An Overview of Predictive Biomarkers and Detection Approaches for Immunotherapy Response in GI Malignancies Article Swipe
Xinyu Chai
,
Yiwen Zhang
,
Zhihui Shi
,
Ruiling Yang
,
Xumin Liu
,
Yueting Zhou
,
Caiyang Li
,
Zhenhui Li
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1111/jgh.16930
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1111/jgh.16930
This review provides an in‐depth exploration of the evolving role of immunotherapy in gastrointestinal (GI) cancers, with a particular focus on immune checkpoint inhibitors (ICIs) and their associated predictive biomarkers. We present a detailed analysis of established biomarkers, such as PD‐L1, microsatellite instability (MSI), tumor mutational burden (TMB), and the tumor microenvironment (TME), as well as emerging biomarkers, including gut microbiota and Epstein–Barr virus (EBV). The predictive value of these biomarkers in guiding clinical decision‐making and optimizing immunotherapy outcomes is thoroughly discussed. Additionally, we highlight recent advancements in biomarker evaluation technologies, including next‐generation sequencing (NGS), multiplex immunohistochemistry, and artificial intelligence (AI)–driven models. These technologies are instrumental in advancing precision medicine by enhancing the accuracy and efficiency of biomarker detection and facilitating personalized treatment approaches. The integration of these predictive biomarkers with advanced detection technologies has significantly improved the clinical efficacy of immunotherapy in GI cancers by addressing challenges such as tumor heterogeneity, immune evasion, and variable patient responses. By providing a deeper understanding of tumor biology and patient‐specific factors, these tools offer the potential to optimize patient selection, treatment regimens, and, ultimately, clinical outcomes. This review underscores the transformative impact of combining predictive biomarkers with cutting‐edge technologies, marking a significant step forward in the field of precision oncology for GI cancer treatment.
Related Topics
Concepts
Medicine
Immunotherapy
Biomarker
Precision medicine
Microsatellite instability
Multiplex
Personalized medicine
Biomarker discovery
Tumor microenvironment
Cancer
Cancer immunotherapy
Oncology
Bioinformatics
Computational biology
Internal medicine
Pathology
Biology
Proteomics
Allele
Biochemistry
Microsatellite
Gene
Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.1111/jgh.16930
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/jgh.16930
- OA Status
- bronze
- References
- 93
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4408349268
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4408349268Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1111/jgh.16930Digital Object Identifier
- Title
-
An Overview of Predictive Biomarkers and Detection Approaches for Immunotherapy Response in GI MalignanciesWork title
- Type
-
reviewOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-03-12Full publication date if available
- Authors
-
Xinyu Chai, Yiwen Zhang, Zhihui Shi, Ruiling Yang, Xumin Liu, Yueting Zhou, Caiyang Li, Zhenhui LiList of authors in order
- Landing page
-
https://doi.org/10.1111/jgh.16930Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/jgh.16930Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/jgh.16930Direct OA link when available
- Concepts
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Medicine, Immunotherapy, Biomarker, Precision medicine, Microsatellite instability, Multiplex, Personalized medicine, Biomarker discovery, Tumor microenvironment, Cancer, Cancer immunotherapy, Oncology, Bioinformatics, Computational biology, Internal medicine, Pathology, Biology, Proteomics, Allele, Biochemistry, Microsatellite, GeneTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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93Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.biomarkers. | 30 |
| abstract_inverted_index.established | 37 |
| abstract_inverted_index.exploration | 6 |
| abstract_inverted_index.instability | 43 |
| abstract_inverted_index.integration | 126 |
| abstract_inverted_index.significant | 200 |
| abstract_inverted_index.ultimately, | 182 |
| abstract_inverted_index.underscores | 187 |
| abstract_inverted_index.advancements | 87 |
| abstract_inverted_index.facilitating | 121 |
| abstract_inverted_index.instrumental | 106 |
| abstract_inverted_index.intelligence | 100 |
| abstract_inverted_index.personalized | 122 |
| abstract_inverted_index.technologies | 104, 134 |
| abstract_inverted_index.(AI)–driven | 101 |
| abstract_inverted_index.Additionally, | 83 |
| abstract_inverted_index.immunotherapy | 12, 78, 142 |
| abstract_inverted_index.significantly | 136 |
| abstract_inverted_index.technologies, | 91, 197 |
| abstract_inverted_index.understanding | 163 |
| abstract_inverted_index.Epstein–Barr | 63 |
| abstract_inverted_index.cutting‐edge | 196 |
| abstract_inverted_index.heterogeneity, | 152 |
| abstract_inverted_index.microsatellite | 42 |
| abstract_inverted_index.transformative | 189 |
| abstract_inverted_index.gastrointestinal | 14 |
| abstract_inverted_index.microenvironment | 52 |
| abstract_inverted_index.decision‐making | 75 |
| abstract_inverted_index.next‐generation | 93 |
| abstract_inverted_index.patient‐specific | 168 |
| abstract_inverted_index.immunohistochemistry, | 97 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5016516907 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I26080491 |
| citation_normalized_percentile.value | 0.10201086 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |