Predictive Value of miRNAs Markers for Advanced Lung Squamous Cell Carcinoma
Background and objective Lung cancer is one of the leading causes of cancer-related mortality worldwide, with above 80% of cases be non-small cell lung cancer (NSCLC), among which lung squamous cell carcinoma (LUSC) occupies a significant proportion. Although comprehensive cancer therapies have cons...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Chinese Anti-Cancer Association; Chinese Antituberculosis Association
2025-05-01
|
| Series: | Chinese Journal of Lung Cancer |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.3779/j.issn.1009-3419.2025.102.16 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849336615164444672 |
|---|---|
| author | Anna WANG Jingjing CONG Yingjia WANG Xin’ge LI Junjian PI Kaijing LIU Hongjie ZHANG Xiaoyan YAN Hongmei LI |
| author_facet | Anna WANG Jingjing CONG Yingjia WANG Xin’ge LI Junjian PI Kaijing LIU Hongjie ZHANG Xiaoyan YAN Hongmei LI |
| author_sort | Anna WANG |
| collection | DOAJ |
| description | Background and objective Lung cancer is one of the leading causes of cancer-related mortality worldwide, with above 80% of cases be non-small cell lung cancer (NSCLC), among which lung squamous cell carcinoma (LUSC) occupies a significant proportion. Although comprehensive cancer therapies have considerably improved the overall survival of patients, patients with advanced LUSC have a poorer prognosis. Therefore, there is a need for a biomarker to predict the progress of advanced LUSC in order to improve prognosis through early diagnosis. Previous studies have shown that miRNAs are differentially expressed in lung cancer tissues and play roles as potential oncogenes or tumor suppressors. The aim of this study is to identify differentially expressed miRNAs between early-stage and advanced-stage LUSC, and to establish a set of miRNAs that can predict the progress of advanced LUSC. Methods Clinical data and miRNA-related data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Bioinformatic methods were applied to analyze the data. Receiver operating characteristic (ROC) curves were plotted, and various online tools were used to predict target genes, with subsequent analysis of the potential biological mechanisms of these genes. Results A total of 58 differentially expressed miRNAs were identified between the experiment group and the control group. Seven miRNAs were selected for potential construction of a miRNA biomarker through LASSO regression, and based on the area under the curve (AUC) values of each miRNA, four of these miRNAs (miR-377-3p, miR-4779, miR-6803-5p, miR-3960) were ultimately chosen as biomarkers for predicting advanced LUSC. The AUC under the ROC curve for the combined four miRNAs was 0.865. Enrichment analysis showed that these target genes were involved in several pathways, including cancer-related pathways, mitogen-activated protein kinase (MAPK) signaling pathway, serine/threonine kinase, and tyrosine kinase signaling pathways. Conclusion The combined use of miR-377-3p, miR-4779, miR-6803-5p and miR-3960 provides a good predictive ability for the progress of advanced LUSC patients, with an AUC of 0.865. |
| format | Article |
| id | doaj-art-0c960d678e4b4f22a60a618ad5e62fa0 |
| institution | Kabale University |
| issn | 1009-3419 1999-6187 |
| language | zho |
| publishDate | 2025-05-01 |
| publisher | Chinese Anti-Cancer Association; Chinese Antituberculosis Association |
| record_format | Article |
| series | Chinese Journal of Lung Cancer |
| spelling | doaj-art-0c960d678e4b4f22a60a618ad5e62fa02025-08-20T03:44:55ZzhoChinese Anti-Cancer Association; Chinese Antituberculosis AssociationChinese Journal of Lung Cancer1009-34191999-61872025-05-0128532533310.3779/j.issn.1009-3419.2025.102.16Predictive Value of miRNAs Markers for Advanced Lung Squamous Cell CarcinomaAnna WANG0Jingjing CONG1Yingjia WANG2Xin’ge LI3Junjian PI4Kaijing LIU5Hongjie ZHANG6Xiaoyan YAN7Hongmei LI8Department of Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, ChinaDepartment of Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, ChinaCollege of Basic Medical Sciences, Shandong First Medical University, Jinan 250117, ChinaCollege of Medicine, Hainan Vocational University of Science
and Technology, Haikou 570000, ChinaQingdao Medical College, Qingdao University, Qingdao 266071, ChinaDepartment of Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, ChinaDepartment of Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, ChinaDepartment of Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, ChinaDepartment of Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, ChinaBackground and objective Lung cancer is one of the leading causes of cancer-related mortality worldwide, with above 80% of cases be non-small cell lung cancer (NSCLC), among which lung squamous cell carcinoma (LUSC) occupies a significant proportion. Although comprehensive cancer therapies have considerably improved the overall survival of patients, patients with advanced LUSC have a poorer prognosis. Therefore, there is a need for a biomarker to predict the progress of advanced LUSC in order to improve prognosis through early diagnosis. Previous studies have shown that miRNAs are differentially expressed in lung cancer tissues and play roles as potential oncogenes or tumor suppressors. The aim of this study is to identify differentially expressed miRNAs between early-stage and advanced-stage LUSC, and to establish a set of miRNAs that can predict the progress of advanced LUSC. Methods Clinical data and miRNA-related data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Bioinformatic methods were applied to analyze the data. Receiver operating characteristic (ROC) curves were plotted, and various online tools were used to predict target genes, with subsequent analysis of the potential biological mechanisms of these genes. Results A total of 58 differentially expressed miRNAs were identified between the experiment group and the control group. Seven miRNAs were selected for potential construction of a miRNA biomarker through LASSO regression, and based on the area under the curve (AUC) values of each miRNA, four of these miRNAs (miR-377-3p, miR-4779, miR-6803-5p, miR-3960) were ultimately chosen as biomarkers for predicting advanced LUSC. The AUC under the ROC curve for the combined four miRNAs was 0.865. Enrichment analysis showed that these target genes were involved in several pathways, including cancer-related pathways, mitogen-activated protein kinase (MAPK) signaling pathway, serine/threonine kinase, and tyrosine kinase signaling pathways. Conclusion The combined use of miR-377-3p, miR-4779, miR-6803-5p and miR-3960 provides a good predictive ability for the progress of advanced LUSC patients, with an AUC of 0.865.http://dx.doi.org/10.3779/j.issn.1009-3419.2025.102.16lung neoplasmsadvanced lung squamous cell carcinomamirnasbiomarkersenrichment analysis |
| spellingShingle | Anna WANG Jingjing CONG Yingjia WANG Xin’ge LI Junjian PI Kaijing LIU Hongjie ZHANG Xiaoyan YAN Hongmei LI Predictive Value of miRNAs Markers for Advanced Lung Squamous Cell Carcinoma Chinese Journal of Lung Cancer lung neoplasms advanced lung squamous cell carcinoma mirnas biomarkers enrichment analysis |
| title | Predictive Value of miRNAs Markers for Advanced Lung Squamous Cell Carcinoma |
| title_full | Predictive Value of miRNAs Markers for Advanced Lung Squamous Cell Carcinoma |
| title_fullStr | Predictive Value of miRNAs Markers for Advanced Lung Squamous Cell Carcinoma |
| title_full_unstemmed | Predictive Value of miRNAs Markers for Advanced Lung Squamous Cell Carcinoma |
| title_short | Predictive Value of miRNAs Markers for Advanced Lung Squamous Cell Carcinoma |
| title_sort | predictive value of mirnas markers for advanced lung squamous cell carcinoma |
| topic | lung neoplasms advanced lung squamous cell carcinoma mirnas biomarkers enrichment analysis |
| url | http://dx.doi.org/10.3779/j.issn.1009-3419.2025.102.16 |
| work_keys_str_mv | AT annawang predictivevalueofmirnasmarkersforadvancedlungsquamouscellcarcinoma AT jingjingcong predictivevalueofmirnasmarkersforadvancedlungsquamouscellcarcinoma AT yingjiawang predictivevalueofmirnasmarkersforadvancedlungsquamouscellcarcinoma AT xingeli predictivevalueofmirnasmarkersforadvancedlungsquamouscellcarcinoma AT junjianpi predictivevalueofmirnasmarkersforadvancedlungsquamouscellcarcinoma AT kaijingliu predictivevalueofmirnasmarkersforadvancedlungsquamouscellcarcinoma AT hongjiezhang predictivevalueofmirnasmarkersforadvancedlungsquamouscellcarcinoma AT xiaoyanyan predictivevalueofmirnasmarkersforadvancedlungsquamouscellcarcinoma AT hongmeili predictivevalueofmirnasmarkersforadvancedlungsquamouscellcarcinoma |