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Gul Mohammad A, Li D, He R, Lei X, Mao L, Zhang B, Zhong X, Yin Z, Cao W, Zhang W, Hei R, Zheng Q, Zhang Y. Integrated analyses of an RNA binding protein-based signature related to tumor immune microenvironment and candidate drugs in osteosarcoma. Am J Transl Res 2022; 14:2501-2526. [PMID: 35559393 PMCID: PMC9091083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 03/24/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVE Osteosarcoma is the most frequent primary bone malignancy, associated with frequent recurrence and lung metastasis. RNA-binding proteins (RBPs) are pivotal in regulating several aspects of cancer biology. Nonetheless, interaction between RBPs and the osteosarcoma immune microenvironment is poorly understood. We investigated whether RBPs can predict prognosis and immunotherapy response in osteosarcoma patients. METHODS We constructed an RBP-related prognostic signature (RRPS) by univariate coupled with multivariate analyses and verified the independent prognostic efficacy of the signature. Single-sample Gene Set Enrichment Analysis (ssGSEA) along with ESTIMATE analysis were carried out to investigate the variations in immune characteristics between subgroups with various RRPS-scores. Furthermore, we investigatedpossible small molecule drugs using the connectivity map database and validated the expression of hub RBPs by qRT-PCR. RESULTS The RRPS, consisting of seven hub RBPs, was an independent prognostic factor compared to traditional clinical features. The RRPS could distinguish immune functions, immune score, stromal score, tumor purity and tumor infiltration by immune cells in different osteosarcoma subjects. Additionally, patients with high RRPS-scores had lower expression of immune checkpoint genes than patients with low RRPS-scores. We finally identified six small molecule drugs that may improve prognosis in osteosarcoma patients and substantiated notable differences in the contents of these RBPs. CONCLUSION We evaluated the prognostic value and clinical application of an RBPs-based prognostic signature and identified promising biomarkers to predict immune cell infiltration and immunotherapy response in osteosarcoma.
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Affiliation(s)
- Abdulraheem Gul Mohammad
- Department of Orthopedics, Affiliated Hospital of Jiangsu UniversityZhenjiang 212001, Jiangsu, China
| | - Dapeng Li
- Department of Orthopedics, Affiliated Hospital of Jiangsu UniversityZhenjiang 212001, Jiangsu, China
| | - Rong He
- Cancer Institute, The Affiliated People’s Hospital of Jiangsu UniversityZhenjiang 212000, Jiangsu, China
| | - Xuan Lei
- Department of Burn and Plastic Surgery, Affiliated Hospital of Jiangsu UniversityZhenjiang 212001, Jiangsu, China
| | - Lianghao Mao
- Department of Orthopedics, Affiliated Hospital of Jiangsu UniversityZhenjiang 212001, Jiangsu, China
| | - Bing Zhang
- Department of Orthopedics, Affiliated Hospital of Jiangsu UniversityZhenjiang 212001, Jiangsu, China
| | - Xinyu Zhong
- Department of Orthopedics, Affiliated Hospital of Jiangsu UniversityZhenjiang 212001, Jiangsu, China
| | - Zhengyu Yin
- Department of Orthopedics, Affiliated Hospital of Jiangsu UniversityZhenjiang 212001, Jiangsu, China
| | - Wenbing Cao
- Department of Orthopedics, Affiliated Hospital of Jiangsu UniversityZhenjiang 212001, Jiangsu, China
| | - Wenchao Zhang
- Department of Orthopedics, Affiliated Hospital of Jiangsu UniversityZhenjiang 212001, Jiangsu, China
| | - Ruoxuan Hei
- Department of Hematological Laboratory Science, Jiangsu Key Laboratory of Medical Science and Laboratory Medicine, School of Medicine, Jiangsu UniversityZhenjiang 212000, Jiangsu, China
| | - Qiping Zheng
- Department of Hematological Laboratory Science, Jiangsu Key Laboratory of Medical Science and Laboratory Medicine, School of Medicine, Jiangsu UniversityZhenjiang 212000, Jiangsu, China
- Shenzhen Academy of Peptide Targeting Technology at Pingshan, and Shenzhen Tyercan Bio-Pharm Co., Ltd.Shenzhen 518118, Guangdong, China
| | - Yiming Zhang
- Department of Orthopedics, Affiliated Hospital of Jiangsu UniversityZhenjiang 212001, Jiangsu, China
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Chen C, Chen Y, Jin X, Ding Y, Jiang J, Wang H, Yang Y, Lin W, Chen X, Huang Y, Teng L. Identification of Tumor Mutation Burden, Microsatellite Instability, and Somatic Copy Number Alteration Derived Nine Gene Signatures to Predict Clinical Outcomes in STAD. Front Mol Biosci 2022; 9:793403. [PMID: 35480879 PMCID: PMC9037630 DOI: 10.3389/fmolb.2022.793403] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 03/14/2022] [Indexed: 12/11/2022] Open
Abstract
Genomic features, including tumor mutation burden (TMB), microsatellite instability (MSI), and somatic copy number alteration (SCNA), had been demonstrated to be involved with the tumor microenvironment (TME) and outcome of gastric cancer (GC). We obtained profiles of TMB, MSI, and SCNA by processing 405 GC data from The Cancer Genome Atlas (TCGA) and then conducted a comprehensive analysis though “iClusterPlus.” A total of two subgroups were generated, with distinguished prognosis, somatic mutation burden, copy number changes, and immune landscape. We revealed that Cluster1 was marked by a better prognosis, accompanied by higher TMB, MSIsensor score, TMEscore, and lower SCNA burden. Based on these clusters, we screened 196 differentially expressed genes (DEGs), which were subsequently projected into univariate Cox survival analysis. We constructed a 9-gene immune risk score (IRS) model using LASSO-penalized logistic regression. Moreover, the prognostic prediction of IRS was verified by receiver operating characteristic (ROC) curve analysis and nomogram plot. Another independent Gene Expression Omnibus (GEO) contained specimens from 109 GC patients was designed as an external validation. Our works suggested that the 9‐gene‐signature prediction model, which was derived from TMB, MSI, and SCNA, was a promising predictive tool for clinical outcomes in GC patients. This novel methodology may help clinicians uncover the underlying mechanisms and guide future treatment strategies.
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Affiliation(s)
- Chuanzhi Chen
- Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yi Chen
- Department of Oncology-Pathology, Karolinska Institute, Solna, Sweden
| | - Xin Jin
- Department of Breast Surgery, Zhuji Affiliated Hospital of Shaoxing University, Zhuji, China
| | - Yongfeng Ding
- Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Junjie Jiang
- Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Haohao Wang
- Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yan Yang
- Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Wu Lin
- Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xiangliu Chen
- Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yingying Huang
- Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Lisong Teng
- Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- *Correspondence: Lisong Teng,
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