Bioinformatics construction and experimental validation of a cuproptosis-related lncRNA prognostic model in lung adenocarcinoma for immunotherapy response prediction

Li, Linfeng; Cai, Qidong; Wu, Zeyu; Li, Xizhe; Zhou, Wolong; Lu, Liqing; Yi, Bin; Chang, Ruimin; Zhang, Heng; Cheng, Yuanda; Zhang, Chunfang; Zhang, Junjie

doi:10.1038/s41598-023-29684-9

Cited by 11 publications

(11 citation statements)

References 45 publications

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“…Additionally, several research reported GSEC could promote the malignant process of triple-negative breast cancer and hepatocellular carcinoma via the GSEC/miR-202-5p/AXL axis and the GSEC/miR-101-3p/SNX16/PAPOLG axis [38,39], respectively. Furthermore, lncRNA AL606834.1 has been used for prognostic models of lung adenocarcinoma and pancreatic cancer [40,41], AL365181.2 has been applied in multiple prognostic models of lung adenocarcinoma [42,43], and AC012615.1 has been studied in a prognostic model of glioblastoma [44]. These ndings provided the robust evidence for the construction of our DRLS score based on these 5 lncRNAs.…”

Section: Discussionmentioning

confidence: 82%

Disulfidptosis-related lncRNA signatures in lung adenocarcinoma: Predicting prognosis and evaluating the tumor immune microenvironment

Song,

Cao,

Wang

et al. 2023

Preprint

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Background As a novel form of regulated cell death (RCD), disulfidptosis has been reported recently, which brought the significant probability in better understanding for pathogenesis and therapeutic strategies of tumors. Long non-coding RNAs (LncRNAs) regulate the viability of tumor cells by engaging with a range of targets, including DNA, RNA, and proteins. Nonetheless, the understanding about the prognostic value of disulfidptosis-related LncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains incomplete. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRLncRNAs. Methods RNA-seq data and corresponding clinical information were acquired from The Cancer Genome Atlas (TCGA) database, enabling the identification of DRlncRNAs. Subsequently, a prognostic model was formulated for LUAD by utilizing a series of analyses including univariate COX, LASSO, and multivariate COX regression. Patients were then categorized into two groups with distinct level of DRLS score, and subsequently subjected to the consensus clustering analysis for assigning LUAD patients to distinct subtypes by employing the DRlncRNAs. Subsequent studies investigated disparities among groups with distinct risk and molecular subtypes in terms of overall survival (OS), functional enrichment, the tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, in vitro experiments were conducted to validate the LUAD cellular proliferation and migratory behavior upon GSEA knockdown. Results Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells. Conclusion Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD.

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Section: Discussionmentioning

confidence: 82%

Disulfidptosis-related lncRNA signatures in lung adenocarcinoma: Predicting prognosis and evaluating the tumor immune microenvironment

Song,

Cao,

Wang

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Additionally, several research reported GSEC could promote the malignant process of triple-negative breast cancer and hepatocellular carcinoma via the GSEC/miR-202-5p/AXL axis and the GSEC/miR-101-3p/SNX16/PAPOLG axis 38 , 39 , respectively. Furthermore, lncRNA AL606834.1 has been used for prognostic models of lung adenocarcinoma and pancreatic cancer 40 , 41 , AL365181.2 has been applied in multiple prognostic models of lung adenocarcinoma 42 , 43 , and AC012615.1 has been studied in a prognostic model of glioblastoma 44 . These findings provided the robust evidence for the construction of our DRLS score based on these 5 lncRNAs.…”

Section: Discussionmentioning

confidence: 99%

A disulfidptosis-related lncRNA signature for predicting prognosis and evaluating the tumor immune microenvironment of lung adenocarcinoma

Song,

Cao,

Wang

et al. 2024

Sci Rep

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As a novel form of regulated cell death (RCD), disulfidptosis offering a significant opportunity in better understanding of tumor pathogenesis and therapeutic strategies. Long non-coding RNAs (lncRNAs) regulate the biology functions of tumor cells by engaging with a range of targets. However, the prognostic value of disulfidptosis-related lncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains unclear. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRlncRNAs. RNA-seq data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Subsequently, a prognostic model based on DRlncRNAs was constructed using LASSO and COX regression analysis. Patients were stratified into high- and low-risk groups based on their risk scores. Differences between the high-risk and low-risk groups were investigated in terms of overall survival (OS), functional enrichment, tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, the role of lncRNA GSEC in LUAD was validated through in vitro experiments. Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells. Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD.

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“…Yang et al applied a CRlncRNAs model to evaluate the immune infiltration status in head and neck squamous cell carcinoma [ 39 ]. Li et al demonstrated the potential of CRlncRNAs in predicting immunotherapy response in LUAD [ 40 ]. These findings suggest that CRlncRNAs may serve as promising biomarkers for revealing the complex tumor microenvironment and aiding clinicians in formulating personalized immunotherapy for patients.…”

Section: Discussionmentioning

confidence: 99%

Cuproptosis Depicts Immunophenotype and Predicts Immunotherapy Response in Lung Adenocarcinoma

Zhou

Cheng

et al. 2023

JPM

Self Cite

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Background: Although significant progress has been made in immunotherapy for lung adenocarcinoma (LUAD), there is an urgent need to identify effective indicators to screen patients who are suitable for immunotherapy. Systematically investigating the cuproptosis-related genes (CRGs) in LUAD may provide new ideas for patients’ immunotherapy stratification. Method: We comprehensively analyzed the landscape of 12 CRGs in a merged TCGA and GEO LUAD cohort. We investigated the associations between tumor microenvironment and immunophenotypes. We utilized a risk score to predict the prognosis and immunotherapy response for an individual patient. Additionally, we conducted CCK-8 experiments to evaluate the impact of DLGAP5 knockdown on A549 cell proliferation. Result: We utilized an integrative approach to analyze 12 CRGs and differentially expressed genes (DEGs) in LUAD samples, resulting in the identification of two distinct CRG clusters and two gene clusters. Based on these clusters, we generated immunophenotypes and observed that the inflamed phenotype had the most abundant immune infiltrations, while the desert phenotype showed the poorest immune infiltrations. We then developed a risk score model for individual patient prognosis and immunotherapy response prediction. Patients in the low-risk group had higher immune scores and ESTIMATE scores, indicating an active immune state with richer immune cell infiltrations and higher expression of immune checkpoint genes. Moreover, the low-risk group exhibited better immunotherapy response according to IPS, TIDE scores, and Imvigor210 cohort validation results. In addition, our in vitro wet experiments demonstrated that DLGAP5 knockdown could suppress the cell proliferation of A549. Conclusion: Novel cuproptosis molecular patterns reflected the distinct immunophenotypes in LUAD patients. The risk model might pave the way to stratify patients suitable for immunotherapy and predict immunotherapy response.

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Bioinformatics construction and experimental validation of a cuproptosis-related lncRNA prognostic model in lung adenocarcinoma for immunotherapy response prediction

Cited by 11 publications

References 45 publications

Disulfidptosis-related lncRNA signatures in lung adenocarcinoma: Predicting prognosis and evaluating the tumor immune microenvironment

Disulfidptosis-related lncRNA signatures in lung adenocarcinoma: Predicting prognosis and evaluating the tumor immune microenvironment

A disulfidptosis-related lncRNA signature for predicting prognosis and evaluating the tumor immune microenvironment of lung adenocarcinoma

Cuproptosis Depicts Immunophenotype and Predicts Immunotherapy Response in Lung Adenocarcinoma

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