1
|
Zhao S, Wang T, Huang F, Zhao Q, Gong D, Liu J, Yi C, Liang S, Bian E, Tian D, Jing J. A Novel Defined Necroptosis-Related Genes Prognostic Signature for Predicting Prognosis and Treatment of Osteosarcoma. Biochem Genet 2024; 62:831-852. [PMID: 37460861 DOI: 10.1007/s10528-023-10446-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 06/29/2023] [Indexed: 04/20/2024]
Abstract
Osteosarcoma (OS) is a frequent primary malignant bone tumor, with a poor prognosis. Necroptosis is strongly correlated with OS and may be an influential target for treating OS. This study's objective was to establish a necroptosis-related gene (NRG) prognostic signature that could predict OS prognosis and guide OS treatment. First, we identified 20 NRGs associated with OS survival based on the TARGET database. We then derived a 7 NRG prognostic signature. Our findings revealed that the 7 NRG prognostic signature performed well in predicting the survival of OS patients. We next analyzed differences in immunological status and immune cell infiltration. In addition, we examined the relationship between chemo/immunotherapeutic response and the 7-NRG prognostic signature. In addition, to probe the mechanisms underlying the NRG prognostic signature, we performed functional enrichment assays including GO and KEGG. Finally, CHMP4C was selected for functional experiments. Silencing CHMP4C prevented OS cells from proliferating, migrating, and invading. This 7-NRG prognostic signature seems to be an excellent predictor that can provide a fresh direction for OS treatment.
Collapse
Affiliation(s)
- Shibing Zhao
- Department of Orthopaedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
- Institute of Orthopaedics, Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
| | - Tao Wang
- Department of Orthopaedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
- Institute of Orthopaedics, Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
| | - Fei Huang
- Department of Orthopaedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
- Institute of Orthopaedics, Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
| | - Qingzhong Zhao
- Department of Orthopaedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
- Institute of Orthopaedics, Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
| | - Deliang Gong
- Department of Orthopaedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
- Institute of Orthopaedics, Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
| | - Jun Liu
- Department of Orthopaedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
- Institute of Orthopaedics, Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
| | - Chengfeng Yi
- Department of Orthopaedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
- Institute of Orthopaedics, Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
| | - Shuai Liang
- Department of Orthopaedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
- Institute of Orthopaedics, Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China
| | - Erbao Bian
- Department of Orthopaedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China.
- Institute of Orthopaedics, Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China.
| | - Dasheng Tian
- Department of Orthopaedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China.
- Institute of Orthopaedics, Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China.
| | - Juehua Jing
- Department of Orthopaedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China.
- Institute of Orthopaedics, Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China.
| |
Collapse
|
2
|
Chi H, Huang J, Yan Y, Jiang C, Zhang S, Chen H, Jiang L, Zhang J, Zhang Q, Yang G, Tian G. Unraveling the role of disulfidptosis-related LncRNAs in colon cancer: a prognostic indicator for immunotherapy response, chemotherapy sensitivity, and insights into cell death mechanisms. Front Mol Biosci 2023; 10:1254232. [PMID: 37916187 PMCID: PMC10617599 DOI: 10.3389/fmolb.2023.1254232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 10/03/2023] [Indexed: 11/03/2023] Open
Abstract
Background: Colon cancer, a prevalent and deadly malignancy worldwide, ranks as the third leading cause of cancer-related mortality. Disulfidptosis stress triggers a unique form of programmed cell death known as disulfidoptosis, characterized by excessive intracellular cystine accumulation. This study aimed to establish reliable bioindicators based on long non-coding RNAs (LncRNAs) associated with disulfidptosis-induced cell death, providing novel insights into immunotherapeutic response and prognostic assessment in patients with colon adenocarcinoma (COAD). Methods: Univariate Cox proportional hazard analysis and Lasso regression analysis were performed to identify differentially expressed genes strongly associated with prognosis. Subsequently, a multifactorial model for prognostic risk assessment was developed using multiple Cox proportional hazard regression. Furthermore, we conducted comprehensive evaluations of the characteristics of disulfidptosis response-related LncRNAs, considering clinicopathological features, tumor microenvironment, and chemotherapy sensitivity. The expression levels of prognosis-related genes in COAD patients were validated using quantitative real-time fluorescence PCR (qRT-PCR). Additionally, the role of ZEB1-SA1 in colon cancer was investigated through CCK8 assays, wound healing experiment and transwell experiments. Results: disulfidptosis response-related LncRNAs were identified as robust predictors of COAD prognosis. Multifactorial analysis revealed that the risk score derived from these LncRNAs served as an independent prognostic factor for COAD. Patients in the low-risk group exhibited superior overall survival (OS) compared to those in the high-risk group. Accordingly, our developed Nomogram prediction model, integrating clinical characteristics and risk scores, demonstrated excellent prognostic efficacy. In vitro experiments demonstrated that ZEB1-SA1 promoted the proliferation and migration of COAD cells. Conclusion: Leveraging medical big data and artificial intelligence, we constructed a prediction model for disulfidptosis response-related LncRNAs based on the TCGA-COAD cohort, enabling accurate prognostic prediction in colon cancer patients. The implementation of this model in clinical practice can facilitate precise classification of COAD patients, identification of specific subgroups more likely to respond favorably to immunotherapy and chemotherapy, and inform the development of personalized treatment strategies for COAD patients based on scientific evidence.
Collapse
Affiliation(s)
- Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Jinbang Huang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Yang Yan
- The Third Affiliated Hospital of Guizhou Medical University, Duyun, China
| | - Chenglu Jiang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Shengke Zhang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Haiqing Chen
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Lai Jiang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Jieying Zhang
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Qinghong Zhang
- Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, China
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, OH, United States
| | - Gang Tian
- Department of Laboratory Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
| |
Collapse
|
3
|
Todosenko N, Yurova K, Khaziakhmatova O, Malashchenko V, Khlusov I, Litvinova L. Heparin and Heparin-Based Drug Delivery Systems: Pleiotropic Molecular Effects at Multiple Drug Resistance of Osteosarcoma and Immune Cells. Pharmaceutics 2022; 14:pharmaceutics14102181. [PMID: 36297616 PMCID: PMC9612132 DOI: 10.3390/pharmaceutics14102181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 09/29/2022] [Accepted: 10/10/2022] [Indexed: 11/23/2022] Open
Abstract
One of the main problems of modern health care is the growing number of oncological diseases both in the elderly and young population. Inadequately effective chemotherapy, which remains the main method of cancer control, is largely associated with the emergence of multidrug resistance in tumor cells. The search for new solutions to overcome the resistance of malignant cells to pharmacological agents is being actively pursued. Another serious problem is immunosuppression caused both by the tumor cells themselves and by antitumor drugs. Of great interest in this context is heparin, a biomolecule belonging to the class of glycosaminoglycans and possessing a broad spectrum of biological activity, including immunomodulatory and antitumor properties. In the context of the rapid development of the new field of “osteoimmunology,” which focuses on the collaboration of bone and immune cells, heparin and delivery systems based on it may be of intriguing importance for the oncotherapy of malignant bone tumors. Osteosarcoma is a rare but highly aggressive, chemoresistant malignant tumor that affects young adults and is characterized by constant recurrence and metastasis. This review describes the direct and immune-mediated regulatory effects of heparin and drug delivery systems based on it on the molecular mechanisms of (multiple) drug resistance in (onco) pathological conditions of bone tissue, especially osteosarcoma.
Collapse
Affiliation(s)
- Natalia Todosenko
- Center for Immunology and Cellular Biotechnology, Immanuel Kant Baltic Federal University, 236001 Kaliningrad, Russia
| | - Kristina Yurova
- Center for Immunology and Cellular Biotechnology, Immanuel Kant Baltic Federal University, 236001 Kaliningrad, Russia
| | - Olga Khaziakhmatova
- Center for Immunology and Cellular Biotechnology, Immanuel Kant Baltic Federal University, 236001 Kaliningrad, Russia
| | - Vladimir Malashchenko
- Center for Immunology and Cellular Biotechnology, Immanuel Kant Baltic Federal University, 236001 Kaliningrad, Russia
| | - Igor Khlusov
- Department of Morphology and General Pathology, Siberian State Medical University, 634050 Tomsk, Russia
| | - Larisa Litvinova
- Center for Immunology and Cellular Biotechnology, Immanuel Kant Baltic Federal University, 236001 Kaliningrad, Russia
- Correspondence:
| |
Collapse
|
4
|
Jiang M, Jike Y, Gan F, Li J, Hu Y, Xie M, Liu K, Qin W, Bo Z. Verification of Ferroptosis Subcluster-Associated Genes Related to Osteosarcoma and Exploration of Immune Targeted Therapy. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:9942014. [PMID: 36211822 PMCID: PMC9534693 DOI: 10.1155/2022/9942014] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/04/2022] [Accepted: 08/12/2022] [Indexed: 11/17/2022]
Abstract
Background Despite tremendous advances in treating osteosarcoma (OS), the survival rates of patients have failed to improve dramatically over the past decades. Ferroptosis, a newly discovered iron-dependent type of regulated cell death, is implicated in tumors, and its features in OS remain unascertained. We designed to determine the involvement of ferroptosis subcluster-related modular genes in OS progression and prognosis. Methods The OS-related datasets retrieved from GEO and TARGET database were clustered for identifying molecular subclusters with different ferroptosis-related genes (FRGs) expression patterns. Weighted gene coexpression network analysis (WGCNA) was applied to identify modular genes from FRG subclusters. The least absolute shrinkage and selection operator (LASSO) algorithm and multivariable Cox regression analysis were adopted to develop the prognostic model. Potential mechanisms of development and prognosis in OS were explored by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA). Then, a comprehensive analysis was conducted for immune checkpoint markers and assessment of predictive power to drug response. The protein expression levels of the three ferroptosis subcluster-related modular genes were verified by immunohistochemistry. Results Two independent subclusters presenting diverse expression profiles of FRGs were obtained, with significantly different survival states. Ferroptosis subcluster-related modular genes were screened with WGCNA, and the GESA results showed that ferroptosis subcluster-related modular genes could affect the cellular energy metabolism, thus influencing the development and prognosis of osteosarcoma. A prognostic model was established by incorporating three ferroptosis subcluster-related modular genes (LRRC1, ACO2, and CTNNBIP1) and a nomogram by integrating clinical features, and they were evaluated for the predictive power on OS prognosis. The 20 immune checkpoint-related genes confirmed the insensitivity to tumor immunotherapy in high-risk patients. IC50s of Axitinib and Cytarabine suggested a higher sensitivity to the targeted drug. Finally, the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and immunohistochemistry were consistent with bioinformatics analysis. Conclusion Ferroptosis are closely associated with the OS prognosis. The risk-scoring model incorporating three ferroptosis subcluster-related modular genes has shown outstanding advantages in predicting patient prognosis.
Collapse
Affiliation(s)
- Mingyang Jiang
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yiji Jike
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Fu Gan
- Department of Urology Surgery, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
| | - Jia Li
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yang Hu
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Mingjing Xie
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Kaicheng Liu
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Wentao Qin
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Zhandong Bo
- Department of Bone and Joint Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| |
Collapse
|
5
|
Wan L, Zhang W, Liu Z, Yang Z, Tu C, Li Z. A Novel Glutamine Metabolism-Related Gene Signature in Prognostic Prediction of Osteosarcoma. Int J Gen Med 2022; 15:997-1011. [PMID: 35136353 PMCID: PMC8817953 DOI: 10.2147/ijgm.s352859] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 01/21/2022] [Indexed: 12/18/2022] Open
Affiliation(s)
- Lu Wan
- Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China
- Department of Orthopedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China
| | - Wenchao Zhang
- Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China
- Department of Orthopedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China
| | - Zhongyue Liu
- Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China
- Department of Orthopedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China
| | - Zhimin Yang
- Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China
- Department of Orthopedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China
| | - Chao Tu
- Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China
- Department of Orthopedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China
- Correspondence: Chao Tu; Zhihong Li, Tel +86 15974290117; +86 13975112458, Email ;
| | - Zhihong Li
- Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China
- Department of Orthopedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China
| |
Collapse
|
6
|
Cao K, Ma T, Ling X, Liu M, Jiang X, Ma K, Zhu J, Ma J. Development of immune gene pair-based signature predictive of prognosis and immunotherapy in esophageal cancer. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:1591. [PMID: 34790797 PMCID: PMC8576717 DOI: 10.21037/atm-21-5217] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 10/20/2021] [Indexed: 12/13/2022]
Abstract
Background Esophageal cancer (EC) is one of the deadliest solid malignancies, mainly consisting of esophageal squamous cell carcinoma (ESCC) and adenocarcinoma (EAC). Robust biomarkers that can improve patient risk stratification are needed to optimize cancer management. We sought to establish potent prognostic signatures with immune-related gene (IRG) pairs for ESCC and EAC. Methods We obtained differentially expressed IRGs by intersecting the Immunology Database and Analysis Portal (ImmPort) with the transcriptome data set of The Cancer Genome Atlas (TCGA)-ESCC and EAC cohorts. A novel rank-based pairwise comparison algorithm was applied to select effective IRG pairs (IRGPs), followed by constructing a prognostic IRGP signature via the least absolute shrinkage and selection operator (LASSO) regression model. We assessed the predictive power of the IRGP signatures on prognosis, tumor-infiltrating immune cells, and immune checkpoint inhibitor (ICI) efficacy in EC. Kaplan-Meier survival analysis and receiver operating characteristic curves (ROC) were used to evaluate the clinical significance of IRGPs. Univariate and multivariate Cox regression analyses were performed to investigate the association of overall survival (OS) with IRGPs and clinical characteristics. Results We built a 19-IRGP signature for ESCC (n=75) and a 17-IRGP signature for EAC (n=78), with an area under the ROC curve (AUC) of 0.931 and 0.803, respectively. IRGP signature-derived risk scores stratified patients into low- and high-risk groups with significantly different OS in ESCC and EAC (P<0.001). Nomogram and decision curve analysis were used to evaluate the clinical relevance of the prognostic signatures, achieving a C-index of 0.973 in ESCC and 0.880 in EAC. The risk scores were associated with immune and ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) scores and the composition of immune cells in the tumor microenvironment. The association between risk score and human leukocyte antigens (HLAs), mismatch repair (MMR) genes, and immune checkpoint molecules demonstrated its predictive value for ICI response. Differential immune characteristics and predictive value of the risk score were observed in EAC. Conclusions The established immune signatures showed great promise in predicting prognosis, tumor immunogenicity, and immunotherapy response in ESCC and EAC.
Collapse
Affiliation(s)
- Kui Cao
- Department of Clinical Laboratory, Biobank, Harbin Medical University Cancer Hospital, Harbin, China.,Department of Clinical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Tianjiao Ma
- Department of Cardiovascular Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaodong Ling
- Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Mingdong Liu
- Department of Clinical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Xiangyu Jiang
- Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Keru Ma
- Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Jinhong Zhu
- Department of Clinical Laboratory, Biobank, Harbin Medical University Cancer Hospital, Harbin, China
| | - Jianqun Ma
- Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| |
Collapse
|
7
|
Cao K, Liu M, Ma K, Jiang X, Ma J, Zhu J. Prediction of prognosis and immunotherapy response with a robust immune-related lncRNA pair signature in lung adenocarcinoma. Cancer Immunol Immunother 2021; 71:1295-1311. [PMID: 34652523 DOI: 10.1007/s00262-021-03069-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 09/26/2021] [Indexed: 12/24/2022]
Abstract
The tumor immune microenvironment plays essential roles in regulating inflammation, angiogenesis, immune modulation, and sensitivity to therapies. Here, we developed a powerful prognostic signature with immune-related lncRNAs (irlncRNAs) in lung adenocarcinoma (LUAD). We obtained differentially expressed irlncRNAs by intersecting the transcriptome dataset for The Cancer Genome Atlas (TCGA)-LUAD cohort and the ImmLnc database. A rank-based algorithm was applied to select top-ranking altered irlncRNA pairs for the model construction. We built a prognostic signature of 33 irlncRNA pairs comprising 40 unique irlncRNAs in the TCGA-LUAD cohort (training set). The immune signature significantly dichotomized LUAD patients into high- and low-risk groups regarding overall survival, which is likewise independently predictive of prognosis (hazard ratio = 3.580, 95% confidence interval = 2.451-5.229, P < 0.001). A nomogram with a C-index of 0.79 demonstrates the superior prognostic accuracy of the signature. The prognostic accuracy of the signature of 33 irlncRNA pairs was validated using the GSE31210 dataset (validation set) from the Gene Expression Omnibus database. Immune cell infiltration was calculated using ESTIMATE, CIBERSORT, and MCP-count methodologies. The low-risk group exhibited high immune cell infiltration, high mutation burden, high expression of CTLA4 and human leukocyte antigen genes, and low expression of mismatch repair genes, which predicted response to immunotherapy. Interestingly, pRRophetic analysis demonstrated that the high-risk group possessed reverse characteristics was sensitive to chemotherapy. The established immune signature shows marked clinical and translational potential for predicting prognosis, tumor immunogenicity, and therapeutic response in LUAD.
Collapse
Affiliation(s)
- Kui Cao
- Department of Clinical Laboratory, Biobank, Harbin Medical University Cancer Hospital, 150 Haping Road, Harbin, 150040, Heilongjiang, China.,Department of Clinical Oncology, Harbin Medical University Cancer Hospital, 150 Haping Road, Harbin, 150040, Heilongjiang, China
| | - Mingdong Liu
- Department of Clinical Oncology, Harbin Medical University Cancer Hospital, 150 Haping Road, Harbin, 150040, Heilongjiang, China
| | - Keru Ma
- Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, 150 Haping Road, Harbin, 150040, Heilongjiang, China
| | - Xiangyu Jiang
- Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, 150 Haping Road, Harbin, 150040, Heilongjiang, China
| | - Jianqun Ma
- Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, 150 Haping Road, Harbin, 150040, Heilongjiang, China.
| | - Jinhong Zhu
- Department of Clinical Laboratory, Biobank, Harbin Medical University Cancer Hospital, 150 Haping Road, Harbin, 150040, Heilongjiang, China.
| |
Collapse
|
8
|
Investigating Optimal Chemotherapy Options for Osteosarcoma Patients through a Mathematical Model. Cells 2021; 10:cells10082009. [PMID: 34440778 PMCID: PMC8394778 DOI: 10.3390/cells10082009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 08/03/2021] [Accepted: 08/04/2021] [Indexed: 12/22/2022] Open
Abstract
Simple Summary Osteosarcoma is a rare type of cancer with poor prognoses. However, to the best of our knowledge, there are no mathematical models that study the impact of chemotherapy treatments on the osteosarcoma microenvironment. In this study, we developed a data driven mathematical model to analyze the dynamics of the important players in three groups of osteosarcoma tumors with distinct immune patterns in the presence of the most common chemotherapy drugs. The results indicate that the treatments’ start times and optimal dosages depend on the unique growth rate of the tumor, which implies the necessity of personalized medicine. Furthermore, the developed model can be extended by others to build models that can recommend individual-specific optimal dosages. Abstract Since all tumors are unique, they may respond differently to the same treatments. Therefore, it is necessary to study their characteristics individually to find their best treatment options. We built a mathematical model for the interactions between the most common chemotherapy drugs and the osteosarcoma microenvironments of three clusters of tumors with unique immune profiles. We then investigated the effects of chemotherapy with different treatment regimens and various treatment start times on the behaviors of immune and cancer cells in each cluster. Saliently, we suggest the optimal drug dosages for the tumors in each cluster. The results show that abundances of dendritic cells and HMGB1 increase when drugs are given and decrease when drugs are absent. Populations of helper T cells, cytotoxic cells, and IFN-γ grow, and populations of cancer cells and other immune cells shrink during treatment. According to the model, the MAP regimen does a good job at killing cancer, and is more effective than doxorubicin and cisplatin combined or methotrexate alone. The results also indicate that it is important to consider the tumor’s unique growth rate when deciding the treatment details, as fast growing tumors need early treatment start times and high dosages.
Collapse
|
9
|
Wang J, Gong M, Xiong Z, Zhao Y, Xing D. Bioinformatics integrated analysis to investigate candidate biomarkers and associated metabolites in osteosarcoma. J Orthop Surg Res 2021; 16:432. [PMID: 34225733 PMCID: PMC8256509 DOI: 10.1186/s13018-021-02578-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 06/24/2021] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND This study hoped to explore the potential biomarkers and associated metabolites during osteosarcoma (OS) progression based on bioinformatics integrated analysis. METHODS Gene expression profiles of GSE28424, including 19 human OS cell lines (OS group) and 4 human normal long bone tissue samples (control group), were downloaded. The differentially expressed genes (DEGs) in OS vs. control were investigated. The enrichment investigation was performed based on DEGs, followed by protein-protein interaction network analysis. Then, the feature genes associated with OS were explored, followed by survival analysis to reveal prognostic genes. The qRT-PCR assay was performed to test the expression of these genes. Finally, the OS-associated metabolites and disease-metabolic network were further investigated. RESULTS Totally, 357 DEGs were revealed between the OS vs. control groups. These DEGs, such as CXCL12, were mainly involved in functions like leukocyte migration. Then, totally, 38 feature genes were explored, of which 8 genes showed significant associations with the survival of patients. High expression of CXCL12, CEBPA, SPARCL1, CAT, TUBA1A, and ALDH1A1 was associated with longer survival time, while high expression of CFLAR and STC2 was associated with poor survival. Finally, a disease-metabolic network was constructed with 25 nodes including two disease-associated metabolites cyclophosphamide and bisphenol A (BPA). BPA showed interactions with multiple prognosis-related genes, such as CXCL12 and STC2. CONCLUSION We identified 8 prognosis-related genes in OS. CXCL12 might participate in OS progression via leukocyte migration function. BPA might be an important metabolite interacting with multiple prognosis-related genes.
Collapse
Affiliation(s)
- Jun Wang
- Department of Orthopedics and Trauma, The Second Hospital of Shandong University, No. 247 Beiyuan Street, Jinan, 250033 China
| | - Mingzhi Gong
- Department of Orthopedics and Trauma, The Second Hospital of Shandong University, No. 247 Beiyuan Street, Jinan, 250033 China
| | - Zhenggang Xiong
- Department of Orthopedics and Trauma, The Second Hospital of Shandong University, No. 247 Beiyuan Street, Jinan, 250033 China
| | - Yangyang Zhao
- Department of Orthopedics and Trauma, The Second Hospital of Shandong University, No. 247 Beiyuan Street, Jinan, 250033 China
| | - Deguo Xing
- Department of Orthopedics and Trauma, The Second Hospital of Shandong University, No. 247 Beiyuan Street, Jinan, 250033 China
| |
Collapse
|
10
|
Construction and Validation of an Autophagy-Related Prognostic Model for Osteosarcoma Patients. JOURNAL OF ONCOLOGY 2021; 2021:9943465. [PMID: 34194501 PMCID: PMC8181090 DOI: 10.1155/2021/9943465] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 05/07/2021] [Indexed: 12/17/2022]
Abstract
While the prognostic value of autophagy-related genes (ARGs) in OS patients remains scarcely known, increasing evidence is indicating that autophagy is closely associated with the development and progression of osteosarcoma (OS). Therefore, we explored the prognostic value of ARGs in OS patients and illuminate associated mechanisms in this study. When the OS patients in the training/validation cohort were stratified into high- and low-risk groups according to the risk model established using least absolute shrinkage and selection operator (LASSO) regression analysis, we observed that patients in the low-risk group possessed better prognosis (P < 0.0001). Univariate/Multivariate COX regression and subgroup analysis demonstrated that the ARGs-based risk model was an independent survival indicator for OS patients. The nomogram incorporating the risk model and clinical features exhibited excellent prognostic accuracy. GO, KEGG, and GSVA analyses collectively indicated that bone development-associated pathway mediated the contribution of ARGs to the malignance of OS. Immune infiltration analysis suggested the potential pivotal role of macrophage in OS. In summary, the risk model based on 12 ARGs possessed potent capacity in predicting the prognosis of OS patients. Our work may assist clinicians to map out more reasonable treatment strategies and facilitate individual-targeted therapy in osteosarcoma.
Collapse
|
11
|
Li LQ, Zhang LH, Yuan YB, Lu XC, Zhang Y, Liu YK, Wen J, Khader MA, Liu T, Li JZ, Zhang Y. Signature based on metabolic-related gene pairs can predict overall survival of osteosarcoma patients. Cancer Med 2021; 10:4493-4509. [PMID: 34047495 PMCID: PMC8267140 DOI: 10.1002/cam4.3984] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 04/20/2021] [Accepted: 04/23/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Osteosarcoma is a tumour of malignant origin in children and adolescents. Recent progression indicates that it is necessary to develop new therapies to improve the patient's prognosis rather than strengthen anti-tumour chemotherapy. Researchers recently realised that cancer is a kind of disease with a metabolic disorder, and metabolic reprogramming is becoming a new cancer hallmark. Hence, our study's primary purpose is to explore the value of genes related to osteosarcoma metabolism. METHODS From public databases, three osteosarcoma datasets with adequate clinical information were obtained. Besides, the IMvigor dataset through the 'IMvigor' package as a supplement was downloaded, the metabolic-related genes were identified, and these genes were used to construct the metabolic-related gene pairs (MRGP). Based on the prognosis-related MRGP, two molecular subtypes were identified. There are significant differences in the metabolic characteristics between the two molecular subtypes. Subsequently, the MRGP signature is constructed using the least absolute shrinkage and selection operator regression method. Finally, use SubMap analysis to evaluate the response of patients in the MRPG signature group to immunotherapy. RESULTS The MRGP signature can reliably predict overall survival in patients with osteosarcoma. The MRGP signature is also associated with osteosarcoma patients' metastatic status and can be used for subsequent risk classification of metastatic patients. The immunotherapy is more likely to benefit the patients in the MRGP low-risk group. CONCLUSION Metabolic-related gene pairs signature can assess the prognosis of patients with osteosarcoma.
Collapse
Affiliation(s)
- Long-Qing Li
- Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China
| | - Liang-Hao Zhang
- Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China
| | - Yao-Bo Yuan
- Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xin-Chang Lu
- Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China
| | - Yi Zhang
- Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China
| | - Yong-Kui Liu
- Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China
| | - Jia Wen
- Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China
| | - Manhas Abdul Khader
- Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China
| | - Tao Liu
- Department of Orthopedics, Gushi County People's Hospital, Xinyang, Henan, PR China
| | - Jia-Zhen Li
- Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China
| | - Yan Zhang
- Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China
| |
Collapse
|
12
|
Wang X, Cao K, Guo E, Mao X, Guo L, Zhang C, Guo J, Wang G, Yang X, Sun J, Miao S. Identification of Immune-Related LncRNA Pairs for Predicting Prognosis and Immunotherapeutic Response in Head and Neck Squamous Cell Carcinoma. Front Immunol 2021; 12:658631. [PMID: 33995377 PMCID: PMC8116744 DOI: 10.3389/fimmu.2021.658631] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 04/09/2021] [Indexed: 12/12/2022] Open
Abstract
Long noncoding RNAs (lncRNAs) have multiple functions with regard to the cancer immunity response and the tumor microenvironment. The prognosis of head and neck squamous cell carcinoma (HNSCC) is still poor currently, and it may be effective to predict the clinical outcome and immunotherapeutic response of HNSCC by immunogenic analysis. Therefore, by using univariate COX analysis and Lasso Cox regression, we identified a signature consisting of 21 immune-related lncRNA pairs (IRLPs) that predicted clinical outcome and Immunotherapeutic response in HNSCC. Specifically, it was associated with immune cell infiltration (i.e., T cells CD4 memory resting, CD8 T cells, macrophages M0, M2, and NK cells), and more importantly this signature was strongly related with immune checkpoint inhibitors (ICIs) [such as PDCD1 (r = -0.35, P < 0.001), CTLA4 (r = -0.26, P < 0.001), LAG3 (r = -0.22, P < 0.001) and HAVCR2 (r = -0.2, P < 0.001)] and immunotherapy-related biomarkers (MMR and HLA). The present study highlighted the value of the 21 IRLPs signature as a predictor of prognosis and immunotherapeutic response in HNSCC.
Collapse
Affiliation(s)
- Xueying Wang
- Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Kui Cao
- Department of Laboratory, Harbin Medical University Cancer Hospital, Harbin, China
| | - Erliang Guo
- Department of Surgery, The 2nd Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xionghui Mao
- Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Lunhua Guo
- Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Cong Zhang
- Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Junnan Guo
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Gang Wang
- Department of Head and Neck Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, China
| | - Xianguang Yang
- Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Ji Sun
- Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Susheng Miao
- Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| |
Collapse
|
13
|
Le T, Su S, Shahriyari L. Immune classification of osteosarcoma. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:1879-1897. [PMID: 33757216 PMCID: PMC7992873 DOI: 10.3934/mbe.2021098] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
Tumor immune microenvironment has been shown to be important in predicting the tumor progression and the outcome of treatments. This work aims to identify different immune patterns in osteosarcoma and their clinical characteristics. We use the latest and best performing deconvolution method, CIBERSORTx, to obtain the relative abundance of 22 immune cells. Then we cluster patients based on their estimated immune abundance and study the characteristics of these clusters, along with the relationship between immune infiltration and outcome of patients. We find that abundance of CD8 T cells, NK cells and M1 Macrophages have a positive association with prognosis, while abundance of γδ T cells, Mast cells, M0 Macrophages and Dendritic cells have a negative association with prognosis. Accordingly, the cluster with the lowest proportion of CD8 T cells, M1 Macrophages and highest proportion of M0 Macrophages has the worst outcome among clusters. By grouping patients with similar immune patterns, we are also able to suggest treatments that are specific to the tumor microenvironment.
Collapse
Affiliation(s)
- Trang Le
- Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA MA 01003-9305, USA
| | - Sumeyye Su
- Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA MA 01003-9305, USA
| | - Leili Shahriyari
- Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA MA 01003-9305, USA
| |
Collapse
|