Article(id=1276202964121416184, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1276202956391313894, articleNumber=null, orderNo=null, doi=10.3981/j.issn.1000-7857.2025.07.00102, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1752768000000, receivedDateStr=2025-07-18, revisedDate=1766246400000, revisedDateStr=2025-12-21, acceptedDate=null, acceptedDateStr=null, onlineDate=1782200097351, onlineDateStr=2026-06-23, pubDate=1781280000000, pubDateStr=2026-06-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1782200097351, onlineIssueDateStr=2026-06-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1782200097351, creator=13701087609, updateTime=1782200097351, updator=13701087609, issue=Issue{id=1276202956391313894, tenantId=1146029695717560320, journalId=1146031591421210625, year='2026', volume='44', issue='11', pageStart='1', pageEnd='136', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1782200095507, creator=13701087609, updateTime=1782200147766, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1276203176344810276, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1276202956391313894, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1276203176344810277, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1276202956391313894, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=17, endPage=23, ext={EN=ArticleExt(id=1276202965727834618, articleId=1276202964121416184, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Heating up "cold" tumors: Breaking through the immunotherapy impasse in glioblastoma, columnId=1150494641880182997, journalTitle=Science & Technology Review, columnName=Commentary, runingTitle=null, highlight=null, articleAbstract=

Immunotherapies represented by immune checkpoint inhibitors and CAR−T cell therapy have fundamentally transformed the cancer treatment landscape, yet they have repeatedly failed against the most lethal brain tumor, glioblastoma (GBM). Why does this "immunological storm" that has swept through oncology suddenly "extinguish" within the brain This review addresses a core scientific question: Are our current immunotherapy strategies trapped in a "whack−a−mole" predicament when confronting GBM's fortress−like immunosuppressive tumor microenvironment (TME), lacking a comprehensive battle blueprint Through critical examination of the root causes underlying current therapeutic failures, we identify fundamental limitations in drug delivery, target selection, and microenvironment remodeling across three critical dimensions. We propose that future breakthroughs must pivot from "single−target approaches" toward "multi−step, sequential TME holistic remodeling." This requires developing more intelligent delivery systems to "breach the fortress walls," implementing metabolic interventions and targeted suppressive cell elimination to "purify the battlefield," and ultimately "create winning opportunities" for immune effector cells. This review also explores how novel preclinical models and dynamic biomarkers can guide the implementation of this complex strategy, aiming to provide new insights and inspiration for igniting this "immunological desert" of GBM.

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以免疫检查点抑制剂和嵌合抗原受体T细胞免疫疗法(chimeric antigen receptor T−Cell immunotherapy,CAR−T)为代表的免疫疗法,彻底改变了肿瘤治疗格局,但在最凶险的脑瘤——胶质母细胞瘤(glioblastoma, GBM)面前却屡屡受挫。为何这股席卷肿瘤界的“免疫风暴”独独在脑内“熄火”?从一个核心科学问题出发:面对GBM固若金汤的免疫抑制肿瘤微环境(tumor microenvironment, TME),当前的免疫治疗策略是否正陷入“打地鼠”式的困境,缺乏整体性的作战蓝图?通过对现有疗法失败根源的批判性思辨,指出当前策略在药物递送、靶点选择和微环境重塑3个层面存在的根本性局限。提出未来的破局点必须从“单一靶向”转向“多步、有序的TME整体重塑”。这需要开发更智能的递送系统以“攻破城墙”,通过代谢干预和靶向抑制细胞来“净化战场”,最终为免疫效应细胞“创造胜机”。同时探讨了利用新型临床前模型和动态生物标志物来指导这一复杂战略的实施,以期为点燃GBM这片“免疫荒漠”提供新的思路与启示。

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程兴,副主任医师,研究方向为脑胶质瘤的基础及临床,电子信箱:

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程兴,副主任医师,研究方向为脑胶质瘤的基础及临床,电子信箱:

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程兴,副主任医师,研究方向为脑胶质瘤的基础及临床,电子信箱:

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Cell, 2020, 180(1): 188−204. e22., articleTitle=A patient−derived glioblastoma organoid model and biobank recapitulates inter− and intra−tumoral heterogeneity, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1276202967988564488, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1276202964121416184, xref=null, ext=[AuthorCompanyExt(id=1276202968001147401, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1276202964121416184, companyId=1276202967988564488, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Neuro−oncology, Chongqing University Cancer Hospital, Chongqing 400030, China), AuthorCompanyExt(id=1276202968009536010, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1276202964121416184, companyId=1276202967988564488, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=重庆大学附属肿瘤医院神经肿瘤科,重庆 400030)])], figs=[ArticleFig(id=1276202974686867998, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1276202964121416184, language=EN, label=null, caption=null, figureFileSmall=RBe9rfN4vIhNBfKDq12uvg==, figureFileBig=KW/VyruDXLoZ6tmc3EQhlw==, tableContent=null), ArticleFig(id=1276202975047578143, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1276202964121416184, language=CN, label=图1, caption=GBM免疫治疗的核心挑战

左侧,免疫细胞的攻击被“血脑屏障”所阻挡;右侧,在由“缺氧”和“酸中毒”构成的“TME”内部,免疫抑制细胞(Treg,MDSC,TAM)释放抑制信号,保护着肿瘤细胞,使免疫疗法难以生效

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终点指标中位总生存期
(mOS)/月
12个月
总生存率/%
中位无进展生存期
(mPFS)/月
客观缓解率
(ORR)/%
注:HR>1.0表示尼沃利尤单抗组风险更高(结果更差);P<0.001表示差异具有高度统计学意义;尼沃利尤单抗显著劣于贝伐珠单抗的指标;−表示无数据。
尼沃利尤单抗组 (Nivolumab)9.8421.57.80
贝伐珠单抗组 (Bevacizumab)10423.523.10
风险比(HR1.041.97
P0.76<0.001
), ArticleFig(id=1276202976788214309, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1276202964121416184, language=CN, label=表1, caption=

CheckMate 143关键临床数据总结

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终点指标中位总生存期
(mOS)/月
12个月
总生存率/%
中位无进展生存期
(mPFS)/月
客观缓解率
(ORR)/%
注:HR>1.0表示尼沃利尤单抗组风险更高(结果更差);P<0.001表示差异具有高度统计学意义;尼沃利尤单抗显著劣于贝伐珠单抗的指标;−表示无数据。
尼沃利尤单抗组 (Nivolumab)9.8421.57.80
贝伐珠单抗组 (Bevacizumab)10423.523.10
风险比(HR1.041.97
P0.76<0.001
), ArticleFig(id=1276202976859517478, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1276202964121416184, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
检查点/通路主要表达细胞主要配体/作用机制在GBM抵抗中的作用
注:代偿性上调:当PD−1被阻断后,TIM−3、LAG−3、TIGIT等检查点分子表达显著上调;冗余机制:多个并行的抑制通路确保即使一个被阻断,其他仍能维持免疫抑制;适应性抵抗:TME动态调整,形成"天罗地网"式的免疫逃逸网络;治疗启示:需要联合阻断多个通路,而非单靶点线性思维。
TIM−3耗竭的CD8+细胞Galectin−9 介导T细胞耗竭和功能障碍,其表达在PD−1抑制后上调,是主要的适应性抵抗机制之一
TregsCEACAM−1
NK细胞HMGB1
巨噬细胞
LAG−3活化的T细胞MHC−II 负向调控T细胞活化与增殖,与PD−1协同作用加剧T细胞耗竭。Relatlimab(抗LAG−3)与Nivolumab联用已获批用于黑色素瘤
TregsLSECtin
NK细胞FGL1
TIGITT细胞PVR(CD155) 与CD226竞争配体,传递抑制信号,限制T细胞和NK细胞的效应功能。在PD−1抑制后表达上调
NK细胞Nectin−2(CD112)
TGF−β通路肿瘤细胞TGF−β受体I/II 强效、多效性抑制因子。抑制多种免疫细胞(T细胞、NK细胞)功能,诱导Tregs分化,促进肿瘤侵袭和血管生成
Tregs
巨噬细胞
星形胶质细胞
), ArticleFig(id=1276202976947597863, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1276202964121416184, language=CN, label=表2, caption=

GBM中PD−1/PD−L1抑制后的主要代偿性免疫抑制通路

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检查点/通路主要表达细胞主要配体/作用机制在GBM抵抗中的作用
注:代偿性上调:当PD−1被阻断后,TIM−3、LAG−3、TIGIT等检查点分子表达显著上调;冗余机制:多个并行的抑制通路确保即使一个被阻断,其他仍能维持免疫抑制;适应性抵抗:TME动态调整,形成"天罗地网"式的免疫逃逸网络;治疗启示:需要联合阻断多个通路,而非单靶点线性思维。
TIM−3耗竭的CD8+细胞Galectin−9 介导T细胞耗竭和功能障碍,其表达在PD−1抑制后上调,是主要的适应性抵抗机制之一
TregsCEACAM−1
NK细胞HMGB1
巨噬细胞
LAG−3活化的T细胞MHC−II 负向调控T细胞活化与增殖,与PD−1协同作用加剧T细胞耗竭。Relatlimab(抗LAG−3)与Nivolumab联用已获批用于黑色素瘤
TregsLSECtin
NK细胞FGL1
TIGITT细胞PVR(CD155) 与CD226竞争配体,传递抑制信号,限制T细胞和NK细胞的效应功能。在PD−1抑制后表达上调
NK细胞Nectin−2(CD112)
TGF−β通路肿瘤细胞TGF−β受体I/II 强效、多效性抑制因子。抑制多种免疫细胞(T细胞、NK细胞)功能,诱导Tregs分化,促进肿瘤侵袭和血管生成
Tregs
巨噬细胞
星形胶质细胞
), ArticleFig(id=1276202977140535848, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1276202964121416184, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
代谢特征量化水平/机制对抗肿瘤免疫细胞(T细胞,NK细胞)的影响对促肿瘤免疫细胞(Tregs,TAMs,MDSCs)的影响
注:对抗肿瘤细胞:缺氧+酸中毒+营养剥夺=三重打击,导致功能衰竭;对促肿瘤细胞:适应性强+能量来源多样+功能增强=环境优势;核心问题:代谢环境系统性地削弱“好人”、壮大“坏人”;治疗启示:不解决“后勤保障”问题,输送再多免疫“士兵”都可能徒劳。
缺氧(hypoxia) 中位氧分压:5~9 mmHg(正常脑组织:25~40 mmHg) 重度缺氧状态 抑制T细胞活化和功能;诱导T细胞耗竭;限制NK细胞的细胞毒性 诱导HIF−1α,促进TAMs向M2型极化;增强MDSCs的免疫抑制功能;促进Tregs招募
酸中毒(acidosis) 细胞外pH:~6.8(正常脑组织pH:~7.1)高乳酸环境 直接抑制T细胞和NK细胞的细胞毒功能;诱导T细胞无能状态(anergy);阻碍细胞因子分泌 促进M2型TAMs极化;增强Tregs的抑制功能;乳酸可作为能量来源
葡萄糖剥夺 糖酵解速率为正常细胞约200倍,瓦博格效应肿瘤细胞疯狂掠夺葡萄糖 效应T细胞依赖糖酵解供能,葡萄糖缺乏导致其能量衰竭,功能受损 Tregs和M2型TAMs对糖酵解依赖性较低,更能适应低糖环境
氨基酸耗竭 IDO酶介导的色氨酸分解犬尿氨酸pathway激活 色氨酸耗竭导致T细胞周期停滞和凋亡;犬尿氨酸等代谢物直接抑制T细胞功能 诱导耐受性树突状细胞;促进Tregs的分化和功能
), ArticleFig(id=1276202977253782057, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1276202964121416184, language=CN, label=表3, caption=

GBM TME的代谢特征及其对免疫细胞的差异化影响

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代谢特征量化水平/机制对抗肿瘤免疫细胞(T细胞,NK细胞)的影响对促肿瘤免疫细胞(Tregs,TAMs,MDSCs)的影响
注:对抗肿瘤细胞:缺氧+酸中毒+营养剥夺=三重打击,导致功能衰竭;对促肿瘤细胞:适应性强+能量来源多样+功能增强=环境优势;核心问题:代谢环境系统性地削弱“好人”、壮大“坏人”;治疗启示:不解决“后勤保障”问题,输送再多免疫“士兵”都可能徒劳。
缺氧(hypoxia) 中位氧分压:5~9 mmHg(正常脑组织:25~40 mmHg) 重度缺氧状态 抑制T细胞活化和功能;诱导T细胞耗竭;限制NK细胞的细胞毒性 诱导HIF−1α,促进TAMs向M2型极化;增强MDSCs的免疫抑制功能;促进Tregs招募
酸中毒(acidosis) 细胞外pH:~6.8(正常脑组织pH:~7.1)高乳酸环境 直接抑制T细胞和NK细胞的细胞毒功能;诱导T细胞无能状态(anergy);阻碍细胞因子分泌 促进M2型TAMs极化;增强Tregs的抑制功能;乳酸可作为能量来源
葡萄糖剥夺 糖酵解速率为正常细胞约200倍,瓦博格效应肿瘤细胞疯狂掠夺葡萄糖 效应T细胞依赖糖酵解供能,葡萄糖缺乏导致其能量衰竭,功能受损 Tregs和M2型TAMs对糖酵解依赖性较低,更能适应低糖环境
氨基酸耗竭 IDO酶介导的色氨酸分解犬尿氨酸pathway激活 色氨酸耗竭导致T细胞周期停滞和凋亡;犬尿氨酸等代谢物直接抑制T细胞功能 诱导耐受性树突状细胞;促进Tregs的分化和功能
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科技导报 | 科技评论 2026,44(11): 17-23
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科技导报 | 科技评论 2026, 44(11): 17-23
“冷”肿瘤如何“热”起来?——破局胶质母细胞瘤免疫治疗困境
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程兴 , 杨海峰
作者信息
  • 重庆大学附属肿瘤医院神经肿瘤科,重庆 400030
  • 程兴,副主任医师,研究方向为脑胶质瘤的基础及临床,电子信箱:

Heating up "cold" tumors: Breaking through the immunotherapy impasse in glioblastoma
Xing CHENG , Haifeng YANG
Affiliations
  • Department of Neuro−oncology, Chongqing University Cancer Hospital, Chongqing 400030, China
出版时间: 2026-06-13 doi: 10.3981/j.issn.1000-7857.2025.07.00102
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以免疫检查点抑制剂和嵌合抗原受体T细胞免疫疗法(chimeric antigen receptor T−Cell immunotherapy,CAR−T)为代表的免疫疗法,彻底改变了肿瘤治疗格局,但在最凶险的脑瘤——胶质母细胞瘤(glioblastoma, GBM)面前却屡屡受挫。为何这股席卷肿瘤界的“免疫风暴”独独在脑内“熄火”?从一个核心科学问题出发:面对GBM固若金汤的免疫抑制肿瘤微环境(tumor microenvironment, TME),当前的免疫治疗策略是否正陷入“打地鼠”式的困境,缺乏整体性的作战蓝图?通过对现有疗法失败根源的批判性思辨,指出当前策略在药物递送、靶点选择和微环境重塑3个层面存在的根本性局限。提出未来的破局点必须从“单一靶向”转向“多步、有序的TME整体重塑”。这需要开发更智能的递送系统以“攻破城墙”,通过代谢干预和靶向抑制细胞来“净化战场”,最终为免疫效应细胞“创造胜机”。同时探讨了利用新型临床前模型和动态生物标志物来指导这一复杂战略的实施,以期为点燃GBM这片“免疫荒漠”提供新的思路与启示。

胶质母细胞瘤  /  免疫治疗  /  肿瘤微环境  /  免疫抑制  /  治疗困境

Immunotherapies represented by immune checkpoint inhibitors and CAR−T cell therapy have fundamentally transformed the cancer treatment landscape, yet they have repeatedly failed against the most lethal brain tumor, glioblastoma (GBM). Why does this "immunological storm" that has swept through oncology suddenly "extinguish" within the brain This review addresses a core scientific question: Are our current immunotherapy strategies trapped in a "whack−a−mole" predicament when confronting GBM's fortress−like immunosuppressive tumor microenvironment (TME), lacking a comprehensive battle blueprint Through critical examination of the root causes underlying current therapeutic failures, we identify fundamental limitations in drug delivery, target selection, and microenvironment remodeling across three critical dimensions. We propose that future breakthroughs must pivot from "single−target approaches" toward "multi−step, sequential TME holistic remodeling." This requires developing more intelligent delivery systems to "breach the fortress walls," implementing metabolic interventions and targeted suppressive cell elimination to "purify the battlefield," and ultimately "create winning opportunities" for immune effector cells. This review also explores how novel preclinical models and dynamic biomarkers can guide the implementation of this complex strategy, aiming to provide new insights and inspiration for igniting this "immunological desert" of GBM.

glioblastoma  /  immunotherapy  /  tumor microenvironment  /  immunosuppression  /  therapeutic challenges
程兴, 杨海峰. “冷”肿瘤如何“热”起来?——破局胶质母细胞瘤免疫治疗困境. 科技导报, 2026 , 44 (11) : 17 -23 . DOI: 10.3981/j.issn.1000-7857.2025.07.00102
Xing CHENG, Haifeng YANG. Heating up "cold" tumors: Breaking through the immunotherapy impasse in glioblastoma[J]. Science & Technology Review, 2026 , 44 (11) : 17 -23 . DOI: 10.3981/j.issn.1000-7857.2025.07.00102
近年来,以程序性细胞死亡蛋白−1(programmed death−1,PD−1)抑制剂与嵌合抗原受体T细胞免疫疗法(chimeric antigen receptor T−Cell immunotherapy,CAR−T)为代表的免疫治疗在众多实体瘤中取得了突破性成功,为无数晚期癌症患者带来了长期生存的曙光。然而,这道曙光却未能照亮胶质母细胞瘤(glioblastoma, GBM)的阴霾。作为成人中最具侵袭性的颅内恶性肿瘤,GBM的预后极其严峻,患者中位总生存期(median overall survival,mOS)徘徊于15~20个月,5年生存率不足10%[12]。在此背景下,被寄予厚望的免疫疗法,无论是以免疫检查点抑制剂还是CAR−T为基础的临床试验,几乎无一例外地宣告失败。
这一系列结果迫使我们直面一个核心问题:对于GBM,究竟是免疫疗法这一“武器”本身无效,还是采用的“战术”从根本上就存在缺陷?学界普遍将症结指向GBM独特的免疫抑制性肿瘤微环境(tumor microenvironment,TME)。这个微环境如同一座壁垒森严的“要塞”,综合运用物理屏障(血脑屏障)、免疫抑制细胞军团、可溶性抑制分子网络以及恶劣的代谢条件,构建起一套强大、立体的防御体系,能轻易地将免疫攻击化解于无形(图1)。但更深层次的问题在于,是否一直在用一种过于简化的视角看待这座“要塞”?当前逐个击破TME组成部分的策略,无异于“头痛医头,脚痛医脚”。这种战术是否从根本上低估了其防御体系的复杂性、动态适应性与内部协同性?是否已陷入一场“按下葫芦浮起瓢”的徒劳消耗战,而从未真正瞄准其防御体系的“阿喀琉斯之踵”?
将GBM的TME比作一个多层次的防御堡垒,目前的策略似乎在每个层面都遇到了难以逾越的障碍。这些障碍并非孤立存在,而是相互关联、协同作用,形成了一个动态的、具有强大适应性的防御体系。
免疫治疗的首要挑战,在于如何将大分子抗体或细胞药物有效递送至肿瘤部位。血脑屏障(blood brain barrier,BBB)与血肿瘤屏障(blood–tumour barrier,BTB)构成了难以逾越的物理天堑[34]。尽管通常认为肿瘤会导致屏障“渗漏”,但这种渗漏极不均匀,尤其在肿瘤复发的根源——浸润边缘区域,屏障往往保持完好。此外,即便在通透性增加的区域,肿瘤内部的高压环境和药物外排机制也会严重阻碍药物的有效累积[5]
然而,单纯将失败归咎于递送效率也面临挑战。一项“机会窗口”研究揭示了颠覆性的“尼沃利尤单抗悖论”:结果发现,全身给药的PD−1抑制剂尼沃利尤单抗,实际上能够穿透屏障,并成功饱和肿瘤内T细胞上的PD−1靶点。这一发现极具颠覆性,表明药物递送的“最后一公里”问题可能并非不可逾越的鸿沟[6]。但问题是,如果作为“武器”的尼沃利尤单抗已成功到达“战场”上的靶点(T细胞上的PD−1),为何在大型临床试验中却依然无法产生有效的抗肿瘤效果?这“尼沃利尤单抗悖论”有力地证明,药物递送固然是挑战,但它远非失败的唯一解释[78]
即便部分免疫“武器”突破了物理屏障,它们面对的也是一个由多种免疫抑制细胞(如同“叛军”和“间谍”)和可溶性分子(如同弥漫的“毒气”)构成的立体化、协同化的防御网络。当前基于“一个靶点、一种药物”的线性思维,在这种复杂防御体系面前显得捉襟见肘。
最具说服力的例证是CheckMate 143临床试验。在该试验中,用于复发性GBM的PD−1抑制剂尼沃利尤单抗,其疗效未能优于,甚至在某些指标上劣于抗血管药物贝伐珠单抗,最终未能改善患者的总生存期[9]。更令人担忧的是,在次要终点上,尼沃利尤单抗组的客观缓解率(objective response rate,ORR)和无进展生存期(progress free survival,PFS)甚至显著低于贝伐珠单抗组(表1)。
为何会这样?其根本原因在于肿瘤的适应性抵抗机制。研究揭示,当PD−1这一免疫检查点被抑制后,TME会迅速、代偿性地“唤醒”其他并行的抑制通路,如TIM−3、LAG−3、TIGIT和CTLA−4等检查点分子的表达会急剧上调[10]。这形成了一种“打地鼠”的困境:敲下一个抑制靶点,更多的靶点会立刻涌现,持续抑制T细胞功能,使其陷入耗竭。这种适应性逃逸,再加上TGF−β、IDO等其他抑制因素,共同编织了一张免疫抑制的天罗地网,使得基于线性思维的单靶点阻断策略在GBM这类高度复杂的肿瘤面前,几乎注定失败(表2)。
免疫治疗的最终执行者是T细胞等免疫“士兵”,但GBM的TME不仅布满了“敌人”,更是一片让他们无法生存的代谢“焦土”。
这片“焦土”的特征是重度缺氧(氧分压低至5~9 mmHg)与严重酸中毒(pH低至6.8)[11]。其根源在于GBM细胞发动的“代谢战”:它们通过“瓦博格效应”,以高达正常细胞200倍的速率进行糖酵解。这种疯狂的代谢模式对免疫“士兵”造成了双重打击。
1) 剥夺“口粮”:效应T细胞的活化、增殖和执行杀伤功能,同样高度依赖糖酵解来快速供能。GBM细胞对葡萄糖的疯狂掠夺,直接导致微环境中的葡萄糖枯竭,使得进入战场的T细胞因缺乏“燃料”而无法有效工作。
2) 释放“毒气”:糖酵解产生的大量副产品——乳酸,不仅造成了环境的酸中毒,其本身也是一种强效的免疫抑制分子。高浓度的乳酸能够直接抑制T细胞和NK细胞的细胞毒性功能,诱导T细胞“无能”,并阻碍其增殖和细胞因子的分泌[12]
极具讽刺的是,这个扼杀抗癌“士兵”的环境,却为调节性T细胞(Tregs)和M2型巨噬细胞(TAMs)等免疫抑制细胞提供了“沃土”。这些细胞不依赖葡萄糖,甚至能利用乳酸作为能量,并在其刺激下增强抑制功能[13]。因此,GBM的代谢微环境构成了一个精妙的筛选系统:它系统性地削弱和淘汰了具有抗肿瘤能力的效应细胞,同时滋养和壮大了有助于肿瘤生长的抑制性细胞群体(表3)。这就提出了一个尖锐的问题:在一个让“士兵”饥寒交迫,甚至中毒身亡的战场上,输送再多、再精良的免疫“武器”或“士兵”,是否都注定是徒劳?
对当前困境的思辨,并非要否定免疫治疗在GBM领域的潜力,而是呼唤一种战略上的根本性转变:我们必须摒弃过去那种试图通过单一武器或简单组合进行“单点爆破”的线性思维,转向一种有序、多步、整体性的“体系作战”模式。这一新战略的核心思想是,治疗的主要目标不应再仅是直接杀死肿瘤细胞,而应是系统性地重塑整个TME,将其从一个促进肿瘤生长、抑制免疫的“冷”状态,改造为一个有利于免疫细胞发挥作用的“热”状态。这一过程可以被设想为一个逻辑清晰的3步作战计划:第1步“破城”,第2步“清场”,第3步“总攻”。
“体系作战”的首要前提,是确保治疗药物能无障碍地进入整个“战场”,尤其是受BBB保护的肿瘤浸润区。为此,必须将局部、精准的药物递送技术提升到战略核心地位。
聚焦超声(focused ultrasound,FUS)技术代表了一种极具潜力的非侵入性“破城”手段。它通过体外超声与静脉注射的微泡协同作用,利用微泡振荡产生的温和机械力,暂时并可逆地打开血脑屏障。这会形成一个持续数小时的“治疗窗口”,让抗体、CAR−T细胞等大分子药物得以进入肿瘤[6,10]。其核心优势在于靶向精准,可通过磁共振成像(magnetic resonance imaging,MRI)实时监控,安全性高(图2)。
脑部毛细血管内皮细胞紧密相连,形成血脑屏障。从体外发射的聚焦超声波束,汇聚于该血管段。血管内流动着治疗药物分子(如抗体)和微泡。图2中放大图详细展示超声波作用下,微泡发生振荡(扩张和收缩),其机械力推开内皮细胞间的紧密连接,形成一个暂时的缝隙,使得原本被阻挡在血管内的药物分子得以穿过屏障,进入脑组织。
对流增强递送(convection−enhanced delivery,CED)与FUS不同,是一种侵入性但更为直接的递送方式。它通过外科手术将细微导管植入肿瘤区域,利用微量泵施加正压,将高浓度药物溶液直接“泵”入脑组织。该技术利用“对流”原理而非“扩散”,能将药物均匀覆盖到更广阔的组织区域,从根本上绕过了血脑屏障,理论上可递送任何类型的治疗药物(图3)。
一根细长的导管从颅骨外穿入,尖端置于肿瘤内部或边缘。导管连接到一个外部的微量输注泵。在输注泵产生的正压力驱动下,药物溶液从导管尖端流出,通过“对流”(bulk flow)的方式在脑组织间隙中弥散开来,形成一个范围远大于传统扩散的、均匀的药物分布云团[812]
在确保“主力部队”能够顺利进入战场后,第二步关键任务是“净化战场”,即系统性地瓦解TME中的免疫抑制网络,并改善恶劣的代谢环境,为后续的免疫攻击创造有利条件。值得强调的是,许多用于“清场”的药物在作为单药治疗GBM时均已宣告失败,但这恰恰反证了“体系作战”的必要性——它们并非无效,而是需要被整合到一个更大的战略框架中。
清除“叛军”与“间谍”——靶向抑制性免疫细胞。肿瘤相关巨噬细胞(tumor−associated macrophages,TAMs)是GBM微环境中数量最多的免疫细胞,其M2表型具有强烈的免疫抑制和促血管生成作用。集落刺激因子−1(CSF−1)及其受体(CSF−1R)是调控TAMs生存、分化和功能的关键通路。CSF−1R抑制剂(如PLX3397)的Ⅱ期临床试验结果发人深省:尽管该药物耐受性良好且能有效穿透血脑屏障,但作为单药治疗复发性GBM时,并未显示出任何客观缓解。这一“成功的失败”说明,仅移除一种抑制性细胞,在缺少后续有效攻击的情况下,不足以逆转战局[14]
中和“毒气”——阻断抑制性信号分子。TGF−β是GBM微环境中最强大的免疫抑制细胞因子之一,它能抑制几乎所有类型免疫细胞的活性,并促进Tregs的分化。针对TGF−β的抑制剂,如小分子抑制剂Galunisertib,也已在GBM中进行了临床试验,但单药或与标准放化疗联合时,均未能证明显著的生存获益。IDO1酶通过降解色氨酸,不仅剥夺了T细胞必需的氨基酸,其代谢产物犬尿氨酸还具有直接的免疫抑制作用[5,13]。这些单药治疗的失败案例共同指向一个结论:在GBM强大的、多通路协同的免疫抑制网络中,单纯“清场”而不进行“总攻”是远远不够的。
在通过创新的递送技术“破城”并利用靶向药物初步“清场”之后,TME的状态已经从“极度冰冷”转变为“微冷”或“中性”。此时,引入能够强力激发免疫系统、将肿瘤转“热”的“主力部队”,其效能将得到极大放大。
干扰素基因刺激因子(stimulator of interferon gene,STING)通路是连接先天免疫和适应性免疫的关键桥梁。当细胞质中出现异常DNA时,STING通路被激活,引发强烈的Ⅰ型干扰素(IFN−Ⅰ)应答。直接向肿瘤内注射STING激动剂,相当于人为地模拟了一场强烈的“病毒感染”,能够迅速将免疫“冷”肿瘤转变为“热”肿瘤。一项在患有自发性GBM的犬类中进行的临床试验,为这一策略提供了令人振奋的证据。向犬的GBM肿瘤内立体定向注射STING激动剂IACS−8779,不仅耐受性良好,而且观察到了剂量依赖性的肿瘤缩小,其中一只犬甚至达到了影像学上的完全缓解[1314]
树突状细胞(dendritic cell,DC)疫苗是一种高度个体化的主动免疫疗法。从患者外周血中分离出单核细胞,在体外诱导分化为树突状细胞,然后用从患者自身肿瘤组织中提取的抗原来“加载”这些DC。在众多失败的GBM免疫治疗试验中,DC疫苗DCVax−L的Ⅲ期临床试验是为数不多的亮点之一。结果显示,与外部对照组相比,DCVax−L联合标准治疗能够显著延长新诊断GBM患者(mOS:19.3个月vs 16.5个月)和复发GBM患者(mOS:13.2个月vs 7.8个月)的总生存期[15]
GBM免疫治疗的过往困境,主要源于对肿瘤复杂微环境的认知和干预策略过于线性化。然而,临床试验的挫折并非终点,反而为我们指明了未来的方向。未来的出路,必然要求完成一场深刻的战略思维转变。这包括3大核心转变:从“以肿瘤细胞为中心”向“以TME为整体”的观念转变,认识到重塑微环境是成功的前提;从“单兵作战”向“多步协同的体系作战”的战术转变,通过“破城”“清场”“总攻”的有序组合,系统性瓦解肿瘤防御;从“群体化治疗”向“个体化动态施策”的模式转变,利用生物标志物为每位患者定制并优化治疗方案。
通过整合创新的药物递送技术、TME重塑药物与强效免疫激活疗法,有充分理由相信,GBM免疫治疗的“坚冰”终将被打破,为患者带来真正的生存希望。
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doi: 10.3981/j.issn.1000-7857.2025.07.00102
  • 接收时间:2025-07-18
  • 首发时间:2026-06-23
  • 出版时间:2026-06-13
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  • 收稿日期:2025-07-18
  • 修回日期:2025-12-21
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    重庆大学附属肿瘤医院神经肿瘤科,重庆 400030
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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