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Article(id=1198619428880478800, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1198619422425448948, articleNumber=null, orderNo=null, doi=10.11855/j.issn.0577-7402.1968.2023.0620, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1659974400000, receivedDateStr=2022-08-09, revisedDate=null, revisedDateStr=null, acceptedDate=1670860800000, acceptedDateStr=2022-12-13, onlineDate=1763702741116, onlineDateStr=2025-11-21, pubDate=1716825600000, pubDateStr=2024-05-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1763702741116, onlineIssueDateStr=2025-11-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1763702741116, creator=13701087609, updateTime=1763702741116, updator=13701087609, issue=Issue{id=1198619422425448948, tenantId=1146029695717560320, journalId=1189873630562394117, year='2024', volume='49', issue='5', pageStart='489', pageEnd='610', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1763702739578, creator=13701087609, updateTime=1763702927730, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1198620211667628088, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1198619422425448948, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1198620211667628089, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1198619422425448948, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=557, endPage=569, ext={EN=ArticleExt(id=1198619429383795292, articleId=1198619428880478800, tenantId=1146029695717560320, journalId=1189873630562394117, language=EN, title=Role of senescent genes in the treatment, prognosis and tumor microenvironment for osteosarcoma, columnId=1190310110212751762, journalTitle=Medical Journal of Chinese People’s Liberation Army, columnName=Basic Research, runingTitle=null, highlight=null, articleAbstract=

Objective To analyze and verify the role of senescent genes in the treatment, prognosis, and tumor microenvironment (TME) characteristics of osteoblastic osteosarcoma, bioinformatic methods were employed. Methods Senescent genes were obtained from the China National Genome Science database (https://ngdc.cncb.ac.cn/aging/index). The gene expression profile and clinical information of osteosarcoma patients were sourced from the TARGET database (https://ocg.cancer.gov/programs/target), while single-cell RNA-sequencing (scRNA-seq) data was collected from GSE162454 on the Gene Expression Omnibus (GEO) for downstream analysis. Osteosarcoma cells were classified based on scRNA-seq, and differential expression analysis between osteoblasts/chondroblasts and other cell types was conducted to identify differently expressed genes (DEGs). After matching with the senescent genes, prognostic senescent DEGs were identified through univariable and multivariable Cox regression analysis. Subsequently, the osteosarcoma senescent-related model (OSRM) was constructed, and the risk score was calculated. The role of OSRM in treatment, prognosis, and TME of osteosarcoma was further investigated. Results The analysis revealed that GSE162454 contained 6 osteosarcoma samples, with 19 933 cells identified after filtering, quality control, and normalization. Seventeen cellular subtypes were identified using uniform manifold approximation and projection (UMAP) methods. A total of 4821 DEGs were found between osteoblasts/chondroblasts and other subtypes, with 132 senescent DEGs obtained after matching with the senescent gene set. In the TARGET database, 4 prognostic senescent DEGs [ADH5 (alcohol dehydrogenase 5), ARHGAP1 (Rho GTPase activating protein 1), APOE (apolipoprotein E), and ATF4 (activating transcription factor 4)] were identified through univariable and multivariable Cox analyses to construct OSRM. Based on risk score, patients were stratified into high- and low-risk groups, with the latter showing better prognosis (HR=0.13, 95%CI 0.06-0.28, P<0.001) and higher sensitivity to immune checkpoint inhibitors. qRT-PCR and Western blotting confirmed the high expression of senescent genes ADH5 (P<0.01), APOE (P<0.01), and ATF4 (P<0.05) in the K7M2 osteosarcoma cell line, suggesting the potential for predicting the response to anti-PD-1 immunotherapy for osteosarcoma. Conclusions scRNA-seq facilitated the division of osteosarcoma into 17 cell subtypes. ADH5, ARHGAP1, APOE, and ATF4 emerged as potential cancer-promoting or suppressing senescent genes in osteosarcoma. OSRM was found to be associated with treatment response, prognosis, and TME characteristics, thereby promoting the molecular pathological diagnosis of osteoblastic osteosarcoma and prediction for anti-PD-1 immunotherapy.

, correspAuthors=Zhen-Hai Hou, authorNote=null, correspAuthorsNote=
E-mail:
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目的 利用生物信息学技术分析并验证衰老基因在成骨型骨肉瘤患者治疗、预后及肿瘤微环境(TME)中的作用。方法 从中国国家基因组科学数据库(https://ngdc.cncb.ac.cn/aging/index)中获取衰老相关基因，从TARGET数据库(https://ocg.cancer.gov/programs/target)中获取骨肉瘤患者的基因表达谱和临床信息，并从基因表达数据库(GEO)中获取骨肉瘤的单细胞数据集GSE162454用于下游分析。通过单细胞数据集对骨肉瘤细胞进行分型，寻找成骨细胞/成软骨细胞与其他细胞亚型的差异化表达基因(DEGs)，并与衰老相关基因进行比对。采用单因素、多因素Cox回归分析确定预后相关衰老DEGs基因，构建骨肉瘤衰老相关模型(OSRM)并计算风险评分，分析OSRM在骨肉瘤治疗、预后及TME中的特征。结果 GSE162454共包含6个骨肉瘤样本，经过滤质控后共有19 933个细胞。经统一流形逼近与投影(UMAP)聚类后确定17个细胞亚群。成骨细胞/成软骨细胞与其他亚群间共有4821个DEGs，与衰老基因集比对后共获取132个衰老相关DEGs。在TARGET数据库中，单因素、多因素Cox分析获取了4个预后基因：ADH5(醇脱氢酶5)、ARHGAP1(Rho GTPase激活蛋白1)、APOE(载脂蛋白E)、ATF4(激活转录因子4)用于构建OSRM。依据风险评分将84例成骨型骨肉瘤患者分为高风险组(n=42)与低风险组(n=42)，低风险组预后较好(HR=0.13，95%CI 0.06~0.28，P<0.001)，且对免疫检查点抑制剂有较强的应答敏感性。qRT-PCR和Western blotting证实PD-1过表达的K7M2细胞中ADH5(P<0.01)、APOE(P<0.001)、ATF4(P<0.05)呈持续高表达，可预测抗PD-1对骨肉瘤的免疫治疗效果。结论 ADH5、ARHGAP1、APOE、ATF4是成骨型骨肉瘤中潜在的衰老相关促癌或抑癌基因，基于这些基因构建的OSRM可判断骨肉瘤的治疗应答、预后和TME特征。OSRM关键基因促进了骨肉瘤的分子病理诊断，并可作为预测抗PD-1免疫治疗应答的潜在生物标志物。

, correspAuthors=侯振海, authorNote=null, correspAuthorsNote=
侯振海，E-mail：
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徐天波，主治医师，主要从事骨科创伤、关节、脊柱等方面的临床研究

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徐天波，主治医师，主要从事骨科创伤、关节、脊柱等方面的临床研究

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徐天波，主治医师，主要从事骨科创伤、关节、脊柱等方面的临床研究

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Mol Med Rep, 2018, 17(3): 3658-3666., articleTitle=ATF4 regulated by MYC has an important function in anoikis resistance in human osteosarcoma cells, refAbstract=null), Reference(id=1198630243503272838, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, doi=null, pmid=null, pmcid=null, year=2019, volume=9, issue=21, pageStart=6334, pageEnd=6353, url=null, language=null, rfNumber=[35], rfOrder=34, authorNames=Luo J, Xia Y, Yin Y, journalName=Theranostics, refType=null, unstructuredReference=Luo J, Xia Y, Yin Y, et al. ATF4 destabilizes RET through nonclassical GRP78 inhibition to enhance chemosensitivity to bortezomib in human osteosarcoma[J]. Theranostics, 2019, 9(21): 6334-6353., articleTitle=ATF4 destabilizes RET through nonclassical GRP78 inhibition to enhance chemosensitivity to bortezomib in human osteosarcoma, refAbstract=null)], funds=[Fund(id=1198630239325745998, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, awardId=2019KY538, language=EN, fundingSource=Medical Health Science and Technology Project of Zhejiang Provincial Health Commission(2019KY538), fundOrder=null, country=null), Fund(id=1198630239384466256, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, awardId=2019KY538, language=CN, fundingSource=浙江省医药卫生科研计划项目(2019KY538), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1198630233608909496, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, xref=null, ext=[AuthorCompanyExt(id=1198630233621492407, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, companyId=1198630233608909496, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Third Orthopedic, the 903 Hospital of the Joint Support Force of the Chinese PLA, Hangzhou, Zhejiang 310000, China), AuthorCompanyExt(id=1198630233625686712, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, companyId=1198630233608909496, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=解放军联勤保障部队第903医院骨三科，浙江杭州 310000)])], figs=[ArticleFig(id=1198630235873833748, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=EN, label=Fig.1, caption=Results of scRNA-seq dimensionality reduction and clustering, figureFileSmall=0xjGe1nhQTF/7AR3XKpa3g==, figureFileBig=p2Wth3MFVj1Mq9K+sx7iRg==, tableContent=null), ArticleFig(id=1198630235970302744, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=CN, label=图1, caption=单细胞测序数据的降维与聚类结果

DC. 树突细胞；NK细胞. 自然杀伤细胞；NKT. 自然杀伤性T细胞；A. GSE162454可由UMAP划分为17个细胞亚群；B. 所有细胞亚群中免疫细胞相关亚群与非免疫细胞相关亚群的构成情况；C. 利用SingleR软件将所有细胞注释成8个细胞亚群；D. 手动完成17个细胞亚群的注释结果

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RUNX2. 矮小相关转录因子；COL1A1. α1-1型胶原基因；CDH11. 钙黏着蛋白11；IBSP. 整联蛋白结合涎蛋白；SOX9. SRY框转录因子9；ACAN. 人软骨蛋白聚糖；PTH1R. 甲状旁腺激素受体；TNFAIP6. 肿瘤坏死因子A诱导蛋白6；GAS1. 生长停滞特异蛋白1；SLC7A2. 溶质载体家族7；TNC. 腱生蛋白C；ACP5. 酸性磷酸酶5；CTSK. 组织蛋白酶K；MMP9. 基质金属蛋白酶9；A. 成骨细胞；B. 成软骨细胞；C. 软骨细胞；D. 破骨细胞

, figureFileSmall=zyeDhdxlqNfoaMJ8qWiJcA==, figureFileBig=/PbyBhrm5R4dnociNXtoyg==, tableContent=null), ArticleFig(id=1198630237257954081, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=EN, label=Fig.3, caption=Feature plots for biomarkers of osteoblasts/chondroblasts, figureFileSmall=mX6dBCtWMeDdMrsSzKeHOg==, figureFileBig=GScUpOrJ4DkRXb0D6BZv7Q==, tableContent=null), ArticleFig(id=1198630237379588901, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=CN, label=图3, caption=成骨细胞/成软骨细胞标志物的表达分布

RUNX2. 矮小相关转录因子；COL1A1. α1-1型胶原基因；CDH11. 钙黏着蛋白11；IBSP. 整联蛋白结合涎蛋白；SOX9. SRY框转录因子9；ACAN. 人软骨蛋白聚糖；PTH1R. 甲状旁腺激素受体；A. 成骨细胞亚群标志物(RUNX2、COL1A1、CDH11、IBSP)的表达分布；B. 成软骨细胞亚群标志物(SOX9、ACAN、PTH1R)的表达分布

, figureFileSmall=mX6dBCtWMeDdMrsSzKeHOg==, figureFileBig=GScUpOrJ4DkRXb0D6BZv7Q==, tableContent=null), ArticleFig(id=1198630237471863592, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=EN, label=Fig.4, caption=Construction of the OSRM model, figureFileSmall=sFvzOKVUlvKXw66/CoMQNA==, figureFileBig=u2styeZ6PZIjHyH9F9vgmw==, tableContent=null), ArticleFig(id=1198630237610275627, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=CN, label=图4, caption=OSRM模型的构建

OSAM. 骨肉瘤衰老相关模型；DEGs. 差异化表达基因；ADH5. 醇脱氢酶5；APOE. 载脂蛋白E；ARHGAP1. RhoGTP酶激活蛋白1；ATF4. 转录激活因子4；A. 各细胞亚群间最显著的10个DEGs的热图；B. 单因素Cox分析鉴定出5个骨肉瘤预后相关的衰老DEGs；C. 多因素Cox分析鉴定出4个骨肉瘤预后相关的衰老DEGs

, figureFileSmall=sFvzOKVUlvKXw66/CoMQNA==, figureFileBig=u2styeZ6PZIjHyH9F9vgmw==, tableContent=null), ArticleFig(id=1198630237731910445, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=EN, label=Fig.5, caption=Analysis of the predictive value of OSRM model, figureFileSmall=IwPCzpCuxuxW5uEeffzbAw==, figureFileBig=rfxPhPoPx5Vj+3QGFp6Ngg==, tableContent=null), ArticleFig(id=1198630237811602222, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=CN, label=图5, caption=OSRM模型的预测价值分析

OSAM. 骨肉瘤衰老相关模型；ROC. 受试者工作特征曲线；ADH5. 醇脱氢酶5；APOE. 载脂蛋白E；ARHGAP1. RhoGTP酶激活蛋白1；ATF4. 转录激活因子4；A. 高、低风险组的生存曲线；B. OSAM的ROC曲线；C. 高、低风险组的风险曲线，黄色点表示低OSRM风险患者，绿色点表示高OSRM风险患者；D. 骨肉瘤患者生存状态与风险评分的关系；E. ADH5、ARHGAP1、APOE、ATF4在高、低风险组的表达热图

, figureFileSmall=IwPCzpCuxuxW5uEeffzbAw==, figureFileBig=rfxPhPoPx5Vj+3QGFp6Ngg==, tableContent=null), ArticleFig(id=1198630237895488307, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=EN, label=Fig.6, caption=Evaluation of immune cell infiltration in osteosarcoma TME using the CIBERSORT algorithm, figureFileSmall=DaIqGK8Cy8hW8CNJ5JYa4Q==, figureFileBig=pmtxUfWpV6DUvE192g4vAA==, tableContent=null), ArticleFig(id=1198630237966791473, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=CN, label=图6, caption=CIBERSORT算法评估骨肉瘤TME中的免疫细胞浸润情况

TME. 肿瘤微环境；A. 高、低风险组的肿瘤免疫浸润情况；B. 基于M1型巨噬细胞表达量的生存曲线(P=0.044)；C. 基于活化态CD4+记忆T细胞表达量的生存曲线(P=0.003)

, figureFileSmall=DaIqGK8Cy8hW8CNJ5JYa4Q==, figureFileBig=pmtxUfWpV6DUvE192g4vAA==, tableContent=null), ArticleFig(id=1198630238046483253, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=EN, label=Fig.7, caption=Response of high- and low-risk groups to immune checkpoint inhibitors, figureFileSmall=Qk72NZ9h9p6wrz0ck8tf5w==, figureFileBig=xDfvkSbrSsWJTkB+h6lK1Q==, tableContent=null), ArticleFig(id=1198630238126175030, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=CN, label=图7, caption=高、低风险组免疫检查点抑制剂的应答情况

PD-1. 程序性细胞死亡因子1；CTLA-4. 细胞毒性T淋巴细胞相关抗原4；noR. 对免疫检查点抑制剂治疗无反应；R. 对免疫检查点抑制剂治疗有反应

, figureFileSmall=Qk72NZ9h9p6wrz0ck8tf5w==, figureFileBig=xDfvkSbrSsWJTkB+h6lK1Q==, tableContent=null), ArticleFig(id=1198630238239421242, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=EN, label=Fig.8, caption=Immunohistochemistry exhibited the expression of ADH5, ARHGAP1, APOE and ATF4 in high- and low-expression groups of patients with osteoblastic osteosarcoma, figureFileSmall=UiEbrPx+v2UvFwFHcowVEw==, figureFileBig=A04EChIN1Ci6ViLM1MQhIg==, tableContent=null), ArticleFig(id=1198630238386221884, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=CN, label=图8, caption=免疫组化检测ADH5、ARHGAP1、APOE、ATF4在高、低表达组成骨型骨肉瘤患者中的表达情况

ADH5. 醇脱氢酶5；ARHGAP1. RhoGTP酶激活蛋白1；APOE. 载脂蛋白E；ATF4. 转录激活因子4

, figureFileSmall=UiEbrPx+v2UvFwFHcowVEw==, figureFileBig=A04EChIN1Ci6ViLM1MQhIg==, tableContent=null), ArticleFig(id=1198630238465913661, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=EN, label=Fig.9, caption=The impact of osteosarcoma senescent related model on immune activity, figureFileSmall=dGL0Czw7Z37Asoe1QPjVPw==, figureFileBig=4HQkNn37URX9fLrEe2umbw==, tableContent=null), ArticleFig(id=1198630238549799742, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=CN, label=图9, caption=骨肉瘤衰老相关模型基因对免疫活动的影响

IL23A. 白细胞介素23A；TNFA. 肿瘤坏死因子α；IL12A. 白细胞介素12A；MIF. 巨噬细胞迁移抑制因子；IL17A. 白细胞介素17A；TGFBI. 转化生长因子诱导蛋白；IL6. 白细胞介素6；IL1B. 白细胞介素1B；IL18. 白细胞介素18；PDL1. 程序性死亡因子配体1；LAG3. 淋巴细胞活化基因3；IDO1. 吲哚胺2，3-双加氧酶1；TNFRSF8. 肿瘤坏死因子受体超家族成员8；PDL2. 程序性死亡因子配体2；TIM3. T细胞免疫球蛋白3；A. RT-qPCR检测ATF4-NT质粒转染的K7M2细胞系与pCMV组(对照组)中免疫炎性因子的表达情况；B. RT-qPCR检测ATF4-NT质粒转染的K7M2细胞系与pCMV组(对照组)中免疫检查点分子的表达情况；*P<0.05，**P<0.01，***P<0.001

, figureFileSmall=dGL0Czw7Z37Asoe1QPjVPw==, figureFileBig=4HQkNn37URX9fLrEe2umbw==, tableContent=null), ArticleFig(id=1198630238663045953, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=EN, label=Fig.10, caption=The expression of ADH5, APOE, and ATF4 in PD-1 transfected K7M2 cell line, figureFileSmall=1VX0+nB4Q62yFM6MWS/d4Q==, figureFileBig=CljkFB158YPf0+KHGfNK1g==, tableContent=null), ArticleFig(id=1198630238767903556, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=CN, label=图10, caption=ADH5、APOE、ATF4在PD-1转染后K7M2细胞系的表达情况

ADH5. 醇脱氢酶5；APOE. 载脂蛋白E；ATF4. 转录激活因子4；A. Western blotting检测ADH5、APOE、ATF4在PD-1转染的K7M2细胞系与对照组中的表达情况；B. RT-qPCR证实ADH5、APOE、ATF4在PD-1转染的K7M2细胞系中均较对照组呈高表达；*P<0.05，**P<0.01，***P<0.001

, figureFileSmall=1VX0+nB4Q62yFM6MWS/d4Q==, figureFileBig=CljkFB158YPf0+KHGfNK1g==, tableContent=null), ArticleFig(id=1198630238855983942, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=EN, label=Tab.1, caption=

scRNA-seq annotation results and markers for each subtype

, figureFileSmall=null, figureFileBig=null, tableContent=
细胞亚群(中文)细胞亚群(英文)细胞亚群标志物单细胞亚群对应编号
髓样细胞亚群Myeloid cellsCD74、CD14、FCGR3A0
T细胞亚群T cellsCD3、IL7R、CD8A、CD4、NKG71
软骨细胞亚群ChondrocytesTNFAIP6、GAS1、SLC7A2、TNC2
巨噬细胞亚群MacrophageCD163、ARG1、CCL2、CD14、CD683
DC细胞亚群DC cellsCD1D、FCER1A、CLEC9A、CCR7、CD14、CD1634
NKT细胞亚群NKT cellsNKG7、GNLY、CD3、IL7R、CD8A5
成纤维细胞亚群FibroblastsDCN、COL1A16
单核细胞亚群MonocyteCD14、CX3CR17
B细胞亚群B cellsMYLPF、CD19、JCHAIN8
成软骨细胞亚群Chondroblastic cellsSOX9、ACAN、PTH1R9
未知细胞亚群UnknownUnknown10
增殖细胞亚群Proliferating cellsMKI67、TOP2A、PCNA11
NK细胞亚群NK cellsNKG7、GNLY12
破骨细胞亚群OsteoclastsACP5、CTSK、MMP913
内皮细胞亚群Endothelial cellsPECAM1、VWF14
成骨细胞亚群Osteoblastic cellsRUNX2、COL1A1、CDH11、IBSP15
上皮细胞亚群Epithelial cellCD14、CD45、EpCAM16
), ArticleFig(id=1198630238939870025, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=CN, label=表1, caption=

单细胞亚群注释及其标志物

, figureFileSmall=null, figureFileBig=null, tableContent=
细胞亚群(中文)细胞亚群(英文)细胞亚群标志物单细胞亚群对应编号
髓样细胞亚群Myeloid cellsCD74、CD14、FCGR3A0
T细胞亚群T cellsCD3、IL7R、CD8A、CD4、NKG71
软骨细胞亚群ChondrocytesTNFAIP6、GAS1、SLC7A2、TNC2
巨噬细胞亚群MacrophageCD163、ARG1、CCL2、CD14、CD683
DC细胞亚群DC cellsCD1D、FCER1A、CLEC9A、CCR7、CD14、CD1634
NKT细胞亚群NKT cellsNKG7、GNLY、CD3、IL7R、CD8A5
成纤维细胞亚群FibroblastsDCN、COL1A16
单核细胞亚群MonocyteCD14、CX3CR17
B细胞亚群B cellsMYLPF、CD19、JCHAIN8
成软骨细胞亚群Chondroblastic cellsSOX9、ACAN、PTH1R9
未知细胞亚群UnknownUnknown10
增殖细胞亚群Proliferating cellsMKI67、TOP2A、PCNA11
NK细胞亚群NK cellsNKG7、GNLY12
破骨细胞亚群OsteoclastsACP5、CTSK、MMP913
内皮细胞亚群Endothelial cellsPECAM1、VWF14
成骨细胞亚群Osteoblastic cellsRUNX2、COL1A1、CDH11、IBSP15
上皮细胞亚群Epithelial cellCD14、CD45、EpCAM16
), ArticleFig(id=1198630239019561802, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=EN, label=Tab.2, caption=

Primer sequences for RT-qPCR

, figureFileSmall=null, figureFileBig=null, tableContent=
基因引物序列(5'-3')
PD-1正义：CCAGGATGGTTCTTAGACTCCC
反义：TTTAGCACGAAGCTCTCCGAT
ADH5正义：ATGGCGAACGAGGTTATCAAG
反义：CATGTCCCAAGATCACTGGAAAA
APOE正义：GTTGCTGGTCACATTCCTGG
反义：GCAGGTAATCCCAAAAGCGAC
ATF4正义：ATGACCGAAATGAGCTTCCTG
反义：GCTGGAGAACCCATGAGGT
β-actin正义：GTGGGGCGCCCCAGGCACCA
反义：CTCCTTAATGTCACGCACGATTTC
), ArticleFig(id=1198630239124419403, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198619428880478800, language=CN, label=表2, caption=

RT-qPCR引物序列

, figureFileSmall=null, figureFileBig=null, tableContent=
基因引物序列(5'-3')
PD-1正义：CCAGGATGGTTCTTAGACTCCC
反义：TTTAGCACGAAGCTCTCCGAT
ADH5正义：ATGGCGAACGAGGTTATCAAG
反义：CATGTCCCAAGATCACTGGAAAA
APOE正义：GTTGCTGGTCACATTCCTGG
反义：GCAGGTAATCCCAAAAGCGAC
ATF4正义：ATGACCGAAATGAGCTTCCTG
反义：GCTGGAGAACCCATGAGGT
β-actin正义：GTGGGGCGCCCCAGGCACCA
反义：CTCCTTAATGTCACGCACGATTTC
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衰老基因在骨肉瘤治疗、预后及肿瘤微环境中的作用研究
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徐天波 , 刘德国 , 顾增辉 , 郑宇翔 , 侯振海 *
解放军医学杂志 | 基础研究 2024,49(5): 557-569
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解放军医学杂志 | 基础研究 2024, 49(5): 557-569
衰老基因在骨肉瘤治疗、预后及肿瘤微环境中的作用研究
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徐天波, 刘德国, 顾增辉, 郑宇翔, 侯振海*
作者信息
  • 解放军联勤保障部队第903医院骨三科，浙江杭州 310000

    • 徐天波，主治医师，主要从事骨科创伤、关节、脊柱等方面的临床研究

通讯作者:

侯振海，E-mail：
Role of senescent genes in the treatment, prognosis and tumor microenvironment for osteosarcoma
Tian-Bo Xu, De-Guo Liu, Zeng-Hui Gu, Yu-Xiang Zheng, Zhen-Hai Hou*
Affiliations
  • Department of Third Orthopedic, the 903 Hospital of the Joint Support Force of the Chinese PLA, Hangzhou, Zhejiang 310000, China
出版时间: 2024-05-28 doi: 10.11855/j.issn.0577-7402.1968.2023.0620
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目的 利用生物信息学技术分析并验证衰老基因在成骨型骨肉瘤患者治疗、预后及肿瘤微环境(TME)中的作用。方法 从中国国家基因组科学数据库(https://ngdc.cncb.ac.cn/aging/index)中获取衰老相关基因，从TARGET数据库(https://ocg.cancer.gov/programs/target)中获取骨肉瘤患者的基因表达谱和临床信息，并从基因表达数据库(GEO)中获取骨肉瘤的单细胞数据集GSE162454用于下游分析。通过单细胞数据集对骨肉瘤细胞进行分型，寻找成骨细胞/成软骨细胞与其他细胞亚型的差异化表达基因(DEGs)，并与衰老相关基因进行比对。采用单因素、多因素Cox回归分析确定预后相关衰老DEGs基因，构建骨肉瘤衰老相关模型(OSRM)并计算风险评分，分析OSRM在骨肉瘤治疗、预后及TME中的特征。结果 GSE162454共包含6个骨肉瘤样本，经过滤质控后共有19 933个细胞。经统一流形逼近与投影(UMAP)聚类后确定17个细胞亚群。成骨细胞/成软骨细胞与其他亚群间共有4821个DEGs，与衰老基因集比对后共获取132个衰老相关DEGs。在TARGET数据库中，单因素、多因素Cox分析获取了4个预后基因：ADH5(醇脱氢酶5)、ARHGAP1(Rho GTPase激活蛋白1)、APOE(载脂蛋白E)、ATF4(激活转录因子4)用于构建OSRM。依据风险评分将84例成骨型骨肉瘤患者分为高风险组(n=42)与低风险组(n=42)，低风险组预后较好(HR=0.13，95%CI 0.06~0.28，P<0.001)，且对免疫检查点抑制剂有较强的应答敏感性。qRT-PCR和Western blotting证实PD-1过表达的K7M2细胞中ADH5(P<0.01)、APOE(P<0.001)、ATF4(P<0.05)呈持续高表达，可预测抗PD-1对骨肉瘤的免疫治疗效果。结论 ADH5、ARHGAP1、APOE、ATF4是成骨型骨肉瘤中潜在的衰老相关促癌或抑癌基因，基于这些基因构建的OSRM可判断骨肉瘤的治疗应答、预后和TME特征。OSRM关键基因促进了骨肉瘤的分子病理诊断，并可作为预测抗PD-1免疫治疗应答的潜在生物标志物。

骨肉瘤  /  免疫微环境  /  预测模型  /  生物信息学分析

Objective To analyze and verify the role of senescent genes in the treatment, prognosis, and tumor microenvironment (TME) characteristics of osteoblastic osteosarcoma, bioinformatic methods were employed. Methods Senescent genes were obtained from the China National Genome Science database (https://ngdc.cncb.ac.cn/aging/index). The gene expression profile and clinical information of osteosarcoma patients were sourced from the TARGET database (https://ocg.cancer.gov/programs/target), while single-cell RNA-sequencing (scRNA-seq) data was collected from GSE162454 on the Gene Expression Omnibus (GEO) for downstream analysis. Osteosarcoma cells were classified based on scRNA-seq, and differential expression analysis between osteoblasts/chondroblasts and other cell types was conducted to identify differently expressed genes (DEGs). After matching with the senescent genes, prognostic senescent DEGs were identified through univariable and multivariable Cox regression analysis. Subsequently, the osteosarcoma senescent-related model (OSRM) was constructed, and the risk score was calculated. The role of OSRM in treatment, prognosis, and TME of osteosarcoma was further investigated. Results The analysis revealed that GSE162454 contained 6 osteosarcoma samples, with 19 933 cells identified after filtering, quality control, and normalization. Seventeen cellular subtypes were identified using uniform manifold approximation and projection (UMAP) methods. A total of 4821 DEGs were found between osteoblasts/chondroblasts and other subtypes, with 132 senescent DEGs obtained after matching with the senescent gene set. In the TARGET database, 4 prognostic senescent DEGs [ADH5 (alcohol dehydrogenase 5), ARHGAP1 (Rho GTPase activating protein 1), APOE (apolipoprotein E), and ATF4 (activating transcription factor 4)] were identified through univariable and multivariable Cox analyses to construct OSRM. Based on risk score, patients were stratified into high- and low-risk groups, with the latter showing better prognosis (HR=0.13, 95%CI 0.06-0.28, P<0.001) and higher sensitivity to immune checkpoint inhibitors. qRT-PCR and Western blotting confirmed the high expression of senescent genes ADH5 (P<0.01), APOE (P<0.01), and ATF4 (P<0.05) in the K7M2 osteosarcoma cell line, suggesting the potential for predicting the response to anti-PD-1 immunotherapy for osteosarcoma. Conclusions scRNA-seq facilitated the division of osteosarcoma into 17 cell subtypes. ADH5, ARHGAP1, APOE, and ATF4 emerged as potential cancer-promoting or suppressing senescent genes in osteosarcoma. OSRM was found to be associated with treatment response, prognosis, and TME characteristics, thereby promoting the molecular pathological diagnosis of osteoblastic osteosarcoma and prediction for anti-PD-1 immunotherapy.

osteosarcoma  /  immune microenvironment  /  risk model  /  bioinformatic analysis
徐天波, 刘德国, 顾增辉, 郑宇翔, 侯振海. 衰老基因在骨肉瘤治疗、预后及肿瘤微环境中的作用研究. 解放军医学杂志, 2024 , 49 (5) : 557 -569 . DOI: 10.11855/j.issn.0577-7402.1968.2023.0620
Tian-Bo Xu, De-Guo Liu, Zeng-Hui Gu, Yu-Xiang Zheng, Zhen-Hai Hou. Role of senescent genes in the treatment, prognosis and tumor microenvironment for osteosarcoma[J]. Medical Journal of Chinese People’s Liberation Army, 2024 , 49 (5) : 557 -569 . DOI: 10.11855/j.issn.0577-7402.1968.2023.0620
正文
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骨肉瘤是最常见的骨原发性恶性肿瘤，具有高度侵袭性，且病死率高，预后极差[1-2]。长骨干骺端为骨肉瘤主要发病部位，以股骨和胫骨最为常见[3]。据报道，晚期及转移性骨肉瘤患者5年生存率为20%[4]。既往虽有包括靶向治疗在内的各种系统性治疗方案可供选择，但骨肉瘤的治疗效果并未得到显著改善[4-6]。因此，进一步探究骨肉瘤的发病机制，寻找理想的肿瘤生物学标志物和治疗靶点有助于延长患者生存期[7]。如何延缓衰老并延长预期寿命是一项长期挑战[8]。目前的研究热点正从衰老表型逐渐延伸至胰岛素样信号通路[9]、雷帕霉素(target of rapamycin，TOR)靶向通路[10]、NAD+信号通路[11]、昼夜节律机制[12]、线粒体与氧化应激信号通路[13]、细胞老化通路[14]、慢性炎症通路[15]和蛋白质稳态机制[16]等。衰老细胞的特性之一是衰老相关的分泌表型(senescence associated secretory phenotype，SASP)，可分泌多种生物活性物质如炎性介质、趋化因子、生长因子和蛋白酶等[17-18]。在骨关节炎中，衰老细胞可分泌基质金属蛋白酶3(matrix metalloproteinase，MMP3)和白细胞介素6，两者均与骨关节炎的病程相关[19]。近年来研究表明，衰老基因广泛参与成骨与破骨过程，同时可调节成骨细胞和破骨细胞的功能，且与骨质疏松、成骨不全、骨肿瘤等多种骨骼相关疾病有关[8,20]。蛋白质精氨酸酶甲基转移酶5(protein arginine methyltransferase 5，PRMT5)为表观遗传酶，可通过调控DNA修复酶的表达和DNA损伤信号通路诱导细胞衰老。在成骨型骨肉瘤中硫氧还蛋白互作蛋白(thioredoxin interacting protein，TXNIP)参与PRMT5对细胞衰老及p21蛋白的表达调控，抗E3泛素蛋白连接酶TRIM21(tripartite motif-containing 21)可作为分子伴侣协同PRMT5调控TXNIP/p21轴进而干预骨肉瘤衰老进程[21]。本研究基于TARGET数据库和基因表达数据库(gene expression omnibus，GEO)的mRNA测序数据、临床数据和单细胞测序(single-cell RNA sequencing，scRNA-seq)数据，构建成骨型骨肉瘤衰老相关模型(osteosarcoma senescent related model，OSRM)，探究衰老基因在骨肉瘤预后、治疗和肿瘤微环境(tumor microenvironment，TME)中的作用，并进行验证。
1 材料与方法
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1.1 数据获取及预处理
从中国国家基因组科学数据库(https://ngdc.cncb.ac.cn/aging/index)中获取500个衰老相关基因[22]。从GEO数据库中获取scRNA-seq数据集GSE162454，主要基于R软件的Seurat平台进行分析。GSE162454数据集包含6个成骨型骨肉瘤样本(GSM4952363、GSM4952364、GSM4952365、GSM5155198、GSM5155199、GSM5155200)，基于Illumina NovaSeq 6000平台完成测序[23]。6个样本共19 933个细胞通过Harmony法进行合并、质控和过滤(feature值>300；count值<100 000；线粒体基因含量<10%)。数据校正后，对排名前2000位的高变基因(highly variable genes，HVGs)进行主成分分析(principal component analysis，PCA)，批次效应采用Harmony法去除。统一流形逼近与投影(uniform manifold approximation and projection，UMAP)法可聚类出17个细胞亚群，在各细胞亚群间完成差异化表达分析[log2|FC|>2，错误发现率(false discover rate，FDR)<0.05]，并对各亚群最显著的10个差异化表达基因(differently expressed genes，DEGs)可视化。通过SingleR软件进行细胞亚群的初步注释，参考其结果进一步行手工注释。挑选成骨细胞/成软骨细胞与其他细胞亚群间的DEGs进行下游分析。
从TARGET数据库(https://ocg.cancer.gov/programs/target)中获取88例成骨型骨肉瘤患者的临床信息，包含完整的mRNA测序信息和临床数据。将mRNA表达矩阵进行TPM转化，对表达值进行log2处理。对于多个相同基因，表达量取平均值，并去除表达量非常低的基因。临床数据的结局指标主要为总生存期(overall survival，OS)。剔除基因表达或临床信息缺失的患者，最终纳入84例。
1.2 单细胞数据处理
由limma包完成scRNA-seq数据集的差异化表达。对骨肉瘤及相关细胞亚群的手工注释参考文献[24]，细胞亚群的标志物总结见表1。因成骨细胞/成软骨细胞与细胞衰老密切相关，故主要选取成骨细胞和成软骨细胞与其他细胞亚群的DEGs用于下游分析。
1.3 OSRM模型构建
将成骨细胞/成软骨细胞与其他细胞亚群的DEGs和衰老相关基因进行比对，获取衰老相关DEGs。在TARGET数据库中采用单因素和多因素Cox回归分析确定预后相关衰老DEGs，根据以下公式计算风险评分：Risk score=∑i=1n βixi，其中βi是每个纳入OSRM模型的基因经Cox回归计算出的系数，xi是每个纳入OSRM模型的基因相对表达量，具体方法参照文献[25]。由4个预后相关衰老DEGs构建OSRM，根据风险评分的中位值将骨肉瘤患者分为高风险组(n=42)与低风险组(n=42)。
1.4 OSRM模型的预测价值分析
采用生存曲线对两组患者进行生存分析，受试者工作特征曲线(receiver operating curve，ROC)评估OSRM模型的预测准确性。由heatmap包绘制热图展示构建OSRM模型的基因在两组中的表达情况，同时绘制风险曲线和点图进一步展示两组患者的生存情况。由CIBERSORT算法评估骨肉瘤TME中的免疫细胞浸润情况。CIBERSORT是一种去卷积的工具，基于已知的参考数据集，能够提供22种免疫细胞的表达情况[26]。采用TIDE(the tumor immune dysfunction and exclusion，http://tide.dfci.harvard.edu/)算法和Submap算法(https://cloud.genepattern.org/gp)评估两组患者对免疫检查点抑制剂的应答情况[27]。
1.5 免疫组化
选取2018年3月-2021年9月解放军联勤保障部队第903医院收治的病理诊断为成骨型骨肉瘤患者12例，其中男6例，女6例，平均年龄17.2岁。本研究获解放军联勤保障部队第903医院伦理委员会审批(IEC-FOC-024-2.0)，所有患者及家属均签署知情同意书。
根据阳性细胞率和染色强度分别对12例病理样本进行评分。阳性细胞率评分：无阳性染色细胞为0分，阳性细胞率≤10%为1分，10%~25%为2分，25%~50%为3分，50%~75%为4分，>75%为5分。染色强度评分：细胞无染色为0分，出现黄色染色为1分，棕色染色为2分，褐色染色为3分。阳性细胞率评分与染色强度评分之和作为最终评分。0~1分为阴性，2~4分为弱阳性，5~6分为阳性，7~8分为强阳性。阴性和弱阳性代表低表达，阳性和强阳性代表高表达。根据最终评分将12例患者分为低表达组(n=4)与高表达组(n=8)，采用免疫组化验证OSRM关键基因在两组患者中的表达情况。
1.6 质粒构建和转染
将来自HEK293细胞系(ATCC-CRL-1573)的转录激活因子4(activating transcription factor 4，ATF4)序列(ATF4-NT)克隆到巨细胞病毒质粒(pCMV)载体中，构建重组质粒pCMV-ATF4-NT。将人T淋巴细胞系(ATCC-TIB-161)的程序性细胞死亡因子1(programmed cell death ligand 1，PD-1)序列克隆到pCMV载体中，构建重组质粒pCMV-PD-1。
取小鼠骨肉瘤成骨细胞系K7M2(Procell，中国武汉)，设置pCMV组(转染pCMV)、ATF4过表达组(转染重组质粒pCMV-ATF4-NT)与对照组(转染pCMV)、PD-1过表达组(转染重组质粒pCMV-PD-1)，使用脂质体3000(美国Invitrogen公司)进行转染。
1.6.1 RT-qPCR
K7M2细胞系于含10%小牛血清(FBS，美国Gibco公司)和1%青霉素-链霉素的DMEM培养基中，置于37 ℃、5% CO2环境中培养。应用Trizol试剂提取总RNA。经NanoDrop 2000(美国Thermo Fisher Scientific公司)定量后，通过PrimeScript反转录合成cDNA™；使用SYBR预混物ExTaq Ⅱ(日本TaKaRa公司)采用Light Cycler 480仪器(美国Roche公司)进行RT-qPCR检测，共40个循环，实验重复3次。以β-actin为内参，采用2-ΔΔCT法计算目的基因相对表达量，引物序列见表2。
1.6.2 Western blotting
用PBS缓冲液洗涤细胞，并用蛋白酶抑制剂和磷酸酶抑制剂的放射免疫沉淀测定缓冲液(RIPA)裂解细胞；离心收集上清液用于蛋白定量。将提取的蛋白质行SDS-PAGE凝胶电泳分离并转移至PVDF膜上，室温下5%脱脂奶粉或牛血清白蛋白(BSA)中封闭；加入抗-乙醇脱氢酶-5(alcohol dehydrogenase 5，ADH5；1:1500；ab177932)、抗-载脂蛋白E(apolipoprotein E，APOE；1:1500；ab108813)、抗-转录激活因子4(activating transcription factor 4，ATF4；1:1000；ab184909)、抗-程序性细胞死亡受体1(programmed cell death ligand 1，PD-1；1:100；ab52587)和抗-GAPDH(1:500；ab8245)一抗(武汉Abcam公司)4 ℃下孵育过夜；加入与HRP连接的二抗共孵育，在Bio-Rad XRS检测系统(Hercules，美国)中，通过增强化学发光(ECL)法检测目的蛋白相对表达量。
1.7 统计学处理
采用R软件(v4.2.1)进行统计分析。计量资料以$\bar{x}±s$表示，两组间比较采用Wilcoxon检验。生存分析采用Cox比例风险回归分析，并绘制Kaplan-Meier生存曲线，组间比较采用Log-rank检验。ROC曲线由pROC包进行绘制。P<0.05为差异有统计学意义。
2 结果
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2.1 单细胞测序数据结果
GSE162454数据集中共含有6个骨肉瘤样本，质控和过滤后共有19 933个细胞。经UMAP降维后确定17个细胞亚群(图1A)，其中免疫细胞相关亚群与非免疫细胞相关亚群的比例接近1∶1(图1B)。通过SingleR软件自动注释，共获得8个细胞亚群，即B细胞亚群、内皮细胞亚群、单核细胞亚群、T细胞亚群、软骨细胞亚群、巨噬细胞亚群、神经元亚群、组织干细胞亚群(图1C)；结合骨肉瘤细胞亚群标志物，手动完成17个细胞亚群的注释，分别为B细胞亚群、树突细胞(dendritic cells，DC)亚群、自然杀伤性T细胞(natural killer T cells，NKT细胞)亚群、自然杀伤细胞(natural killer T cells，NK细胞)亚群、T细胞亚群、成骨细胞亚群、成软骨细胞亚群、成纤维细胞亚群、单核细胞亚群、巨噬细胞亚群、内皮细胞亚群、破骨细胞亚群、软骨细胞亚群、上皮细胞亚群、髓样细胞亚群、增殖细胞亚群和未知细胞亚群(图1D)。
细胞亚群标志物在各细胞亚群中的表达情况如图2A-D所示，可见第15亚群为成骨细胞亚群，第9亚群为成软骨细胞亚群，第13亚群为破骨细胞亚群。从中国国家基因组科学数据库中共获取500个衰老相关基因，成骨细胞和成软骨细胞具有骨干细胞的分化潜能，并与衰老相关，因此选取成骨细胞/成软骨细胞和剩余细胞亚群间的4821个DEGs与500个衰老相关基因进行比对，共获取132个衰老相关DEGs。
成骨细胞亚群标志物RUNX2、COL1A1、CDH11、IBSP在成骨细胞亚群中呈高表达(图3A)，成软骨细胞亚群标志物SOX9、ACAN、PTH1R在成软骨细胞亚群中呈高表达(图3B)。
2.2 OSRM模型构建及预测价值
热图展示了17个细胞亚群间差异最显著的10个基因(图4A)，热图的颜色越接近于黄色表明DEGs在该细胞亚群中处于高表达，越接近紫色表明DEGs在该细胞亚群中处于低表达。在TARGET数据库中构建OSRM，单因素和多因素Cox回归分析显示，ADH5(HR=0.288， 95%CI 0.138~0.600， P=0.001)、APOE(HR=0.618， 95%CI 0.438~0.873， P=0.006)、ARHGAP1(HR=0.264， 95%CI 0.113~0.618， P=0.002)、ATF4(HR=2.716， 95%CI 1.176~6.273， P=0.019)等4个衰老DEGs与预后相关(图4B、C)。
生存分析显示，低风险组生存期明显长于高风险组(HR=0.13，95%CI 0.06~0.28，P<0.001；图5A)；ROC曲线分析显示，OSRM模型预测效能较高(AUC=0.786，图5B)。风险曲线分析显示，低风险组患者风险评分低于高风险组(图5C)；低风险评分患者的存活率高于高风险评分患者(图5D)。基因表达的热图显示，ADH5和ARHGAP1在骨肉瘤中呈低表达，APOE和ATF4在骨肉瘤中呈高表达(图5E)。
通过CIBERSORT算法定量TME的免疫细胞浸润情况，高、低风险组无明显差异(图6A)，而M1型巨噬细胞(HR=0.86，95%CI 0.74~0.92，P=0.044)和活化态CD4+记忆T细胞(HR=0.47，95%CI 0.30~0.64，P=0.003)与肿瘤预后相关(图6B、C)。
TIDE和Submap算法证实，低风险组患者对免疫检查点抑制剂有更好的应答效果(P<0.001，图7)。
2.3 免疫组化验证关键基因与骨肉瘤的关系
免疫组化检测结果显示，OSRM中ADH5和ARHGAP1在高、低表达组均呈低表达，而APOE和ATF4在高、低表达组均呈高表达(图8)。
2.4 OSRM衰老基因与免疫应答的相关性
为证实OSRM衰老基因与骨肉瘤免疫反应的相关性，在K7M2细胞系中过表达ATF4来诱发细胞衰老。
RT-qPCR检测结果显示，与pCMV组比较，ATF4过表达组代表性免疫炎性因子IL23A(P<0.05)、TNFA(P<0.01)、IL12A(P<0.05)、TGFBI(P<0.05)、IL6(P<0.001)、IL1B(P<0.001)、IL18(P<0.05)，以及免疫检查点分子PDL1(P<0.001)、IDO1(P<0.001)、TNFRSF8(P<0.001)、PDL2(P<0.001) mRNA相对表达量均明显升高(图9)。
在K7M2细胞系中过表达PD-1，建立PD-1免疫治疗敏感的骨肉瘤细胞系。Western blotting和RT-qPCR检测结果显示，PD-1过表达的K7M2细胞中ADH5(P<0.01)、APOE(P<0.01)、ATF4(P<0.05)呈持续高表达(图10)。
3 讨论
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骨肉瘤是儿童与青少年常见的骨肿瘤，多发生于长骨干骺端，以特征性的骨样沉积改变和高转移率为特征[28]。骨肉瘤具有典型的瘤内异质性，存在多种病理亚型，其中成骨型骨肉瘤约占60%，相当于成纤维细胞型和成软骨细胞型的总和[29]。既往研究表明，成骨细胞具有肿瘤干细胞的潜能，通常被认为是骨肉瘤细胞的起源[30-31]。目前骨肉瘤患者的标准治疗策略仍是术前新辅助化疗+手术切除肿瘤(截肢或保肢手术)+术后辅助化疗，然而在现有治疗方案下，转移性骨肉瘤患者的10年生存率仍低于20%[32]。本研究主要利用GSE1624541的scRNA-seq数据和来自TARGET数据库的mRNA测序与临床数据，对成骨型骨肉瘤进行细胞亚群划分，并构建了OSRM模型，以指导骨肉瘤的分型、预后判断和治疗。
Ma等[33]基于GSE1624541进行成骨型骨肉瘤单细胞亚型划分和后续分析，利用t-分布随机近邻嵌入(t-distributed stochastic neighbor embedding，t-SNE)将骨肉瘤聚类为14个细胞亚群，手动完成9个细胞亚群的注释。对于大宗的scRNA-seq数据，UMAP较t-SNE能够更多地保留数据全局结构，且对嵌入维数无限制，更容易扩展到更高维度的数据集中。此外，Ma等[33]对scRNA-seq设置的过滤条件为feature值>100，线粒体基因表达量<35%，与本研究有所区别。Zhou等[24]对7例原发性成骨型骨肉瘤、2例复发性骨肉瘤和2例肺部转移性骨肉瘤完成单细胞测序，由t-SNE将100 987个细胞划分为11个细胞亚群，发现T细胞免疫球蛋白和ITIM结构域蛋白(T cell immunoreceptor with Ig and ITIM domains，TIGIT)抑制剂可通过增高TIGIT阳性细胞百分比从而增强CD3+ T细胞对骨肉瘤的杀伤作用。该研究揭示了骨肉瘤的肿瘤内部异质性，为实现骨肉瘤的免疫治疗提供了机制方面的证据。
本研究结果显示，依据ADH5、ARHGAP1、APOE、ATF4等4个基因将骨肉瘤患者分为高、低风险组，低风险组具有更好的OS和免疫治疗敏感性。Mo等[34]证实，MYC可作用于ATF4的启动子从而抑制传统型骨肉瘤的失巢凋亡作用，促进肿瘤生长和侵袭，因此下调MYC对ATF4的调控可促进失巢凋亡行为，起到治疗肿瘤的作用。Luo等[35]也揭示了ATF4可抑制RET/GRP78阳性表达成骨型骨肉瘤的增殖并增强肿瘤对蛋白酶体抑制剂—硼替佐米的治疗敏感性。OSRM中ADH5和APOE基因在骨肉瘤中的作用鲜有报道，其可能成为新的分子病理诊断标志物和治疗的潜在靶点。
本研究的不足之处在于scRNA-seq的样本量偏小，且受限于TARGET数据库的数据类型，无法提供更多骨肉瘤多组学维度的数据。此外，实验验证尚停留于细胞水平，需要更多动物实验和体内实验验证结论。
综上所述，成骨型骨肉瘤可被scRNA-seq数据分为17个细胞亚群，ADH5、ARHGAP1、APOE、ATF4是骨肉瘤中衰老相关的抑癌或促癌基因。由上述基因构建的OSRM可预测成骨型骨肉瘤的治疗应答、预后和TME特征。OSRM关键基因在一定程度上为骨肉瘤的分子病理诊断提供了依据，也可作为预测抗PD-1免疫疗法对骨肉瘤患者疗效的潜在生物标志物。
基金
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  • 浙江省医药卫生科研计划项目(2019KY538)
文献
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2024年第49卷第5期
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doi: 10.11855/j.issn.0577-7402.1968.2023.0620
  • 接收时间：2022-08-09
  • 首发时间：2025-11-21
  • 出版时间：2024-05-28
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  • 收稿日期：2022-08-09
  • 录用日期：2022-12-13
基金
Medical Health Science and Technology Project of Zhejiang Provincial Health Commission(2019KY538)
浙江省医药卫生科研计划项目(2019KY538)
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    解放军联勤保障部队第903医院骨三科，浙江杭州 310000

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侯振海，E-mail：
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2种不同金属材料的力学参数
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Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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