Identification of an Autophagy-Related lncRNA Prognostic Signature and Related Tumor Immunity Research in Lung Adenocarcinoma

Chen, Hang; Hu, Zeyang; Sang, Menglu; Ni, Saiqi; Ye, Lin; Wu, Chengfang; Mu, Yinyu; Liu, Kaitai; Wu, Shibo; Li, Ni; Xu, Guodong

doi:10.3389/fgene.2021.767694

Cited by 11 publications

(10 citation statements)

References 56 publications

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“… 29 Increasing scholars have screened effective and reliable targets through bioinformatics analyses to predict the prognosis, explore the tumor immunity, and even select suitable anti‐tumor drugs of patients with tumors, which benefited greatly the patients with malignant tumors. 30 , 31 …”

Section: Discussionmentioning

confidence: 99%

Silencing oncogene cell division cycle associated 5 induces apoptosis and G1 phase arrest of non‐small cell lung cancer cells via p53‐p21 signaling pathway

Shen¹,

Tong²,

Chen³

et al. 2022

Clinical Laboratory Analysis

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Backgrounds: As a regulator of cell cycle, cell division cycle-associated 5 (CDCA5) is involved in the progression of various malignant tumors. However, the potential relationship between CDCA5 and lung cancer has not been reported. Methods:In our study, we analyzed the expression of CDCA5 in a variety of malignant tumors, performed Kaplan-Meier survival analysis of lung adenocarcinoma (LUAD), explored the potential relationship between CDCA5 expression and clinicopathological characteristics, assessed the predictive capability of at different stages of clinicopathological characteristics, revealed the enriched functions and signaling pathways among LUAD paitents with high CDCA5 expression, and investigated the correlation between PD-1, PD-L1, and CDCA5 through bioinformatics analyses. Subsequently, we performed quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) and western blotting (WB) to demonstrate that CDCA5 mediates the p53-p21 pathway and regulates the cell cycle. Result: CDCA5 is probably involved in the occurrence and development of NSCLC, and function as a reliable biomarker for predicting the survival outcomes of patients with early stage of patients with LUAD. Furthermore, CDCA5 may be a promising indicator of immunotherapy efficacy. In addition, silencing the expression of CDCA5 significantly increased the proportion of apoptotic NSCLC cells, and caused NSCLC cells to be arrested in the G1 phase. Conslusion: In conclusion, CDCA5 regulated the cell cycle of NSCLC cells by mediating the p53-p21 signaling pathway, participating in the development and progression of NSCLC patients.

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Section: Discussionmentioning

confidence: 99%

Silencing oncogene cell division cycle associated 5 induces apoptosis and G1 phase arrest of non‐small cell lung cancer cells via p53‐p21 signaling pathway

Shen¹,

Tong²,

Chen³

et al. 2022

Clinical Laboratory Analysis

Self Cite

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“…The depletion of Linc00176 disrupted the cell cycle and induced necroptosis in hepatocellular carcinoma via regulating the expression of miRNAs, such as miR-9 and miR-185 ( Tran et al, 2018 ). Based on the important role of lncRNA on the tumor, the prognostic signatures based on lncRNAs of LUAD patients have been widely introduced ( Chen H et al, 2021 ; Xu et al, 2021 ). Nevertheless, research on necroptosis-related lncRNAs (NRlncRNAs) in LUAD prognosis and tumor immune microenvironment (TIME) has not been reported.…”

Section: Introductionmentioning

confidence: 99%

A Novel Necroptosis-Related lncRNA Signature Predicts the Prognosis of Lung Adenocarcinoma

Luo

Wang

et al. 2022

Front. Genet.

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Background: Necroptosis is closely related to the tumorigenesis and development of cancer. An increasing number of studies have demonstrated that targeting necroptosis could be a novel treatment strategy for cancer. However, the predictive potential of necroptosis-related long noncoding RNAs (lncRNAs) in lung adenocarcinoma (LUAD) still needs to be clarified. This study aimed to construct a prognostic signature based on necroptosis-related lncRNAs to predict the prognosis of LUAD.Methods: We downloaded RNA sequencing data from The Cancer Genome Atlas database. Co-expression network analysis, univariate Cox regression, and least absolute shrinkage and selection operator were adopted to identify necroptosis-related prognostic lncRNAs. We constructed the predictive signature by multivariate Cox regression. Kaplan–Meier analysis, time-dependent receiver operating characteristics, nomogram, and calibration curves were used to validate and evaluate the signature. Subsequently, we used gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) to explore the relationship between the predictive signature and tumor immune microenvironment of risk groups. Finally, the correlation between the predictive signature and immune checkpoint expression of LUAD patients was also analyzed.Results: We constructed a signature composed of 7 necroptosis-related lncRNAs (AC026355.2, AC099850.3, AF131215.5, UST-AS2, ARHGAP26-AS1, FAM83A-AS1, and AC010999.2). The signature could serve as an independent predictor for LUAD patients. Compared with clinicopathological variables, the necroptosis-related lncRNA signature has a higher diagnostic efficiency, with the area under the receiver operating characteristic curve being 0.723. Meanwhile, when patients were stratified according to different clinicopathological variables, the overall survival of patients in the high-risk group was shorter than that of those in the low-risk group. GSEA showed that tumor- and immune-related pathways were mainly enriched in the low-risk group. ssGSEA further confirmed that the predictive signature was significantly related to the immune status of LUAD patients. The immune checkpoint analysis displayed that low-risk patients had a higher immune checkpoint expression, such as CTLA-4, HAVCR2, PD-1, and TIGIT. This suggested that immunological function is more active in the low-risk group LUAD patients who might benefit from checkpoint blockade immunotherapies.Conclusion: The predictive signature can independently predict the prognosis of LUAD, helps elucidate the mechanism of necroptosis-related lncRNAs in LUAD, and provides immunotherapy guidance for patients with LUAD.

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“…Recent research reports have set up signatures based on lncRNAs for the purpose of evaluating the prognosis of patients with cancer. lncRNA-related models of LUAD, such as immune-related lncRNAs 20 – 22 , autophagy-related lncRNAs 23 – 25 , pyroptosis-related lncRNAs 26 , and methylation-driven lncRNAs 27 , were reported in previous studies. In this study, we constructed the models of risk coefficient, which were essential in the assessment of the LUAD patients’ prognosis based on the nrlncRNA pairs.…”

Section: Discussionmentioning

confidence: 86%

Risk coefficient model of necroptosis-related lncRNA in predicting the prognosis of patients with lung adenocarcinoma

Chen

Xie

et al. 2022

Sci Rep

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Model algorithms were used in constructing the risk coefficient model of necroptosis-related long non-coding RNA in identifying novel potential biomarkers in the prediction of the sensitivity to chemotherapeutic agents and prognosis of patients with lung adenocarcinoma (LUAD). Clinic and transcriptomic data of LUAD were obtained from The Cancer Genome Atlas. Differently expressed necroptosis-related long non-coding RNAs got identified by performing both the univariate and co-expression Cox regression analyses. Subsequently, the least absolute shrinkage and selection operator technique was adopted in constructing the nrlncRNA model. We made a comparison of the areas under the curve, did the count of the values of Akaike information criterion of 1-year, 2-year, as well as 3-year receiver operating characteristic curves, after which the cut-off value was determined for the construction of an optimal model to be used in identifying high risk and low risk patients. Genes, tumor-infiltrating immune cells, clinical correlation analysis, and chemotherapeutic agents data of both the high-risk and low-risk subgroups were also performed. We identified 26 DEnrlncRNA pairs, which were involved in the Cox regression model constructed. The curve areas under survival periods of 1 year, 2 years, and 3 years of patients with LUAD were 0.834, 0.790, and 0.821, respectively. The cut-off value set was 2.031, which was used in the identification of either the high-risk or low-risk patients. Poor outcomes were observed in patients belonging to the high-risk group. The risk score was the independent predictor of the LUAD outcome (p < 0.001). The expression levels of immune checkpoint and infiltration of specific immune cells were anticipated by the gene risk model. The high-risk group was found to be highly sensitive to docetaxel, erlotinib, cisplatin, and paclitaxel. The model established through nrlncRNA pairs irrespective of the levels of expression could give a prediction on the LUAD patients’ prognosis and assist in identifying the patients who might gain more benefit from chemotherapeutic agents.

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Identification of an Autophagy-Related lncRNA Prognostic Signature and Related Tumor Immunity Research in Lung Adenocarcinoma

Cited by 11 publications

References 56 publications

Silencing oncogene cell division cycle associated 5 induces apoptosis and G1 phase arrest of non‐small cell lung cancer cells via p53‐p21 signaling pathway

Silencing oncogene cell division cycle associated 5 induces apoptosis and G1 phase arrest of non‐small cell lung cancer cells via p53‐p21 signaling pathway

A Novel Necroptosis-Related lncRNA Signature Predicts the Prognosis of Lung Adenocarcinoma

Risk coefficient model of necroptosis-related lncRNA in predicting the prognosis of patients with lung adenocarcinoma

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