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Wang N, Bing X, Li Y, Yao J, Dai Z, Yu D, Ouyang A. Study of radiomics based on dual-energy CT for nuclear grading and T-staging in renal clear cell carcinoma. Medicine (Baltimore) 2024; 103:e37288. [PMID: 38457546 PMCID: PMC10919525 DOI: 10.1097/md.0000000000037288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 12/23/2023] [Accepted: 01/25/2024] [Indexed: 03/10/2024] Open
Abstract
INTRODUCTION Clear cell renal cell carcinoma (ccRCC) is the most lethal subtype of renal cell carcinoma with a high invasive potential. Radiomics has attracted much attention in predicting the preoperative T-staging and nuclear grade of ccRCC. OBJECTIVE The objective was to evaluate the efficacy of dual-energy computed tomography (DECT) radiomics in predicting ccRCC grade and T-stage while optimizing the models. METHODS 200 ccRCC patients underwent preoperative DECT scanning and were randomized into training and validation cohorts. Radiomics models based on 70 KeV, 100 KeV, 150 KeV, iodine-based material decomposition images (IMDI), virtual noncontrasted images (VNC), mixed energy images (MEI) and MEI + IMDI were established for grading and T-staging. Receiver operating characteristic analysis and decision curve analysis (DCA) were performed. The area under the curve (AUC) values were compared using Delong test. RESULTS For grading, the AUC values of these models ranged from 0.64 to 0.97 during training and from 0.54 to 0.72 during validation. In the validation cohort, the performance of MEI + IMDI model was optimal, with an AUC of 0.72, sensitivity of 0.71, and specificity of 0.70. The AUC value for the 70 KeV model was higher than those for the 100 KeV, 150 KeV, and MEI models. For T-staging, these models achieved AUC values of 0.83 to 1.00 in training and 0.59 to 0.82 in validation. The validation cohort demonstrated AUCs of 0.82 and 0.70, sensitivities of 0.71 and 0.71, and specificities of 0.80 and 0.60 for the MEI + IMDI and IMDI models, respectively. In terms of grading and T-staging, the MEI + IMDI model had the highest AUC in validation, with IMDI coming in second. There were statistically significant differences between the MEI + IMDI model and the 70 KeV, 100 KeV, 150 KeV, MEI, and VNC models in terms of grading (P < .05) and staging (P ≤ .001). DCA showed that both MEI + IDMI and IDMI models outperformed other models in predicting grade and stage of ccRCC. CONCLUSIONS DECT radiomics models were helpful in grading and T-staging of ccRCC. The combined model of MEI + IMDI achieved favorable results.
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Affiliation(s)
- Ning Wang
- Department of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, Shandong Province, P. R. China
| | - Xue Bing
- Department of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, Shandong Province, P. R. China
| | - Yuhan Li
- Department of Radiology, Longkou Traditional Chinese Medicine Hospital, Yantai 265700, Shandong Province, P. R. China
| | - Jian Yao
- Department of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, Shandong Province, P. R. China
| | - Zhengjun Dai
- Scientific Research Department, Huiying Medical Technology Co., Ltd, Beijing 100192, P. R. China
| | - Dexin Yu
- Department of Radiology, Qilu Hospital of Shandong University, Jinan 250012, Shandong Province, P. R. China
| | - Aimei Ouyang
- Department of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, Shandong Province, P. R. China
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Zhang Q, Lin B, Chen H, Ye Y, Huang Y, Chen Z, Li J. Lipid metabolism-related gene expression in the immune microenvironment predicts prognostic outcomes in renal cell carcinoma. Front Immunol 2023; 14:1324205. [PMID: 38090559 PMCID: PMC10712371 DOI: 10.3389/fimmu.2023.1324205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 11/15/2023] [Indexed: 12/18/2023] Open
Abstract
Background Rates of renal cell carcinoma (RCC) occurrence and mortality are steadily rising. In an effort to address this issue, the present bioinformatics study was developed with the goal of identifying major lipid metabolism biomarkers and immune infiltration characteristics associated with RCC cases. Methods The Cancer Genome Atlas (TCGA) and E-MTAB-1980 were used to obtain matched clinical and RNA expression data from patients diagnosed with RCC. A LASSO algorithm and multivariate Cox regression analyses were employed to design a prognostic risk model for these patients. The tumor immune microenvironment (TIME) in RCC patients was further interrogated through ESTIMATE, TIMER, and single-cell gene set enrichment analysis (ssGSEA) analyses. Gene Ontology (GO), KEGG, and GSEA enrichment approaches were further employed to gauge the mechanistic basis for the observed results. Differences in gene expression and associated functional changes were then validated through appropriate molecular biology assays. Results Through the approach detailed above, a risk model based on 8 genes associated with RCC patient overall survival and lipid metabolism was ultimately identified that was capable of aiding in the diagnosis of this cancer type. Poorer prognostic outcomes in the analyzed RCC patients were associated with higher immune scores, lower levels of tumor purity, greater immune cell infiltration, and higher relative immune status. In GO and KEGG enrichment analyses, genes that were differentially expressed between risk groups were primarily related to the immune response and substance metabolism. GSEA analyses additionally revealed that the most enriched factors in the high-risk group included the stable internal environment, peroxisomes, and fatty acid metabolism. Subsequent experimental validation in vitro and in vivo revealed that the most significantly differentially expressed gene identified herein, ALOX5, was capable of suppressing RCC tumor cell proliferation, invasivity, and migration. Conclusion In summary, a risk model was successfully established that was significantly related to RCC patient prognosis and TIME composition, offering a robust foundation for the development of novel targeted therapeutic agents and individualized treatment regimens. In both immunoassays and functional analyses, dysregulated lipid metabolism was associated with aberrant immunological activity and the reprogramming of fatty acid metabolic activity, contributing to poorer outcomes.
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Affiliation(s)
- Qian Zhang
- Department of Rehabilitation Medicine, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Bingbiao Lin
- Department of Urology, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China
- Department of Radiotherapy, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Huikun Chen
- Department of Urology, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yinyan Ye
- Department of Rehabilitation Medicine, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yijie Huang
- Department of Rehabilitation Medicine, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Zhen Chen
- Department of Rehabilitation Medicine, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Jun Li
- Department of Urology, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China
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Han GD, Dai J, Hui HX, Zhu J. ALOX5AP suppresses osteosarcoma progression via Wnt/β-catenin/EMT pathway and associates with clinical prognosis and immune infiltration. J Orthop Surg Res 2023; 18:446. [PMID: 37344882 DOI: 10.1186/s13018-023-03919-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 06/08/2023] [Indexed: 06/23/2023] Open
Abstract
Osteosarcoma (OS) is one of the most common malignant neoplasms in children and adolescents. Immune infiltration into the microenvironment of the tumor has a positive correlation with overall survival in patients with OS. The purpose of this study was to search for potential diagnostic markers that are involved in immune cell infiltration for OS. Patients with OS who acquired metastases within 5 years (n = 34) were compared to patients who did not develop metastases within 5 years (n = 19). Differentially expressed genes (DEGs) were tested for in both patient groups. To discover possible biomarkers, the LASSO regression model and the SVM-RFE analysis were both carried out. With the assistance of CIBERSORT, the compositional patterns of the 22 different types of immune cell fraction in OS were estimated. In this research, a total of 33 DEGs were obtained: 33 genes were significantly downregulated. Moreover, we identified six critical genes, including ALOX5AP, HLA-DOA, HLA-DMA, HLA-DRB4, HCLS1 and LOC647450. ROC assays confirmed their diagnostic value with AUC > 0.7. In addition, we found that the six critical genes were associated with immune infiltration. Then, we confirmed the expression of ALOX5AP was distinctly decreased in OS specimens and cell lines. High expression of ALOX5AP predicted an advanced clinical stage and overall survival of OS patients. Functionally, we found that overexpression of ALOX5AP distinctly suppressed the proliferation, migration, invasion and EMT via modulating Wnt/β-catenin signaling. Overall, we found that ALOX5AP overexpression inhibits OS development via regulation of Wnt/β-catenin signaling pathways, suggesting ALOX5AP as a novel molecular biomarker for enhanced therapy of OS.
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Affiliation(s)
- Guo-Dong Han
- Department of Orthopedics, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, China
| | - Jian Dai
- Department of Orthopedics, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, China
| | - Hong-Xia Hui
- Department of Medical Oncology, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, China
| | - Jing Zhu
- Department of Medical Oncology, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, China.
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Xi Y, Song L, Wang S, Zhou H, Ren J, Zhang R, Fu F, Yang Q, Duan G, Wang J. Identification of basement membrane-related prognostic signature for predicting prognosis, immune response and potential drug prediction in papillary renal cell carcinoma. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2023; 20:10694-10724. [PMID: 37322956 DOI: 10.3934/mbe.2023474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Papillary renal cell carcinoma (PRCC) is a malignant neoplasm of the kidney and is highly interesting due to its increasing incidence. Many studies have shown that the basement membrane (BM) plays an important role in the development of cancer, and structural and functional changes in the BM can be observed in most renal lesions. However, the role of BM in the malignant progression of PRCC and its impact on prognosis has not been fully studied. Therefore, this study aimed to explore the functional and prognostic value of basement membrane-associated genes (BMs) in PRCC patients. We identified differentially expressed BMs between PRCC tumor samples and normal tissue and systematically explored the relevance of BMs to immune infiltration. Moreover, we constructed a risk signature based on these differentially expressed genes (DEGs) using Lasso regression analysis and demonstrated their independence using Cox regression analysis. Finally, we predicted 9 small molecule drugs with the potential to treat PRCC and compared the differences in sensitivity to commonly used chemotherapeutic agents between high and low-risk groups to better target patients for more precise treatment planning. Taken together, our study suggested that BMs might play a crucial role in the development of PRCC, and these results might provide new insights into the treatment of PRCC.
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Affiliation(s)
- Yujia Xi
- Department of Urology, The Second Hospital of Shanxi Medical University, Taiyuan, China
| | - Liying Song
- Second School of Clinical Medicine, Shanxi Medical University, Taiyuan, China
| | - Shuang Wang
- Second School of Clinical Medicine, Shanxi Medical University, Taiyuan, China
| | - Haonan Zhou
- First School of Clinical Medicine, Shanxi Medical University, Taiyuan, China
| | - Jieying Ren
- School of Basic Medicine, Shanxi Medical University, Taiyuan, China
| | - Ran Zhang
- School of Public Health, Shanxi Medical University, Taiyuan, China
| | - Feifan Fu
- School of Basic Medicine, Shanxi Medical University, Taiyuan, China
| | - Qian Yang
- School of Basic Medicine, Shanxi Medical University, Taiyuan, China
| | - Guosheng Duan
- Second School of Clinical Medicine, Shanxi Medical University, Taiyuan, China
| | - Jingqi Wang
- Department of Urology, The Second Hospital of Shanxi Medical University, Taiyuan, China
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