Integrative analysis of immune-related multi-omics profiles identifies distinct prognosis and tumor microenvironment patterns in osteosarcoma

作者全名："Shi, Deyao; Mu, Shidai; Pu, Feifei; Liu, Jianxiang; Zhong, Binlong; Hu, Binwu; Ni, Na; Wang, Hao; Luu, Hue H.; Haydon, Rex C.; Shen, Le; Zhang, Zhicai; He, Tong-Chuan; Shao, Zengwu"

作者地址："[Shi, Deyao; Pu, Feifei; Liu, Jianxiang; Zhong, Binlong; Hu, Binwu; Zhang, Zhicai; Shao, Zengwu] Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Dept Orthopaed, Jiefang Rd 1277, Wuhan 430022, Peoples R China; [Shi, Deyao; Ni, Na; Wang, Hao; Luu, Hue H.; Haydon, Rex C.; Shen, Le; He, Tong-Chuan] Univ Chicago, Dept Orthopaed Surg & Rehabil Med, Mol Oncol Lab, Med Ctr, 5841 South Maryland Ave,MC3079, Chicago, IL 60637 USA; [Mu, Shidai] Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Inst Hematol, Wuhan, Peoples R China; [Ni, Na; Wang, Hao] Chongqing Med Univ, Sch Lab Med, Dept Clin Biochem, Minist Educ,Key Lab Diagnost Med, Chongqing, Peoples R China; [Shen, Le; He, Tong-Chuan] Univ Chicago, Dept Surg, Med Ctr, Chicago, IL 60637 USA"

通信作者："Zhang, ZC; Shao, ZW (通讯作者)，Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Dept Orthopaed, Jiefang Rd 1277, Wuhan 430022, Peoples R China.; He, TC (通讯作者)，Univ Chicago, Dept Orthopaed Surg & Rehabil Med, Mol Oncol Lab, Med Ctr, 5841 South Maryland Ave,MC3079, Chicago, IL 60637 USA."

来源：MOLECULAR ONCOLOGY

ESI学科分类：MOLECULAR BIOLOGY & GENETICS

WOS号：WOS:000736927300001

JCR分区：Q1

影响因子：6.6

年份：2022

卷号：16

期号：11

开始页：2174

结束页：2194

文献类型：Article

关键词：DNA methylation; osteosarcoma; prognostic risk model; transcriptomics; tumor immunology; tumor microenvironment

摘要："Osteosarcoma (OS) is the most common primary malignancy of bone. Epigenetic regulation plays a pivotal role in cancer development in various aspects, including immune response. In this study, we studied the potential association of alterations in the DNA methylation and transcription of immune-related genes with changes in the tumor microenvironment (TME) and tumor prognosis of OS. We obtained multi-omics data for OS patients from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. By referring to curated immune signatures and using a consensus clustering method, we categorized patients based on immune-related DNA methylation patterns (IMPs), and evaluated prognosis and TME characteristics of the resulting patient subgroups. Subsequently, we used a machine-learning approach to construct an IMP-associated prognostic risk model incorporating the expression of a six-gene signature (MYC, COL13A1, UHRF2, MT1A, ACTB, and GBP1), which was then validated in an independent patient cohort. Furthermore, we evaluated TME patterns, transcriptional variation in biological pathways, somatic copy number alteration, anticancer drug sensitivity, and potential responsiveness to immune checkpoint inhibitor therapy with regard to our IMP-associated signature scoring model. By integrative IMP and transcriptomic analysis, we uncovered distinct prognosis and TME patterns in OS. Finally, we constructed a classifying model, which may aid in prognosis prediction and provide a potential rationale for targeted- and immune checkpoint inhibitor therapy in OS."

基金机构：National Institutes of Health [CA226303]; University of Chicago Cancer Center Support Grant [P30CA014599]; National Center for Advancing Translational Sciences of the National Institutes of Health [UL1 TR000430]; Mabel Green Myers Research Endowment Fund; University of Chicago Orthopaedics Alumni Fund

基金资助正文："The results here are based on data generated by the Therapeutically Applicable Research to Generate Effective Treatments (TARGET, https://ocg.cancer.gov/programs/target) initiative, phs000218. The data used for this analysis are available at https://portal.gdc.cancer.gov/projects.The study reported herein fully satisfies the TARGET Publication Guidelines (https://ocg.cancer.gov/programs/target/target-publicationguidelines).The authors thank TARGET and GEO developed by the National Institutes of Health, and the ArrayExpress developed by the European Bioinformatics Institute. The reported work was supported in part by research grants from the National Institutes of Health (CA226303 to T-CH). This project was also supported in part by the University of Chicago Cancer Center Support Grant (P30CA014599) and the National Center for Advancing Translational Sciences of the National Institutes of Health through Grant Number UL1 TR000430. T-CH was supported by the Mabel Green Myers Research Endowment Fund and the University of Chicago Orthopaedics Alumni Fund. Funding sources were not involved in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication."