术前免疫炎症指标及AFP对HCC肝切除术后 预后价值的研究现状
Research Status of Preoperative Immune-Inflammatory Markers and Alpha-Fetoprotein in Predicting Prognosis after Hepatectomy for Hepatocellular Carcinoma
摘要: 肝细胞癌(HCC)是全球癌症相关死亡的主要病因之一,早期诊断与精准预后评估对改善患者生存至关重要。近年来,术前免疫炎症指标与甲胎蛋白(AFP)在HCC患者预后评估中的价值日益受到关注。这些生物标志物不仅能反映机体全身性炎症状态,亦与肿瘤生物学行为及预后密切相关。现有研究表明,术前免疫炎症指标如中性粒细胞–淋巴细胞比值(NLR)、血小板–淋巴细胞比值(PLR)、全身免疫炎症指数(SII)等,与HCC患者术后生存率及复发风险显著相关。同时,AFP作为经典的肝癌血清标志物,其水平变化亦被证实与患者预后具有显著关联。然而,术前免疫炎症指标与AFP联合应用于术后预后预测的具体机制尚待进一步阐明。本文综述术前免疫炎症指标及AFP在HCC肝切除术后预后评估中的最新研究进展,探讨其临床转化潜力,以期为HCC术后个体化治疗策略提供依据。
Abstract: Hepatocellular carcinoma (HCC) represents one of the leading causes of cancer-related mortality worldwide. Early diagnosis and precise prognostic evaluation are crucial for improving patient survival. In recent years, the prognostic value of preoperative immune-inflammatory markers and alpha-fetoprotein (AFP) in HCC patients has garnered increasing attention. These biomarkers not only reflect the systemic inflammatory status of the host but are also closely associated with tumor biology and prognosis. Existing studies indicate that preoperative immune-inflammatory markers, such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII), are significantly correlated with postoperative survival rates and recurrence risk in HCC patients. Concurrently, AFP, a classic serum tumor marker for liver cancer, has also been confirmed to have a significant association with patient prognosis. However, the specific mechanisms underlying the combined application of preoperative immune-inflammatory markers and AFP for postoperative prognosis prediction require further elucidation. This article reviews the latest research progress on preoperative immune-inflammatory markers and AFP in prognostic assessment following hepatectomy for HCC, explores their potential for clinical translation, and aims to provide a basis for individualized postoperative treatment strategies for HCC.
文章引用:邹建, 牛超, 白亦焘, 王宁, 唐继红. 术前免疫炎症指标及AFP对HCC肝切除术后 预后价值的研究现状[J]. 临床医学进展, 2026, 16(3): 2692-2700. https://doi.org/10.12677/acm.2026.1631069

1. 前言

原发性肝癌是全世界第七大发病率的癌症,也是第四大癌症死亡原因,大多国家的肝癌发病率正在逐步上升[1]。原发性肝癌(Primary Liver Cancer, PLC)是全球范围内严重威胁人类健康的恶性肿瘤,其主要病理类型为肝细胞癌(Hepatocellular Carcinoma, HCC),约占所有病例的75%至90% [2]。该疾病的发生发展是一个多因素、多步骤的复杂过程,通常根植于慢性肝脏损伤所导致的肝硬化微环境之中,涉及病毒性感染、代谢紊乱、酒精滥用以及遗传易感性等多种致病因素的长期作用。从发病机制上看,慢性乙型肝炎病毒(HBV)和丙型肝炎病毒(HCV)感染是全球范围内最主要的危险因素,尤其在亚洲和非洲地区,HBV感染与HCC的发生具有明确的因果关系[3]。HCC恶性程度较高,尽管目前已经存在多种针对HCC的治疗方案,包括手术、射频消融、TACE、肝移植等。对于早期HCC来说,肝切除术是治疗肝细胞癌最有效的根治性治疗之一,但手术后的预后较差,5年内复发率高达70%,肝内复发率60%~80% [4]。因此,HCC手术治疗后的预后评估对指导患者的进一步治疗及延长生存期有着重要意义。

越来越多的证据表明,免疫与炎症反应在肿瘤进展和转移中发挥关键作用,炎症微环境是肿瘤发生发展的核心组成部分[5]。多数HCC发生于慢性炎症背景下的肝硬化,炎症与肿瘤之间的相互作用尤为显著。全身性炎症状态不仅参与肿瘤发生发展,亦对HCC患者预后具有提示作用。因此,反映机体炎症状态的循环生物标志物被广泛用于评估HCC预后。甲胎蛋白(AFP)作为HCC早期筛查与诊断的经典血清标志物,亦被用于疗效评价与复发监测[6]。本文旨在综述术前免疫炎症指标及AFP在HCC肝切除术后预后预测中的研究现状与进展,以期为临床实践提供参考。

2. 肝细胞癌的肿瘤微环境

慢性炎症是HCC发生的重要驱动因素,大多数HCC都源于慢性炎症和肝损伤的环境[7]。HCC的肿瘤微环境(Tumor Microenvironment, TME)是一个高度复杂且动态的生态系统,在HCC的发生、发展、侵袭、转移以及对治疗的抵抗中扮演着至关重要的角色[8]-[10]。TME不仅是肿瘤细胞的物理支撑结构,更是肿瘤细胞与周围宿主细胞、细胞外基质(ECM)和各种信号分子之间进行复杂相互作用的“战场”,这些相互作用深刻地影响着肿瘤的生物学行为和患者的预后[8] [9] [11]

HCC的TME由多种细胞成分和非细胞成分构成,这些成分协同作用,共同塑造了肿瘤的恶性表型[8] [10] [12] [13]。细胞成分包括:肿瘤细胞、免疫细胞、基质细胞、肝星状细胞(HSCs)、内皮细胞等。HCC的肿瘤细胞本身是TME的核心组成部分,它们通过分泌细胞因子、趋化因子和生长因子,积极重塑周围微环境以促进自身生长和免疫逃逸[12] [13]。TME中浸润着多种免疫细胞,包括肿瘤相关巨噬细胞(TAMs)、调节性T细胞(Tregs)、髓源性抑制细胞(MDSCs)、细胞毒性T淋巴细胞(CTLs)、自然杀伤(NK)细胞和树突状细胞(DCs)等[13]-[15]。其中,TAMs通常是HCCTME中最丰富的免疫细胞,并且主要表现为M2型巨噬细胞,具有促进肿瘤生长、血管生成、免疫抑制、肿瘤侵袭和转移以及治疗抵抗等作用[8]。Tregs和MDSCs也通过抑制抗肿瘤免疫反应,促进肿瘤免疫逃逸[13] [14]。癌相关成纤维细胞(CAFs)是TME中重要的基质细胞,通过分泌细胞外基质蛋白、生长因子和细胞因子,促进HCC的增殖、侵袭、转移、血管生成、免疫抑制和治疗抵抗[16]。CAFs能够被肿瘤细胞招募,并大量分泌I型胶原蛋白,激活赖氨酰氧化酶(LOX),增加细胞外基质的交联和硬度[17]。这种基质硬度的增加可以通过整合素–局灶粘附激酶(Integrin-FAK)信号通路激活YAP/TAZ转录共激活因子,进一步促进肿瘤细胞的增殖和抑制凋亡[18]。HSCs在肝损伤和纤维化中发挥关键作用,在HCCTME中活化的HSCs转变为肌成纤维细胞样细胞,成为CAFs的主要来源之一,并通过分泌ECM和旁分泌因子,促进肿瘤生长和免疫抑制[19]。内皮细胞形成肿瘤血管,支持肿瘤的快速生长。非细胞成分包括ECM、各种信号分子以及缺氧环境等。ECM由胶原蛋白、蛋白聚糖、糖胺聚糖等组成,在HCCTME中通常发生重塑,变得异常硬化和致密,这不仅为肿瘤细胞提供了物理支架,也通过力学信号传导影响肿瘤细胞行为,促进肿瘤进展[20]。各种细胞因子(如IL-6、TGF-β)、趋化因子、生长因子(如VEGF)和非编码RNA等,它们在细胞间通信中起关键作用,调控肿瘤进展、免疫抑制和血管生成[13] [14]。肿瘤内部的快速增殖和血管生成不足导致局部缺氧,缺氧环境通过诱导缺氧诱导因子(HIF-1α)稳定,促进肿瘤细胞的糖酵解、血管生成和免疫抑制[19]

HCC的发生发展、复发转移都依赖于其微环境进行,即使行根治性手术治疗,这种微环境也容易残留并促进新生肿瘤的发生,导致早期复发。而TME的存在也为炎症相关肿瘤包括HCC的预后提供了更多、更便捷、更有效的预测方向。

3. 相关免疫炎症指标

近年来各种炎症指标被提出,用来反应全身炎症,并可以用来预测HCC手术后的预后情况。包括2014年由Hu等人提出的全身免疫炎症指数(SII),是预测肝癌患者生存和复发的独立危险因素[21];2016年由Qi等人提出的全身炎症反应指数(SIRI) [22],虽提出是用来预测胰腺癌患者化疗后生存期的指标,但经过研究发现,也可作为HCC手术后的预后指标[23];2020年由Fucà G等提出的泛免疫炎症值(PIV) [24],它在特定类型的恶性肿瘤中已证明具有显著的预后生物标志物价值,包括结肠癌和乳腺癌[25]。除此之外还有许多炎症性血液指标,如中性粒细胞–淋巴细胞比(NLR)、血小板–淋巴细胞比(PLR)和淋巴细胞–单核细胞比(LMR),都是不同癌症类型的重要预后标志[23]。研究证明高NLR与HCC预后或复发显著相关,表明NLR是HCC患者预后或复发的良好预测因子[26];PLR在局限性和转移性HCC中都可以作为不良预后因子[27];LMR是肝细胞癌不良预后的独立危险因素[28]

3.1. 中性粒细胞与淋巴细胞比值(NLR)

NLR定义为外周血中性粒细胞计数与淋巴细胞计数的比值。

计算公式为: NLR= ( × 10 9 /L ) ( × 10 9 /L )

该指标整合了代表非特异性免疫的中性粒细胞与代表适应性细胞免疫的淋巴细胞信息,综合反映疾病状态下两者的动态平衡。NLR升高常提示机体抗肿瘤免疫功能减弱、炎症反应增强,与肿瘤进展及不良预后相关[29]

3.2. 血小板与淋巴细胞比值(PLR)

PLR定义为外周血血小板计数与淋巴细胞计数的比值,

计算公式为: PLR= ( × 10 9 /L ) ( × 10 9 /L )

PLR是一种反映炎症与血液凝集状态的综合性指标。高PLR通常提示机体处于慢性炎症状态,肿瘤微环境有利于肿瘤生长和转移,与多种肿瘤的不良预后相关[30]

3.3. 淋巴细胞与单核细胞比值(LMR)

LMR是一种基于外周血常规检测计算得出的炎症性生物标志物,近年来在多种疾病的预后评估中展现出重要价值。

计算公式为: LMR= ( × 10 9 /L ) ( × 10 9 /L )

它反映了机体免疫系统中适应性免疫与先天性免疫之间的动态平衡状态[31]。在肝细胞癌中,多项研究均一致显示低LMR与更差的临床结局相关[32] [33]

3.4. 全身免疫炎症指数(SII)

计算方式: SII=( × 10 9 /L )× ( × 10 9 /L ) ( × 10 9 /L )

作为一项基于外周血淋巴细胞、中性粒细胞和血小板计数的综合指标,SII对肿瘤复发和转移的预测价值可能通过这三种细胞的功能及其与循环肿瘤细胞(CTCs)的密切关系来阐明,CTCs在术后复发和转移的启动中起着重要作用。术前SII升高表明患者处于炎症状态和免疫反应较弱[21]。相较于NLR和PLR等单一或双因素比值指标,SII通过同时纳入血小板这一参与凝血和炎症过程的重要成分,能更全面地反映机体促炎与抗炎通路的失衡状态。一项纳入268例患者的队列研究发现,SII是预测免疫治疗疗效的独立因子,高SII组患者的中位总生存期(OS)仅为14.2个月,远低于低SII组的31.7个月(HR = 2.84, 95%CI: 1.92~4.20) [34]。另一项针对肝切除术后患者的多中心研究证实,SII对无复发生存期(RFS)的预测效能优于传统指标中性粒细胞/淋巴细胞比值(NLR)和血小板/淋巴细胞比值(PLR),其曲线下面积(AUC)在训练集和验证集中分别达0.72和0.70 (P < 0.05 vs. NLR/PLR) [21]

3.5. 全身炎症反应指数(SIRI)

计算方式: SIRI=( × 10 9 /L )× ( × 10 9 /L ) ( × 10 9 /L )

全身炎症反应指数是一种基于外周血中性粒细胞、单核细胞和淋巴细胞计数计算的炎症指标,其核心在于反映促炎细胞与抗炎细胞之间的平衡。它通过整合中性粒细胞、单核细胞和淋巴细胞的动态变化,能够较全面地评估机体的全身炎症反应程度[35]。中性粒细胞在急性炎症中快速升高,单核细胞参与慢性炎症或组织修复过程,而淋巴细胞减少通常提示免疫功能抑制。因此,SIRI升高意味着促炎细胞占优势,抗炎细胞功能相对不足,反映了机体免疫炎症网络的失衡。目前的研究发现SIRI与肝细胞癌的预后有明显的关系[23]。一项纳入360例患者的研究证实SIRI是根治性切除术后HCC患者1年RFS的独立预后因素。建立的列线图在预测OS、RFS、1年RFS和2年RFS时分别获得了较好的一致性指数,分别为0.772 (95%CI: 0.730~0.814)、0.774 (95%CI: 0.734~0.815)、0.809 (95%CI: 0.766~0.852)和0.756 (95%CI: 0.696~0.816) [36]

SII与SIRI相比,在HCC领域,虽然两者都显示出重要的预后价值,但目前尚缺乏前瞻性多中心研究直接比较SII和SIRI在HCC患者中的预测效能。SII主要基于血小板、中性粒细胞和淋巴细胞计数,而SIRI则以中性粒细胞、单核细胞和淋巴细胞计数为基础。SII同时囊括了代表促炎和促转移潜力的中性粒细胞与血小板,以及代表抗肿瘤免疫潜力的淋巴细胞。高SII值精准地捕捉了“促炎力量增强”与“免疫监视力量削弱”并存的失衡状态,这种状态是肿瘤成功实现免疫逃逸和远处扩散的系统性体现。而SIRI侧重于髓系来源的炎症细胞(中性粒细胞和单核细胞)与淋巴细胞的比值。高SIRI反映了髓系免疫抑制占主导的格局,这与肿瘤相关的骨髓造血重塑和免疫抑制密切相关。

综上所述,术前免疫炎症指数是一类非侵入性、成本低廉且易于获取的预后生物标志物。它们从宿主免疫–炎症反应的独特视角,补充了传统TNM分期和AFP评估的不足,为HCC患者的个体化风险分层和治疗决策提供了重要依据。

4. 甲胎蛋白

甲胎蛋白(AFP)是HCC最常用的血清肿瘤标志物之一。AFP是一种典型的“癌胚抗原”,在胎儿发育期间由肝脏和卵黄囊大量合成,出生后迅速下降至极低水平。在成年个体中,当肝细胞发生恶性转化并出现去分化现象时,会重新激活这一原本沉默的基因程序,导致AFP再度分泌入血[37]

研究表明,约60%~70%的HCC患者血清AFP水平升高,通常以20 ng/mL或400 ng/mL作为临床常用阈值进行风险分层[38]。然而,其诊断价值受到敏感性和特异性的双重限制:一方面,并非所有HCC患者均表现为AFP升高,部分分化良好型或某些特殊分子亚型的HCC可呈现阴性状态,此类患者占比可达一定比例;另一方面,慢性病毒性肝炎、肝硬化等良性肝病活动期亦可引起AFP轻度至中度上升,造成假阳性结果。AFP的升高通常与晚期肿瘤、较大的肿瘤体积以及更差的预后相关,对于接受肝切除术的HCC患者,术前AFP水平可以作为预后因素[39]

4.1. 术前AFP水平

术前AFP水平是预测HCC患者肝切除术后复发和生存的重要指标,高AFP水平通常预示着肿瘤分化差、微血管侵犯风险高以及术后早期复发率增加。即使在巴塞罗那临床肝癌(BCLC) 0/A期的早期HCC患者中,高AFP水平也与较差的预后相关[40]。一项多中心研究表明,术前AFP高水平与术后复发和总生存率较差独立相关[6]

4.2. 术后AFP不完全转化与动态变化

除了术前AFP水平,术后AFP的变化模式也具有重要的预后意义。血清AFP不完全转化(serological incomplete conversion, SIC),即术后AFP水平未能降至正常或持续高水平,被认为是术后复发和预后不良的良好预测因子[41]。AFP比率,即术前与术后AFP水平的比值,也被用于评估HCC患者的预后,AFP比率低(术后AFP下降不显著)的患者往往预后较差[42]。对于AFP阴性HCC患者,AFP比率同样具有预测价值[43]

一项针对600名接受肝切除术的AFP阴性HCC患者进行的回顾性分析发现,AFP比率(定义为术前1周AFP水平与术后20~40天AFP水平之比)是一个独立的预后因素。该研究表明,AFP比率较高的患者其总体生存期(OS)和无复发生存期(RFS)显著优于比率较低的患者[44]。这一发现提示,即使基础AFP水平低于常规诊断阈值(通常为<20 ng/mL或<25 ng/mL),肿瘤组织内可能仍存在微弱的AFP合成能力,而手术成功切除肿瘤后,这种微弱的合成源被彻底清除,导致AFP水平进一步下降,从而形成一个较高的比率。因此,一个较高的AFP比率可能间接反映了肿瘤负荷的完全清除和根治性手术的成功。反之,一个较低的比率则可能意味着术后仍有残留的肿瘤组织持续分泌微量AFP,或者肿瘤本身具有更强的侵袭性,导致早期复发。

4.3. AFP与其他标志物的联合应用

尽管AFP在HCC诊疗中应用广泛,但其仍存在假阳性和假阴性问题,临床应用中需加以识别和警惕。假阳性情况:AFP升高并非HCC所独有,多种良性疾病也可导致AFP水平上升。假阴性情况:部分HCC患者AFP水平可始终正常或仅轻度升高。

鉴于AFP的假阳性和假阴性问题,临床实践中常采用联合检测策略以提高诊断的准确性和预后评估的可靠性。AFP与其他肿瘤标志物或炎症指标联合应用可以提高预后预测的准确性。

4.3.1. AFP与PIVKA-II (异常凝血酶原)

PIVKA-II是另一个重要的HCC标志物。其在HCC的发生发展中具有重要的临床意义,现已成为HCC诊断、预后评估和治疗监测中的关键血清学标志物之一[45]。AFP和PIVKA-II的联合检测或术后不完全转化状态,可以提供更准确的HCC复发和生存预测[6]

4.3.2. AFP与CA19-9 (糖类抗原19-9)

CA19-9是一种广泛应用于临床的肿瘤标志物,该标志物在健康人群中血清水平通常较低,但在多种消化系统恶性肿瘤中显著升高,尤其在胰腺导管腺癌(PDAC)中具有重要的诊断与预后评估价值。一项研究评估了术前血清AFP和CA19-9联合预测HCC患者肝切除术后预后的价值,联合指标与HCC术后的不良预后显著相关[46]

4.3.3. AFP与CRP (C反应蛋白)

在癌症患者中,系统性炎症状态与肿瘤进展、恶病质和不良预后密切相关,CRP可作为肿瘤负荷和生存期的预后标志物。AFP与CRP的联合升高,对HCC患者的预后具有重要意义[47]

5. 总结与展望

术前免疫炎症指标与AFP对HCC肝切除术后预后具有显著的独立及联合预测价值。在免疫炎症指标方面,NLR、PLR、LMR、SII及SIRI均被证实是HCC患者术后预后的独立危险因素,其中SII与SIRI作为更综合性的炎症指标,在预后评估中展现独特优势。AFP作为经典肿瘤标志物,其术前水平是HCC术后预后的重要预测因子。

在HCC术后预后评估中,术前免疫炎症指标与AFP的重要性日益凸显。免疫炎症反应在肿瘤发生发展中起关键作用,而AFP作为传统标志物亦显示出良好应用潜力。探索两者联合应用,可能为HCC个体化预后评估提供更精确的工具。尽管当前研究仍存在一定局限性,但随着标准化推进、联合模型优化及机制探索的深入,这些简便、经济、易获取的指标有望在HCC个体化精准诊疗中发挥日益重要的作用。

未来研究可进一步探索上述指标与临床病理特征、影像学表现及分子标志物的整合,开发更为全面、精准的预后预测模型。

NOTES

*共同第一作者。

#通讯作者。

参考文献

[1] Petrick, J.L. and McGlynn, K.A. (2019) The Changing Epidemiology of Primary Liver Cancer. Current Epidemiology Reports, 6, 104-111. [Google Scholar] [CrossRef] [PubMed]
[2] Galle, P.R., Forner, A., Llovet, J.M., Mazzaferro, V., Piscaglia, F., Raoul, J., et al. (2018) EASL Clinical Practice Guidelines: Management of Hepatocellular Carcinoma. Journal of Hepatology, 69, 182-236. [Google Scholar] [CrossRef] [PubMed]
[3] Yip, T.C. and Wong, G.L. (2024) Transforming the Landscape of Liver Cancer Detection and Care. Nature Reviews Gastroenterology & Hepatology, 22, 86-87. [Google Scholar] [CrossRef] [PubMed]
[4] Xiang, Z., Deng, J., Liang, H., Jiang, M., Liang, Y., Liu, Z., et al. (2025) Artificial Intelligence for the Prediction of Posthepatectomy Recurrence in Hepatocellular Carcinoma: A Systematic Review and Meta-analysis. Annals of Medicine, 57, Article ID: 2568118. [Google Scholar] [CrossRef
[5] Grivennikov, S.I., Greten, F.R. and Karin, M. (2010) Immunity, Inflammation, and Cancer. Cell, 140, 883-899. [Google Scholar] [CrossRef] [PubMed]
[6] Wang, M., Qian, G., Xiao, H., Liu, X., Sun, L., Chen, Z., et al. (2024) Prognostic Significance of Postoperative Serological Incomplete Conversion of AFP and PIVKA-II after Hepatic Resection for Hepatocellular Carcinoma: A Multicenter Analysis of 1755 Patients. The Oncologist, 29, e1723-e1733. [Google Scholar] [CrossRef] [PubMed]
[7] Chen, R., Yen, C., Lin, Y., Wang, J., Tasi, T., Huang, Y., et al. (2021) CPAP Enhances and Maintains Chronic Inflammation in Hepatocytes to Promote Hepatocarcinogenesis. Cell Death & Disease, 12, Article No. 983. [Google Scholar] [CrossRef] [PubMed]
[8] Tahmasebi Birgani, M. and Carloni, V. (2017) Tumor Microenvironment, a Paradigm in Hepatocellular Carcinoma Progression and Therapy. International Journal of Molecular Sciences, 18, Article 405. [Google Scholar] [CrossRef] [PubMed]
[9] 杜义江, 肖长义. 微环境与肝癌发病机制的研究进展[J]. 基础医学与临床, 2015, 35(2): 248-252.
[10] Santhakumar, C., Gane, E.J., Liu, K. and McCaughan, G.W. (2020) Current Perspectives on the Tumor Microenvironment in Hepatocellular Carcinoma. Hepatology International, 14, 947-957. [Google Scholar] [CrossRef] [PubMed]
[11] Chen, W., Tan, M., Zhang, H., Gao, T., Ren, J., Cheng, S., et al. (2024) Signaling Molecules in the Microenvironment of Hepatocellular Carcinoma. Functional & Integrative Genomics, 24, Article No. 146. [Google Scholar] [CrossRef] [PubMed]
[12] Galasso, L., Cerrito, L., Maccauro, V., Termite, F., Ainora, M.E., Gasbarrini, A., et al. (2024) Hepatocellular Carcinoma and the Multifaceted Relationship with Its Microenvironment: Attacking the Hepatocellular Carcinoma Defensive Fortress. Cancers, 16, Article 1837. [Google Scholar] [CrossRef] [PubMed]
[13] Xie, D., Liu, Y., Xu, F., Dang, Z., Li, M., Zhang, Q., et al. (2025) Immune Microenvironment and Immunotherapy in Hepatocellular Carcinoma: Mechanisms and Advances. Frontiers in Immunology, 16, Article 1581098. [Google Scholar] [CrossRef] [PubMed]
[14] Zarlashat, Y., Ghaffar, A., Guerra, F. and Picca, A. (2025) Immunological Landscape and Molecular Therapeutic Targets of the Tumor Microenvironment in Hepatocellular Carcinoma. International Journal of Molecular Sciences, 26, Article 7836. [Google Scholar] [CrossRef
[15] Chen, Y., Zhou, Y., Yan, Z., Tong, P., Xia, Q. and He, K. (2023) Effect of Infiltrating Immune Cells in Tumor Microenvironment on Metastasis of Hepatocellular Carcinoma. Cellular Oncology, 46, 1595-1604. [Google Scholar] [CrossRef] [PubMed]
[16] Zhang, J., Gu, C., Song, Q., Zhu, M., Xu, Y., Xiao, M., et al. (2020) Identifying Cancer-Associated Fibroblasts as Emerging Targets for Hepatocellular Carcinoma. Cell & Bioscience, 10, Article No. 127. [Google Scholar] [CrossRef] [PubMed]
[17] Minini, M. and Fouassier, L. (2023) Cancer-Associated Fibroblasts and Extracellular Matrix: Therapeutical Strategies for Modulating the Cholangiocarcinoma Microenvironment. Current Oncology, 30, 4185-4196. [Google Scholar] [CrossRef] [PubMed]
[18] Teo, K., Abeysekera, K.W.M., Adams, L., Aigner, E., Anstee, Q.M., Banales, J.M., et al. (2021) Rs641738C > T near MBOAT7 Is Associated with Liver Fat, ALT and Fibrosis in NAFLD: A Meta-Analysis. Journal of Hepatology, 74, 20-30. [Google Scholar] [CrossRef] [PubMed]
[19] Altalbawy, F.M.A., Zwamel, A.H., Sanghvi, G., Roopashree, R., Kumari, M., Kashyap, A., et al. (2025) Interactions in Hepatic Tumor Microenvironment: Potential Targets and Modulations for Effective Therapy. PathologyResearch and Practice, 272, Article ID: 156074. [Google Scholar] [CrossRef] [PubMed]
[20] Su, X., Yan, X. and Zhang, H. (2025) The Tumor Microenvironment in Hepatocellular Carcinoma: Mechanistic Insights and Therapeutic Potential of Traditional Chinese Medicine. Molecular Cancer, 24, Article No. 173. [Google Scholar] [CrossRef] [PubMed]
[21] Hu, B., Yang, X., Xu, Y., Sun, Y., Sun, C., Guo, W., et al. (2014) Systemic Immune-Inflammation Index Predicts Prognosis of Patients after Curative Resection for Hepatocellular Carcinoma. Clinical Cancer Research, 20, 6212-6222. [Google Scholar] [CrossRef] [PubMed]
[22] Qi, Q., Zhuang, L., Shen, Y., Geng, Y., Yu, S., Chen, H., et al. (2016) A Novel Systemic Inflammation Response Index (SIRI) for Predicting the Survival of Patients with Pancreatic Cancer after Chemotherapy. Cancer, 122, 2158-2167. [Google Scholar] [CrossRef] [PubMed]
[23] Zhang, S. and Tang, Z. (2024) Prognostic and Clinicopathological Significance of Systemic Inflammation Response Index in Patients with Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis. Frontiers in Immunology, 15, Article 1291840. [Google Scholar] [CrossRef] [PubMed]
[24] Fucà, G., Guarini, V., Antoniotti, C., Morano, F., Moretto, R., Corallo, S., et al. (2020) The Pan-Immune-Inflammation Value Is a New Prognostic Biomarker in Metastatic Colorectal Cancer: Results from a Pooled-Analysis of the Valentino and TRIBE First-Line Trials. British Journal of Cancer, 123, 403-409. [Google Scholar] [CrossRef] [PubMed]
[25] Kuang, T., Qiu, Z., Wang, K., Zhang, L., Dong, K. and Wang, W. (2024) Pan-Immune Inflammation Value as a Prognostic Biomarker for Cancer Patients Treated with Immune Checkpoint Inhibitors. Frontiers in Immunology, 15, Article 1326083. [Google Scholar] [CrossRef] [PubMed]
[26] Xu, C., Wu, F., Du, L., Dong, Y. and Lin, S. (2023) Significant Association between High Neutrophil-Lymphocyte Ratio and Poor Prognosis in Patients with Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis. Frontiers in Immunology, 14, Article 1211399. [Google Scholar] [CrossRef] [PubMed]
[27] Zhou, Q., Jiang, Z., Ye, T., Yu, L., Wang, Q., Lin, P., et al. (2025) Prognostic Value of Platelet-To-Lymphocyte Ratio in Hepatocellular Carcinoma Patients Treated with Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis. BMC Gastroenterology, 25, Article No. 437. [Google Scholar] [CrossRef] [PubMed]
[28] Yang, J., Qian, J., Wu, Z., Zhang, W., Yin, Z., Shen, W., et al. (2024) Exploring the Factors Affecting the Occurrence of Postoperative MVI and the Prognosis of Hepatocellular Carcinoma Patients Treated with Hepatectomy: A Multicenter Retrospective Study. Cancer Medicine, 13, e6933. [Google Scholar] [CrossRef] [PubMed]
[29] Crișan, D., Procopeț, B., Crăciun, R., Ștefănescu, H., Gheorghe, L., Sporea, I., et al. (2025) The Role of Easy-To-Use Non-Invasive Scores in the Assessment of Hepatocellular Carcinoma Prognosis—Data from the Romanian Hepatocellular Carcinoma Registry. Journal of Gastrointestinal and Liver Diseases, 34, 205-213. [Google Scholar] [CrossRef] [PubMed]
[30] She, S., Shi, J., Zhu, J., Yang, F., Yu, J. and Dai, K. (2024) Impact of Inflammation and the Immune System on Hepatocellular Carcinoma Recurrence after Hepatectomy. Cancer Medicine, 13, e7018. [Google Scholar] [CrossRef] [PubMed]
[31] Shibutani, M., Maeda, K., Nagahara, H., et al. (2015) Prognostic Significance of the Lymphocyte-To-Monocyte Ratio in Patients with Metastatic Colorectal Cancer. World Journal of Gastroenterology, 21, 9966-9973. [Google Scholar] [CrossRef] [PubMed]
[32] Tian, Y., Zhang, Y., Zhu, W., Chen, X., Zhou, H. and Chen, W. (2018) Peripheral Blood Lymphocyte-To-Monocyte Ratio as a Useful Prognostic Factor in Newly Diagnosed Multiple Myeloma. BioMed Research International, 2018, Article ID: 9434637. [Google Scholar] [CrossRef] [PubMed]
[33] Lin, Z. (2015) Lymphocyte-To-Monocyte Ratio Predicts Survival of Patients with Hepatocellular Carcinoma after Curative Resection. World Journal of Gastroenterology, 21, 10898-10906. [Google Scholar] [CrossRef] [PubMed]
[34] He, T., Xu, B., Wang, L., Wang, Z., Shi, H., Zhong, C., et al. (2025) The Prognostic Value of Systemic Immune-Inflammation Index in Patients with Unresectable Hepatocellular Carcinoma Treated with Immune-Based Therapy. Biomarker Research, 13, Article No. 10. [Google Scholar] [CrossRef] [PubMed]
[35] Li, S., Xu, H., Wang, W., Gao, H., Li, H., Zhang, S., et al. (2019) The Systemic Inflammation Response Index Predicts Survival and Recurrence in Patients with Resectable Pancreatic Ductal Adenocarcinoma. Cancer Management and Research, 11, 3327-3337. [Google Scholar] [CrossRef] [PubMed]
[36] Mao, S., Yu, X., Sun, J., Yang, Y., Shan, Y., Sun, J., et al. (2022) Development of Nomogram Models of Inflammatory Markers Based on Clinical Database to Predict Prognosis for Hepatocellular Carcinoma after Surgical Resection. BMC Cancer, 22, Article No. 249. [Google Scholar] [CrossRef] [PubMed]
[37] Meng, W., Bai, B., Bai, Z., et al. (2016) The Immunosuppression Role of α-Fetoprotein in Human Hepatocellular Carcinoma. Discovery Medicine, 21, 489-494.
[38] Di Carlo, I., Mannino, M., Toro, A., Ardiri, A., Galia, A., Cappello, G., et al. (2012) Persistent Increase in Alpha-Fetoprotein Level in a Patient without Underlying Liver Disease Who Underwent Curative Resection of Hepatocellular Carcinoma. a Case Report and Review of the Literature. World Journal of Surgical Oncology, 10, Article No. 79. [Google Scholar] [CrossRef] [PubMed]
[39] Blank, S., Wang, Q., Fiel, M.I., Luan, W., Kim, K.W., Kadri, H., et al. (2013) Assessing Prognostic Significance of Preoperative Alpha-Fetoprotein in Hepatitis B-Associated Hepatocellular Carcinoma: Normal Is Not the New Normal. Annals of Surgical Oncology, 21, 986-994. [Google Scholar] [CrossRef] [PubMed]
[40] Yao, L., Fan, Z., Wang, M., Diao, Y., Chen, T., Zeng, Y., et al. (2023) Prognostic Value of Serum α‐Fetoprotein Level as an Important Characteristic of Tumor Biology for Patients Undergoing Liver Resection of Early-Stage Hepatocellular Carcinoma (BCLC Stage 0/A): A Large Multicenter Analysis. Annals of Surgical Oncology, 31, 1219-1231. [Google Scholar] [CrossRef] [PubMed]
[41] Liang, L., Wang, M., Zhang, Y., Zhang, W., Zhang, C., Lau, W.Y., et al. (2021) Association of Postoperative Biomarker Response with Recurrence and Survival in Patients with Hepatocellular Carcinoma and High α-Fetoprotein Expressions (>400 ng/ml). Journal of Hepatocellular Carcinoma, 8, 103-118. [Google Scholar] [CrossRef] [PubMed]
[42] Sun, L., Cen, W., Tang, W., Deng, L., Wang, F., Ji, X., et al. (2022) α-Fetoprotein Ratio Predicts α-Fetoprotein Positive Hepatocellular Cancer Patient Prognosis after Hepatectomy. Disease Markers, 2022, Article ID: 7640560. [Google Scholar] [CrossRef] [PubMed]
[43] Hwang, S., Moon, D., Kim, K., Ahn, C., Song, G., Jung, D., et al. (2021) Prognostic Accuracy of the ADV Score Following Resection of Hepatocellular Carcinoma with Portal Vein Tumor Thrombosis. Journal of Gastrointestinal Surgery, 25, 1745-1759. [Google Scholar] [CrossRef] [PubMed]
[44] Sun, L., Cen, W., Zeng, X., Zhong, Y., Deng, L., Yang, J., et al. (2024) The Prognostic Value of α-Fetoprotein Ratio in Patients with Resectable α-Fetoprotein-Negative Hepatocellular Carcinoma. The American Surgeon™, 90, 1240-1249. [Google Scholar] [CrossRef] [PubMed]
[45] Widdershoven, J., van Munster, P., De Abreu, R., Bosman, H., van Lith, T., van der Putten-van Meyel, M., et al. (1987) Four Methods Compared for Measuring Des-Carboxy-Prothrombin (PIVKA-II). Clinical Chemistry, 33, 2074-2078. [Google Scholar] [CrossRef
[46] Zhang, J., Qin, S.D., Li, Y., Lu, F., Gong, W.F., Zhong, J.H., et al. (2022) Prognostic Significance of Combined Α-Fetoprotein and CA19-9 for Hepatocellular Carcinoma after Hepatectomy. World Journal of Surgical Oncology, 20, Article No. 346. [Google Scholar] [CrossRef] [PubMed]
[47] Lin, K., Chen, Q., Tang, S., Lin, Z., Zhang, J., Zheng, S., et al. (2023) Prognostic Implications of α-Fetoprotein and C-Reactive Protein Elevation in Hepatocellular Carcinoma Following Resection (PACE): A Large Cohort Study of 2770 Patients. BMC Cancer, 23, Article No. 1190. [Google Scholar] [CrossRef] [PubMed]