic target for LUAD patients.

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“…Recently, a number of studies have demonstrated that exosomes can carry biomarkers, and have diagnostic and prognostic value (45)(46)(47). Although certain studies have demonstrated that mRNAs in peripheral blood can be used as biomarkers for the clinical diagnosis of LUAD and LUSC (48,49), to the best of our knowledge, there is currently no relevant research available on the mRNAs from exosomes. In the present study, exosomes were isolated from patient serum and the diagnostic value of exosomes as biomarkers to distinguish LUAD from LUSC was investigated.…”

Section: Discussionmentioning

confidence: 99%

Use of four genes in exosomes as biomarkers for the identification of lung adenocarcinoma and lung squamous cell carcinoma

Cao

Wang

et al. 2021

Oncol Lett

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The determination of biomarkers in the blood specific for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is crucial for the selection of effective treatment strategies and the prediction of prognosis. The purpose of the present study was to analyze the differentially expressed genes (DEGs) in LUSC and LUAD from The Cancer Genome Atlas (TCGA) database. In order to identify the potential biomarkers for non-small cell lung cancer (NSCLC) for clinical diagnosis, bioinformatics was used to analyze the DEGs of two subtypes of NSCLC, LUAD and LUSC. Exosomes were isolated from the serum of patients with LUAD or LUSC and identified using transmission electron microscopy, nanoparticle tracking analysis and western blot analysis. A total of four differential exosomal mRNAs were selected for validation with serum samples from 70 patients with NSCLC via reverse transcription-quantitative polymerase chain reaction. Receiver operating characteristic curves were established to evaluate the clinical diagnostic value of four DEGs for patients with LUAD and LUSC. The analysis based on TCGA data revealed the DEGs in LUSC and LUAD: A total of 1,619 genes were differentially expressed in patients with LUSC and LUAD. DEGs analyzed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that inflammation-related signaling pathways, such as complement pathways, and multiple autoimmune diseases, such as systemic lupus erythematosus and asthma were mainly enriched in LUAD. The cell cycle, Hippo signaling pathway, Rap1 signaling pathway and Wnt signaling pathway were the main signaling pathways enriched in LUSC. The combination of tumor protein P63 (TP63), keratin 5 (KRT5), CEA cell adhesion molecule 6 (CEACAM6) and surfactant protein B (SFTPB) improved the specificity and sensitivity in the diagnosis of different lung cancer subtypes. Exosomal TP63, KRT5, CEACAM6 and SFTPB mRNAs can thus be used as biomarkers to differentiate between LUSC and LUAD, and may provide a novel strategy for their differential diagnosis and treatment.

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The value of CEP55 gene as a diagnostic biomarker and independent prognostic factor in LUAD and LUSC

Cited by 24 publications

References 25 publications

m6A-related lncRNAs are potential biomarkers for predicting prognoses and immune responses in patients with LUAD

m6A-related lncRNAs are potential biomarkers for predicting prognoses and immune responses in patients with LUAD

KIF11 Serves as an Independent Prognostic Factor and Therapeutic Target for Patients With Lung Adenocarcinoma

Use of four genes in exosomes as biomarkers for the identification of lung adenocarcinoma and lung squamous cell carcinoma

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