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Sanchez A, Lhuillier J, Grosjean G, Ayadi L, Maenner S. The Long Non-Coding RNA ANRIL in Cancers. Cancers (Basel) 2023; 15:4160. [PMID: 37627188 PMCID: PMC10453084 DOI: 10.3390/cancers15164160] [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: 07/27/2023] [Revised: 08/14/2023] [Accepted: 08/15/2023] [Indexed: 08/27/2023] Open
Abstract
ANRIL (Antisense Noncoding RNA in the INK4 Locus), a long non-coding RNA encoded in the human chromosome 9p21 region, is a critical factor for regulating gene expression by interacting with multiple proteins and miRNAs. It has been found to play important roles in various cellular processes, including cell cycle control and proliferation. Dysregulation of ANRIL has been associated with several diseases like cancers and cardiovascular diseases, for instance. Understanding the oncogenic role of ANRIL and its potential as a diagnostic and prognostic biomarker in cancer is crucial. This review provides insights into the regulatory mechanisms and oncogenic significance of the 9p21 locus and ANRIL in cancer.
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Affiliation(s)
| | | | | | - Lilia Ayadi
- CNRS, Université de Lorraine, IMoPA, F-54000 Nancy, France
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Zhang X, Wen Z, Wang Q, Ren L, Zhao S. A novel stratification framework based on anoikis-related genes for predicting the prognosis in patients with osteosarcoma. Front Immunol 2023; 14:1199869. [PMID: 37575253 PMCID: PMC10413143 DOI: 10.3389/fimmu.2023.1199869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 07/13/2023] [Indexed: 08/15/2023] Open
Abstract
Background Anoikis resistance is a prerequisite for the successful development of osteosarcoma (OS) metastases, whether the expression of anoikis-related genes (ARGs) correlates with OS prognosis remains unclear. This study aimed to investigate the feasibility of using ARGs as prognostic tools for the risk stratification of OS. Methods The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provided transcriptome information relevant to OS. The GeneCards database was used to identify ARGs. Differentially expressed ARGs (DEARGs) were identified by overlapping ARGs with common differentially expressed genes (DEGs) between OS and normal samples from the GSE16088, GSE19276, and GSE99671 datasets. Anoikis-related clusters of patients were obtained by consistent clustering, and gene set variation analysis (GSVA) of the different clusters was completed. Next, a risk model was created using Cox regression analyses. Risk scores and clinical features were assessed for independent prognostic values, and a nomogram model was constructed. Subsequently, a functional enrichment analysis of the high- and low-risk groups was performed. In addition, the immunological characteristics of OS samples were compared between the high- and low-risk groups, and their sensitivity to therapeutic agents was explored. Results Seven DEARGs between OS and normal samples were obtained by intersecting 501 ARGs with 68 common DEGs. BNIP3 and CXCL12 were significantly differentially expressed between both clusters (P<0.05) and were identified as prognosis-related genes. The risk model showed that the risk score and tumor metastasis were independent prognostic factors of patients with OS. A nomogram combining risk score and tumor metastasis effectively predicted the prognosis. In addition, patients in the high-risk group had low immune scores and high tumor purity. The levels of immune cell infiltration, expression of human leukocyte antigen (HLA) genes, immune response gene sets, and immune checkpoints were lower in the high-risk group than those in the low-risk group. The low-risk group was sensitive to the immune checkpoint PD-1 inhibitor, and the high-risk group exhibited lower inhibitory concentration values by 50% for 24 drugs, including AG.014699, AMG.706, and AZD6482. Conclusion The prognostic stratification framework of patients with OS based on ARGs, such as BNIP3 and CXCL12, may lead to more efficient clinical management.
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Affiliation(s)
- Xiaoyan Zhang
- Department of Spine Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Department of Nutrition, College of Public Health of Sun Yat-Sen University, Guangzhou, China
| | - Zhenxing Wen
- Department of Spine Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Orthopaedics and Traumatology, Guangzhou, China
| | - Qi Wang
- Department of Oncology, Nanyang Central Hospital, Nanyang, China
| | - Lijuan Ren
- Molecular Diagnosis and Gene Testing Center, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Shengli Zhao
- Department of Spine Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Orthopaedics and Traumatology, Guangzhou, China
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de Azevedo JWV, de Medeiros Fernandes TAA, Fernandes JV, de Azevedo JCV, Lanza DCF, Bezerra CM, Andrade VS, de Araújo JMG, Fernandes JV. Biology and pathogenesis of human osteosarcoma. Oncol Lett 2019; 19:1099-1116. [PMID: 31966039 PMCID: PMC6955653 DOI: 10.3892/ol.2019.11229] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 09/10/2019] [Indexed: 12/26/2022] Open
Abstract
Osteosarcoma (OS) is a bone tumor of mesenchymal origin, most frequently occurring during the rapid growth phase of long bones, and usually located in the epiphyseal growth plates of the femur or the tibia. Its most common feature is genome disorganization, aneuploidy with chromosomal alterations, deregulation of tumor suppressor genes and of the cell cycle, and an absence of DNA repair. This suggests the involvement of surveillance failures, DNA repair or apoptosis control during osteogenesis, allowing the survival of cells which have undergone alterations during differentiation. Epigenetic events, including DNA methylation, histone modifications, nucleosome remodeling and expression of non-coding RNAs have been identified as possible risk factors for the tumor. It has been reported that p53 target genes or those genes that have their activity modulated by p53, in addition to other tumor suppressor genes, are silenced in OS-derived cell lines by hypermethylation of their promoters. In osteogenesis, osteoblasts are formed from pluripotent mesenchymal cells, with potential for self-renewal, proliferation and differentiation into various cell types. This involves complex signaling pathways and multiple factors. Any disturbance in this process can cause deregulation of the differentiation and proliferation of these cells, leading to the malignant phenotype. Therefore, the origin of OS seems to be multifactorial, involving the deregulation of differentiation of mesenchymal cells and tumor suppressor genes, activation of oncogenes, epigenetic events and the production of cytokines.
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Affiliation(s)
| | | | | | | | | | - Christiane Medeiros Bezerra
- Department of Microbiology and Parasitology, Federal University of Rio Grande do Norte, 59072-970 Natal, RN, Brazil
| | - Vânia Sousa Andrade
- Department of Microbiology and Parasitology, Federal University of Rio Grande do Norte, 59072-970 Natal, RN, Brazil
| | | | - José Veríssimo Fernandes
- Department of Microbiology and Parasitology, Federal University of Rio Grande do Norte, 59072-970 Natal, RN, Brazil
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Huang R, Xian S, Shi T, Yan P, Hu P, Yin H, Meng T, Huang Z. Evaluating and Predicting the Probability of Death in Patients with Non-Metastatic Osteosarcoma: A Population-Based Study. Med Sci Monit 2019; 25:4675-4690. [PMID: 31231119 PMCID: PMC6604676 DOI: 10.12659/msm.915418] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Osteosarcoma is one of the most common bone tumors, with strong local aggressiveness and early metastasis. The aim of this study was to describe the epidemiological data and evaluate the prognostic factors for overall survival (OS) and cause-specific survival (CSS) in patients with non-metastatic osteosarcoma. MATERIAL AND METHODS Patients histologically diagnosed with non-metastatic osteosarcoma between 2005 and 2014 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Survival analysis, machine learning, and Lasso regression were used to identify the prognostic factors for OS and CSS, and the accuracy of the nomograms was tested and compared with the American Joint Committee on Cancer (AJCC) staging systems. RESULTS The entire cohort comprised 1000 patients with non-metastatic osteosarcoma. The multivariable analysis suggested that age, tumor size, grade, and American Joint Committee on Cancer (AJCC) T staging were independent prognostic factors for OS and CSS. Additionally, the nomograms based on these results could better predict probability of OS (Internal validation C-index, 0.7095) and CSS (0.7100) compared with the sixth (OS: 0.613; CSS: 0.628) and seventh edition AJCC staging systems (0.602, 0.613). CONCLUSIONS Relatively young age and low histopathological grade were favorable factors for both OS and CSS. Nomograms based on multivariable models worked well in predicting the probability of death for patients with non-metastatic osteosarcoma.
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Affiliation(s)
- Runzhi Huang
- Division of Spine Surgery, Department of Orthopedics, Tongji Hospital, Tongji University School of Medicine, Shanghai, China (mainland).,Key Laboratory of Spine and Spinal cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Shanghai, China (mainland)
| | - Shuyuan Xian
- Department of Orthopedics, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China (mainland)
| | - Tingting Shi
- Tongji University School of Medicine, Tongji University, Shanghai, China (mainland)
| | - Penghui Yan
- Department of Orthopedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China (mainland)
| | - Peng Hu
- Department of Orthopedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China (mainland)
| | - Huabin Yin
- Department of Orthopedics, Shanghai Bone Tumor Institute, Shanghai General Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China (mainland)
| | - Tong Meng
- Division of Spine Surgery, Department of Orthopedics, Tongji Hospital, Tongji University School of Medicine, Shanghai, China (mainland).,Key Laboratory of Spine and Spinal cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Shanghai, China (mainland)
| | - Zongqiang Huang
- Department of Orthopedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China (mainland)
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