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Enhancing clinical precision in lung cancer tissue biopsy through elevated response-threshold of an endoplasmic reticulum-targeted fluorogenic probe

内质网 肺癌 活检 癌症研究 病理 医学 癌症 化学 生物 细胞生物学 内科学
作者
Zhiyang Yuwen,Xing‐Long Chen,Kexin Chen,Tenglong Zou,Guojiang Mao,Hong‐Wen Liu,Lemeng Zhang
出处
期刊:Materials today bio [Elsevier BV]
卷期号:32: 101654-101654 被引量:3
标识
DOI:10.1016/j.mtbio.2025.101654
摘要

Lung carcinoma is the leading cause of mortality globally, posing a significant public health concern. Fluorescent-mediated tumor imaging is emerging as a novel diagnostic and therapeutic approach in clinical practice. Nevertheless, traditional probes lack accuracy in diagnosing tumors due to the overlap in baseline values of certain tumor biomarkers between normal and tumor cells as both exhibit turn-on fluorescence, rendering it impossible to distinguish tumor tissue from normal tissue with high resolution. We introduce a sensing strategy that constructs a probe with an elevated biomarker response-threshold and targeting ability for the endoplasmic reticulum (ER), enabling precise distinction between tumor and normal cells, and successfully develop such a probe. Elevating the response-threshold is advantageous in minimizing interference from baseline values of biomarkers in normal cells. Additionally, targeting the ER ensures that the probe's response range is consistent with the biomarker content in the ER, collectively enhancing differentiation between normal and cancer cells. Using this novel probe, a distinct bright fluorescence signal from tumors could be observed in confocal imaging of tumor tissues from tumor-bearing mice after intravenous injection, in stark contrast to the limited fluorescence emanating from normal tissues. Furthermore, this probe demonstrated exceptional precision in distinguishing clinical lung cancer tissue from para-cancer tissue. This work presents a more reliable tumor detection strategy, capable of accurate diagnosis even when the biomarker is highly expressed in both normal and tumor tissues. It promises to be a valuable tool for future clinical applications, particularly in intraoperative assisted resection.
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