An Overview of Predictive Biomarkers and Detection Approaches for Immunotherapy Response in GI Malignancies

IF 3.7 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY
Xinyu Chai, Yiwen Zhang, Zhihui Shi, Ruiling Yang, Xumin Liu, Yueting Zhou, Caiyang Li, Zhenhui Li
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Abstract

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.

Abstract Image

胃肠道恶性肿瘤免疫治疗反应的预测性生物标志物和检测方法综述。
这篇综述深入探讨了免疫治疗在胃肠道(GI)癌症中的作用,特别关注免疫检查点抑制剂(ICIs)及其相关的预测性生物标志物。我们详细分析了已建立的生物标志物,如PD-L1、微卫星不稳定性(MSI)、肿瘤突变负担(TMB)和肿瘤微环境(TME),以及新兴的生物标志物,包括肠道微生物群和eb病毒(EBV)。深入讨论了这些生物标志物在指导临床决策和优化免疫治疗结果方面的预测价值。此外,我们还重点介绍了生物标志物评估技术的最新进展,包括下一代测序(NGS)、多重免疫组织化学和人工智能(AI)驱动的模型。这些技术通过提高生物标志物检测的准确性和效率以及促进个性化治疗方法,有助于推进精准医疗。将这些预测性生物标志物与先进的检测技术相结合,通过解决肿瘤异质性、免疫逃避和患者反应变化等挑战,显著提高了胃肠道癌症免疫治疗的临床疗效。通过更深入地了解肿瘤生物学和患者特异性因素,这些工具为优化患者选择、治疗方案以及最终的临床结果提供了可能。这篇综述强调了将预测性生物标志物与尖端技术相结合的变革性影响,标志着精准肿瘤学在胃肠道癌症治疗领域迈出了重要一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.90
自引率
2.40%
发文量
326
审稿时长
2.3 months
期刊介绍: Journal of Gastroenterology and Hepatology is produced 12 times per year and publishes peer-reviewed original papers, reviews and editorials concerned with clinical practice and research in the fields of hepatology, gastroenterology and endoscopy. Papers cover the medical, radiological, pathological, biochemical, physiological and historical aspects of the subject areas. All submitted papers are reviewed by at least two referees expert in the field of the submitted paper.
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