An abnormal metabolism-related gene, ALG3, is a potential diagnostic and prognostic biomarker for lung adenocarcinoma

To explore the abnormal metabolism-related genes that affect the prognosis of patients with lung adenocarcinoma (LUAD), and analyze the relationship with immune infiltration and competing endogenous RNA (ceRNA) network. Transcriptome data of LUAD were downloaded from the Cancer Genome Atlas database...

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Veröffentlicht in:Medicine (Baltimore) 2024-09, Vol.103 (37), p.e38746
Hauptverfasser: Reyimu, Abdusemer, Cheng, Xiang, Liu, Wen, Kaisaier, Aihemaitijiang, Wang, Xinying, Sha, Yinzhong, Guo, Ruijie, Paerhati, Pawuziye, Maimaiti, Maimaituxun, He, Chuanjiang, Li, Li, Zou, Xiaoguang, Xu, Aimin
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container_title Medicine (Baltimore)
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creator Reyimu, Abdusemer
Cheng, Xiang
Liu, Wen
Kaisaier, Aihemaitijiang
Wang, Xinying
Sha, Yinzhong
Guo, Ruijie
Paerhati, Pawuziye
Maimaiti, Maimaituxun
He, Chuanjiang
Li, Li
Zou, Xiaoguang
Xu, Aimin
description To explore the abnormal metabolism-related genes that affect the prognosis of patients with lung adenocarcinoma (LUAD), and analyze the relationship with immune infiltration and competing endogenous RNA (ceRNA) network. Transcriptome data of LUAD were downloaded from the Cancer Genome Atlas database. Abnormal metabolism-related differentially expressed genes in LUAD were screened by the R language. Cox analysis was used to construct LUAD prognostic risk model. Kaplan-Meier test, ROC curve and nomograms were used to evaluate the predictive ability of metabolic related gene prognostic model. CIBERSORT algorithm was used to analyze the relationship between risk score and immune infiltration. The starBase database constructed a regulatory network consistent with the ceRNA hypothesis. IHC experiments were performed to verify the differential expression of ALG3 in LUAD and paracancerous samples. In this study, 42 abnormal metabolism-related differential genes were screened. After survival analysis, the final 5 metabolism-related genes were used as the construction of prognosis model, including ALG3, COL7A1, KL, MST1, and SLC52A1. In the model, the survival rate of LUAD patients in the high-risk subgroup was lower than that in the low-risk group. In addition, the risk score of the constructed LUAD prognostic model can be used as an independent prognostic factor for patients. According to the analysis of CIBERSORT algorithm, the risk score is related to the infiltration of multiple immune cells. The potential ceRNA network of model genes in LUAD was constructed through the starBase database. IHC experiments revealed that ALG3 expression was upregulated in LUAD. The prognostic model of LUAD reveals the relationship between metabolism and prognosis of LUAD, and provides a novel perspective for diagnosis and research of LUAD.
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Transcriptome data of LUAD were downloaded from the Cancer Genome Atlas database. Abnormal metabolism-related differentially expressed genes in LUAD were screened by the R language. Cox analysis was used to construct LUAD prognostic risk model. Kaplan-Meier test, ROC curve and nomograms were used to evaluate the predictive ability of metabolic related gene prognostic model. CIBERSORT algorithm was used to analyze the relationship between risk score and immune infiltration. The starBase database constructed a regulatory network consistent with the ceRNA hypothesis. IHC experiments were performed to verify the differential expression of ALG3 in LUAD and paracancerous samples. In this study, 42 abnormal metabolism-related differential genes were screened. After survival analysis, the final 5 metabolism-related genes were used as the construction of prognosis model, including ALG3, COL7A1, KL, MST1, and SLC52A1. 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The prognostic model of LUAD reveals the relationship between metabolism and prognosis of LUAD, and provides a novel perspective for diagnosis and research of LUAD.</description><subject>Adenocarcinoma of Lung - genetics</subject><subject>Adenocarcinoma of Lung - metabolism</subject><subject>Adenocarcinoma of Lung - mortality</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Biomarkers, Tumor - metabolism</subject><subject>Clinical Trial/Experimental Study</subject><subject>Female</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Humans</subject><subject>Kaplan-Meier Estimate</subject><subject>Lung Neoplasms - diagnosis</subject><subject>Lung Neoplasms - genetics</subject><subject>Lung Neoplasms - metabolism</subject><subject>Lung Neoplasms - mortality</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Nomograms</subject><subject>Prognosis</subject><subject>ROC Curve</subject><subject>Transcriptome</subject><issn>0025-7974</issn><issn>1536-5964</issn><issn>1536-5964</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdUclKxTAUDaLoc_gCQbJ0YTVj26zk4QxP3LgPN2n6jLbJM2kF_96Ks3dzuZzhHjgI7VNyTImqTm7Pj8nP8LoS5RqaUcnLQqpSrKMZIUwWlarEFtrO-ZEQyismNtEWV6yuGKczNM4DBhNi6qHDvRvAxM7nvkiug8E1eOmCO8LzxRU_wj5jwKs4uDD4id14WIaYB28xhAavUvw6jY89pCeXcBsT7sawxNC4EC0k68OE7aKNFrrs9j73Drq_vLg_uy4Wd1c3Z_NFYVldDoVTLWWmcdxKMGCJNFDSdspulKEWaskYb3gJBGRLhKGEVZa1UgnFpBQt30GnH7ar0fSusVPwBJ1eJT_Fe9URvP6LBP-gl_FFUyqIUFxMDoefDik-jy4PuvfZuq6D4OKYNaekFLKqyTuVf1Btijkn137_oUS_F6Zvz_X_wibVwe-I35qvhvgbT3CTDg</recordid><startdate>20240913</startdate><enddate>20240913</enddate><creator>Reyimu, Abdusemer</creator><creator>Cheng, Xiang</creator><creator>Liu, Wen</creator><creator>Kaisaier, Aihemaitijiang</creator><creator>Wang, Xinying</creator><creator>Sha, Yinzhong</creator><creator>Guo, Ruijie</creator><creator>Paerhati, Pawuziye</creator><creator>Maimaiti, Maimaituxun</creator><creator>He, Chuanjiang</creator><creator>Li, Li</creator><creator>Zou, Xiaoguang</creator><creator>Xu, Aimin</creator><general>Lippincott Williams &amp; 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Transcriptome data of LUAD were downloaded from the Cancer Genome Atlas database. Abnormal metabolism-related differentially expressed genes in LUAD were screened by the R language. Cox analysis was used to construct LUAD prognostic risk model. Kaplan-Meier test, ROC curve and nomograms were used to evaluate the predictive ability of metabolic related gene prognostic model. CIBERSORT algorithm was used to analyze the relationship between risk score and immune infiltration. The starBase database constructed a regulatory network consistent with the ceRNA hypothesis. IHC experiments were performed to verify the differential expression of ALG3 in LUAD and paracancerous samples. In this study, 42 abnormal metabolism-related differential genes were screened. After survival analysis, the final 5 metabolism-related genes were used as the construction of prognosis model, including ALG3, COL7A1, KL, MST1, and SLC52A1. In the model, the survival rate of LUAD patients in the high-risk subgroup was lower than that in the low-risk group. In addition, the risk score of the constructed LUAD prognostic model can be used as an independent prognostic factor for patients. According to the analysis of CIBERSORT algorithm, the risk score is related to the infiltration of multiple immune cells. The potential ceRNA network of model genes in LUAD was constructed through the starBase database. IHC experiments revealed that ALG3 expression was upregulated in LUAD. The prognostic model of LUAD reveals the relationship between metabolism and prognosis of LUAD, and provides a novel perspective for diagnosis and research of LUAD.</abstract><cop>United States</cop><pub>Lippincott Williams &amp; Wilkins</pub><pmid>39287231</pmid><doi>10.1097/MD.0000000000038746</doi><orcidid>https://orcid.org/0000-0002-9323-2390</orcidid><oa>free_for_read</oa></addata></record>
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source Wolters Kluwer Open Health; MEDLINE; DOAJ Directory of Open Access Journals; IngentaConnect Free/Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Alma/SFX Local Collection
subjects Adenocarcinoma of Lung - genetics
Adenocarcinoma of Lung - metabolism
Adenocarcinoma of Lung - mortality
Biomarkers, Tumor - genetics
Biomarkers, Tumor - metabolism
Clinical Trial/Experimental Study
Female
Gene Expression Regulation, Neoplastic
Humans
Kaplan-Meier Estimate
Lung Neoplasms - diagnosis
Lung Neoplasms - genetics
Lung Neoplasms - metabolism
Lung Neoplasms - mortality
Male
Middle Aged
Nomograms
Prognosis
ROC Curve
Transcriptome
title An abnormal metabolism-related gene, ALG3, is a potential diagnostic and prognostic biomarker for lung adenocarcinoma
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