Background

Cancer-related deaths due to hepatocellular carcinoma (HCC) rank fourth worldwide, presenting an abysmal outlook. Due to its insidious onset and asymptomatic nature, most patients are not diagnosed until later stages [1,2,3].

Immunotherapy is supported by the immune tolerance of the liver and the predominantly immunosuppressed microenvironment of HCC [4]. Since 2017, programmed death-1 (PD-1) inhibitors have been approved as second-line therapies for advanced hepatocellular carcinoma (aHCC). Although an encouraging response rate has been observed [5, 6], they have been unsuccessful due to insufficient statistical significance in subsequent phase III randomized clinical trials (RCTs) [7, 8]. Combination therapy is develo** rapidly. Basic research has shown that the PD-1 inhibitor combined with tyrosine kinase inhibitors (TKIs) or anti-vascular endothelial growth factor (VEGF) antibody can enhance antitumor efficacy by increasing lymphocyte infiltration, weakening the immunosuppressive state, and promoting the normalization of blood vessels [9,10,11]. In clinical studies, the combination of atezolizumab, a programmed death ligand 1 (PD-L1) inhibitor, and bevacizumab, an anti-VEGF inhibitor, significantly prolonged progression-free survival (PFS) and overall survival (OS) compared with the classic treatment; thus, this combined treatment represents a new systemic treatment for HCC [12].

Good efficacy has been demonstrated in PD-1/PD-L1 inhibitor-based systemic therapy for aHCC; however, only a fraction of patients (15–40%) have benefited. Moreover, a significant percentage of patients who undergo treatment encounter disease progression (approximately 20–30%). Identifying biomarkers and prognostic factors for immunotherapy efficacy and their underlying mechanisms is crucial for patient selection, stratified management, and future related clinical research. Therefore, this review focuses mainly on research progress on biomarkers and prognostic factors of aHCC.

Table 1 The PD-L1 expression as the biomarker in the advanced hepatocellular carcinoma clinical trials of immunotherapy
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Biomarkers of hepatocellular carcinoma immunotherapy

Tumor microenvironment

PD-L1 expression

Even though PD-L1 expression remains a topic of debate in immunotherapy [13], most studies still support it as a predictor of response and prognosis (details are summarized in Table 1). According to CheckMate 040, PD-L1 expression is an effective biomarker. With expression ≥ 1% as the cut-off value for defining PD-L1 positive expression, positive individuals had a more promising objective response rate (ORR) than negative individuals [5]. Comparable results were obtained in the subgroup analysis of CheckMate 459, where individuals treated with nivolumab who obtained PD-L1 ≥ 1% were prone to experience longer median OS than those who did not [14]. In the KEYNOTE-224 study, the combined positive score (CPS) ≥ 1 was found to be a better predictor of high ORR and PFS compared to the tumor proportion score (TPS ≥ 1%) [6]. The phase 1b study (GO30140) [15] and phase II study (NCT02989922, camrelizumab) [43]. According to Bassaganyas and colleagues, high broad CNAs are linked to immune exclusion and proliferation, and the CNA broad score could predict ICI therapy response in HCC [44].

The TP53 gene has been linked to the immune environment in HCC. As compared to individuals with wild-type TP53, those possessing TP53 mutations exhibited a shorter OS and recurrence-free survival [45]. CTNNB1 is another gene of interest, and basic research determined its role in immune escape and anti-PD-1 resistance [46]. It may function as a biomarker of immune rejection in individuals with aHCC. A small cohort enrolled HCC patients treated with ICIs showed that poor prognosis was related to altered WNT/β-catenin signaling, showing decreased disease control rate (0% vs. 53%), shorter median PFS (2.0 vs. 7.4 months), and shorter median OS (9.1 vs. 15.2 months) [47]. Additional investigations are suggested to comprehend its underlying mechanism on immunotherapy resistance [47, 48]. The GO30140 study showed that high expression of immune genes (CD274) and effector T signaling genes (GZMB, PRF1, and CXCL9) was linked with highly satisfying outcomes, including ORR and PFS. On the contrary, high expression of Notch pathway activation genes was a negative predictor [49]. The Checkmate 040 study subgroup results revealed that better ORR and OS were linked with high expression of inflammatory gene signals (CD274, CD8A, LAG3, and STAT1) [22].

Clinical features of tumors

Tumor burden

The macroscopic features of a tumor, such as its size and location, are more easily noticeable to a clinician than its microscopic features.

The size of a tumor is a crucial prognostic factor. A study of 33 nivolumab-treated patients found that those with tumors smaller than 5 cm (P = 0.034) and albumin-bilirubin (ALBI) scores of 1 (P = 0.040) had a better prognosis [50]. The results remained significant in a multivariate analysis for tumors smaller than 5 cm and ALBI scores of 1. Another study of 261 patients with HCC in Korea showed that those with small tumors (< 10 cm) had a high likelihood of responding to therapy (11.4% vs. 5.5%) and better PFS and OS (P < 0.05) [51]. Moreover, Huang et al. found that in cases of multifocal HCC, small lesions had strong immune infiltration and were responsive to PD-1 inhibitors [109]. A subsequent phase III confirmatory study made clear that Sin/Bev greatly improved median OS and PFS in comparison to sorafenib [110].

PD-1/PD-L1 inhibitors combined with TKIs

Several large phase III RCTs of PD-1/PD-L1 inhibitors bonded with TKIs have been conducted, but the efficacy of this regimen compared with TKI monotherapy is controversial. For the portfolio of camrelizumab plus apatinib, a phase II RCT showed that the ORR in the first-line cohort was 34.3% and 22.5% in the second-line cohort, showing good therapeutic effects [111]. The subsequent phase III CARES-310 trial showed that compared with sorafenib, camrelizumab plus rivoceranib (also referred to as apatinib) therapy led to a 48% reduction in the risk of disease progression (median PFS: 5.6 vs. 3.7 months) and a 38% reduction in the risk of death (median OS: 22.1 vs. 15.2 months) [112]. In the LEAP-002 trial, lenvatinib combined with pembrolizumab showed an improvement in PFS over lenvatinib monotherapy, although the results did not satisfy the validity threshold [113]. Similarly, cabozantinib plus atezolizumab offered improved PFS compared with sorafenib alone but without improving OS [114]. According to a phase II RCT conducted recently in naive-treatment patients, tislelizumab combined with lenvatinib achieved a 38.7% ORR and a 9.7-month median PFS [115]. Additional clinical trials are being conducted to assess the effectiveness of this regimen.

PD-1/PD-L1 inhibitor combined with CTLA-4 inhibitor

In another CheckMate 040 sub-cohort, different doses of nivolumab combined with ipilimumab were used to treat sorafenib-resistant aHCC. Approximately 30% of the cases responded to this regimen with a median OS of 22.8 months [17]. The latest HIMALAYA trial showed excellent efficacy of the Single Tremelimumab Regular Interval Durvalumab (STRIDE) regimen. STRIDE significantly outperformed sorafenib in OS (median OS: 16.4 vs. 13.8 months). However, tumor responses were substantially better with sorafenib, which presented a 22-month median duration of response [19]. Additional details on these critical trials are summarized in Table 3.

Table 3 The critical trials of unresectable hepatocellular carcinoma immunotherapy
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The recently developed bispecific antibody (BsAb) drug (i.e., AK104) has shown potential in solid tumors [116]. Consequently, research on such agents is being conducted in aHCC. Additionally, novel combinations of immunotherapeutic agents are being explored for the treatment of aHCC, with a focus on newly developed ICIs such as TIGIT and LAG3 inhibitors. The umbrella study (NCT04524871) serves as a representative example of these endeavors. Furthermore, several prospective clinical studies focus on the combinations of local therapies (e.g., transarterial chemoembolization) with immunotherapy in intermediate HCC. Noteworthy studies in this area include LEAP-012, ABC-HCC, and EMERALD. The effectiveness of this regimen has already been demonstrated in the retrospective study [39]. Moreover, prospective research on the combination of stereotactic radiation therapy with immunotherapy is currently unfolding. The key ongoing clinical trials studying immunotherapies for unresectable HCC are listed in Table 4.

Table 4 Key ongoing advanced hepatocellular carcinoma immunotherapy clinical trials
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Conclusions and perspectives

Systemic therapy using PD-1/PD-L1 inhibitors has been shown to be effective in treating HCC; however, this treatment is only beneficial to a subset of patients. Therefore, biomarker analysis is crucial for identifying individuals who will most likely respond to this treatment. A summary of the aforementioned biomarkers is shown in Fig. 1 and Supplementary Table 1.

Fig. 1
figure 1

The summary of the biomarkers in PD-1/PD-L1 inhibitor-based therapy in aHCC. Current studies on biomarkers are focused on the tumor microenvironment, tumor genomics, tumor clinical features, host clinical features, liquid biopsy, and gut microbiota. Abbreviations: AFP, alpha-fetoprotein; aHCC, advanced hepatocellular carcinoma; ALBI, albumin-bilirubin; cfDNA, cell-free DNA; CNAs, copy number alterations; CTC, circulating tumor cell; ctDNA, circulating tumor DNA; ECOG, Eastern Cooperative Oncology Group; EOB-MRI, Gd-EOB-DTPA-enhanced magnetic resonance imaging; HBV, hepatitis B virus; HCV, hepatitis C virus; IL-6, interleukin-6; IO, immunotherapy; irAE, immune-related adverse event; LDH, lactate dehydrogenase; MRE, magnetic resonance elastography; NLR, neutrophil-lymphocyte ratio; PD-1, programmed death-1; PD-L1, programmed death ligand 1; PET/CT, positron emission tomography-computed tomography; PG-SGA, patient-generated subjective global assessment; PIVKA-II, abnormal prothrombin; PLR, platelet-to-lymphocyte ratio; TBS, tumor burden score; TGF-β, Transforming Growth Factor beta; TIB, tumor immune barrier; TILs, tumor-infiltrating lymphocytes; Treg, regulatory T cell; TMB, tumor mutational burden

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Despite the importance of biomarkers in HCC, their use faces several challenges. First, the methods used for immunotherapy lack uniformity. As more studies combine PD-1/PD-L1 inhibitors with TKI/VEGF therapy, the underlying mechanisms and effectiveness may vary. Second, although some cases of HCC can be diagnosed through imaging, pathological tissue may not be available in all cases, thus increasing the difficulty of analyzing the immune microenvironment. Limited biomarkers are available for dynamic monitoring, and data are scarce for adjusting treatment after drug resistance.

With continued advances in research on HCC immunotherapy, mainly through extensive sample studies and subsequent subgroup analyses, biomarkers will hopefully become more widespread, which will allow for earlier identification of the target population. In the future, cutting-edge non-invasive monitoring methods (such as ctDNA), imaging parameters (such as PET/CT), and multi-dimensional information from artificial intelligence radiomics and single-cell sequencing sources may help us to comprehensively understand the mechanisms behind HCC immunotherapy response and the causes of drug resistance. These findings will ultimately result in more tailored treatment options.