Most cancers diagnosed in routine clinical practice are characterized by a suppressive tumor immune microenvironment (TME), which enables them to evade anti-tumor immunity. Since immune checkpoint inhibitors (ICIs) aim to reactivate anti-tumor immunity, understanding the characteristics of the TME is crucial for predicting the efficacy of ICI-based treatments [
1].
Yim et al. [
2] developed an immune signature score (ISS) based on mRNA expression to stratify patients with hepatocellular carcinoma (HCC) treated with atezolizumab plus bevacizumab (Atezo/Bev). Among patients classified as high responders by the ISS, those treated with the Atezo/Bev combination exhibited improved overall survival (OS), progression-free survival, and a better objective response rate, such outcomes not observed in patients treated with sorafenib. To create a practical tool, the ISS was refined to include the expression profile of 10 key genes (ISS10). A significant correlation was found between ISS10 and the response to Atezo/Bev as well as nivolumab and ipilimumab (Nivo/Ipi) treatment. The ISS10 high subtype exhibited a more favorable TME, characterized by higher proportions of anti-tumor macrophages and activated T-cells.
Several transcriptomics-based approaches have been conducted to classify HCC according to the TME and to identify molecular signatures for predicting responsiveness to ICIs. HCCs are generally classified into two main TME classes: one characterized by abundant immune cells within the tumor (inflamed class, 25–40% of HCC cases) and the other by a paucity of immune-related cells (non-in-flamed class, 60–75%). A subset of inflamed HCCs (15– 20%) shows particularly high infiltration of CD8
+ cytotoxic T lymphocytes (CTLs), with low levels of immunosuppressive cells, such as regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs). This subclass has been referred to as “immune active,” “immunogenic,” “cytolytic activity,” or “immune-activated”. Inflamed HCCs are also characterized by high expression of molecules involved in antigen presentation (e.g., Human Leukocyte Antigen), activation of dendritic cells (DCs), infiltration of M1 macrophages, high expression of chemokines that attract immune effector cells (e.g., CCL4, CCL5, CXCL10, CXCL11), and enhanced interferon-γ (IFN-γ) and programmed cell death 1 (PD-1) signaling [
3-
7]. Additionally, the presence of tertiary lymphoid structures, which are thought to be involved in the establishment and maintenance of acquired immunity, is more frequently observed [
3,
8]. These findings strongly suggest that this subclass is characterized by robust antigen presentation, immune cell recruitment, and subsequent anti-tumor immune responses. The TME profile that contributes to the efficacy of Atezo/Bev combination therapy reportedly includes a high intratumoral density of CD8
+ CTLs, high expression of effector T cell-related molecules and PD-L1, and low proportions of Tregs [
9], consistent with the features of the “immune active” subclass.
Conversely, a subclass within non-inflamed HCCs shows sparse tumor-infiltrating lymphocytes (TILs) and a high frequency of β-catenin mutations [
3,
7]. This subclass, often referred to as “immune excluded” or “immune desert,” exhibits activation of the WNT/β-catenin signaling pathway and accounts for approximately 20–30% of HCCs. These tumors demonstrate low expression of molecules involved in antigen presentation and of cytokines/chemokines that activate immune effecter cells. Molecules related to IFN-γ signaling and immune checkpoint pathways are also expressed at low levels. This subclass is reportedly associated with high expression of hepatocyte nuclear factor 4A, which is involved in hepatocyte differentiation, along with nuclear accumulation of β-catenin. Thus, this subclass may exhibit features of differentiated HCC with activation of WNT/β-catenin signaling. While this type of HCC shows a relatively favorable prognosis, it is believed to have low responsiveness to immunotherapies due to the paucity of anti-tumor immune effector cells [
9,
10]. However, despite genomic alterations in the WNT/β-catenin signaling pathway being proposed as a cause for sparse DCs and TILs [
11], analyses of samples from large prospective trial cohorts do not support the role of genes involved in this pathway as biomarkers for non-responders. Another study indicate that baseline gene expression signatures related to differentiation correlate with more favorable outcomes, whereas activation of signaling pathways associated with aggressive disease is linked with poorer outcomes on ICIs [
12]. This evidence suggests that a prolonged anti-tumor immune response may well induce the production of various immunosuppressive cytokines, chemokines, growth factors, and metabolites, which attract immunosuppressive cells into tumor tissues and eventually establish a solid immunosuppressive TME.
While numerous studies have reported associations between the TME and the efficacy of ICIs in HCC, there are currently no established biomarkers that can reliably predict clinical response in real-world practice. The ICI-containing treatment regimens approved for HCC include durvalumab monotherapy (anti-PD-L1 antibody), the combination of durvalumab and tremelimumab (Durva/Treme: anti-PDL1 and anti-CTLA-4 antibody), and Atezo/Bev combination therapy (anti-PD-L1 and anti-VEGF-A antibody). The first two are considered pure ICI treatments, while the Atezo/Bev combination is defined as a combination of an ICI and an anti-VEGF molecular-targeted agent. Regarding the exploration of biomarkers for combination of ICI and an anti-VEGF molecular-targeted agent, analyses of 358 HCC patients enrolled in the phase 1 (GO30140) and phase 3 (IMbrave150) trials of the Atezo/Bev combination therapy have been reported (
Table 1). Pre-existing immunity, defined by high PD-L1 expression, high expression of effector T cell (Teff)-related genes (CXCL9, PRF1, GZMB), and high CD8
+ TIL density, was also associated with favorable outcomes, like those observed in pure ICI therapy. On the other hand, a high ratio of Tregs to effector T cells and the expression of oncofetal proteins were associated with poorer clinical benefits [
9,
13]. Interestingly, when comparing the outcomes of Atezo/Bev combination with atezolizumab monotherapy, improved outcomes with Atezo/Bev were observed in patients with increased infiltration of Tregs and myeloid cells, as well as high expression of VEGF receptor and high tumor vessel density [
9]. Therefore, HCC patients with higher levels of Treg and myeloid cell proliferation, and/or angiogenesis in tumor, which reflect features observed in a subset of non-inflamed tumors, may benefit from VEGFtargeted ICI combination therapy, a benefit not observed with pure ICI therapies. From this perspective, VEGF-targeted therapies may play a role in modulating immunosuppressive cells and contributing to the conversion of an immunosuppressive TME into an immune-active one. Furthermore, in a real-world setting, the Atezo/Bev combination therapy has been reported to be more effective in HCC patients with high neutrophil-to-lymphocyte ratio (NLR) [
13].
In contrast, exploration of biomarkers for pure ICI treatments, nivolumab monotherapy, using samples before treatment have shown that PD-L1 expression, an inflammatory gene expression signature, and the low NLR and platelet-to-lymphocyte ratio in peripheral blood are associated with improved survival outcomes and response rates, according to data from the phase 1/2 CheckMate 040 clinical trial (
Table 1) [
14]. A part of these findings aligns with data from the phase 3 CheckMate 459 study, which reported an association between baseline expression of inflammationassociated genes and benefit from nivolumab compared to sorafenib using transcriptomic analysis [
15]. Another analysis found a correlation between clinical responses and an increase in CD8
+ TILs, specifically with an increase in two effector T-cell clusters, in HCC patients who received perioperative pure ICI therapy (Nivo/Ipi) followed by surgical resection [
16]. A phase 2 study (KEYNOTE-224) using the anti-PD-1 antibody pembrolizumab as second-line therapy also showed a trend towards higher ORR in patients with high PD-L1 expression in tumor tissue compared to those with low PD-L1 expression (
Table 1) [
17]. In a single-arm study involving HCC patients who received second-line pembrolizumab, responders exhibited elevated levels of intratumoral CTLs on pretreatment biopsy samples [
18]. Peripheral blood mononuclear cells from pre-treatment and posttreatment samples were also analyzed using single-cell RNA sequencing, demonstrating that patients with a response or stable disease had elevated circulating cytotoxic CD8
+ T-cell levels, whereas those with progressive disease had an increased number of both CD14
+ and CD16
+ monocytes and activation of neutrophil-associated signaling pathways. A clinical trial involving tremelimumab monotherapy, an anti-CTLA-4 antibody, in hepatitis C-related HCC patients, also demonstrated that changes in serum IFN-γ levels at day 60 of treatment were associated with an anti-tumor response [
19].
Although the long-term follow-up of an expanded cohort from CheckMate 040 for the combination of Nivo/Ipi failed to show a clear relationship between tumor PD-L1 expression or CD8
+ TILs and OS, likely due to the effects of subsequent treatments altering the TME [
20], many reports commonly pointed out that features indicative of pre-existing immunity, including high PD-L1 expression, Teff cell gene signatures, and dense CD8
+ TILs, enrich the benefit from pure ICI treatment in HCC patients. However, current predictive biomarkers leave considerable room for improvement. Especially, although anti-VEGF therapy has the potential to improve the immunosuppressive TME by regulating Tregs and MDSCs, further large cohort study is required to determine the role of anti-VEGF agents in noninflamed HCCs.
Yim et al. reported a practical tool, ISS10, for predicting outcomes of ICI-based therapy. To achieve substantial improvements, future biomarker studies should likely require multimodal integration of data from pathology, medical image, and health records, as well as omics data. Information regarding tumor heterogeneity, clonal structure, and neoantigen expression patterns should also be considered [
21]. Given the complexity of TME analysis, the application of deep learning and generative learning technologies will be valuable. Such efforts will be crucial for refining patient stratification and personalizing treatment approaches to enhance the effectiveness of ICI-based regimens.
ACKNOWLEDGMENTS
This work was supported in part by a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (KAKENHI: 24K10393, N. Nishida). There is no conflict of interest to declare.
FOOTNOTES
-
Conflicts of Interest
The author has no conflicts to disclose.
Table 1.Clinical trial reported for ICI-based therapy and exploratory biomarker study
Table 1.
|
Type |
ICI and anti-VEGF combination |
Pure ICI |
|
Trial |
IMbrave 150 & GO30140 |
HIMALAYA |
Checkmate 459 |
Checkmate 040 |
Checkmate 040 |
KEYNOTE-224 |
|
Phase |
Phase III and phase I |
Phase III |
Phase III |
Phase I/II |
Phase I/II |
Phase II |
|
Agents |
Atezo/Bev combination |
Durva/Treme combination |
Nivolumab |
Nivolumab |
Nivo/Ipi combination |
pembrolizumab |
|
Design |
Atezo/Bev vs. sorafenib |
Durva/Treme vs. durvalumab vs. sorafenib |
Nivolumab vs. sorafenib |
Nivolumab |
Nivo/Ipi (for 2nd line therapy) |
pembrolizumab (n=52) |
|
Biomarker |
Treg/Teff ratio, |
PD-L1 (tumor area) |
PD-L1 (tumor cell) |
PD-L1 (tumor cell), |
PD-L1 (tumor cell) |
PD-L1 (CPS and TPS) |
|
PD-L1 expression, |
T-cell infiltration, |
|
CD8+ TIL, |
inflammatory gene signature, |
|
Teff gene expression signature, |
NLR and PLR |
|
Atezo/Bev response signature. |
|
|
Myeloid inflammation signature |
|
|
Observation |
Teff gene expression signature, Atezo/Bev response signature, myeloid inflammation signature, high PD-L1 expression, and dense CD8+ TIL is associated with improved mPFS. |
No correlation with response. |
No correlation with OSa
|
PD-L1 in tumor cell ≥ 1%, CD3+ and CD8+ T-cell infiltration, inflammatory gene signature, and low NLR and PLR are associated with improved OS. |
Both patients with PD-L1-posivtive and -negative HCC responded to treatment. |
PD-L1 CPS is associated with response. |
|
A high ratio of Tregs to Teff cells is associated with poorer clinical benefits. |
Baseline expression of inflammationassociated genes shows benefit in nivolumab treatment [14] |
|
Reference |
[8] |
b
|
[14], a
|
[13] |
C
|
[16] |
Abbreviations
atezolizumab and bevacizumab
cytotoxic T lymphocyte antigen-4
C-X-C motif chemokine ligand
durvalumab and tremelimumab combination therapy
immune checkpoint inhibitors
myeloid-derived suppressor cells
programmed cell death ligand 1
progression-free survival
transforming growth factor
tumorinfiltrating lymphocytes
tumor immune microenvironment
vascular endothelial growth factor
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Citations
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