Article(id=1320441080546448114, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1320441010094715145, articleNumber=null, orderNo=null, doi=10.16016/j.2097-0927.202601002, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1767283200000, receivedDateStr=2026-01-02, revisedDate=1769356800000, revisedDateStr=2026-01-26, acceptedDate=null, acceptedDateStr=null, onlineDate=1792747286211, onlineDateStr=2026-10-23, pubDate=1774800000000, pubDateStr=2026-03-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792747286211, onlineIssueDateStr=2026-10-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792747286211, creator=13701087609, updateTime=1792747286211, updator=13701087609, issue=Issue{id=1320441010094715145, tenantId=1146029695717560320, journalId=1319373162502258839, year='2026', volume='48', issue='6', pageStart='663', pageEnd='830', issueExtLink='null', onlineDate='null', pubDate='1774800000000', pubDateStr='2026-03-30', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792747269413, creator='13701087609', updateTime=1792749761919, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1320451464481321472, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1320441010094715145, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1320451464481321473, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1320441010094715145, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=745, endPage=756, ext={EN=ArticleExt(id=1320441080730997491, articleId=1320441080546448114, tenantId=1146029695717560320, journalId=1319373162502258839, language=EN, title=Streptococcus anginosus mediates CD8+ T cell dysfunction via upregulating PD-L1 in gastric cancer cells, columnId=1320434418116837551, journalTitle=Journal of Army Medical University, columnName=Basic Medicine, runingTitle=null, highlight=null, articleAbstract=
Objective

Recent evidence shows that Streptococcus anginosus (S.a) promotes the development of gastric cancer (GC). However, its role in GC progression, particularly its impact on tumor immune microenvironment (TIME), remains unclear. This study aims to investigate the role of S. a in advanced GC and test the hypothesis that S. a upregulates PD-L1 expression in GC cells, thereby inhibiting CD8+ T cell function.

Methods

Based on in-house RNA sequencing (RNA-seq) raw data (n=98), a computational pipeline was established to determine the relative abundance of S.a (S.a score). In parallel, a machine learning-based signature gene model was constructed to infer S. a abundance from gene expression matrices of public cohorts. Using these approaches, GC patients were stratified into S.a-high (S.ahigh) and S.a-low (S.alow) groups according to the median abundance. Single-cell RNA sequencing (scRNA-seq) data (n=23) were integrated to analyze differences in cellular composition within the TIME between the 2 groups. For in vitro validation, human (NUGC-3) and murine (TKM) GC cell lines were treated with S.a for 8 h, followed by quantification of PD-L1 expression via qPCR and Western blotting. Cytotoxic function of CD8+ T cells against S.a-pretreated GC cells was evaluated by flow cytometry in co-culture systems. where S.a-pretreated cancer cells were incubated with CD8⁺ T cells, and cytotoxicity was measured by flow cytometry. For in vivo validation, a C57BL/6 mouse orthotopic GC model was established; the experimental group received S.a bacterial suspension via oral gavage, while the control group received sterile culture medium, with continuous intervention for 6 weeks (n=6). Tumor burden was evaluated by in vivo imaging, tumor volume, and stomach weight.

Results

The abundance of S. a was significantly higher in GC tissues than in normal gastric mucosa (P=0.000 850), and high abundance was associated with poor prognosis (HR=1.49, 95%CI: 1.09 to 2.04, P=0.013 9). Analysis of the TIME using scRNA-seq data revealed distinct cellular compositions between GC tissues with varying S.a levels. Notably, S.ahigh GC tissues exhibited a significant increase in CD8+ T cell infiltration (P<0.000 1), yet these cells predominantly displayed an exhausted phenotype (P<0.000 1). Further analysis identified a subset of GC cells whose abundance is correlated positively with both S.a levels (Spearman’s rho=0.288, P<0.000 1) and proportion of exhausted CD8⁺ T cells (Spearman’s rho=0.522, P<0.000 1), suggesting their potential roles in modulating CD8⁺ T cell function. Mechanistically, S.a treatment significantly upregulated PD-L1 expression in GC cells (P<0.000 1). In co-culture assays, S.a-pretreated cancer cells impaired the cytotoxic function of CD8⁺ T cells (P=0.000 526). In vivo results demonstrated that the mice in the S. a gavage group exhibited significantly higher tumor bioluminescence intensity (P=0.030 6), larger tumor volume (P=0.045 3), and increased stomach weight (P=0.030 6) compared to the control group.

Conclusion

Enriched S.a abundance not only reshapes the TIME of GC, but also mediates CD8+ T cell exhaustion and facilitates tumor immune evasion by inducing high PD-L1 expression in GC cells.

, authors=Huilin PAN1, Jiayi JIANG1, Linyu WU1, Xipeng ZHENG1, Yongying HOU2, Junyu XIANG1, Zhongyi QIN1, Dongfeng CHEN1, Qiaoqiao ZHANG3, Zengjie LEI4, Xiaoyuan CHU4, Bin WANG1, Lei WANG1, Qiang MA2, Tao WANG1, authorsList=Huilin PAN, Jiayi JIANG, Linyu WU, Xipeng ZHENG, Yongying HOU, Junyu XIANG, Zhongyi QIN, Dongfeng CHEN, Qiaoqiao ZHANG, Zengjie LEI, Xiaoyuan CHU, Bin WANG, Lei WANG, Qiang MA, Tao WANG, authorCompany=null, correspAuthors=Qiang MA, Tao WANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=© 2026 Journal of Army Medical University, copyrightOwner=Editorial Office of Journal of Army Medical University, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1320441081917985532, articleId=1320441080546448114, tenantId=1146029695717560320, journalId=1319373162502258839, language=CN, title=咽峡炎链球菌通过上调胃癌细胞PD-L1表达介导CD8⁺ T细胞功能抑制, columnId=1320434418343329969, journalTitle=陆军军医大学学报, columnName=论著·基础医学, runingTitle=null, highlight=null, articleAbstract=
目的

新近研究发现,咽峡炎链球菌(Streptococcus anginosus,S. a)可促进胃癌(gastric cancer,GC)发生,但其在胃癌进展中的作用,特别是对肿瘤免疫微环境(tumor immune microenvironment,TIME)的影响机制尚未阐明。本研究拟探讨S. a在进展期胃癌中的作用,并验证其是否通过诱导胃癌细胞上调程序性死亡配体1(programmed death-ligand 1,PD-L1)表达,抑制CD8+ T细胞功能的科学假说。

方法

基于自产的转录组测序(RNA-seq)原始数据(n=98),构建S.a相对丰度(S. a score)的计算流程;另一方面,利用机器学习的方法构建特征基因模型,从公共队列的基因表达矩阵中推导S.a的丰度水平。基于上述方法,根据丰度中位数将胃癌患者分为S. a高丰度组(S.ahigh)与S. a低丰度组(S.alow)。结合单细胞转录组测序数据(n=23),分析两组患者肿瘤免疫微环境中细胞构成的差异。体外验证实验使用S.a处理人(NUGC-3)和鼠(TKM)胃癌细胞系8 h,通过定量PCR与Western blot检测PD-L1表达变化;并通过流式细胞术检测共培养体系中CD8+ T细胞对S.a预处理胃癌细胞的杀伤功能变化。体内实验采用C57BL/6小鼠原位胃癌模型,实验组通过口服灌胃给予S.a菌液,对照组给予无菌培养基,持续干预6周(每组n=6),通过活体成像、肿瘤体积及胃重比较评估肿瘤负荷。

结果

胃癌组织中S.a的丰度显著高于正常胃黏膜(P=0.000 850),且高丰度与预后不良有关(HR=1.49,95%CI;1.09~2.04,P=0.013 9)。通过单细胞转录组数据解析TIME,发现S.a含量不同的胃癌组织具有显著差异的TIME细胞构成,其中S.a丰度高的胃癌组织中CD8+ T细胞数量显著增多(P<0.000 1),但多呈耗竭状态(P<0.000 1)。我们进一步发现胃癌细胞可能是影响CD8+ T细胞功能状态的重要细胞群体,存在一群与S.a丰度(Spearman’s rho=0.288,P<0.000 1)及耗竭CD8+ T细胞(Spearman’s rho=0.522,P<0.000 1)均显著正相关的胃癌细胞。在机制上,S.a处理可显著上调胃癌细胞PD-L1的表达(P<0.000 1)。共培养实验证实,经S.a预处理的胃癌细胞能降低CD8+ T细胞的杀伤功能(P=0.000 526)。体内实验结果显示,S.a灌胃组小鼠的肿瘤成像(P=0.030 6)、肿瘤体积(P=0.045 3)及胃重(P=0.030 6)显著高于对照组。

结论

胃癌中丰度增加的S.a在重塑肿瘤免疫微环境的同时,通过诱导胃癌细胞高表达PD-L1而介导CD8+ T细胞产生耗竭表型、协助肿瘤免疫逃逸。

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王涛,E-mail:
马强,E-mail:
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MA Qiang,E-mail:
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A: Pipeline for evaluating the relative abundance of S.a based on raw RNA-seq data; B: S. a scores inferred from raw RNA-seq data in normal (n=38) and GC tissues (n=60); C: Representative images of HE staining (left), FISH (blue: nuclear, green: S. a probe) (middle), and magnified views (right) of normal and cancerous gastric tissue sections; D: Semi-quantitative analysis of MFI; E: Kaplan-Meier curves of OS in low and high S. a groups. S.a: Streptococcus anginosus; GC: Gastric cancer; FISH: Fluorescence in situ hybridization; MFI: Mean fluorescence intensity; OS: Overall survival; TCGA: The Cancer Genome Atlas; ACRG: Asian Cancer Research Group

, figureFileSmall=uLwfA2pVWEpa6T4vW8DGkg==, figureFileBig=DcHe2+4PlKShTcrxP2PbFg==, tableContent=null), ArticleFig(id=1320441091380335454, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1320441080546448114, language=EN, label=Figure 2, caption=Exhausted CD8+ T cells are enriched in TIME of S. ahighGC, figureFileSmall=JXB9a82DqU/F3nIjcLVzSg==, figureFileBig=2I0+6Lvy5369Jn9pw0Oydg==, tableContent=null), ArticleFig(id=1320441091451638623, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1320441080546448114, language=CN, label=图2, caption=S. a高丰度的胃癌免疫微环境中显著富集耗竭型CD8+ T细胞

A: UMAP of cell clusters from scRNA-seq dataset GSE150290 (n=23); B: Bar plot showing differences in TIME cellular composition between S. ahighand S. alowGC samples; C: UMAP of CD8+ T cell subclusters in dataset GSE150290; D: Bar plot illustrating alterations in CD8⁺ T cell subpopulations between S. ahighand S. alowgroups; E: Proportion of exhausted CD8+ T cells between S. ahighand S. alowsamples in scRNA-seq dataset GSE206785 (n=24); F, G: Comparison of Tex score (left), PDCD1 (PD-1) (middle) and CD274 (PD-L1) (right) expression between S. ahighand S. alowsamples in TCGA-STAD (n=408) (F) and GSE84437 (n=434) (G) cohorts; H: Representative images of HE staining and immunofluorescence assay from S. ahighand S. alowsamples; I: Quantification of PD1⁺ CD8⁺ T cells of indicated group. TIME: tumor immune microenvironment; S. a: Streptococcus anginosus; UMAP: Uniform manifold approximation and projection; Tex: Exhausted CD8⁺ T cells

, figureFileSmall=JXB9a82DqU/F3nIjcLVzSg==, figureFileBig=2I0+6Lvy5369Jn9pw0Oydg==, tableContent=null), ArticleFig(id=1320441091514553184, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1320441080546448114, language=EN, label=Figure 3, caption=S. a promotes PD-L1 expression in GC cells, figureFileSmall=LchexjXaggCyCrYCP/4jjg==, figureFileBig=0AlJqGhXaEnwWP1Flqx2LA==, tableContent=null), ArticleFig(id=1320441091573273441, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1320441080546448114, language=CN, label=图3, caption=S. a促进胃癌细胞表达PD-L1

A: CellChat-based incoming signaling network (left) to CD8⁺ T cells in the S. ahighgroup and its quantitative bar plot (right); B: UMAP visualization of cancer cell subsets; C: Bar plots of the proportion (left) and the differences (right) for 10 cancer cell subsets between S. ahighand S. alow group; D, E: The correlation between the signature score of 2# subset and S. a signature score (D), as well as Tex score (E) in ACRG (n=300) (left) and GSE84437 (n=434) (right) cohort; F: Immune checkpoint gene expression across the 2# subset and other cancer cell subsets; G, H: Relative transcription (G) and protein levels (H) of CD274 (PD-L1) in rodent (TKM) and human (NUGC-3) GC cell lines with or without 8 h of S. a treatment (MOI: 50). S. a: Streptococcus anginosus; GC: Gastric cancer; UMAP: Uniform manifold approximation and projection; ns: not significant

, figureFileSmall=LchexjXaggCyCrYCP/4jjg==, figureFileBig=0AlJqGhXaEnwWP1Flqx2LA==, tableContent=null), ArticleFig(id=1320441091648770914, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1320441080546448114, language=EN, label=Figure 4, caption=S. a impairs the cytotoxic function of CD8⁺ T cells to promote tumor growth, figureFileSmall=ddZbvCCzGSKwv3ToWZX72w==, figureFileBig=lUqyhQUaxsosHZ1ruxqnAA==, tableContent=null), ArticleFig(id=1320441091720074083, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1320441080546448114, language=CN, label=图4, caption=S. a抑制CD8+ T细胞的杀伤功能,促进肿瘤生长

A: Survival of OVA-expressing TKM cells following co-culture with OVA-specific CD8⁺ T cells after S.a exposure, as determined by flow cytometry and normalized to TKM cells cultured alone; B: CCK-8 assay for OVA-expressing TKM cells with or without 8 h of S. a treatment (MOI: 50); C: Flow cytometric analysis of PD-1, IFN-γ, granzyme B, and perforin expression in OVA-specific CD8⁺ T cells with or without S.a exposure; D to H: Orthotopic gastric tumor growth following TKM cell implantation with S.a or BHI gavage, shown by representative bioluminescence images (D), quantitative tumor signal intensity (E), gross morphology (F), tumor volume (G), and stomach weight (H). OVA: Ovalbumin

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咽峡炎链球菌通过上调胃癌细胞PD-L1表达介导CD8⁺ T细胞功能抑制
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潘惠琳 1 , 蒋佳艺 1 , 吴林育 1 , 郑喜鹏 1 , 侯永英 2 , 向俊宇 1 , 覃中毅 1 , 陈东风 1 , 张巧巧 3 , 雷增杰 4 , 褚晓源 4 , 王斌 1 , 王磊 1 , 马强 2 , 王涛 1
陆军军医大学学报 | 论著·基础医学 2026,48(6): 745-756
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陆军军医大学学报 |论著·基础医学 2026 , 48 (6) : 745 -756
咽峡炎链球菌通过上调胃癌细胞PD-L1表达介导CD8⁺ T细胞功能抑制
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潘惠琳1, 蒋佳艺1, 吴林育1, 郑喜鹏1, 侯永英2, 向俊宇1, 覃中毅1, 陈东风1, 张巧巧3, 雷增杰4, 褚晓源4, 王斌1, 王磊1, 马强2 , 王涛1
作者信息
  • 1陆军军医大学(第三军医大学)大坪医院,消化内科,消化系统肿瘤精准防治重庆市重点实验室,重庆
  • 2陆军军医大学(第三军医大学)大坪医院,病理科,重庆
  • 3金凤实验室,重庆
  • 4南京大学医学院附属金陵医院(东部战区总医院)肿瘤科,江苏 南京
通讯作者:
王涛,E-mail:
马强,E-mail:
WANG Tao,E-mail:
MA Qiang,E-mail:
Streptococcus anginosus mediates CD8+ T cell dysfunction via upregulating PD-L1 in gastric cancer cells
Huilin PAN1, Jiayi JIANG1, Linyu WU1, Xipeng ZHENG1, Yongying HOU2, Junyu XIANG1, Zhongyi QIN1, Dongfeng CHEN1, Qiaoqiao ZHANG3, Zengjie LEI4, Xiaoyuan CHU4, Bin WANG1, Lei WANG1, Qiang MA2 , Tao WANG1
Affiliations
  • 1Department of Gastroenterology, Chongqing Key Laboratory of Precise Prevention and Treatment of Digestive Malignancies,
  • 2Department of Pathology, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing
  • 3Jinfeng Laboratory, Chongqing
  • 4Department of Medical Oncology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University (General Hospital of the Eastern Theater Command of the People’s Liberation Army), Nanjing, Jiangsu Province, China
出版时间: 2026-03-30 doi: 10.16016/j.2097-0927.202601002
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目的

新近研究发现,咽峡炎链球菌(Streptococcus anginosus,S. a)可促进胃癌(gastric cancer,GC)发生,但其在胃癌进展中的作用,特别是对肿瘤免疫微环境(tumor immune microenvironment,TIME)的影响机制尚未阐明。本研究拟探讨S. a在进展期胃癌中的作用,并验证其是否通过诱导胃癌细胞上调程序性死亡配体1(programmed death-ligand 1,PD-L1)表达,抑制CD8+ T细胞功能的科学假说。

方法

基于自产的转录组测序(RNA-seq)原始数据(n=98),构建S.a相对丰度(S. a score)的计算流程;另一方面,利用机器学习的方法构建特征基因模型,从公共队列的基因表达矩阵中推导S.a的丰度水平。基于上述方法,根据丰度中位数将胃癌患者分为S. a高丰度组(S.ahigh)与S. a低丰度组(S.alow)。结合单细胞转录组测序数据(n=23),分析两组患者肿瘤免疫微环境中细胞构成的差异。体外验证实验使用S.a处理人(NUGC-3)和鼠(TKM)胃癌细胞系8 h,通过定量PCR与Western blot检测PD-L1表达变化;并通过流式细胞术检测共培养体系中CD8+ T细胞对S.a预处理胃癌细胞的杀伤功能变化。体内实验采用C57BL/6小鼠原位胃癌模型,实验组通过口服灌胃给予S.a菌液,对照组给予无菌培养基,持续干预6周(每组n=6),通过活体成像、肿瘤体积及胃重比较评估肿瘤负荷。

结果

胃癌组织中S.a的丰度显著高于正常胃黏膜(P=0.000 850),且高丰度与预后不良有关(HR=1.49,95%CI;1.09~2.04,P=0.013 9)。通过单细胞转录组数据解析TIME,发现S.a含量不同的胃癌组织具有显著差异的TIME细胞构成,其中S.a丰度高的胃癌组织中CD8+ T细胞数量显著增多(P<0.000 1),但多呈耗竭状态(P<0.000 1)。我们进一步发现胃癌细胞可能是影响CD8+ T细胞功能状态的重要细胞群体,存在一群与S.a丰度(Spearman’s rho=0.288,P<0.000 1)及耗竭CD8+ T细胞(Spearman’s rho=0.522,P<0.000 1)均显著正相关的胃癌细胞。在机制上,S.a处理可显著上调胃癌细胞PD-L1的表达(P<0.000 1)。共培养实验证实,经S.a预处理的胃癌细胞能降低CD8+ T细胞的杀伤功能(P=0.000 526)。体内实验结果显示,S.a灌胃组小鼠的肿瘤成像(P=0.030 6)、肿瘤体积(P=0.045 3)及胃重(P=0.030 6)显著高于对照组。

结论

胃癌中丰度增加的S.a在重塑肿瘤免疫微环境的同时,通过诱导胃癌细胞高表达PD-L1而介导CD8+ T细胞产生耗竭表型、协助肿瘤免疫逃逸。

胃癌  /  咽峡炎链球菌  /  肿瘤免疫微环境  /  耗竭型CD8+ T细胞
Objective

Recent evidence shows that Streptococcus anginosus (S.a) promotes the development of gastric cancer (GC). However, its role in GC progression, particularly its impact on tumor immune microenvironment (TIME), remains unclear. This study aims to investigate the role of S. a in advanced GC and test the hypothesis that S. a upregulates PD-L1 expression in GC cells, thereby inhibiting CD8+ T cell function.

Methods

Based on in-house RNA sequencing (RNA-seq) raw data (n=98), a computational pipeline was established to determine the relative abundance of S.a (S.a score). In parallel, a machine learning-based signature gene model was constructed to infer S. a abundance from gene expression matrices of public cohorts. Using these approaches, GC patients were stratified into S.a-high (S.ahigh) and S.a-low (S.alow) groups according to the median abundance. Single-cell RNA sequencing (scRNA-seq) data (n=23) were integrated to analyze differences in cellular composition within the TIME between the 2 groups. For in vitro validation, human (NUGC-3) and murine (TKM) GC cell lines were treated with S.a for 8 h, followed by quantification of PD-L1 expression via qPCR and Western blotting. Cytotoxic function of CD8+ T cells against S.a-pretreated GC cells was evaluated by flow cytometry in co-culture systems. where S.a-pretreated cancer cells were incubated with CD8⁺ T cells, and cytotoxicity was measured by flow cytometry. For in vivo validation, a C57BL/6 mouse orthotopic GC model was established; the experimental group received S.a bacterial suspension via oral gavage, while the control group received sterile culture medium, with continuous intervention for 6 weeks (n=6). Tumor burden was evaluated by in vivo imaging, tumor volume, and stomach weight.

Results

The abundance of S. a was significantly higher in GC tissues than in normal gastric mucosa (P=0.000 850), and high abundance was associated with poor prognosis (HR=1.49, 95%CI: 1.09 to 2.04, P=0.013 9). Analysis of the TIME using scRNA-seq data revealed distinct cellular compositions between GC tissues with varying S.a levels. Notably, S.ahigh GC tissues exhibited a significant increase in CD8+ T cell infiltration (P<0.000 1), yet these cells predominantly displayed an exhausted phenotype (P<0.000 1). Further analysis identified a subset of GC cells whose abundance is correlated positively with both S.a levels (Spearman’s rho=0.288, P<0.000 1) and proportion of exhausted CD8⁺ T cells (Spearman’s rho=0.522, P<0.000 1), suggesting their potential roles in modulating CD8⁺ T cell function. Mechanistically, S.a treatment significantly upregulated PD-L1 expression in GC cells (P<0.000 1). In co-culture assays, S.a-pretreated cancer cells impaired the cytotoxic function of CD8⁺ T cells (P=0.000 526). In vivo results demonstrated that the mice in the S. a gavage group exhibited significantly higher tumor bioluminescence intensity (P=0.030 6), larger tumor volume (P=0.045 3), and increased stomach weight (P=0.030 6) compared to the control group.

Conclusion

Enriched S.a abundance not only reshapes the TIME of GC, but also mediates CD8+ T cell exhaustion and facilitates tumor immune evasion by inducing high PD-L1 expression in GC cells.

gastric cancer  /  Streptococcus anginosus  /  tumor immune microenvironment  /  exhausted CD8⁺ T cells
潘惠琳, 蒋佳艺, 吴林育, 郑喜鹏, 侯永英, 向俊宇, 覃中毅, 陈东风, 张巧巧, 雷增杰, 褚晓源, 王斌, 王磊, 马强, 王涛. 咽峡炎链球菌通过上调胃癌细胞PD-L1表达介导CD8⁺ T细胞功能抑制. 陆军军医大学学报, 2026 , 48 (6) : 745 -756 . DOI: 10.16016/j.2097-0927.202601002
Huilin PAN, Jiayi JIANG, Linyu WU, Xipeng ZHENG, Yongying HOU, Junyu XIANG, Zhongyi QIN, Dongfeng CHEN, Qiaoqiao ZHANG, Zengjie LEI, Xiaoyuan CHU, Bin WANG, Lei WANG, Qiang MA, Tao WANG. Streptococcus anginosus mediates CD8+ T cell dysfunction via upregulating PD-L1 in gastric cancer cells[J]. Journal of Army Medical University, 2026 , 48 (6) : 745 -756 . DOI: 10.16016/j.2097-0927.202601002
胃癌(gastric cancer,GC)是全球第五大常见恶性肿瘤,同时也是导致癌症相关死亡的第五大病因[1]。然而,胃癌恶性生物学行为的产生及调控机制均未完全阐明[1]。作为新近提出的癌症特征标志之一[2],微生物组在胃癌发生发展过程中发挥重要作用:例如,幽门螺杆菌(Helicobacter pylori,H. pylori)作为经典胃癌“致病菌”,可通过激活Janus激酶-信号转导与转录激活因子(janus kinase-signal transducer and activator of transcription,JAK-STAT)、核因子κB(nuclear factor kappa-light-chain-enhancer of activated B cells,NF-κB)和Wnt/β-连环蛋白(wingless-related integration site/β- catenin,Wnt/β-catenin)等多条通路促进胃癌发生[3]。而在进展期胃癌中,H.pylori可通过诱导干扰素‑γ(interferon‑gamma,IFN‑γ),白细胞介素‑17(interleukin‑17,IL‑17)、白细胞介素‑21(interleukin‑21,IL-21)、白细胞介素‑22(interleukin‑22,IL-22)等炎症因子持续释放,进而影响细胞毒性T细胞、调节性T细胞、中性粒细胞等多种免疫细胞的功能状态,持续推动胃癌进展[4-5]。
除H.pylori外,其他胃内微生物也与胃癌发生发展密切相关。新近研究发现,胃内咽峡炎链球菌(Streptococcus anginosus,S.a)可通过TMPC-Annexin A2轴激活胃黏膜上皮细胞中的丝裂原活化蛋白激酶(mitogen-activated protein kinase,MAPK)信号通路,进而促进胃癌发生[6]。另有研究显示,定植于肿瘤免疫微环境(tumor immune microenvironment,TIME)中的微生物有重塑TIME细胞构成、促进肿瘤转移等恶性行为的作用[7-9]。然而,S.a在促进胃癌发生后是否仍存在于进展期胃癌、是否通过调控免疫功能等方式进而影响肿瘤恶性进展,仍不清楚。
有鉴于此,本研究通过分析多个常规转录组与单细胞转录组数据,结合体外与体内实验验证,以探讨S.a对胃癌恶性进展的影响及其潜在机制。我们发现S.a不仅能存在于进展期胃癌TIME中,且与胃癌患者预后不良相关。并且,S.a高低组之间的TIME细胞构成具有显著差异,高丰度S.a与耗竭CD8+ T细胞数量增加密切相关。其中,S.a通过上调胃癌细胞PD-L1表达水平,进而抑制CD8+ T的杀伤功能,可能是导致上述现象的重要原因。综上,本研究初步发现了S.a在进展期胃癌中的免疫抑制作用及分子机理,有望为理解胃癌免疫逃逸机制、提高胃癌免疫治疗效果提供新的思路。
本研究采用了课题组自产的RNA测序(RNA-seq)数据(内部数据,有原始的raw data文件)与多组公共数据(外部数据,仅有表达矩阵文件)。内部数据集包含38例正常胃组织与60例原发性胃癌组织的原始RNA测序数据;外部数据集下载自癌症基因组图谱-胃腺癌项目(the cancer genome atlas-stomach adenocarcinoma,TCGA-STAD)[10](https://portal.gdc.cancer.gov/projects/TCGA-STAD/,用于图1E、2F)、亚洲癌症研究组(Asian cancer research group,ACRG)[11](https://www.ncbi.nlm.nih.gov/geo/,编号GSE62254,用于图1E、3D、3E)以及基因表达综合数据库的(gene expression omnibus,GEO)数据集GSE84437[12](https://www.ncbi.nlm.nih.gov/geo/,编号GSE84437,用于图2G、3D、3E)。本研究所用的单细胞数据来源于GEO数据库GSE150290[13](23例胃癌,用于图2A~D、3A~F)和GSE206785[14](24例胃癌,用于图2E)。
研究方案已通过陆军特色医学中心伦理委员会审批[批准号:2025(231)],并在医学研究登记备案信息系统完成备案(备案编号:MR-50-25-048139)。
使用fastp (v0.23.4)对RNA测序原始数据质控后,将清洗后读段通过Bowtie2(v2.5.0)比对到人类参考基因组。随后,利用SAMtools(v1.20)提取未能比对至人类基因组的读段,并借助基于k-mer的工具Kraken2(v2.1.3)对这些未比对序列进行物种分类,再通过Bracken(v3.0)完成丰度校正[15-16],最后得到咽峡炎链球菌的丰度评分(S.a score)。该方法用于图1A~B的分析。
为了获得内部数据的基因表达矩阵,首先使用FastQC(v0.12.1)评估原始读段的质量,并利用TrimGalore(v0.6.10)去除接头序列和低质量碱基,获得清洗后的读段用于后续比对。通过HISAT2(v2.2.1)将这些读段比对到人类参考基因组(GRCh38/hg38)后,运用featureCounts (Subread,v2.0.8)进行基因水平的读段计数,得到基因表达矩阵供下游分析。
为从公共数据(不包含原始读段,仅有基因表达矩阵)中推断S.a相对丰度,我们构建了基于特征基因集的另一种计算模型。具体做法是:将内部队列获得的S.a score与对应的样本基因表达矩阵作为广义线性模型提升(generalized linear model boosting,glmBoost)算法[17]的输入,从而筛选出与S.a丰度相关的特征基因集(S.a signature)。随后,利用IOBR(v0.99.0)R包[18],在各样本表达矩阵根据该特征集计算出每个样本的S.a特征评分(S.a signature score)。在我们内部数据集的测试中,该评分与基于原始RNA-seq数据推导的S.a评分呈显著正相关(Spearman’s rho=0.580,P=1.18×10-6),提示了该计算模型的可靠性。上述方法用于图1E、2F-2G、3D-3E的分析。
以下方法用于图2A~E、3A~F的分析。首先采用Seurat (v4.4.0)处理scRNA-seq数据,筛选保留特征基因数在500~7 000、线粒体含量低于10%且基因计数超过1 000的细胞。归一化后,通过scDblFinder (v1.18.0)识别并剔除双细胞。接着,对预处理后的数据进行主成分分析(principal component analysis,PCA)、均匀流形近似和投影(uniform manifold approximation and projection,UMAP)可视化。在此基础上,先依据经典标记基因完成初步的细胞类型注释,再通过差异上调基因分析对CD8+ T细胞及胃癌细胞亚群进行更精细的亚群鉴定。
对于单细胞样本的S. a丰度鉴定,我们采用Seurat R包的“AggregateExpression”函数,先将数据转化为伪批量表达矩阵,再依据S.a丰度相关的特征基因集(S.a signature)对其进行打分,进而将组织分为S.a高丰度组与低丰度组。
本研究使用CellChat(v2.2.0)工具推断肿瘤微环境中CD8+ T细胞所接收的细胞间通信信号。为量化耗竭型CD8+ T(exhausted CD8+ T cells,Tex)细胞和2#癌细胞亚群的特征评分用于相关性分析,我们根据每个亚群的差异表达基因,筛选出差异表达倍数变化最高的前5个基因来构建特征列表。随后使用IOBR包分别计算每个样本的Tex和2#癌细胞亚群的特征评分。
本研究利用荧光原位杂交技术检测正常、胃癌组织中S.a的丰度(图1C~D)。在按照直接荧光细菌原位杂交检测试剂盒(Exonbio,#D-0016)说明书对石蜡切片进行预处理后,将探针(Exonbio,序列:TCAA-GCATCTAACATGTGTTACATACTG[19],稀释1∶100)与35%杂交缓冲液混合,滴加到切片上避光孵育48 h。孵育完成后,切片经洗涤、脱水及风干,并以DAPI复染细胞核。染色完成后,使用荧光显微镜采集图像。
以下方法用于图2H~I的检测内容。染色步骤按照双标三色多重荧光染色试剂盒(AiFang,#AFIHC023)说明书进行。组织切片在脱蜡、复水后,使用碱性EDTA缓冲液(ZSGB-Bio,#ZLI-9069)在高温高压条件下进行抗原修复。待切片冷却至室温,用过氧化氢封闭液孵育15 min以淬灭内源性过氧化物酶,再以山羊血清封闭液阻断非特异性结合。此后,滴加CD8A(Proteintech,#66868-1-Ig,1∶10 000)或PD-1(Abcam,#ab237728,1∶50)一抗,于4 ℃孵育过夜。次日进行二抗孵育及TSA荧光标记,重复上述步骤完成第二轮染色。最后以DAPI复染细胞核,于荧光显微镜下成像。
本研究所用的小鼠胃癌细胞系来源于课题组先前构建的带有荧光素酶表达的基因型为Trp53fl/fl;KrasLSL-G12D/+;MycOE (TKM)的小鼠胃癌细胞。人胃癌细胞系NUGC-3购自科佰生物技术有限公司(#CBP60492)。
TKM细胞和NUGC-3细胞分别在含10%胎牛血清(Viva Cell,#C04001-500)和1%青霉素-链霉素(Thermo Fisher Scientific,#15140-122)的DMEM培养基(Thermo Fisher Scientific,#C11995500BT)和RPMI 1640培养基(Thermo Fisher Scientific,#C11875500CP)中培养。所有细胞置于37 ℃、5%CO2的湿润培养箱中培育。上述方法培养的细胞用于图3G~H。
在37 ℃微需氧条件下,S. a(ATCC,#33397)于脑心浸液(brain heart infusion,BHI)琼脂平板培养24 h后转至液体培养基中扩增。在S.a处理前,我们将细胞的培养基更换为不含抗生素的培养基,并按感染复数(multiplicity of infection,MOI)=50接种S.a共培养8 h,对照组则添加等量的无菌BHI。以上方法用于图3G~H、4中S.a的培养及处理。
在图3G中,我们用下述的方法提取并检测基因相对表达水平:采用总RNA提取试剂盒(TIANGEN, #DP451)提取细胞RNA,经逆转录试剂盒(TaKaRa, #RR092A)合成cDNA。以TB Green Premix Ex Taq II FAST(TaKaRa, #RR830A)为反应体系,在实时荧光定量PCR仪上检测CD274(PD-L1)表达,引物序列如下:小鼠Cd274,正向5′-GCTCCAAAGGACTTGTACGTG-3′,反向5′-TGATCTGAAGGGCAGCATTTC-3′;小鼠Gapdh,正向5′-AGGTCGGTGTGAACGGATTTG-3′,反向5′-TGTAGACCATGTAGTTGAGGTCA-3′。人CD274,正向5′-TGGCATTTGCTGAACGCATTT-3′,反向5′-TG-CAGCCAGGTCTAATTGTTTT-3′;人GAPDH,正向5′-ACAACTTTGGTATCGTGGAAGG-3′,反向5′-GCC-ATCACGCCACAGTTTC-3′。
相对基因表达量以Gapdh/GAPDH为内参进行归一化,并使用2-ΔΔCt方法计算。
使用RIPA裂解缓冲液(Invent,#IN-WB001)提取细胞总蛋白,经浓度测定后上样,进行SDS-PAGE电泳并转至PVDF膜。用5%脱脂奶粉室温封闭2 h,随后在4 ℃下将PVDF膜与特异性PD-L1(Proteintech,#66248-1,1∶5 000)一抗孵育过夜。次日以二抗(abcam,#ab131368,1∶10 000)室温孵育2 h,并完成曝光显影。利用Image-Lab软件(Bio-Rad,v6.1)对蛋白质条带进行分析。该部分方法对应图3H。
采用表达卵清蛋白(ovalbumin,OVA)的胃癌细胞和OVA特异性CD8+ T细胞共培养体系评估CD8+ T细胞毒性。共培养实验按照先前报道的方法进行[20]。具体而言,我们从OT-1 C57BL/6小鼠脾脏分选出CD8+ T细胞(BioLegend #480035),并置于10% FBS、10 ng/mL IL-2(MCE,#HY-P7077)和0.75 μg/mL SIINFEKL肽段(MCE,#HY-P1771A)的培养基中活化7 d,以制备OVA特异性CD8+ T细胞。通过慢病毒转导构建稳定表达OVA的TKM细胞,将其按照1×105/孔的数目添加至24孔板,细胞贴壁后,加入S.a或等体积无菌BHI处理8 h。处理结束后,用含有10%青霉素-链霉素的PBS清洗孔板3次,按1∶1比例(数量依据预实验中经8 h S.a处理后的TKM细胞数计算)加入OVA特异性CD8+ T细胞,共培养24 h,并设置仅含靶细胞的对照组(无CD8+ T细胞)。共培养体系及单独培养体系中均添加10 ng/mL重组IL-2。共培养后,使用FITC Annexin V/PI凋亡检测试剂盒(BioLegend #640914)分析靶细胞凋亡。该部分方法对应图4A。
在图4B中,为评估S.a是否会直接影响肿瘤细胞增殖:我们将TKM细胞接种于96孔板中,细胞贴壁后,对其进行S.a(S.a+)或BHI处理(S.a-),处理结束后用含有10%青霉素-链霉素的PBS清洗孔板3次。接着,每孔加入90 μL新鲜培养基与10 μL CCK-8试剂(BOSTER,#AR1160),继续孵育1 h。最后,使用酶标仪测定各孔在450 nm处的吸光度,以此评估细胞增殖活性。
OVA特异性CD8+ T细胞的制备同1.11节,将细胞分为两组,在含细胞刺激混合液(eBioscience, #00-4970)及蛋白转运抑制剂混合液(eBioscience, #00-4980)的培养基中,分别加入S.a或等体积无菌BHI处理8 h。处理结束后,收集并计数细胞。随后用抗PD-1抗体(BioLegend, #135213)在4 ℃避光条件下进行表面染色30 min。染色后细胞经PBS洗涤,使用固定破膜试剂盒(eBioscience)进行固定与破膜处理,再于破膜缓冲液中与抗IFN-γ(BioLegend, #505809)、抗颗粒酶B(Granzyme B)(#372213)及抗穿孔素(Perforin)(#154305)抗体进行胞内染色30 min。染色步骤结束后,细胞经洗涤重悬,并于上机前加入DAPI染料,完成上机检测。该部分方法对应图4C。
以下动物实验方法对应图4D~H。本研究所用实验动物均为6~8周龄的C57BL/6雌性小鼠(集萃药康)。通过浆膜下注射构建胃癌原位移植瘤模型(每只小鼠注射5×105个TKM细胞)。成瘤后,将荷瘤小鼠随机分为两组,按近期Cell杂志文章报道的方法[6],分别给予每周2次BHI(S.a-)或S.a灌胃(S.a+)处理。其中,S.a灌胃剂量为2×109 CFU。6周后,通过活体荧光成像系统对小鼠进行活体成像,并采用Living Image软件定量分析肿瘤区域荧光强度。最后处死小鼠,完整剥离胃组织,称重并拍摄大体形态照片。
所有动物均在陆军军医大学SPF级动物设施中饲养,相关实验操作按照陆军军医大学实验动物福利与伦理委员会批准的方案进行(批准号:AMUWEC 20257064)。
本研究中的统计分析借助SPSS26和R 4.4.0软件进行。对于符合正态分布的连续变量,使用独立样本t检验;对于不服从正态分布的连续变量,使用Mann-Whitney U检验或Kruskal-Wallis检验。生存分析方面,采用Kaplan-Meier法绘制生存曲线并进行单因素分析。变量间的相关性通过Spearman相关性进行分析。显著性水平设定为P<0.05。
为比较正常胃黏膜与胃癌组织中S.a的丰度差异,我们首先对38例正常胃黏膜样本和60例胃癌样本进行了常规转录组测序,并基于先前研究报道的方法[15-16]建立了从原始RNA-seq数据(原始读段)中推断S.a评分(S.a score)的计算流程(图1A)。我们从中发现,胃癌组织的S. a评分显著高于正常胃黏膜(P=0.000 850,图1B);荧光原位杂交(fluorescence in situ hybridization,FISH)与平均荧光强度的半定量分析结果也显示:与正常胃黏膜相比,胃癌组织中的S.a信号更为密集,提示其具有更高的S.a水平(P=0.012 6,图 1C、D)。上述生物信息学和组织学的结果初步显示:S.a不仅可存在于胃癌组织中,且丰度高于正常胃黏膜,提示其可能具有促进胃癌恶性表型的潜在作用。
患者的生存时间是肿瘤多种恶性表型共同作用的最终结果。为在公共数据(不包含原始读段,仅能下载到基因表达矩阵)中探讨S.a对胃癌患者预后的影响,我们利用机器学习工具构建了用特征基因集(S.a signature)得分推断S.a相对含量的另一种计算模型,并以此对大型胃癌队列TCGA-STAD和ACRG提供的基因表达矩阵进行S.a特征基因打分(S.a signature score)、划分S.a高丰度组(S.ahigh)和S.a低丰度组(S.alow)。在这两个大型队列中,S.a高丰度组的胃癌患者均显示出更短的总生存时间(图1E),提示S.a高丰度的胃癌进展较快,患者临床预后较差。
TIME是影响肿瘤患者预后的关键因素[5, 21],其细胞构成决定了抗肿瘤免疫功能状态[22]。由于S.a在胃癌TIME中广泛分布(图1C),提示其可能与微环境中的多种细胞作用密切。为进一步研究S.a是否能影响TIME细胞构成,我们分析了来自23例原发性胃癌患者(GSE150290)[13]的单细胞RNA测序(scRNA-seq)数据。经过质控后,共得到60 770个细胞。利用经典标记基因,我们将这些细胞注释为10个亚群:包括免疫细胞(CD4+ T细胞、B细胞、浆细胞、CD8+ T细胞、单核/巨噬细胞和肥大细胞)、胃癌细胞以及基质细胞(内皮细胞、成纤维细胞和平滑肌细胞)(图2A)。随后,基于S.a丰度的特征基因模型,我们对scRNA-seq生成的伪批量转录组数据进行评分,并据此将样本分为S. a高丰度与低丰度组。比较分析结果显示,两组之间TIME的细胞组成存在显著差异(图2B):S.a高丰度组中,CD8+ T细胞、单核/巨噬细胞、CD4+ T细胞、平滑肌细胞、肥大细胞和成纤维细胞比例显著上升,而B细胞和肿瘤细胞比例则明显降低(图2B)。以上结果提示,S.a可能与胃癌TIME细胞成分的重塑密切相关。
CD8+ T细胞的功能状态是影响肿瘤恶性进展与患者预后的关键因素之一[23-25],为此我们进一步细分了CD8+ T细胞亚群(图2C)以比较在S.a高低两组之间的差异。分析结果显示:耗竭型CD8+ T(exhausted CD8+ T cells,Tex)细胞的比例在S.a高丰度组中的增加最为显著(图2D)。这一发现也在另一独立的scRNA-seq数据集(GSE206785,n=24)[14]中得到了验证(图2E)。在大型胃癌队列TCGA-STAD(n=408)[10]和GSE84437(n=434)[12]中,S.a高丰度的胃癌样本不仅具有更高的耗竭CD8+ T细胞评分[26],且关键免疫检查点分子PD-1[27]及其配体PD-L1[28]的表达水平也较S. a低丰度组显著上调(图2F~G)。我们进一步通过组织学水平验证发现,S.a高丰度的胃癌组织中PD-1+ CD8+ T细胞的数量显著增加(图2H~I)。上述多个队列的生物信息学分析及免疫荧光检测结果共同提示,胃癌TIME中存在的S.a虽能诱导TIME产生更多CD8+ T细胞,但可能通过PD-1/PD-L1轴使其大多数处于耗竭状态,从而维持免疫抑制的肿瘤微环境。
为探索S.a导致CD8+ T细胞耗竭的机制,我们对scRNA-seq数据GSE150290[13]进行了细胞间通讯分析。结果显示,S.a高丰度胃癌组织中CD8+ T细胞主要接收由肿瘤细胞释放的信号,提示胃癌细胞可能是导致CD8+ T细胞耗竭的重要原因(图 3A)。
因此,我们将肿瘤细胞亚群进一步聚类,并根据差异上调基因区分出10个胃癌细胞亚群(标记为1#~10#)(图3B),同时基于各胃癌组织的伪批量转录组数据划分了S.a高、低丰度的样本。差异分析显示,相较于S.a低丰度组,2#胃癌细胞亚群的含量在S.a高丰度组中的上调最为明显(图3C)。对ACRG[11](n=300)和GSE84437队列[12](n=434)的分析显示,2#胃癌细胞亚群的含量与S.a丰度(图3D)以及Tex细胞评分均呈显著正相关(图3E),提示其可能作为一群响应S.a的胃癌细胞,诱导CD8+ T细胞耗竭。
免疫检查点分子的数量或功能变化是介导CD8+ T细胞耗竭过程的关键原因[29]。为探索2#胃癌细胞亚群导致CD8+ T细胞耗竭的可能机制,我们在2#胃癌细胞亚群与其他亚群之间,比较了CD274[29]、PDCD1LG2[30]、PVR[31]、PVRL2[32]、LGALS9[33]等多个与CD8+ T细胞功能抑制及耗竭密切相关的免疫抑制分子的表达差异。其中,经典免疫检查点分子CD274(PD-L1)[34]在2#胃癌细胞亚群中的上调表达倍数显著高于其他检查点(图3F),从而提示S.a可能具有促进胃癌细胞表达PD-L1的能力。为了验证这一点,我们在体外实验中用S. a分别处理小鼠胃癌细胞(TKM)与人胃癌细胞(NUGC-3),发现其确能促进PD-L1的mRNA(图 3G)与蛋白表达水平(图3H)。这些数据共同提示:S. a通过诱导胃癌细胞表达PD-L1等免疫抑制分子,从而损害CD8+ T细胞的抗肿瘤功能。
为评估S.a 对CD8+ T细胞杀伤功能的影响,我们构建了由小鼠OVA特异性CD8+ T细胞与表达OVA的TKM细胞组成的共培养体系,并发现S.a处理可显著增加共培养体系中存活的肿瘤细胞比例(图4A),且此效应与肿瘤细胞增殖无关,因S. a 处理并不能显著促进肿瘤细胞的增殖水平(图4B)。而且,相比于不含菌的对照组,在S.a处理8 h后,OVA特异性CD8+ T细胞的PD-1、效应分子(IFN-γ、Granzyme B、Perforin)的表达均未产生有统计学差异的显著变化(图4C)。这些结果提示,S.a以肿瘤细胞依赖的方式抑制CD8+ T细胞的抗原特异性细胞毒性。
随后,我们利用小鼠原位移植瘤模型,观察S. a在免疫功能完整的动物水平上对胃癌的影响。小动物活体荧光成像显示:与对照组相比,S. a处理组的肿瘤荧光信号显著增强(图4D~E),提示该组具有更高的肿瘤负荷。取材后的大体观察与测量亦表明,S. a处理组的肿瘤体积更大(图4F~G)、胃重量显著增加(图4H)。这些结果共同支持了S.a通过抑制CD8+ T细胞的肿瘤杀伤功能,从而促进胃癌生长的假说。
近期研究表明,S. a在癌前病变阶段即可通过MAPK/ERK通路驱动胃上皮细胞化生与异型增生[6],从而首次揭示了该菌的致癌作用。在本研究中,我们进一步发现S. a仍能继续存在于进展期胃癌组织中,且其丰度进一步增加。我们的结果与既往研究[6, 35-37]共同提示,S. a这种新确证的胃癌相关微生物可能在胃癌发生发展的全过程中均发挥促癌作用。
本研究中,我们一方面通过分析大型胃癌公共队列发现S. a丰度高的患者具有较高PD-1表达水平;另一方面通过生信分析与实验验证发现S.a也具有诱导胃癌细胞表达PD-L1进而导致CD8+ T细胞功能抑制的作用,均可能是导致肿瘤免疫逃逸及患者预后不良的重要原因。然而,S. a产生这种效应机制尚不明确。其中,PAMP(pathogen-associated molecular patterns)- PRR(pattern recognition receptors)轴可感知异种抗原、触发IFN-α/β等炎症因子持续释放[38]。IFN-α可直接刺激CD8+ T细胞,虽短期内可促进其快速克隆性扩增,但持续暴露则导致其耗竭[39]。近期研究发现,胃内幽门螺杆菌可在激活PAMP-PRR通路的同时[40-42],诱导PD-L1与PD-1的表达[42-43]。作为同样可促进胃癌发生[6]并定植于胃癌微环境中的细菌,S.a与PD-L1/PD-1表达的相关性提示PAMP-PRR轴确有可能在其中发挥重要作用。有趣的是,近期研究报道S.a可通过其表面黏附素TMPC(一种具有PAMP样功能的细菌蛋白)诱导胃上皮细胞表达炎症因子Ccl20和Ccl8[6],为深入研究S. a是否通过PAMP-PRR通路上调PD-L1提供了线索。
同时我们还发现,S.a高丰度的胃癌组织中也具有高表达PD-1的特征,提示CD8+ T细胞处于功能耗竭状态。本研究虽初步显示该过程需要肿瘤细胞参与,但并未排除S.a通过其他非肿瘤细胞诱导CD8+ T细胞表达PD-1的可能性;加之S.a具有重塑胃癌免疫微环境细胞组分的潜能,故胃癌微环境中的多种细胞均有可能参与S.a诱导CD8+ T细胞表达PD-1的过程。其中,前段所述研究提示S.a可能通过PAMP-PRR轴介导固有免疫与适应性免疫失衡,进而持续产生炎症因子。由于长期慢性的炎症因子刺激可导致CD8+ T细胞表达PD-1等抑制分子并处于功能耗竭状态[44],这可能是S.a驱动PD-1+ CD8+ T细胞产生的重要原因之一:S.a通过PAMP-PRR信号激发肿瘤细胞炎症反应,通过持续释放的炎症因子上调CD8+T细胞的PD-1表达。
综上所述,本研究初步发现S.a可存在于进展期胃癌组织中,并可能通过刺激胃癌细胞表达PD-L1,进而抑制CD8+ T细胞杀伤功能、导致肿瘤进展。我们的发现为解释胃癌恶性进展及免疫逃逸提供了新了证据,具有一定的临床转化潜能,但仍存在局限性:在分子机制上,未能充分阐明S. a上调胃癌组织表达PD-L1及PD-1的机制;在临床应用场景上,S. a是否能成为预测免疫检查点抑制剂疗效的生物标志物及增敏靶点,仍需要通过更多的临床前研究数据予以回答[45-46],以为潜在的临床转化提供更充分的理论依据。

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doi: 10.16016/j.2097-0927.202601002
  • 接收时间:2026-01-02
  • 首发时间:2026-10-23
  • 出版时间:2026-03-30
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  • 收稿日期:2026-01-02
  • 修回日期:2026-01-26
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    1陆军军医大学(第三军医大学)大坪医院,消化内科,消化系统肿瘤精准防治重庆市重点实验室,重庆
    2陆军军医大学(第三军医大学)大坪医院,病理科,重庆
    3金凤实验室,重庆
    4南京大学医学院附属金陵医院(东部战区总医院)肿瘤科,江苏 南京

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王涛,E-mail:
马强,E-mail:
WANG Tao,E-mail:
MA Qiang,E-mail:
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2种不同金属材料的力学参数
科
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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