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通过傅里叶变换红外光谱法开发用于术中结直肠癌诊断的可转移通用红外生物标志物。

Developing transferable and universal IR biomarkers for intraoperative colorectal cancer diagnosis via FTIR spectroscopy.

作者信息

Li Ran, Allen Heather C

机构信息

Department of Chemistry and Biochemistry, The Ohio State University, 100 West 18th Avenue, Columbus, OH, 43210, USA.

Department of Pathology, The Ohio State University, Graves Hall, 333 West 10th Ave, Columbus, OH, 43210, USA.

出版信息

Sci Rep. 2025 Jul 2;15(1):22944. doi: 10.1038/s41598-025-05068-z.

Abstract

Histological staining has long been the gold standard for cancer detection, but it is limited by subjectivity and delayed results. Fourier Transform Infrared Spectroscopy (FTIR) has emerged as a promising technique, offering the advantages of objectivity and real-time analysis. Despite its potential, IR biomarkers developed in different studies are based on varying experimental conditions, including different tissue preparation methods, instrumentation, and patient heterogeneity, which hinder their generalizability and transferability. In this study, tissue spectra from various colorectal cancer cases were systematically collected, and IR biomarkers were developed using the band ratios identified in these spectra. Their ability to differentiate cancer-bearing from non-cancer-bearing tissues was evaluated using a machine learning technique. The results show that the top three biomarkers are b1 (1740/1236), b2 (1740/1162) and b3 (1740/1080). When transferring these biomarkers to a new case (approved under the Ohio State University Institutional Review Board # 2011C0085), b1 effectively differentiates tumor, normal, and margin tissues, while the performance of the b2 and b3 are less satisfactory. This suggests that b1 is more robust and sensitive to key molecular features, whereas b2 and b3 are more likely to be affected by tissue heterogeneity or experimental variations. Combining biomarkers enhances tissue differentiation, but the enhancement plateaus after two to three key biomarkers, as adding more introduces overlapping or redundant information. This study provides a benchmark for future research, with the aim of advancing the clinical translation of noninvasive infrared spectroscopy for intraoperative applications.

摘要

组织学染色长期以来一直是癌症检测的金标准,但它受主观性和结果延迟的限制。傅里叶变换红外光谱(FTIR)已成为一种很有前景的技术,具有客观性和实时分析的优点。尽管有其潜力,但不同研究中开发的红外生物标志物是基于不同的实验条件,包括不同的组织制备方法、仪器设备和患者异质性,这阻碍了它们的通用性和可转移性。在本研究中,系统收集了各种结直肠癌病例的组织光谱,并利用这些光谱中确定的波段比值开发了红外生物标志物。使用机器学习技术评估了它们区分癌组织和非癌组织的能力。结果表明,排名前三的生物标志物是b1(1740/1236)、b2(1740/1162)和b3(1740/1080)。当将这些生物标志物应用于一个新病例(经俄亥俄州立大学机构审查委员会#2011C0085批准)时,b1能有效区分肿瘤、正常和边缘组织,而b2和b3的表现则不太令人满意。这表明b1对关键分子特征更稳健、更敏感,而b2和b3更容易受到组织异质性或实验变化的影响。组合生物标志物可增强组织分化,但在两到三个关键生物标志物之后增强效果趋于平稳,因为添加更多生物标志物会引入重叠或冗余信息。本研究为未来研究提供了一个基准,旨在推进术中应用非侵入性红外光谱的临床转化。

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