Predictive Biomarkers for Immune-Checkpoint Inhibitor Treatment Response in Patients with Hepatocellular Carcinoma
Abstract
:1. Introduction
2. Biomarkers Related to the Interaction between T Cells and Tumor Cells
2.1. DNA Damage Repair Pathway (dMMR/MSI-H)
2.2. Tumor Antigen Presentation
2.2.1. PD-L1/PD-1 Expression
2.2.2. TMB
2.2.3. Interferon-Gamma Signaling Pathway
2.2.4. Alterations in Genes Related to Immune Function
2.3. Biomarkers Related to the Tumor Microenvironment
Cytokines and Chemokines
2.4. Tumor Infiltrating Lymphocyte (TIL)
3. Circulating Biomarkers
3.1. Circulating Tumor DNA and Circulating Tumor Cells
3.2. Serum Alpha-Fetoprotein (AFP) and CRP
3.3. Neutrophil-to-Lymphocyte Ratio (NLR) and Platelet-to-Lymphocyte Ratio (PLR)
4. Host-Related Biomarkers
4.1. Etiology
4.2. Performance Status and Liver Function
4.3. Disease Status and Tumor Burden
4.4. Gut Microbiome
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
AFP | Alpha-feroprotein |
ALBI | Albumin-bilirubin |
BCLC | Barcelona Clinic Liver Cancer |
BER | Base excision repair |
CNA | Circulating nucleic acids |
CPS | Combined positive score |
CR/PR | Complete response/Partial response |
CTC | Circulating tumor cell |
ctDNA | Circulating tumor DNA |
CTLA | Cytotoxic T-lymphocyte associated protein |
DDR | DNA damage repair |
ECOG | Eastern Cooperative Oncology Group |
FADD | FAS-associated death domain |
GEP | Gene express pattern |
HBV | Hepatitis B virus |
HCC | Hepatocellular carcinoma |
HCV | Hepatitis C virus |
HPV | Human papillomavirus |
HR | Homologous recombination |
ICI | Immune checkpoint inhibitor |
IFN-γ | Interferon-gamma |
IHC | Immunohistochemistry |
IL | Interlurkin |
IRGPI | Immune related gene-based prognostic index |
JAK | Janus kinase |
MGMT | O6-methylguanine–DNA methyltransferase |
MMR | Mismatch repair |
MSI | Microsatellite instability |
NAFLD | Non-alcoholic fatty liver disease |
NASH | Non-alcoholic steatohepatitis |
NGS | Next-generation sequencing |
NLR/PLR | Neutrophil to lymphocyte ratio/Platelet to lymphocyte ratio |
NOS2 | Nitric oxide synthase 2 |
NSCLC | Non-small cell lung cancer |
ORR | Objective response rate |
PD-(L)1 | Programmed death-(ligand)1 |
PFS | Progression-free survival |
POLE/POLD | Polymerase ε/Polymerase δ |
SOCS | Suppressor of cytokine signaling protein |
STAT | Signal transducers and activators of transcription |
TACE | Trans-arterial chemoembolization |
TC | Tumor cells |
TGF-β | Transforming growth factor-β |
TKI | Tyrosine kinase inhibitor |
TME | Tumor microenvironment |
TMB | Tumor mutational burden |
TNF | Tumor necrosis factor |
Treg | Regulatory T cell |
UCC | Urothelial carcinoma |
VEGF | Vascular endothelial growth factor |
WES | Whole exome sequencing |
WGS | Whole genome sequencing |
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IMBRAVE150 [44] | CHECKMATE 459 [6,242] | HIMALAYA [45,207,243] (STRIDE/Durvalumab) | |
---|---|---|---|
Age ≥ 65 | 0.69 (0.49–0.98) | 0.88 (0.68–1.12) | 0.73 (0.58–0.93)/0.83 (0.66–1.06) |
Male | 0.64 (0.49–0.83) | 0.73 (0.61–0.88)/0.86 (0.72–1.03) | |
Asian | 0.62 (0.42–0.93) | 0.74 (0.56–0.98) | 0.68 (0.52–0.89)/0.83 (0.64–1.06) |
ECOG 1 | 0.56 (0.39–0.80) | 0.74 (0.57–0.95)/0.85 (0.66–1.10) | |
BCLC C | 0.63 (0.48–0.82) | 0.78 (0.65–0.95) | 0.76 (0.63–0.91)/0.86 (0.72–1.03) |
AFP | |||
< 400 ng/mL | 0.58 (0.42–0.81) | 0.98 (0.78–1.24) | 0.82 (0.63–1.05)/0.78 (0.61–1.01) |
≥ 400 ng/mL | 0.77 (0.53–1.12) | 0.67 (0.51–0.88) | 0.64 (0.45–0.91)/0.73 (0.53–1.03) |
MVI: No | 0.66 (0.47–0.92) | 0.77 (0.63–0.93)/0.87 (0.72–1.05) | |
EH spread: Yes | 0.60 (0.44–0.81) | 0.67 (0.53–0.84)/0.79 (0.64–0.98) | |
MVI and/orEH spread: YES | 0.64 (0.49–0.85) | 0.74 (0.61–0.90) | 0.73 (0.59–0.89)/0.82 (0.67–1.00) |
HBV | 0.58 (0.40–0.83) | 0.79 (0.59–1.07) | 0.64 (0.48–0.86)/0.78 (0.58–1.04) |
HCV | 0.43 (0.25–0.73) | 0.72 (0.51–1.02) | 1.06 (0.76–1.49)/1.05 (0.75–1.48) |
PD-L1 expression | |||
TC or IC ≥ 1% (SP263) | 0.52 (0.32–0.87) | ||
TC ≥ 1% (28-8, Dako) | 0.80 (0.54–1.19) | ||
TC ≥ 1% (SP263) | 0.85 (0.65–1.11)/0.87 (0.66–1.13) |
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Ji, J.H.; Ha, S.Y.; Lee, D.; Sankar, K.; Koltsova, E.K.; Abou-Alfa, G.K.; Yang, J.D. Predictive Biomarkers for Immune-Checkpoint Inhibitor Treatment Response in Patients with Hepatocellular Carcinoma. Int. J. Mol. Sci. 2023, 24, 7640. https://doi.org/10.3390/ijms24087640
Ji JH, Ha SY, Lee D, Sankar K, Koltsova EK, Abou-Alfa GK, Yang JD. Predictive Biomarkers for Immune-Checkpoint Inhibitor Treatment Response in Patients with Hepatocellular Carcinoma. International Journal of Molecular Sciences. 2023; 24(8):7640. https://doi.org/10.3390/ijms24087640
Chicago/Turabian StyleJi, Jun Ho, Sang Yun Ha, Danbi Lee, Kamya Sankar, Ekaterina K. Koltsova, Ghassan K. Abou-Alfa, and Ju Dong Yang. 2023. "Predictive Biomarkers for Immune-Checkpoint Inhibitor Treatment Response in Patients with Hepatocellular Carcinoma" International Journal of Molecular Sciences 24, no. 8: 7640. https://doi.org/10.3390/ijms24087640
APA StyleJi, J. H., Ha, S. Y., Lee, D., Sankar, K., Koltsova, E. K., Abou-Alfa, G. K., & Yang, J. D. (2023). Predictive Biomarkers for Immune-Checkpoint Inhibitor Treatment Response in Patients with Hepatocellular Carcinoma. International Journal of Molecular Sciences, 24(8), 7640. https://doi.org/10.3390/ijms24087640