Integrated Analysis of Cell Cycle–Related and Immunity-Related Biomarker Signatures to Improve the Prognosis Prediction of Lung Adenocarcinoma

Chen, Fangyu; Song, Jiahang; Ye, Ziqi; Xu, Bing; Cheng, Hongyan; Zhang, Shu; Sun, Xinchen

doi:10.3389/fonc.2021.666826

Cited by 17 publications

(16 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on eight cell cycle-immunity-related genes, Chen et al. ( 26 ) constructed a prognosis model to predict the OS in Lung adenocarcinoma (LUAD) samples, and this model was correlated with immune cell infiltration. Similarly, using bioinformatics analysis, another concurrent study has shown that a G2/M checkpoint-related signature composed of five genes (MARCKS, CCNF, MAPK14, INCENP, and CHAF1A) was connected with the prognosis of gastric cancer (GC) patients ( 27 ).…”

Section: Discussionmentioning

confidence: 99%

A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma

Zhou

Lei

et al. 2022

Front. Oncol.

View full text Add to dashboard Cite

We aimed to propose a cell cycle-related multi/mRNA signature (CCS) for prognosis prediction and uncover new tumor-driver genes for hepatocellular carcinoma (HCC). Cell cycle-related gene sets and HCC samples with mRNA-Seq data were retrieved from public sources. The genes differentially expressed in HCCs relative to normal peritumoral tissues were extracted through statistical analysis. The CCS was constructed by Cox regression analyses. Predictive capacity and clinical practicality of the signature were evaluated and validated. The expression of the function-unknown genes in the CCS was determined by RT-qPCR. Candidate gene TICRR was selected for subsequent validation through functional experiments. A cell cycle-related 13-mRNA signature was generated from the exploratory cohort [The Cancer Genome Atlas (TCGA), n = 371)]. HCC cases were classified as high- vs. low-risk groups per overall survival (OS) [hazard ratio (HR) = 2.699]. Significantly, the CCS exhibited great predictive value for prognosis in three independent cohorts, particularly in GSE76427 cohort [area under the curve (AUC) = 0.835/0.822/0.808/0.821/0.826 at 1/2/3/4/5 years]. The nomogram constructed by integrating clinicopathological features with the CCS indicated high accuracy and practicability. Significant enrichment of tumorigenesis-associated pathways was observed in the high-risk patients by Gene Set Enrichment Analysis (GSEA). RT-qPCR revealed that TICRR was overexpressed in HCC samples. Increased TICRR expression implied poor prognosis in HCC patients. Furthermore, depletion of TICRR in HCC cells decreased cell proliferation and the G1/S transition. In conclusion, the established 13-CCS had efficacy in prognostic prediction of HCC patients. Additionally, TICRR was demonstrated as a tumor-driver gene for this deadly disease.

show abstract

Section: Discussionmentioning

confidence: 99%

A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma

Zhou

Lei

et al. 2022

Front. Oncol.

View full text Add to dashboard Cite

show abstract

“…Wai Hoong Chang et al explored the prognostic value of DNA repair genes in pan-cancer and confirmed that DNA repair genes were associated with dysregulation of cell cycle and hypoxia ( Chang and Lai, 2019 ). Fangyu Chen et al integratedly investigated the predictive value of cell cycle-related and immune-related genes in lung adenocarcinoma ( Chen et al, 2021b ). HCC can be divided into two subtypes with different molecular and clinical characteristics based on DNA damage repair related genes ( Lin et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Immune Landscape and Classification in Lung Adenocarcinoma Based on a Novel Cell Cycle Checkpoints Related Signature for Predicting Prognosis and Therapeutic Response

et al. 2022

View full text Add to dashboard Cite

Lung adenocarcinoma (LUAD) is one of the most common malignancies with the highest mortality globally, and it has a poor prognosis. Cell cycle checkpoints play a central role in the entire system of monitoring cell cycle processes, by regulating the signalling pathway of the cell cycle. Cell cycle checkpoints related genes (CCCRGs) have potential utility in predicting survival, and response to immunotherapies and chemotherapies. To examine this, based on CCCRGs, we identified two lung adenocarcinoma subtypes, called cluster1 and cluster2, by consensus clustering. Enrichment analysis revealed significant discrepancies between the two subtypes in gene sets associated with cell cycle activation and tumor progression. In addition, based on Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, we have developed and validated a cell cycle checkpoints-related risk signature to predict prognosis, tumour immune microenvironment: (TIME), immunotherapy and chemotherapy responses for lung adenocarcinoma patients. Results from calibration plot, decision curve analysis (DCA), and time-dependent receiver operating characteristic curve (ROC) revealed that combining age, gender, pathological stages, and risk score in lung adenocarcinoma patients allowed for a more accurate and predictive nomogram. The area under curve for lung adenocarcinoma patients with 1-, 3-, 5-, and 10-year overall survival was: 0.74, 0.73, 0.75, and 0.81, respectively. Taken together, our proposed 4-CCCRG signature can serve as a clinically useful indicator to help predict patients outcomes, and could provide important guidance for immunotherapies and chemotherapies decision for lung adenocarcinoma patients.

show abstract

“…The predictive power of the CCP gene-derived signatures was also confirmed in early-stage lung adenocarcinoma [ 37 , 38 ]. Furthermore, Chen and colleagues recently developed a risk-predicting signature with eight immunity-related cell cycle genes [ 41 ]. These findings indicate the reliability of predicting prognosis with CCP signatures in cancer.…”

Section: Discussionmentioning

confidence: 99%

Pan-cancer analysis of UBE2T with a focus on prognostic and immunological roles in lung adenocarcinoma

et al. 2022

View full text Add to dashboard Cite

Background Ubiquitin-conjugating enzyme E2 T (UBE2T) is a potential oncogene. However, Pan-cancer analyses of the functional, prognostic and predictive implications of this gene are lacking. Methods We first analyzed UBE2T across 33 tumor types in The Cancer Genome Atlas (TCGA) project. We investigated the expression level of UBE2T and its effect on prognosis using the TCGA database. The correlation between UBE2T and cell cycle in pan-cancer was investigated using the single-cell sequencing data in Cancer Single-cell State Atlas (CancerSEA) database. The Weighted Gene Co-expression Network analysis (WGCNA), Univariate Cox and Least absolute shrinkage and selection operator (LASSO) Cox regression models, and receiver operating characteristic (ROC) were applied to assess the prognostic impact of UBE2T-related cell cycle genes (UrCCGs). Furthermore, the consensus clustering (CC) method was adopted to divide TCGA-lung adenocarcinoma (LUAD) patients into subgroups based on UrCCGs. Prognosis, molecular characteristics, and the immune panorama of subgroups were analyzed using Single-sample Gene Set Enrichment Analysis (ssGSEA). Results derived from TCGA-LUAD patients were validated in International Cancer Genome Consortium (ICGC)-LUAD data. Results UBE2T is highly expressed and is a prognostic risk factor in most tumors. CancerSEA database analysis revealed that UBE2T was positively associated with the cell cycle in various cancers(r > 0.60, p < 0.001). The risk signature of UrCCGs can reliably predict the prognosis of LUAD (AUC1 year = 0.720, AUC3 year = 0.700, AUC5 year = 0.630). The CC method classified the TCGA-LUAD cohort into 4 UrCCG subtypes (G1–G4). Kaplan–Meier survival analysis demonstrated that G2 and G4 subtypes had worse survival than G3 (Log-rank test PTCGA training set < 0.001, PICGC validation set < 0.001). A comprehensive analysis of immune infiltrates, immune checkpoints, and immunogenic cell death modulators unveiled different immune landscapes for the four subtypes. High immunophenoscore in G3 and G4 tumors suggested that these two subtypes were immunologically “hot,” tending to respond to immunotherapy compared to G2 subtypes (p < 0.001). Conclusions UBE2T is a critical oncogene in many cancers. Moreover, UrCCG classified the LUAD cohort into four subgroups with significantly different survival, molecular features, immune infiltrates, and immunotherapy responses. UBE2T may be a therapeutic target and predictor of prognosis and immunotherapy sensitivity.

show abstract

Integrated Analysis of Cell Cycle–Related and Immunity-Related Biomarker Signatures to Improve the Prognosis Prediction of Lung Adenocarcinoma

Cited by 17 publications

References 42 publications

A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma

A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma

Immune Landscape and Classification in Lung Adenocarcinoma Based on a Novel Cell Cycle Checkpoints Related Signature for Predicting Prognosis and Therapeutic Response

Pan-cancer analysis of UBE2T with a focus on prognostic and immunological roles in lung adenocarcinoma

Contact Info

Product

Resources

About