利用生物标志物指导食管癌免疫治疗:迈向精准肿瘤学。

IF 2.5 3区 医学 Q2 ONCOLOGY
Amany I Almars, Sameerah Shaheen, Nahlah M Ghouth, Iman S Abumansour, Asim Abdulaziz Khogeer, Fayez Alsulaimani, Ahmed M Basri, Nasser A Elhawary, Tabinda Hasan, Hailah M Almohaimeed
{"title":"利用生物标志物指导食管癌免疫治疗:迈向精准肿瘤学。","authors":"Amany I Almars, Sameerah Shaheen, Nahlah M Ghouth, Iman S Abumansour, Asim Abdulaziz Khogeer, Fayez Alsulaimani, Ahmed M Basri, Nasser A Elhawary, Tabinda Hasan, Hailah M Almohaimeed","doi":"10.1007/s12094-025-04051-4","DOIUrl":null,"url":null,"abstract":"<p><p>Esophageal cancer (EC) is one of the most serious health issues around the world, ranking seventh among the most lethal types of cancer and eleventh among the most common types of cancer worldwide. Traditional therapies-such as surgery, chemotherapy, and radiation therapy-often yield limited success, especially in the advanced stages of EC, prompting the pursuit of novel and more effective treatment strategies. Immunotherapy has emerged as a promising option; nonetheless, its clinical success is hindered by variable patient responses. This underscores the urgent need for predictive biomarkers that can identify patients most likely to benefit from immunotherapeutic interventions. Biomarker-based patient stratification can improve treatment outcomes, prevent unnecessary exposures, and conserve healthcare resources. This review explores established and emerging biomarkers for predicting response to immunotherapy in EC. We discuss these biomarkers by categorizing them into four major groups: (i) tumor-related biomarkers (PD-L1 expression, tumor mutational burden, and microsatellite instability), (ii) tumor-immune microenvironment-related biomarkers (tumor-infiltrating lymphocytes and immune cell subtypes and ratios), (iii) blood-based biomarkers (circulating tumor DNA, exosomes, and soluble proteins), and (iv) microbiomes (oral, esophageal, and gut microbiomes). In addition, Advancements in biomarker discovery technologies such as high-throughput sequencing, multi-omics approaches, artificial intelligence and machine learning, single-cell analysis, and liquid biopsy are also discussed for their potential to refine biomarker identification and clinical application.</p>","PeriodicalId":50685,"journal":{"name":"Clinical & Translational Oncology","volume":" ","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Harnessing biomarkers to guide immunotherapy in esophageal cancer: toward precision oncology.\",\"authors\":\"Amany I Almars, Sameerah Shaheen, Nahlah M Ghouth, Iman S Abumansour, Asim Abdulaziz Khogeer, Fayez Alsulaimani, Ahmed M Basri, Nasser A Elhawary, Tabinda Hasan, Hailah M Almohaimeed\",\"doi\":\"10.1007/s12094-025-04051-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Esophageal cancer (EC) is one of the most serious health issues around the world, ranking seventh among the most lethal types of cancer and eleventh among the most common types of cancer worldwide. Traditional therapies-such as surgery, chemotherapy, and radiation therapy-often yield limited success, especially in the advanced stages of EC, prompting the pursuit of novel and more effective treatment strategies. Immunotherapy has emerged as a promising option; nonetheless, its clinical success is hindered by variable patient responses. This underscores the urgent need for predictive biomarkers that can identify patients most likely to benefit from immunotherapeutic interventions. Biomarker-based patient stratification can improve treatment outcomes, prevent unnecessary exposures, and conserve healthcare resources. This review explores established and emerging biomarkers for predicting response to immunotherapy in EC. We discuss these biomarkers by categorizing them into four major groups: (i) tumor-related biomarkers (PD-L1 expression, tumor mutational burden, and microsatellite instability), (ii) tumor-immune microenvironment-related biomarkers (tumor-infiltrating lymphocytes and immune cell subtypes and ratios), (iii) blood-based biomarkers (circulating tumor DNA, exosomes, and soluble proteins), and (iv) microbiomes (oral, esophageal, and gut microbiomes). In addition, Advancements in biomarker discovery technologies such as high-throughput sequencing, multi-omics approaches, artificial intelligence and machine learning, single-cell analysis, and liquid biopsy are also discussed for their potential to refine biomarker identification and clinical application.</p>\",\"PeriodicalId\":50685,\"journal\":{\"name\":\"Clinical & Translational Oncology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical & Translational Oncology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s12094-025-04051-4\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical & Translational Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12094-025-04051-4","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

食管癌(EC)是世界上最严重的健康问题之一,在最致命的癌症类型中排名第七,在全球最常见的癌症类型中排名第十一。传统的治疗方法,如手术、化疗和放疗,通常效果有限,特别是在晚期的EC,这促使人们寻求新的更有效的治疗策略。免疫疗法已经成为一种很有前途的选择;尽管如此,它的临床成功仍受到患者反应不一的阻碍。这强调了对预测性生物标志物的迫切需求,这些生物标志物可以识别最有可能从免疫治疗干预中受益的患者。基于生物标志物的患者分层可以改善治疗结果,防止不必要的暴露,并节省医疗资源。本文综述了用于预测EC免疫治疗反应的已建立的和新兴的生物标志物。我们将这些生物标志物分为四大类:(i)肿瘤相关生物标志物(PD-L1表达、肿瘤突变负担和微卫星不稳定性),(ii)肿瘤免疫微环境相关生物标志物(肿瘤浸润淋巴细胞和免疫细胞亚型和比例),(iii)基于血液的生物标志物(循环肿瘤DNA、外泌体和可溶性蛋白),以及(iv)微生物组(口腔、食管和肠道微生物组)。此外,还讨论了生物标志物发现技术的进展,如高通量测序,多组学方法,人工智能和机器学习,单细胞分析和液体活检,以改进生物标志物鉴定和临床应用的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Harnessing biomarkers to guide immunotherapy in esophageal cancer: toward precision oncology.

Esophageal cancer (EC) is one of the most serious health issues around the world, ranking seventh among the most lethal types of cancer and eleventh among the most common types of cancer worldwide. Traditional therapies-such as surgery, chemotherapy, and radiation therapy-often yield limited success, especially in the advanced stages of EC, prompting the pursuit of novel and more effective treatment strategies. Immunotherapy has emerged as a promising option; nonetheless, its clinical success is hindered by variable patient responses. This underscores the urgent need for predictive biomarkers that can identify patients most likely to benefit from immunotherapeutic interventions. Biomarker-based patient stratification can improve treatment outcomes, prevent unnecessary exposures, and conserve healthcare resources. This review explores established and emerging biomarkers for predicting response to immunotherapy in EC. We discuss these biomarkers by categorizing them into four major groups: (i) tumor-related biomarkers (PD-L1 expression, tumor mutational burden, and microsatellite instability), (ii) tumor-immune microenvironment-related biomarkers (tumor-infiltrating lymphocytes and immune cell subtypes and ratios), (iii) blood-based biomarkers (circulating tumor DNA, exosomes, and soluble proteins), and (iv) microbiomes (oral, esophageal, and gut microbiomes). In addition, Advancements in biomarker discovery technologies such as high-throughput sequencing, multi-omics approaches, artificial intelligence and machine learning, single-cell analysis, and liquid biopsy are also discussed for their potential to refine biomarker identification and clinical application.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
6.20
自引率
2.90%
发文量
240
审稿时长
1 months
期刊介绍: Clinical and Translational Oncology is an international journal devoted to fostering interaction between experimental and clinical oncology. It covers all aspects of research on cancer, from the more basic discoveries dealing with both cell and molecular biology of tumour cells, to the most advanced clinical assays of conventional and new drugs. In addition, the journal has a strong commitment to facilitating the transfer of knowledge from the basic laboratory to the clinical practice, with the publication of educational series devoted to closing the gap between molecular and clinical oncologists. Molecular biology of tumours, identification of new targets for cancer therapy, and new technologies for research and treatment of cancer are the major themes covered by the educational series. Full research articles on a broad spectrum of subjects, including the molecular and cellular bases of disease, aetiology, pathophysiology, pathology, epidemiology, clinical features, and the diagnosis, prognosis and treatment of cancer, will be considered for publication.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信