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Chen X, Zhang Z, Qin Z, Zhu X, Wang K, Kang L, Li C, Wang H. Identification and validation of a novel signature based on macrophage marker genes for predicting prognosis and drug response in kidney renal clear cell carcinoma by integrated analysis of single cell and bulk RNA sequencing. Aging (Albany NY) 2024; 16:5676-5702. [PMID: 38517387 PMCID: PMC11006469 DOI: 10.18632/aging.205671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 02/26/2024] [Indexed: 03/23/2024]
Abstract
Macrophages are found in a variety of tumors and play a critical role in shaping the tumor microenvironment, affecting tumor progression, metastasis, and drug resistance. However, the clinical relevance of marker genes associated with macrophage in kidney renal clear cell carcinoma (KIRC) has yet to be documented. In this study, we initiated a thorough examination of single-cell RNA sequencing (scRNA-seq) data for KIRC retrieved from the Gene Expression Omnibus (GEO) database and determined 244 macrophage marker genes (MMGs). Univariate analysis, LASSO regression, and multivariate regression analysis were performed to develop a five-gene prognostic signature in The Cancer Genome Atlas (TCGA) database, which could divide KIRC patients into low-risk (L-R) and high-risk (H-R) groups. Then, a nomogram was constructed to predict the survival rate of KIRC patients at 1, 3, and 5 years, which was well assessed by receiver operating characteristic curve (ROC), calibration curve, and decision curve analyses (DCA). Functional enrichment analysis showed that immune-related pathways (such as immunoglobulin complex, immunoglobulin receptor binding, and cytokine-cytokine receptor interaction) were mainly enriched in the H-R group. Additionally, in comparison to the L-R cohort, patients belonging to the H-R cohort exhibited increased immune cell infiltration, elevated expression of immune checkpoint genes (ICGs), and a higher tumor immune dysfunction and exclusion (TIDE) score. This means that patients in the H-R group may be less sensitive to immunotherapy than those in the L-R group. Finally, IFI30 was validated to increase the ability of KIRC cells to proliferate, invade and migrate in vitro. In summary, our team has for the first time developed and validated a predictive model based on macrophage marker genes to accurately predict overall survival (OS), immune characteristics, and treatment benefit in KIRC patients.
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Affiliation(s)
- Xiaoxu Chen
- Department of Oncology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Precision Medicine for Sex Hormones and Diseases (in Preparation), The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Zheyu Zhang
- Department of Oncology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Precision Medicine for Sex Hormones and Diseases (in Preparation), The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Zheng Qin
- Department of Oncology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Precision Medicine for Sex Hormones and Diseases (in Preparation), The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Xiao Zhu
- Department of Oncology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Precision Medicine for Sex Hormones and Diseases (in Preparation), The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Kaibin Wang
- Department of Oncology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Precision Medicine for Sex Hormones and Diseases (in Preparation), The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Lijuan Kang
- Department of Oncology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Precision Medicine for Sex Hormones and Diseases (in Preparation), The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Changying Li
- Department of Oncology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Precision Medicine for Sex Hormones and Diseases (in Preparation), The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Haitao Wang
- Department of Oncology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Precision Medicine for Sex Hormones and Diseases (in Preparation), The Second Hospital of Tianjin Medical University, Tianjin, China
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Wang R, Huang Y, He J, Jin S, Li X, Tan K, Xia W. The endoplasmic reticulum stress-related genes and molecular typing predicts prognosis and reveals characterization of tumor immune microenvironment in lung squamous cell carcinoma. Discov Oncol 2024; 15:37. [PMID: 38363409 PMCID: PMC10873263 DOI: 10.1007/s12672-024-00887-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 02/07/2024] [Indexed: 02/17/2024] Open
Abstract
BACKGROUND Endoplasmic reticulum stress (ERS) acts critical roles on cell growth, proliferation, and metastasis in various cancers. However, the relationship between ERs and lung squamous cell carcinoma (LUSC) prognoses still remains unclear. METHODS The consensus clustering analysis of ERS-related genes and the differential expression analysis between clusters were investigated in LUSC based on TCGA database. Furthermore, ERS-related prognostic risk models were constructed by LASSO regression and Cox regression analyses. Then, the predictive effect of the risk model was evaluated by Kaplan-Meier, Cox regression, and ROC Curve analyses, as well as validated in the GEO cohort. According to the optimal threshold, patients with LUSC were divided into high- and low- risk groups, and somatic mutations, immune cell infiltration, chemotherapy response and immunotherapy effect were systematically analyzed. RESULTS Two ERS-related clusters were identified in patients with LUSC that had distinct patterns of immune cell infiltration. A 5-genes ERS-related prognostic risk model and nomogram were constructed and validated. Kaplan-Meier curves and Cox regression analysis showed that ERS risk score was an independent prognostic factor (p < 0.001, HR = 1.317, 95% CI = 1.159-1.496). Patients with low-risk scores presented significantly lower TIDE scores and significantly lower IC50 values for common chemotherapy drugs such as cisplatin and gemcitabine. CONCLUSION ERS-related risk signature has certain prognostic value and may be a potential therapeutic target and prognostic biomarker for LUSC patients.
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Affiliation(s)
- Ruolan Wang
- College of Pharmacy, Dali University, Dali, 671000, Yunnan, China
- Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China
| | - Yanhua Huang
- Department of Procurement Management, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China
| | - Juan He
- Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China
| | - Shan Jin
- College of Pharmacy, Dali University, Dali, 671000, Yunnan, China
- Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China
| | - Xin Li
- College of Pharmacy, Dali University, Dali, 671000, Yunnan, China
- Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China
| | - Kun Tan
- Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China
| | - Wei Xia
- Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China.
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