Non-Invasive Biomarkers for Immunotherapy with Hepatocellular Carcinoma: Comparison
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Please note this is a comparison between Version 2 by Camila Xu and Version 3 by Camila Xu.

Tumor biomarkers are cellular and molecular products linked directly or indirectly to the presence of cancer cells that are an expression of the tumor’s intrinsic characteristics and can be identified, measured, and analyzed by specific tests.  Currently, there is an increasing interest in developing novel techniques to extract information on tumor biology directly from patient’s body fluids in a non-invasive way. Liquid biopsy, a non-invasive approach of tumor biomarkers detection, permits a dynamic picture of HCC’s evolution and response to therapy. 

  • biomarkers
  • gut microbiota
  • hepatocellular carcinoma (HCC)
  • liquid biopsy
  • immunotherapy

1. Non-Invasive Tumor Biomarkers: Definition

Tumor biomarkers are cellular and molecular products linked directly or indirectly to the presence of cancer cells and expression of the tumor’s intrinsic characteristics that can be identified, measured, and analyzed by specific tests [1]. They can be used for multiple purposes, mainly for the early detection of a tumor, but also for defining its biological behavior and aggressiveness, and for assessing the response following a therapeutic intervention [2]. 

In the past few years, hepatocellular carcinoma (HCC) biomarkers have been predominantly derived from histological analysis. Currently, there is an increasing interest in developing novel techniques to extract information on tumor biology directly from patient’s body fluids in a non-invasive way [3][4][5]. Liquid biopsy, a non-invasive approach of tumor biomarkers detection, could be performed at different time points, drawing a personalized and dynamic picture of HCC’s evolution and response to therapy [6]. 

There are various tumor by-products that can be measured in the bloodstream alone or in combination [6], some of which are well-known and traditionally linked to the mechanisms of carcinogenesis (e.g., cytokines and alpha-fetoprotein), while others have only recently been studied (e.g., circulating tumor cells, DNA, RNA, and exosomes). The main findings on novel tumor biomarkers of response or resistance to immune checkpoint inhibitors are reported below.

2. Non-Iinvasive Tumor Btumor biomarkers: Ttraditional Bbiomarkers 

2.1. Cytokines, Immune Checkpoints, and Immune Cells

Circulating soluble factors, such as cytokines, have been evaluated as biomarkers over the course of ICI therapy. interleukin 6 (IL-6) and interferon alpha (IFN-alpha) were related to disease progression in HCC patients treated with Atezolizumab/Bevacizumab [7]; specifically, a high serum level of IL-6 was also associated with worse progression free survival (PFS) and Overall survival (OS) and was more frequently found in females; in patients with higher levels of Aspartate Aminotransferase (AST), Alpha Fetoprotein (AFP), and Des-gamma-carboxy prothrombin (DCP) values; and those with reduced liver function[7][8]. Another study conducted in patients receiving Pembrolizumab reported a correlation between [ transforming growth factor (TGF)-beta serum levels upper to 200 pg/mL and risk of poor response, and reduced survival (p = 0.003). Moreover, patients with a high tumor expression of Programmed Death 1 (PD-1) showed higher serum levels of Interpheron-gamma (IFN-gamma) and IL-10, but plasma Programmed Death Ligand 1 (PD-L1) did not correlate with tumor PD-L1 expression. Changes in plasma biomarkers were also observed after treatment: only Chemokine (C-X-C motif) ligand 9 (CXCL9) increased regardless of the response (p = 0.008) [9].

Recent studies demonstrated that PD-L1 expression on (CD) 4 T peripheral lymphocytes before treatment, could influence the response to Immune Checkpoint Inhibitors (ICIs) may be influenced by the prevalence of PD-L1 [10]. During systemic therapy administration, the expression of PD-1 and PD-L1 on double positive Cluster Differentiation 4/8 T cells (CD4/CD8) and on CD4 T cells is different among responders and non responders [11][12]. In HCC patients, a meta-analysis demonstrated that a high soluble PD-L1 (sPD-L1) level correlates with a shorter survival (HR: 2.93; 95% CI: 2.20–3.91; p < 0.00001) [13], moreover, following liver resection, the persistence after treatment of sPD-L1 indicated a poor outcome, suggesting the possibility to apply sPD-L1 analysis for identifying patients eligible for adjuvant immunotherapy [14]. 

In patients with HCC, the response to ICIs is influenced by the number of peripheral effector T cells, which are more prominent in the presence of Cytotoxic T-Lymphocyte Antigen 4 (CTLA-4) and the inducible Co-stimulator ICOS on peripheral blood mononucleate cells (PBMC) surfaces. Moreover, anti-PD-1 agents upregulate cytotoxic T cell effectors with a memory phenotype, also reducing PD-1 expression on their surface, and cause the downregulation of B cells [15]. The presence of CD14+ CD16− Human Leukocyte Antigen-DR isotype (HLA-DRhi) monocytes in peripheral blood before ICIs treatment is another marker of a favorable outcome; monocytes presenting these receptors can favor the infiltration of T cells in tumor tissue, leading to the activation of T cell effectors against cancer [16]. Other studies demonstrated that baseline CD4+ PD-1+ cells predict a successful response to the anti-CTLA-4 Tremelimumab, and that a lower percentage of T regulatory cells as well as higher levels of double positive CD4/CD8 T cells are associated with the response to anti-PD-L1 inhibitors [17][18]. After therapy, an increased number of activated CD4 and CD8 T cells and a reduction in CD4 and CD8 naive T cells was observed. Moreover, the responders had higher levels of cytotoxic CD8 T cells, while the poor responder patients expressed molecules associated with neutrophil-associated pathways. In another study, Nivolumab therapy was associated with an elevation of CD8 αβT cells after 4 weeks of therapy; these cells showed lower levels of PD-1 expression compared to that belonging to patients with disease progression. No significant alteration in regulatory T cells was observed, and the patients achieving disease control (DC) maintained a persistent expression of PD-L1 on their monocytes after 28 and 42 days of treatment. The post treatment changes in the PD-L1 positivity of the patients’ monocytes differed among responders and non-responders after 28 and 42 days. Finally, the low pretreatment expression of PD-1 on peripheral B cells was associated with DC [18]. 

2.2. Neutrophil to Lymphocyte Ratio, Platelet to Lymphocyte Ratio, Prognostic Nutritional Index, and Their Combined Prognostic Value

The Neutrophil to Lymphocytes Ratio (NLR) has been used to evaluate the risk of mortality in patients with liver disease [19], and has also been tested as a prognostic biomarker for immunotherapy in several studies. A decline in the NLR in patients with HCC receiving anti PD-1 therapy was associated with a better response to treatment and improved survival [20]. In patients receiving Atezolizumab plus Bevacizumab, the baseline NLR (cut-off 3.21) resulted to be an independent predictor of response, and was directly linked with PFS [21]. 

Similarly, a high Platelet to Lymphocytes ratio (PLR), an inflammatory marker already correlated with prognosis in patients with HCC [19][21], has been associated with poor prognosis. Finally, a high prognostic Nutritional Index (PNI), obtained by multiplying the serum albumin (g/dL) by the total lymphocyte count, was associated with a response to anti-PD-1 therapy and better survival [22].

Based on these results, a study combined NLR, PLR, and PNI to evaluate their roles as predictors of response to immunotherapy [23]. The blood samples of 362 HCC patients were collected. The median NLR value in the whole cohort was 3.55 (0.06–25.3), the median PLR value was 137.32 (0.17–1100), and the median PNI value was 40.29 (1.11–1270). The previously indicated thresholds for a high mortality risk (NLR ≥ 5, PLR ≥ 300, and PNI < 45) were associated with the presence of portal vein thrombosis, a worse performance status, a more advanced Barcelona Clinic Liver Cancer (BCLC) stage, and worse OS and PFS (limited to PLR and PNI). In the multivariate analysis, an NLR ≥ 5 and a PLR ≥ 300 remained independent prognostic factors for OS (HR 1.73, 95% CI 1.23–2.42, p = 0.002 and HR 1.60, 95% CI 1.6–2.40, p = 0.020, respectively), while the PLR was the only independent predictor of PFS [24].

Finally, albumin, lactate dehydrogenase (LDH), and the NLR were combined in a score named the Gustave Roussy immune score (GRIm-Score), which was able to stratify patients receiving ICIs into responders and non-responders with respect to several tumors [25]. To better mirror the characteristics of HCC, the GRIm-Score was implemented with other circulating markers that resulted independent prognostic factors of survival in a multivariate analysis; therefore, the HCC-GRIm-Score was obtained, including albumin (<35 g/L = 1), LDH (>245 U/L = 1), NLR (≥4.8 = 1), Aspartate Aminotransferase to Alanine Aminotransferase AST-to-ALT ratio (≥1.44 = 1), and total bilirubin (≥22.6 umol/L = 1). Lower scores (from 0 to 2 points) resulted in a better OS [26]. Despite the remarkable results highlighted by these studies on the utility of a combinatory approach of non-invasive biomarkers to improve sensitivity, further and larger clinical trials are needed to apply them in clinical practice.

2.3. Serum Alphafetoprotein

Serum alpha-fetoprotein (AFP) is the HCC-related biomarker that is most used in clinical practice [27][28]. Studies showed that early AFP reduction is associated with a good prognosis in patients with HCC receiving ICIs [29]. Previous in vitro studies demonstrated a pro-oncogenic role of AFP promoting protein kinase A activity and the expression of the pro-oncogenic proteins p53 and p21 and by inhibiting apoptotic pathway [30][31]. In addition, Natural Killer (NK) cells’ activity has been shown to be impaired in the presence of AFP-treated dendritic cells (DCs) [32]. 

Models combining AFP with other biochemical parameters have reported promising results with respect to predicting ICIs response. One of them that includes AFP and C-reactive protein (CRP), named the CRAFITY score, has been recently evaluated in HCC patients receiving anti-PD-1 immunotherapy. The patients with a CRAFITY score of 0 showed a better radiological response and OS compared to patients with a CRAFITY score ≥ 1 [33]. 

Another study combined the CRAFITY score with AFP decline after 6 weeks of treatment with Atezolizumab plus Bevacizumab, generating a classification named CAR (CRAFITY score and AFP Response) [34]. The patients were divided into three classes: those with a low CRAFITY score and good AFP response (class I), either a high CRAFITY score or an unsatisfactory AFP response (class II), and a high CRAFITY score and an unsatisfactory AFP response (class III). The Median Objective Response Rate (ORR) was better in class I than in classes II or III (35% vs. 18.2% vs. 0%). The patients in class I had the best OS and PFS, followed by those in classes II and III (the median OS of class I did not reach the median time exceeding the 12 months of follow-up vs. 11.1 months vs. 4.3 months, p < 0.001; the median PFS was 7.9 months vs. 6.6 months vs. 2.6 months, p = 0.001). 

Another study analyzed the prognostic ability of AFP plus prothrombin induced by vitamin K absence-II (PIVKA-II) in HCC patients treated with anti-PD-1 therapy [35]. Reductions in AFP and PIVKA-II of more than 50% from the baseline levels at 6 weeks of treatment were associated with a favorable ORR and a better OS and PFS. The combination of these results with the Albumin Bilirubin score (ALBI) was included in the AAP score; patients with an AAP score ≥ 2 points showed a significantly longer PFS and OS. Lower serum levels of AFP and soluble intercellular adhesion molecule 1 (sICAM-1)—a soluble factor derived from endothelial cells and involved in inflammatory responses, which is absent in normal hepatocytes [35][36]—were associated with a response to immunotherapy in a recent analysis of the Cancer Genome Atlas Liver Hepatocellular Carcinoma. AFP and ICAM-1 upregulation correlate with an immunosuppressive TME in which CD4 T cells, macrophages, and monocytes are predominant, and the expression of immune checkpoints such as T cell immunoglobulin and ITIM domain (TIGIT), Hepatitis A virus cellular receptor 2 (HAVCR2), PD-1, CTLA4, and LAG3 is enhanced [36].

3. Novel Nnon-Iinvasive Tumor Btumor biomarkers

3.1. Circulating Tumor DNA

Circulanting Tumor DNA (ctDNA) are cell-free DNA products released by tumor cells in the bloodstream during apoptosis or necrosis that are rapidly cleared by macrophages. The concentration of ctDNA in peripheral blood is higher in patients with HCC than in cirrhotic patients without a tumor and healthy controls. Interestingly, tumor size, extrahepatic spread, and vascular invasion are associated with higher ctDNA levels [37][38]. Tumor ctDNA fragments are longer when compared to circulating DNA derived from other apoptotic host cells; indeed, the ratio of ctDNA to the whole circulating DNA length, called DNA integrity, has been used as a marker for the early diagnosis of HCC [38].

A qualitative analysis of somatic gene mutations in HCC-derived ctDNA fragments showed that several oncogenes and tumor suppressor genes such as ARIDNA, tumor protein 53 (TP53), catenin (cadherin-associated protein), and beta 1 (CTNNB1) are involved, and the same mutations were found in tumor tissue in 63% of cases [39]. The presence of Telomerase reverse Transcriptase gene (TERT) mutations in ctDNAs are associated with vascular invasion [40]. Mutations in the PI3K/mTOR pathway correlate with a shorter PFS in patients treated with tyrosine kinase inhibitors (TKIs) but not with ICIs, whereas mutations in MutL homolog 1 are linked to a worse OS [41].

The detection of a TP53 R249S mutation in ctDNA after HCC resection is a marker of a poor disease-free survival (DFS) [42]. ctDNA detectable after curative treatment has been related with microvascular invasion and may predict tumor recurrence and extrahepatic spread. Accordingly, preoperative ctDNA detection was associated with larger HCCs, multiple lesions, microvascular invasion, and shorter PFS and OS [43]. A high tumor mutational burden (TMB) in the tumor genome was associated with an effective immune response against several tumors, due to the increased neoantigen load [44]. In addition to a TMB assessment on liver tissue, an emerging blood-based technique has been described and performed on ctDNA. Blood TMB (bTMB) accurately reflects tissue TMB, as described for several tumors. In a pilot study, the analysis of a cohort of patients with advanced solid tumors treated with immunotherapy demonstrated the correlation between bTMB and tTMB regardless of tumor histology [45]. However, the patients with higher levels of bTMB did not achieve a better OS, but the heterogeneity of the cohort may explain this result. Interestingly, an exploratory analysis from the same study demonstrated a reduction in the ctDNA mutant allele frequency (MAF) over the treatment period in the responders. Similarly, ctDNA MAF has been reported to change dynamically after surgery and to correlate with recurrence-free survival and OS [46]. Despite these promising results, at present, the application of ctDNA as a biomarker is limited, mainly due to the lack of standardized procedures for sample preparation and the difficulty of determining the assay when the ctDNA levels are very low [46].

3.2. Circulating Tumor Cells

Circulating Tumor Cells (CTCs) are rounded, nucleated cells released into the bloodstream from the primary tumor site or from metastatic sites. CTCs express epithelial proteins such as Epithelial Cell Adhesion Molecules (EpCAM); cytokeratin 8, 18, or 19; and stem cells markers, while they lack the CD45 antigen. They can be found as single cells or in clusters, according to their mono- or oligo-clonal origin; CTC clusters are more prone to seeding, as they express transcription factors of genes that enhance proliferation [47].

Despite their low concentration in peripheral blood (about 5–50 CTCs in 7.5 mL of blood) and their short half-life (2.5 h) [48], several studies of different tumors showed that CTCs may be useful as prognostic markers after treatment. Indeed, it has been reported that after HCC surgical resection or locoregional treatment, the CTCs concentration drops [49], whereas any increase after treatment is associated with a higher risk of tumor recurrence [50]. Studies in several cancers showed that CTCs expose immune checkpoints such as PD-L1, PD-L2, and CTLA-4 on their membrane, so they have been evaluated as biomarkers to identify patients suitable for immunotherapy [51]. In a phase I trial, the total number of CTCs and the PD-L1 expression on CTCs was evaluated in patients with advanced gastrointestinal cancers, including HCC, at baseline and following anti-PD-1 therapy [52]. The patients were divided into four categories based on their PD-L1 expression at baseline (negative, low, medium, and high); 74% of the patients showed PD-L1-high CTCs, which correlated with a good treatment response, while the persistence of PD-L1-high CTCs after therapy was associated with a poor outcome. Reductions in total CTCs and in PD-L1 expression on CTCs from the baseline levels were also reported in patients with a stable disease. Even though a positive correlation between baseline PD-L1-high CTCs and disease status was not detected, the average percentage of PD-L1-high CTCs among the total number of CTCs in the patients with disease control was significantly higher compared to the patients with a lower expression of PD-L1-high CTCs; moreover, the PD-L1-high CTC/total CTCs ratio was higher in the responders. Further, the absence of PD-L1-high CTCs at baseline was associated with a higher risk of progression during anti-PD1 therapy. Taken together, these results suggest that the presence and distribution of PD-L1-high CTCs could be a better biomarker in predicting PD-1 therapy response compared to PD-L1 positive CTCs. Another study including only HCC patients confirmed that PD-L1+ CTCs identified responders to ICIs [53].

Despite the promising role of CTCs as a biomarker for HCC, their low concentration in the bloodstream and short half-life can limit the reliability of their respective assay. Moreover, the validated platform has a weak performance with respect to the recognition of CTCs with markers of endothelial-mesenchymal transition. The lack of standardized clinical trials with large cohorts of patients is another concern that should be overcome [54].

3.3. Extracellular Vesicles

Extracellular vesicles (EVs) are nanoparticles that have heterogeneous functions, including the ability to modulate inter-cellular communication, and could influence several processes, such as inflammation and tumorigenesis [55]. EVs can be classified in exosomes (size < 200 nm), derived from the internal budding of endocytic membranes, and microvesicles (MVs) (size > 200 nm), derived from the extroflession of activated cells’ membranes [56]. Exosomes express CD63, CD81, and CD9 on their surfaces and can interact with target cells through exosomal proteins and cellular receptors, the direct fusion of the exosomal membrane with the cell membrane, or endocytosis.

Through autocrine and paracrine mechanisms, exosomes enable the interaction between tumor cells and TME, with immune-modulatory effects and the stimulation of the epithelial to mesenchymal transition that favors vascular invasion and metastatization [56]. Moreover, increasing evidence suggests that the interaction between tumor-derived exosomes, tumor cells, and TME may play a significant role in the development of drug resistance to TKIs in patients with HCC [57][58]. 

The exposure of PD-L1 on exosomes causes the direct inhibition of T cells’ function. Exosomes expressing PD-L1 compete with cancer cells and peritumoral cells in binding ICIs; as a result, lower levels of a drug can target tumor cells, resulting in a mechanism of resistance against therapy [57]. Similar to exosomes, MVs express specific markers on their surface derived from the type of cell that generates them and contain nucleic acids and proteins that could influence several biologic processes. MVs expressing Hepatocyte Paraffin 1 (HepPar1+) have been found to be higher in patients with HCC than in controls without cancer, and their lack of reduction 3 months after liver resection was observed in patients with tumor recurrence [59]. AnnexinV+ EpCAM+ Human Asialoglycoprotein Receptor 1 (ASGPR1+) MVs were able to distinguish patients with cirrhosis and liver cancer (HCC or cholangiocarcinoma) from those with no malignancy, and this was confirmed by the drop in the concentration 7 days after curative resection [60].

EVs contain a variety of proteins, lipids, DNAs, messenger RNAs (mRNAs), microRNAs (miRNAs), and other non-coding RNAs, such as circular RNAs (circRNAs) and long non-coding RNAs (lncRNA) [61]. These genetic products and proteins are similar to those expressed in the tumor tissue; thus, EVs not only reflect a cancer’s features and its dynamic changes but can also regulate various cellular processes such as proliferation, survival, migration, and the inhibition of the anti-tumor response. In particular, long non-coding RNAs (lncRNA) have shown a potential role in modulating immunotherapy responses via TME re-programming, leading to the exhaustion of CD8 cells, which is a well-known marker of a poor response to ICIs [62]. Several signatures based on lncRNAs have been associated with a response to ICIs [63][64][65][66]. Furthermore, circular RNAs (circRNAs) can regulate gene expression and interfere with transcription and peptide translation through the modulation of microRNAs (miRNAs) [67]. In HCC tissue, Circular ubiquitin-like with PHD and ring finger domain 1 (circUHRF1) RNA is upregulated. It decreases the activity and number of NK cells in tumor tissue and has been associated with a resistance to ICIs [68]. CircMET (hsa_circ_0082002), which is highly expressed in HCC tissue and exosomes compared to non-tumor cells, promotes HCC cells’ survival by acting on the miR-30-5p/Snail/dipeptidyl peptidase 4 (DPP4)/CXCL10 axis, with the consequent inhibition of CD8 T cell functions and a resistance to anti-PD-1 therapy [69]. Hsa-crc-0003288 has been demonstrated to increase PD-L1 expression in vitro by the activation of the PI3K/AKT signaling pathway, thereby promoting tumor proliferation and the epithelial to mesenchymal transition of cancer cells [70]. Hsa_circRNA_104348 is upregulated in HCC tumor cells and promotes tumor progression and invasion via the Wnt/beta catenin and miR-187–3p/RTKN2 pathways, leading to a poor response to ICIs [71]. CircRHBDD1 promotes a hypoxic environment by the upregulation of glycolysis; its expression has been analyzed in 18 patients with advanced HCC who received anti-PD-1 therapy: after 4 cycles of treatment, non-responders expressed significantly higher levels of circRHBDD1 compared to responders. To confirm the tumorigenic role of circRHBDD1, its inhibition has been studied in a xenograft model: mice with silenced circRHBDD1 cells presented a better response to anti-PD-1 therapy and an increased infiltration of CD8 cells in tumor tissue [72]. Finally, miRNAs located in EVs can derive from any type of cell, including HCC tumor cells and TME; they contribute to chronic hepatic inflammation and tumorigenesis by promoting tumor growth and immune tolerance and by influencing angiogenesis and extrahepatic spread [73]. MiRNAs can target the 3′-UTR regions of PD-L1 mRNA; otherwise, they can act indirectly on PD-1, as observed in other non-HCC solid tumors [74]. Hsa-miR-329-3p inhibits lysine-specific dymethylase 1A (KDM1A), which increases the methylation of Myocyte Enhancer Factor 2D (MEF2D), reducing the expression of PD-L1 and blocking tumor growth, as demonstrated in a xenograft model of HCC [75]. Other miRNAs, such as miR-675-5p, can upregulate or, as in the case of miR-145, miR-194-5p, and MiR-200, downregulate PD-L1 expression in HCC TME [76]. MiR-34a can target the 3′-UTR regions of PD-L1, thereby reducing its ability to bind to PD-1, increasing the infiltration of CD8 T cells in tumor tissue, and activating DCs [77]. MiR-155 upregulates TIM-3, resulting in an enhanced degree of T cell exhaustion [78]. Conversely, the interaction between miR-155 and the lncRNA Nuclear-Enriched Abundant Transcript 1 (NEAT1) can interfere with tumor progression in mice, thus enhancing CD8 T cell cytolysis. Moreover, miR-449c-5p, which is expressed by NK cells, can bind to TIM-3 mRNA causing its degradation and boosting the immune response in HCC TME [79]. Despite the promising role of EVs as possible non-invasive biomarkers, no gold standard for exosome isolation exists; therefore, a remarkable difference in the terms of sensitivity among the different platforms has been reported. The costs of RNA extraction, sequencing, and characterization are other concerns.

3.4. Antidrug Antibodies

Following the administration of ICIs, patients may present a hyperstimulation of the immune response that leads to the production of antidrug antibodies (ADA). The appearance of ADA has been reported following anti-PD-1, anti-PD-L1, and anti-CTLA-4 therapy, with an incidence that differs between the ICIs classes: the higher levels of ADA (13–54% of patients, with NAb in 4–28% of the cases) have been reported in patients treated with Atezolizumab plus Bevacizumab at different doses and regardless of tumor histology [80]. Atezolizumab serum levels can be influenced by ADA exposure, with an average reduction of 22% in treatment activity in the ADA+ group compared with the ADA- group in vitro [80][81]. Atezolizumab’s efficacy is also reduced by its clearance promoted by ADA. ADA production was shown to be independent of tumor type, line of therapy, treatment dose, or administration as monotherapy or in combination with other drugs, while a male sex, Caucasian ethnicity, extended tumor burden, impaired liver function, a high level of serum C-reactive protein, NLR, and lactate dehydrogenase demonstrated a strong correlation with the development of ADA following ICIs therapy [82]. Despite these results, a meta-analysis that enrolled 7736 patients across 11 clinical trials showed no differences in terms of OS and PFS among ADA+ and ADA- patients or in ADA NAb+ versus ADA NAb-patients [83]. Another meta-analysis including 1086 patients treated with Nivolumab confirmed the absence of negative effects caused by ADA in terms of adverse reactions or a loss of efficacy [84]. According to these results, the assay of ADA as a biomarker affecting the response to immunotherapy appears to be controversial and without a demonstrated usefulness.

4. The Gut Microbiota

In patients with cirrhosis, qualitative and quantitative changes in the gut microbiota compositions have been described, with a relative decrease in beneficial bacteria and an increase in pathological ones [85]. These changes are associated with an inflammatory shift in metabolic and immune processes. Indeed, the intestinal barrier’s impairment and pathological bacterial translocation, which are hallmarks of chronic liver diseases, trigger a pro-inflammatory cascade that culminates in liver-focalized and systemic inflammation [86]. With the progression of liver cirrhosis, this chronic injury with persistent inflammation results in immune exhaustion, which favors HCC development [87].

Considering its profound impact on the immune system, several findings demonstrate that the gut microbiota influences the response to immunotherapy. With respect to HCC patients, Zheng et al. [88] analyzed the gut microbial composition of eight patients affected by BCLC stage C HCC receiving Camrelizumab as a second-line treatment after Sorafenib; stool samples were collected before and after 3 to 12 weeks from the beginning of treatment. The baseline gut microbiota were mainly enriched with Bacteroidetes, followed by Firmicutes and Proteobacteria. After an ICI treatment, the patients who showed an objective tumor response presented an overgrowth of Proteobacteria, with a peak after 12 weeks. Among Proteobacteria, Klebsiella pneumoniae was the main species enriched in the responders, while in the non-responders an overabundance of Escherichia coli was reported. Furthermore, the responders presented an increased abundance of several probiotic bacteria such as Lactobacilli, Bifidobacterium dentium, and Streptococcus thermophilus, which are known to positively influence host immunity. In addition, an increase in Ruminococcaceae and A. muciniphila, which are involved in maintaining intestinal barrier integrity, was reported among responders [88]. Another small study collected stool samples from eight patients with HCC who received the anti-PD-1 agent Nivolumab [89]. The analysis of the gut microbiota demonstrated a higher concentration of Clostridia, Prevotella, and Ruminococcaceae in the responders, while Ruminococcus gnavus was predominant in the non-responder group. Citrobacter freundii, Azospirillum spp., and Enterococcus durans were correlated with a good prognosis in terms of OS and PFS, while Escherichia coli, Lactobacillus reuteri, Streptococcus mutans, and Enterococcus faecium predicted a negative outcome. The composition of the gut microbiota in HCC patients was analyzed at the phylum level, reporting an imbalance in the Firmicutes/Bacteroidetes ratio (below 0.5 or upper than 1.5) that occurred more prevalently in the non-responders than in the responders, while a higher mean ratio of Prevotella spp. to Bacteroides spp. (P/B ratio) was clearly identified in the responders; also, the presence of Akkermansia was detected only in the responders. Mao J. et al. [90] analyzed the fecal samples of 65 patients affected by advanced HCC or biliary tract cancer receiving anti-PD-1 therapies. The results showed that the patients with a clinical benefit response (CBR), considered as a partial or complete response to therapy or a stable disease for a minimum of 6 months, had a relative abundance of Lachnospiraceae bacterium-GAM79 and bacteria from Ruminococcaceae family, while the Veillonellales predominated among the patients without any clinical benefit (NCB). Moreover, a higher abundance of Lachnospiraceae bacterium-GAM79 was associated with a longer PFS and OS, while bacteria from the Veillonellaceae family were associated with a worse clinical outcome. A dynamic analysis of the gut microbiota composition also showed a decrease in bacterial diversity among the NCB group. The importance of Ruminococcaceae in predicting ICIs’ efficacy was confirmed by a retrospective Chinese study, in which the enrichment of Clostridiales/Ruminococcaceae was reported in the responders to anti-PD-1 therapy [91]. The study also showed a positive association between a high abundance of Faecalibacterium, belonging to the Ruminococcaceae family, and a longer PFS, while an increased abundance of Bacteroidales was associated with a worse prognosis.

A recent study including 11 Caucasian cirrhotic patients with HCC treated with Tremelimumab and/or Durvalumab demonstrated that those who achieved DCshowed a lower fecal calprotectin concentration and PD-L1 serum levels at baseline; also, the pre-treatment increased the abundance of Akkermansia observed in patients who achieved DC, in parallel with a reduction in Staphylococcus, Neisseria, and Enterobacteriaceae [92]. Dynamic analyses of the microbiota composition during treatment showed an inverse relationship between alpha diversity; Akkermansia to Enterobacteriaceae (AE) ratio, which was considered as a marker of dysbiosis; and calprotectin levels, reinforcing the hypothesis that intestinal inflammation plays a role in influencing clinical outcomes.

Metabolites derived from the microbiome can also contribute to modulating the response to ICIs, and can be used as biomarkers. A prospective study conducted on 52 patients with advanced solid tumors receiving Nivolumab or Pembrolizumab showed a higher fecal and plasma concentration of SCFAs among responders, and fecal propionic acid was identified as a marker of PFS [93]. A possible explanation for the immune-modulating activity of SCFAs is the inhibition of histone deacetylases (HDACs), which has been associated with a higher expression of PD-1 ligands and sustained PD-1 blockade in melanoma models [94][95].  

In patients with Nonalcoholic fatty liver disease (NAFLD)-related HCC, the overabundance of SCFA-producing bacteria was linked to an immunosuppressive condition, with a higher expression of T regs and a reduced cytotoxic CD8+ T cells response. Accordingly, a recent study by Pfister et al. has demonstrated that, in preclinical models of nonalcoholic steatohepatitis (NASH)-induced HCC, the administration of anti-PD-1 agents induced the expansion of intratumoral CD8+ PD1+ T cells, but this phenomenon did not cause tumor regression, suggesting an impairment in the cytotoxic activity of these lymphocytes [96]. Moreover, the administration of an anti-PD-1 agent induced the development of NASH-HCC and led to an overexpression of exhausted T cells. These findings were followed by a meta-analysis of three major studies on the effect of immunotherapy on patients with non-viral HCC, which confirmed a poor prognosis in terms of the OS and PFS in these patients [97]. These results suggest an impaired and aberrant T cell activation in NASH patients that limits ICIs’ application, and that can be explained by a dysfunctional gut–liver axis [96].

In light of these findings, the gut microbiome’s modulation by antibiotics is a key factor to consider, because in various cancers it has been associated with a worse response to immunotherapy [98]. In particular, a recent study reported a worse survival in patients who received a prior antibiotic treatment, but not in those who had been undergoing a current antibiotic treatment, during ICI therapy [99]. However, in a study on murine models of HCC, a vancomycin administration was associated with a reduction of primary to secondary bile acid conversion, due to the depletion of Gram-positive bacteria in the gut. This research showed a positive correlation between the primary bile acid concentration and CXCR6+ NKT cells’ accumulation in the liver favoring tumor inhibition, whereas secondary bile acids had opposite effects [99]. 

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