血检指标与肺癌骨转移相关性及进展
Correlation and Progression of Blood Test Indicators with Lung Cancer Bone Metastasis
摘要: 肺癌骨转移及其存在的骨相关事件会降低患者生活质量,影响预后,目前骨转移诊断主要依赖影像学及骨髓活检,但存在成本高、依从性差等限制,近年来,血液生物标志物因其便捷、可动态监测、易获取等优势被广泛使用,但存在特异性欠佳等问题,因此综合评估并制定临床个体化治疗和优化至关重要。本文系统阐述了肺癌骨转移的相关机制,总结了与骨转移相关血液生物标志物包括炎症相关指标(如中性粒细胞与淋巴细胞比率、系统性免疫炎症指数)、肿瘤标志物(CEA、CYFRA21-1、NSE)、血细胞参数(RDW、PLT)等,并分析其目前预测和诊断肺癌骨转移的潜力及背后机制,期许未来研究方向聚焦于构建多指标联合预测模型,推动血液生物标志物在肺癌骨转移早期筛查、预后评估及个体化治疗中的临床应用。
Abstract: Lung cancer bone metastasis and the accompanying skeletal-related events can reduce patients’ quality of life and affect prognosis. At present, the diagnosis of bone metastasis mainly relies on imaging and bone marrow biopsy, but these methods have limitations such as high cost and poor adherence. In recent years, blood-based biomarkers have been widely used due to their convenience, dynamic monitorability, and easy accessibility, but they often suffer from limited specificity. Therefore, comprehensive assessment and development of individualized clinical treatment and optimization are crucial. This article systematically explains the mechanisms related to lung cancer bone metastasis, and summarizes bone metastasis–related circulating biomarkers including inflammation-related indices (e.g., neutrophil-to-lymphocyte ratio, systemic inflammatory index), tumor markers (CEA, CYFRA21-1, NSE), blood cell parameters (RDW, PLT), etc., and analyzes their current potential for predicting and diagnosing lung cancer bone metastasis and the underlying mechanisms. Future research directions are expected to focus on constructing multi-parameter combined predictive models to promote the clinical application of blood-based biomarkers in early screening, prognostic assessment, and individualized therapy for lung cancer bone metastasis.
文章引用:蔡红叶, 张在其. 血检指标与肺癌骨转移相关性及进展[J]. 临床医学进展, 2025, 15(12): 2623-2631. https://doi.org/10.12677/acm.2025.15123696

1. 引言

肺癌是全球癌症相关死亡的主要原因之一,其发病率和死亡率均居高不下,导致了沉重的疾病负担。根据2022年我国癌症中心统计数据,2022年我国新增癌症患者482.47万,其中肺癌患者占106.06万人,癌症患者死亡数257.42万人,肺癌患者死亡数占73.33万人[1]。大多数肺癌患者在确诊时已处于晚期,5年生存率不到15%,生存时间不到18个月[2]。在此类病人的病程进展中多伴有远处转移,常见的转移部位包括颅内、骨、淋巴结等[3]。骨骼作为肺癌远处转移的常见目标,脊柱、骨盆等承重中轴骨尤为易感[4]。一旦骨骼被肿瘤细胞侵蚀,除了病理性骨折外,还会导致骨痛、脊髓和神经 压迫、钙盐和磷酸盐平衡紊乱等骨相关事件(skeletal related events, SREs),严重降低患者生活质量,同时加剧家庭的经济负担。有数据表明,肺癌患者骨转移的SREs发生率高达53.4%,如不积极治疗,中位生存时间仅为10个月[5]。尽管肺癌的早期诊疗水平有所提升,但在患者出现明显临床症状前的早期阶段检测病变是具有挑战性的。目前,诊断肿瘤骨转移的方法依赖于骨髓活检及影像学技术[6]。但传统影像学及病理检查可能无法检测小于0.4厘米的病变。且考虑到患者依从性以及这些操作侵入性强、过程复杂且费用高昂,其临床应用受到限制。而有文献报告指出,血清中某些因子的变化可能先于通过影像学检测到骨转移[7]。目前的一些血液生物学标志物包括肿瘤标志物(CEA、CYFRA21-1、NSE)以及骨代谢标志物(骨特异性碱性磷酸酶、N端骨钙素、抗酒石酸酸性磷酸酶5b)被认为与肺癌骨转移存在相关性。在临床工作中,通过对指标检测进行综合评估给肺癌骨转移高危人群的筛查提供了一些参考价值。

2. 肺癌骨转移相关机制

骨转移的发生是一个动态变化的过程。它与来自骨微环境的细胞因子相互作用和骨代谢调节因子的不平衡密切相关。根据骨转移的病变特征,大致分为3类:溶骨型,占骨转移的70%,以破坏正常骨质表现为主。成骨型,占骨转移的10%,骨转移后有异常的促成骨表现。混合型,指两种骨转移均出现的类型。肺癌骨转移的特征是破骨细胞活化导致的骨破坏,病理上以溶骨性病变居多。目前肺癌骨转移相关机制的阐述主要是“种子–土壤”学说及“归巢”机制,最终破坏“成骨–破骨平衡”形成“恶性循环”。

2.1. 肿瘤细胞的恶性转化与侵袭

肺癌骨转移的序幕始于原发灶内肿瘤细胞的“恶性转化与侵袭”。在这一过程中,癌细胞首先经历上皮–间质转化(EMT),其核心是E-钙黏蛋白等上皮标志物下调、而N-钙黏蛋白等间质标志物上调,使细胞间连接丧失,降低细胞间粘附,从而获得强大的迁徙与侵袭能力。同时包括Snail在内的一组转录因子在胚胎发生过程中协调EMT及相关的迁移过程[8]。随后,这些转化后的细胞通过分泌基质金属蛋白酶等水解酶“凿穿”组织屏障为自己开路。另外,肿瘤通过释放血管内皮生长因子等诱导生成结构异常的新生血管,最终癌细胞借助其获得的运动性和蛋白降解能力,穿过被破坏的血管基底膜进入循环系统,完成内渗,成为循环肿瘤细胞(CTCs)。

2.2. 循环存活与骨骼“归巢”

进入循环的肿瘤细胞需要抵抗失巢凋亡和免疫细胞的攻击,通过一些精密的“GPS导航系统”在骨骼微环境中“定居”。最经典的是CXCR4/CXCL12轴。肿瘤细胞表达相对受限的趋化因子和趋化因子受体谱系,利用并调控趋化因子系统,既促进局部肿瘤生长,也有利于远处转移[9]。CXCR4是一种趋化因子受体,作为恶性肿瘤中表达最广泛的受体,其在肿瘤生物学中的作用也研究得最为透彻[10]。CXCR4在肺癌细胞表面高表达,而趋化因子CXCL12作为CXCR4的唯一配体,在骨髓基质细胞,特别是成骨细胞,持续大量分泌,从而使血液中的CTCs感知到从骨髓血管内皮细胞间隙渗出的CXCL12浓度梯度,沿着浓度升高的方向被精准“趋化”至骨骼。其他趋化因子轴如CCL2/CCR2、RANKL/RANK轴在肺癌细胞中也发挥着作用,其相关具体机制目前还在进一步研究。

2.3. 肿瘤定植与微环境适应

骨微环境的组成包括骨细胞、免疫细胞和骨基质,在骨代谢以及肿瘤细胞播散、休眠和生长中起着关键作用[4]。肺癌细胞作为“种子”到达骨骼这一“土壤”后,其定植与微环境适应的过程始于肿瘤细胞休眠。骨损伤形成之前,在肿瘤患者疾病早期骨骼中通常可检测到DTC (游离肿瘤细胞) [11]。当其渗出到骨髓时,DTC要么经历凋亡,要么找到合适的生长生态位,或者进入单细胞休眠状态[12]。DTC进入G0期并降低代谢活性[13]。在这种单细胞休眠状态下,对化疗具有抵抗力,并且可以避免免疫检测[14] [15]。随后,休眠的肿瘤细胞并非被动等待,它们积极与骨骼微环境各种细胞“交流”,通过分泌各种因子改造其周围生态,共同构建一个免疫抑制且富含营养的“前转移龛”供肿瘤细胞生长。

2.4. 恶性循环的建立与骨破坏

肺癌骨转移中“恶性循环”的建立与骨破坏是一个自我放大的致命过程。为了克服肿瘤休眠,肿瘤细胞及周围细胞大量分泌促血管生成因子,通过创建新的血管或利用现有血管诱导骨重塑,同时肿瘤细胞分泌各种因子刺激破骨细胞,抑制成骨细胞,从而恶化骨形成和骨吸收的失衡[16]。其中PTHrP通过刺激骨骼微环境中的成骨细胞/基质细胞高表达RANKL,与破骨细胞前体上的受体RANK结合,强力激活破骨细胞,增强骨吸收同时引发异常骨溶解[17]。而骨基质的破坏将储存于其中的大量生长因子释放到微环境中,进一步刺激肿瘤细胞加速增殖并分泌更多PTHrPD等因子,此外,PTHrP也可抑制OPG的产生,促进骨转移[18]。从而正式引爆“恶性循环”导致骨破坏。

3. 与肺癌骨转移相关指标

3.1. 炎症相关因子

炎症反应在肿瘤微环境中至关重要,与肿瘤的发生、发展、侵袭和转移密切相关[19]。长期暴露于外源性炎症因子会增加癌症风险和进展[20] [21]。慢性炎症通过血管生成、细胞增殖和转移直接或间接地对肿瘤的发展具有促进作用,从而促进肺癌的进展[22]。近年的研究已经将“避免免疫摧毁”及“肿瘤促进性炎症”列为肿瘤的十大标志之一。

中性粒细胞与淋巴细胞比率(NLR)是全系统炎症的一个指标,中性粒细胞是外周血中白细胞含量最丰富的类型,作为人体的主要免疫细胞,它在保护机体同时,也在避免微生物侵袭人体、吞噬病原体。在人体的防御系统中起着重要作用[23]。然而在癌症中,中性粒细胞的作用呈现出复杂性,正如Lehman等人的一项研究指出,肿瘤微环境中的活化中性粒细胞具有双重功能:一方面它们依靠细胞毒性作用杀伤肿瘤细胞;另一方面,又能通过刺激血管生成等途径促进肿瘤进展和转移[23]。因此,肿瘤相关中性粒细胞在一些研究中被认为与许多肿瘤复发和预后以及生存率存在相关性[24]。淋巴细胞是机体的免疫反应细胞,能识别并攻击癌细胞。并在肿瘤微环境中相互作用,影响肿瘤的生长和转移。肿瘤浸润的淋巴细胞(TIL)通常被认为是抗肿瘤反应的标志,包括T细胞、B细胞、自然杀伤(NK)细胞和树突状细胞,每种在肿瘤微环境中都有不同的作用[25]。研究表明,TIL在肺癌治疗和预后中的作用越来越受到认可。NLR可以从全血细胞计数中获得,反映了机体炎症和免疫反应的平衡,其不平衡驱动肿瘤进展和转移[26]。NLR的升高意味着中性粒细胞活性增强,通过分泌趋化因子或促进血管生成,进一步促进肿瘤细胞向骨骼转移。同时淋巴细胞的减少将导致免疫监视功能下降,使癌细胞更易逃避免疫攻击,从而促进转移发生[27]。He等人在近期研究中发现显著升高的NLR被证实是骨转移的独立危险因素,表明其在肺癌骨转移的预测及诊断中具有重要价值[26]

另外,系统性免疫炎症指数(SII)也是一种反映体内的整体炎症状态和免疫反应的指标,近年来被认为是多种实体瘤的预后因素[28] [29]。其计算方法是将血小板乘以中性粒细胞的绝对值,再除以淋巴细胞的总价值[30]。NLR和SII可以预测患者对免疫治疗的反应和各种晚期实体瘤的生存率[31] [32]。有文献提出SII水平升高表明肺癌患者骨转移的可能性更高[26]。目前认为,其潜在的机制可能是作为反映系统性炎症状态的指标,SII通过促进炎症微环境、抑制免疫活性、增强肿瘤细胞的迁移及浸润同时改变骨代谢平衡,从而促进肿瘤在骨髓或骨骼中转移。

3.2. 肿瘤标志物

肿瘤标志物由肿瘤细胞产生并分泌到血液、体液和组织中,在肿瘤的诊断、治疗监测和预后评估中发挥着重要作用。常用的标志物如癌胚抗原(CEA)、细胞角蛋白19片段(CYFRA 21-1)、神经元特异性烯醇酸酶(NSE)等,均已被证明与肺癌的存在及其进展相关。同时CEA、CYFRA 21-1的升高与肿瘤的转移有显著相关性[32]

CEA是一种糖蛋白,通常在肿瘤细胞(尤其是腺癌)中上调表达。其升高常见于多系统肿瘤,包括肺癌。由于特异性不高,在临床实践中常联合其他肿瘤标志物综合判断。肺癌细胞释放CEA进入血液循环,因此CEA升高可提示机体肿瘤负荷。有研究显示,CEA水平与肺癌患者骨转移的发生风险相关,高水平的CEA可能反映了肿瘤的侵袭性和转移能力,提示病人有更强的骨转移倾向[33]

CYFRA21-1 (细胞角蛋白19片段)主要分布于肿瘤上皮细胞质,在鳞状细胞癌中高表达[34]。研究表明作为肺癌患者生存的独立预后因素,其水平升高反应肺癌患者生存期可能缩短,同时与远处转移密切相关[35] [36]。另外,血清CYFRA 21-1在预测肺癌患者术后复发及化疗后进展方面显示出良好的敏感性和特异性[37]。更有进一步研究表明CYFRA21-1诊断肺癌骨转移的敏感度和特异性分别为48.8%和76.6% [32]。因此在联合诊断时可予以参考。

NSE (神经元特异烯醇化酶)是一种细胞特异性同工酶,主要存在于神经元及神经内分泌细胞中。高浓度血清NSE是神经内分泌肿瘤的特异性标志物[38]。随着恶性肿瘤增殖,体液中NSE的水平升高,尤其在神经内分泌肿瘤中显著[39]。在肺癌不同病理类型中,NSE是小细胞肺癌(SCLC)的首选标志物,肿瘤细胞合成并异位分泌多种生物活性物质,包括酶、肽类激素、激素前体,这种异常分泌活性是NSE的变化的直接原因,一般NSE在SCLC中晚期变化明显[40]。一些研究表明,NSE与肿瘤生长也存在关联,因此结合临床观察和指标监测可用来预测肺癌的转移和复发[41]

总体来说,关注这些标志物的动态变化是管理肺癌骨转移病人的重要辅助手段,能为病情监测和治疗决策提供依据。

3.3. 组织学类型

肺癌的组织学类型对其生物学行为和预后有着显著影响,甚至肺癌的转移模式可以通过病理组织学特征来预测。肺癌可分为非小细胞肺癌(NSCLC)和SCLC,前者包括腺癌、鳞状细胞癌和大细胞癌等,后者则表现出高度侵袭性和快速转移特征。在肺癌骨转移中,不同病理类型所占比不同,一项法国多中心的前瞻性研究结果提示在547例肺癌骨转移患者中,腺癌占57.8%,鳞癌占15.3%,小细胞肺癌9%,其他类型肺癌14%~18% [42]。虽然背后的具体机制尚不明确,目前的一些观点主要偏向于腺癌多为周围型,起源于肺组织周边呈浸润性生长,更易进入血管淋巴管内,最终导致远处转移[43]。同时肺腺癌易局部浸润侵犯胸椎及肋骨[44] [45]。其次,腺癌相较其他类型恶性程度低,生存期也相对延长,某种程度提高了骨转移的检出率。关于不同组织学类型肺癌患者血清标志物表达,目前的研究相对欠缺,但有一些观点认为不同类型肺癌患者的血清标志物水平差异性可能与转移能力相关。而生物标志物的表达和细胞信号通路活性可能是影响转移能力的重要因素。

3.4. 血细胞相关指标

长期以来,血小板是常见的反映凝血的指标,近年研究逐渐揭示,它在多种癌症,如结肠癌、肺癌、卵巢癌和胃癌发生及发展中扮演不容忽视的角色[46] [47]。在多数癌症患者中,增多被持续活化的血小板能通过释放生长因子、代谢产物和microRNA等,促使循环肿瘤细胞发生转化。进而推动癌症的远处转移[47]。Zhang等人纳入308例肺腺癌患者,通过分析结果得出当PLT > 300 × 109/L时,骨转移的发生率提升1.463倍,表明血小板是肺癌骨转移的独立危险因素[48]。同时,血小板通过结合肿瘤细胞产生癌栓,从而提高癌细胞的粘附和运动功能,增加癌细胞扩散和转移的概率[5]。另外,当患者血小板升高时,静脉血栓形成以及血行转移的概率均会增加。因此,在临床工作中,对于伴有血小板增多的肺癌患者应定期体检,及早发现转移灶,警惕血栓形成,尽早进行针对性治疗。

红细胞分布宽度(RDW)是反映红细胞大小变化的客观评价指标。通常用于诊断和区分贫血类型,最近研究发现RDW与肿瘤之间也存在关联,一项回顾性研究通过430例肺癌患者和158例健康人(对照组)的临床资料分析得出RDW是肺癌的独立预测因子[49]。基于此,wang等通过荟萃分析,证实治疗前RDW与肺癌患者总生存期(OS)和无病生存期(DFS)显著相关[50]。然而,目前对于这两者联系的确切机制尚未完全阐明。大多数观点主要集中以下几点,首先是癌症介导的炎症微环境扰乱铁代谢并抑制促红细胞生成素产生,导致骨髓中未成熟红细胞释放从而RDW升高[51]。此外,RDW的升高意味着红细胞大小不同和功能受损,影响氧气输送,诱发缺氧微环境,进一步刺激体内血管内皮生长因子(VEGF)和缺氧诱导因子(hypoxia-inducible factor, HIF)表达,加速肿瘤新生血管的形成及进展[52] [53]。癌症的恶病质状态常导致铁、叶酸和维生素B12等造血原料缺乏,直接影响红细胞生成,进而影响体内RDW水平[54]。因此,RDW可被视为一个综合体现机体炎症状态、缺氧程度以及营养状态的整合性生物标志物。目前研究并未指出RDW水平较高的患者易发生骨转移的机制,其可能与肺癌侵犯骨髓组织,影响造血导致红系增殖障碍相关。

4. 结语与展望

对于肺癌的患者,目前临床上采取多学科综合治疗(MDT)模式,为患者制定科学合理的个体化方案,有效延缓肺癌进展及减少骨转移等并发症出现的风险,尽管有研究探讨肺癌的组织学类型与转移的关系以及血液学指标的临床应用,但目前这两者如何共同影响癌症骨转移的相关性研究尚未系统化,需要大量的临床数据验证。如何理解并且运用这些血检指标?总体来说联合检测优于单一指标:单一指标的敏感性和特异性往往有限。研究表明,多个指标联合检测能显著提升诊断的准确性。例如,CEA、CYFRA21-1与ALP联合[55],或钙磷代谢、骨转换标志物等多个血清指标构建的机器学习模型,其诊断价值远高于单一指标[56]。另外还需要关注动态变化趋势:对于肺癌患者,定期复查并观察相关血检指标的动态变化比单次的绝对值更有意义。如果CEA、BAP、β-CTx等指标在随访中持续升高,即使影像学尚未发现问题,也需高度警惕骨转移的可能,并及时进行进一步检查[57]。未来,随着现在液体活检等技术的深入应用,血液学指标必将和影像学及分子分型更加紧密地联系在一起,共同推动肺癌骨转移的精准诊疗,最终为改善患者预后、提高生活质量开辟新路径。

NOTES

*通讯作者。

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