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Wu Y, Ren L, Tang Y, Zhu Z, Liu S, Jiang Y, Zhang S, Zhuang X, Chen Y. Immunobiological signatures and the emerging role of SPP1 in predicting tumor heterogeneity, malignancy, and clinical outcomes in stomach adenocarcinoma. Aging (Albany NY) 2023; 15:11588-11610. [PMID: 37889539 PMCID: PMC10637809 DOI: 10.18632/aging.205148] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 10/02/2023] [Indexed: 10/28/2023]
Abstract
BACKGROUND Immunotherapy, as a form of immunobiological therapy, represents a promising approach for enhancing patients' immune responses. This work aims to present innovative ideas and insights for prognostic assessment and clinical treatment of stomach adenocarcinoma (STAD) by leveraging immunobiological signatures. METHODS We employed weighted gene co-expression network analysis (WGCNA) and unsupervised clustering analysis to identify hub genes. These hub genes were utilized to construct a prognostic risk model, and their impact on the tumor microenvironment (TME) and DNA variations was assessed using large-scale STAD patient cohorts. Additionally, we conducted transfection experiments with plasmids to investigate the influence of SPP1 on the malignancy of HGC27 and NCI-N87 cells. RESULTS Unsupervised clustering of 12 immune-related genes (IRGs) revealed three distinct alteration patterns with unique molecular phenotypes, clinicopathological characteristics, prognosis, and TME features. Using LASSO and multivariate Cox regression analyses, we identified three hub genes (MMP12, SPP1, PLAU) from the IRGs to establish a risk signature. This IRG-related risk model significantly stratified the prognosis risk among STAD patients in the training (n = 522), testing (n = 521), and validation (n = 300) cohorts. Notably, there were discernible differences in therapy responses and TME characteristics, such as tumor purity and lymphocyte infiltration, between the risk model groups. Subsequently, a nomogram that incorporates the IRG signature and clinicopathological factors demonstrated superior sensitivity and specificity in predicting outcomes for STAD patients. Furthermore, down-regulation of SPP1, as observed after siRNA transfection, significantly inhibited the proliferation and migration abilities of HGC27 and NCI-N87 cells. CONCLUSIONS In summary, this study highlights the critical role of immune-related signatures in STAD and offers novel insights into prognosis indicators and immunotherapeutic targets for this condition. SPP1 emerges as an independent prognostic factor for STAD and appears to regulate STAD progression by influencing the immune microenvironment.
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Affiliation(s)
- Yanan Wu
- Department of Gastroenterology, Rudong People’s Hospital, Rudong Hospital Affiliated to Nantong University, Nantong, China
| | - Lingyu Ren
- Department of Gastroenterology, Rudong People’s Hospital, Rudong Hospital Affiliated to Nantong University, Nantong, China
| | - Yichun Tang
- Cancer Research Center Nantong, Nantong Tumor Hospital and Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Zhu Zhu
- Cancer Research Center Nantong, Nantong Tumor Hospital and Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Shifan Liu
- Department of Medical Imaging, Medical School of Nantong University, Nantong, China
| | - Yan Jiang
- Department of Engineering Training Center, Nantong University, Nantong, China
| | - Siming Zhang
- Cancer Research Center Nantong, Nantong Tumor Hospital and Affiliated Tumor Hospital of Nantong University, Nantong, China
| | - Xiaocan Zhuang
- Department of Gastroenterology, Rudong People’s Hospital, Rudong Hospital Affiliated to Nantong University, Nantong, China
| | - Yuanbiao Chen
- Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
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Xiong Z, Xing C, Zhang P, Diao Y, Guang C, Ying Y, Zhang W. Identification of a Novel Protein-Based Prognostic Model in Gastric Cancers. Biomedicines 2023; 11:biomedicines11030983. [PMID: 36979962 PMCID: PMC10046574 DOI: 10.3390/biomedicines11030983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Revised: 02/14/2023] [Accepted: 03/13/2023] [Indexed: 03/30/2023] Open
Abstract
Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide. However, there are still no reliable biomarkers for the prognosis of this disease. This study aims to construct a robust protein-based prognostic prediction model for GC patients. The protein expression data and clinical information of GC patients were downloaded from the TCPA and TCGA databases, and the expressions of 218 proteins in 352 GC patients were analyzed using bioinformatics methods. Additionally, Kaplan-Meier (KM) survival analysis and univariate and multivariate Cox regression analysis were applied to screen the prognosis-related proteins for establishing the prognostic prediction risk model. Finally, five proteins, including NDRG1_pT346, SYK, P90RSK, TIGAR, and XBP1, were related to the risk prognosis of gastric cancer and were selected for model construction. Furthermore, a significant trend toward worse survival was found in the high-risk group (p = 1.495 × 10-7). The time-dependent ROC analysis indicated that the model had better specificity and sensitivity compared to the clinical features at 1, 2, and 3 years (AUC = 0.685, 0.673, and 0.665, respectively). Notably, the independent prognostic analysis results revealed that the model was an independent prognostic factor for GC patients. In conclusion, the robust protein-based model based on five proteins was established, and its potential benefits in the prognostic prediction of GC patients were demonstrated.
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Affiliation(s)
- Zhijuan Xiong
- Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
- Jiangxi Medical Center for Major Public Health Events, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
- The Department of Respiratory and Intensive Care Medicine, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Chutian Xing
- Queen Mary School, Nanchang University, Nanchang 330006, China
| | - Ping Zhang
- The Department of Respiratory and Intensive Care Medicine, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Yunlian Diao
- The Department of Respiratory and Intensive Care Medicine, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Chenxi Guang
- Jiangxi Medical Center for Major Public Health Events, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Ying Ying
- Jiangxi Medical Center for Major Public Health Events, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Wei Zhang
- Jiangxi Medical Center for Major Public Health Events, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
- The Department of Respiratory and Intensive Care Medicine, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
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Liu J, Dai Y, Lu Y, Liu X, Deng J, Lu W, Liu Q. Identification and validation of a new pyroptosis-associated lncRNA signature to predict survival outcomes, immunological responses and drug sensitivity in patients with gastric cancer. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2023; 20:1856-1881. [PMID: 36899512 DOI: 10.3934/mbe.2023085] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
BACKGROUND Gastric cancer (GC) ranks fifth in prevalence among carcinomas worldwide. Both pyroptosis and long noncoding RNAs (lncRNAs) play crucial roles in the occurrence and development of gastric cancer. Therefore, we aimed to construct a pyroptosis-associated lncRNA model to predict the outcomes of patients with gastric cancer. METHODS Pyroptosis-associated lncRNAs were identified through co-expression analysis. Univariate and multivariate Cox regression analyses were performed using the least absolute shrinkage and selection operator (LASSO). Prognostic values were tested through principal component analysis, a predictive nomogram, functional analysis and Kaplan‒Meier analysis. Finally, immunotherapy and drug susceptibility predictions and hub lncRNA validation were performed. RESULTS Using the risk model, GC individuals were classified into two groups: low-risk and high-risk groups. The prognostic signature could distinguish the different risk groups based on principal component analysis. The area under the curve and the conformance index suggested that this risk model was capable of correctly predicting GC patient outcomes. The predicted incidences of the one-, three-, and five-year overall survivals exhibited perfect conformance. Distinct changes in immunological markers were noted between the two risk groups. Finally, greater levels of appropriate chemotherapies were required in the high-risk group. AC005332.1, AC009812.4 and AP000695.1 levels were significantly increased in gastric tumor tissue compared with normal tissue. CONCLUSIONS We created a predictive model based on 10 pyroptosis-associated lncRNAs that could accurately predict the outcomes of GC patients and provide a promising treatment option in the future.
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Affiliation(s)
- Jinsong Liu
- Department of Oncology, Wujin Hospital Affiliated with Jiangsu University, Changzhou 213017, China
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine, Changzhou 213017, China
| | - Yuyang Dai
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine, Changzhou 213017, China
- Department of Radiology, Wujin Hospital Affiliated with Jiangsu University, Changzhou 213017, China
| | - Yueyao Lu
- Department of Oncology, The Changzhou Clinical School of Nanjing Medical University, Changzhou 213017, China
- Department of Oncology, The Wujin Clinical College of Xuzhou Medical University, Changzhou 213017, China
| | - Xiuling Liu
- Department of Oncology, Wujin Hospital Affiliated with Jiangsu University, Changzhou 213017, China
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine, Changzhou 213017, China
| | - Jianzhong Deng
- Department of Oncology, Wujin Hospital Affiliated with Jiangsu University, Changzhou 213017, China
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine, Changzhou 213017, China
| | - Wenbin Lu
- Department of Oncology, Wujin Hospital Affiliated with Jiangsu University, Changzhou 213017, China
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine, Changzhou 213017, China
- Department of Oncology, The Changzhou Clinical School of Nanjing Medical University, Changzhou 213017, China
- Department of Oncology, The Wujin Clinical College of Xuzhou Medical University, Changzhou 213017, China
| | - Qian Liu
- Department of Oncology, Wujin Hospital Affiliated with Jiangsu University, Changzhou 213017, China
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine, Changzhou 213017, China
- Department of Oncology, The Wujin Clinical College of Xuzhou Medical University, Changzhou 213017, China
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Huang Y, Zou Y, Tian Y, Yang Z, Hou Z, Li P, Liu F, Ling J, Wen Y. N6-methylandenosine-related immune genes correlate with prognosis and immune landscapes in gastric cancer. Front Oncol 2022; 12:1009881. [PMID: 36523987 PMCID: PMC9745091 DOI: 10.3389/fonc.2022.1009881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 11/16/2022] [Indexed: 11/10/2023] Open
Abstract
OBJECTIVES This study aimed to probe into the significance of N6-methyladenosine (m6A)-related immune genes (m6AIGs) in predicting prognoses and immune landscapes of patients with gastric cancer (GC). METHODS The clinical data and transcriptomic matrix of GC patients were acquired from The Cancer Genome Atlas database. The clinically meaningful m6AIGs were acquired by univariate Cox regression analysis. GC patients were stratified into different clusters via consensus clustering analysis and different risk subgroups via m6AIGs prognostic signature. The clinicopathological features and tumor microenvironment (TME) in the different clusters and different risk subgroups were explored. The predictive performance was evaluated using the KM method, ROC curves, and univariate and multivariate regression analyses. Moreover, we fabricated a nomogram based on risk scores and clinical risk characteristics. Biological functional analysis was performed based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. The connectivity map was used to screen out potential small molecule drugs for GC patients. RESULTS A total of 14 prognostic m6AIGs and two clusters based on 14 prognostic m6AIGs were identified. A prognostic signature based on 4 m6AIGs and a nomogram based on independent prognostic factors was constructed and validated. Different clusters and different risk subgroups were significantly correlated with TME scores, the distribution of immune cells, and the expression of immune checkpoint genes. Some malignant and immune biological processes and pathways were correlated with the patients with poor prognosis. Ten small molecular drugs with potential therapeutic effect were screened out. CONCLUSIONS This study revealed the prognostic role and significant values of m6AIGs in GC, which enhanced the understanding of m6AIGs and paved the way for developing predictive biomarkers and therapeutic targets for GC.
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Affiliation(s)
- Yuancheng Huang
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Yushan Zou
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Yanhua Tian
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Zehong Yang
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Zhengkun Hou
- Department of Gastroenterology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Peiwu Li
- Department of Gastroenterology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Fengbin Liu
- Department of Gastroenterology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
- Department of Gastroenterology, Baiyun Branch of the First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Jiasheng Ling
- Department of Gastroenterology, Huizhou Hospital of Traditional Chinese Medicine, Huizhou, Guangdong, China
| | - Yi Wen
- Department of Gastroenterology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
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Bioinformatics Analysis Revealing the Correlation between NF-κB Signaling Pathway and Immune Infiltration in Gastric Cancer. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:5385456. [PMID: 35936362 PMCID: PMC9352505 DOI: 10.1155/2022/5385456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 07/05/2022] [Accepted: 07/13/2022] [Indexed: 12/24/2022]
Abstract
Although the emerging of immunotherapy conferred a new landscape of gastric cancer (GC) treatment, its response rate was of significant individual differences. Insight into GC immune microenviroment may contribute to breaking the dilemma. To this end, the enrichment score of NF-κB signaling pathway was calculated in each GC sample from The Cancer Genome Atlas (TCGA) via ssGSEA algorithm, and its association with immune infiltration was estimated. Based on NF-κB-related genes, a risk score was established and its involvement in immune infiltration, tumor mutational burden (TMB), and N6-methyladenosine (M6A) modification was analyzed in GC. The results showed that NF-κB signaling pathway promoted the infiltration of immune cells in GC. In addition, GC samples were divided into low- and high-risk groups according to a seven-gene (CARD11, CCL21, GADD45B, LBP, RELB, TRAF1, and VCAM1) risk score. Although the high-risk group displayed high immune infiltration and high expression of M6A regulatory genes, it remains in an immunosuppressive microenviroment and whereby suffers a poorer outcome. Of note, most of hub genes were related to immune infiltration and could serve as an independent prognostic biomarker. Conclusively, our study emphasized the crucial role of NF-κB signaling pathway in GC immune microenviroment and provided several candidate genes that may participate in immune infiltration.
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