Current Progress on Predictive Biomarkers for Response to Immune Checkpoint Inhibitors in Gastric Cancer: How to Maximize the Immunotherapeutic Benefit?
Abstract
:Simple Summary
Abstract
1. Introduction
2. Recent Clinical Trials of ICIs in Gastric Cancer
2.1. Anti-PD-1 Antibody
2.2. Anti-PD-L1 Antibody
2.3. Anti-CTLA-4 Antibody
3. Predictive Biomarkers for ICIs
3.1. PD-L1
3.2. Mismatch Repair Deficiency/Microsatellite Instability (dMRR/MSI)
3.3. Tumor Mutation Burden (TMB)
3.4. EBV-Positive Status
3.5. Tumor Immune Microenvironment (TIME)
3.6. Specific Genetic Mutations
3.7. Gut Microbiota
3.8. Liquid Biopsy Biomarkers
3.9. Comprehensive Predictive Effect of Biomarkers
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Clinical Trial | Reference | Country | Line | Stage | CPS | Study Design | mOS (Month) | mPFS (Month) | ORR (%) |
---|---|---|---|---|---|---|---|---|---|
ATRATION-2 | [21] | Japan, South Korea, Taiwan | Third or later | III | all | Nivolumab | 5.3 | - | - |
Placebo | 4.1 | - | - | ||||||
ATRATION-4 | [22] | Japan, South Korea, Taiwan | first | III | all | Nivolumab + chemo | 17.5 | 10.5 | - |
Placebo + chemo | 17.2 | 8.3 | - | ||||||
CheckMate-649 | [23] | 29 countries | first | III | CPS ≥ 5 | Nivolumabm + chemo | 14.4 | 8.3 | 60 |
chemo | 11.1 | 6.1 | 45 | ||||||
KEYNOTE-059 | [24] | 16 countries | Third or later | II | CPS ≥ 1 | pembrolizumab | - | - | 15.5 |
CPS < 1 | - | - | 6.4% | ||||||
KEYNOTE-061 | [25] | 30 countries | second | III | CPS ≥ 1 | Pembrolizumab | 9.1 | 1.5 | - |
Paclitaxel | 8.3 | 4.1 | - | ||||||
KEYNOTE-062 | [26] | 29 countries | first | III | CPS ≥ 1 | Pembrolizumab | 10.6 | 2.0 | 14.80 |
Pembrolizumab + chemo | 12.1 | 6.9 | 48.60 | ||||||
placebo + chemo | 11.1 | 6.4 | 37.20 | ||||||
KEYNOTE-859 | [27] | 31 countries | first | III | CPS ≥ 1 | Pembrolizumab + chemo | 12.9 | 6.9 | 51.3 |
placebo + chemo | 11.5 | 5.6 | 42 | ||||||
KEYNOTE-811 | [28] | 20 countries | first | III | CPS ≥ 1 | Pembrolizumab + trastuzumab + c hemo | - | - | 74.4 |
Placebo + trastuzumab + chemo | - | - | 51.9 | ||||||
ORIENT-16 | [29] | China | first | III | CPS ≥ 5 | Sintilimab + chemo | 18.4 | 7.7 | - |
Placebo + chemo | 12.9 | 5.8 | - |
Clinical Trial | Detection Method | Numbers of Patients | Cut-Off Value | TMB-H (%) |
---|---|---|---|---|
NCT0291543 | NK | 54 | ≥12 muts/Mb | 22% |
KEYNOTE-601 | WES | 420 | ≥175 muts/Exons | 18% |
KEYNOTE-601 | FoudationOneCDx | 204 | ≥10 muts/Mb | 17% |
KEYNOTE-602 | FoudationOneCDx | 306 | ≥10 muts/Mb | 16% |
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Liu, Y.; Hu, P.; Xu, L.; Zhang, X.; Li, Z.; Li, Y.; Qiu, H. Current Progress on Predictive Biomarkers for Response to Immune Checkpoint Inhibitors in Gastric Cancer: How to Maximize the Immunotherapeutic Benefit? Cancers 2023, 15, 2273. https://doi.org/10.3390/cancers15082273
Liu Y, Hu P, Xu L, Zhang X, Li Z, Li Y, Qiu H. Current Progress on Predictive Biomarkers for Response to Immune Checkpoint Inhibitors in Gastric Cancer: How to Maximize the Immunotherapeutic Benefit? Cancers. 2023; 15(8):2273. https://doi.org/10.3390/cancers15082273
Chicago/Turabian StyleLiu, Yongqing, Pengbo Hu, Liang Xu, Xiuyuan Zhang, Zhou Li, Yiming Li, and Hong Qiu. 2023. "Current Progress on Predictive Biomarkers for Response to Immune Checkpoint Inhibitors in Gastric Cancer: How to Maximize the Immunotherapeutic Benefit?" Cancers 15, no. 8: 2273. https://doi.org/10.3390/cancers15082273
APA StyleLiu, Y., Hu, P., Xu, L., Zhang, X., Li, Z., Li, Y., & Qiu, H. (2023). Current Progress on Predictive Biomarkers for Response to Immune Checkpoint Inhibitors in Gastric Cancer: How to Maximize the Immunotherapeutic Benefit? Cancers, 15(8), 2273. https://doi.org/10.3390/cancers15082273