AI Article Synopsis
- Gastric cancer management is complicated, but immunotherapy offers hope despite many patients not responding to it and facing side effects.
- Several biomarkers like PD-L1 expression and tumor mutation burden have shown promise in predicting immunotherapy effectiveness, but each has limitations.
- Multi-omics technologies are being explored to discover new predictive biomarkers to better select patients for immunotherapy in gastric cancer, aiming to improve treatment outcomes.
Article Abstract
Gastric cancer presents substantial management challenges, and the advent of immunotherapy has ignited renewed hope among patients. Nevertheless, a significant proportion of patients do not respond to immunotherapy, and adverse events associated with immunotherapy also occur on occasion, underscoring the imperative to identify suitable candidates for treatment. Several biomarkers, including programmed death ligand-1 expression, tumor mutation burden, mismatch repair status, Epstein-Barr Virus infection, circulating tumor DNA, and tumor-infiltrating lymphocytes, have demonstrated potential in predicting the effectiveness of immunotherapy in gastric cancer. However, the quest for the optimal predictive biomarker for gastric cancer immunotherapy remains challenging, as each biomarker carries its own limitations. Recently, multi-omics technologies have emerged as promising platforms for discovering novel biomarkers that may help in selecting gastric cancer patients likely to respond to immunotherapy. The identification of reliable predictive biomarkers for immunotherapy in gastric cancer holds the promise of enhancing patient selection and improving treatment outcomes. In this review, we aim to provide an overview of clinically established biomarkers of immunotherapy in gastric cancer. Additionally, we introduce newly reported biomarkers based on multi-omics studies in the context of gastric cancer immunotherapy, thereby contributing to the ongoing efforts to refine patient stratification and treatment strategies.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10607383 | PMC |
| http://dx.doi.org/10.3390/ijms242015321 | DOI Listing |
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