Detecting microsatellite instability in cancer <i>via</i> multiplexed orthogonal gap-enhanced Raman tags

Microsatellite instability (MSI) is a hallmark of colorectal cancer in immunotherapy, whose phenotypes mainly involve four mismatch repair (MMR) proteins (MlH1, MSH2, MSH6 and PMS2). Since these MMR proteins are highly interdependent, simultaneous detection of these proteins rather than separate detection in cancer is vital to accurately distinguish the MSI phenotypes. In this study, we fabricated four orthogonal gap-enhanced Raman tag (O-GERT) flavors with high sensitivity, superb photostability, and completely separated interference-free signal readouts. With antibody functionalization, these multicolored O-GERTs allowed one-shot detection of these four MMR proteins in cancer tissues with high specificity and spectral resolution. Based on quantitative Raman imaging, these cancer tissues were classified into microsatellite stable (MSS) or high-frequency MSI (MSI-H) subtypes. The detected MSI-H ratios for colorectal, breast and gastric cancers were 13.3%, 6.7% and 3.3%, respectively. Moreover, the correlation between the expression levels of these MMR proteins in colorectal cancer and related clinicopathologic parameters in these subtypes was established for the first time. We further demonstrated that MSI in cancer can serve as a tool for screening Lynch syndrome (a genetic disorder) and predicting potential candidates for immunotherapy by PD1/PD-L1 blockade. To the best of our knowledge, this is the first example of quantitative multiplexed Raman imaging for fast detection of MSI in cancer.

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Publication Details

Journal
Chemical Science
Published
2025-01-01
DOI
https://doi.org/10.1039/d5sc01912e
Citations
3
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
2.81

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article

Detecting microsatellite instability in cancer via multiplexed orthogonal gap-enhanced Raman tags

Lingxin Chen, Guowei Fu, Rong Wu, Changjun Lv et al.
3 citations
Chemical Science
Cancer Genomics and Diagnostics
2.81
article

Detecting microsatellite instability in cancer via multiplexed orthogonal gap-enhanced Raman tags

Lingxin Chen, Guowei Fu, Rong Wu, Changjun Lv, Zhiyang Zhang, Jin Li, Xiaoyan Wang, Qian Zhang
article en
3 citations

Abstract

Microsatellite instability (MSI) is a hallmark of colorectal cancer in immunotherapy, whose phenotypes mainly involve four mismatch repair (MMR) proteins (MlH1, MSH2, MSH6 and PMS2). Since these MMR proteins are highly interdependent, simultaneous detection of these proteins rather than separate detection in cancer is vital to accurately distinguish the MSI phenotypes. In this study, we fabricated four orthogonal gap-enhanced Raman tag (O-GERT) flavors with high sensitivity, superb photostability, and completely separated interference-free signal readouts. With antibody functionalization, these multicolored O-GERTs allowed one-shot detection of these four MMR proteins in cancer tissues with high specificity and spectral resolution. Based on quantitative Raman imaging, these cancer tissues were classified into microsatellite stable (MSS) or high-frequency MSI (MSI-H) subtypes. The detected MSI-H ratios for colorectal, breast and gastric cancers were 13.3%, 6.7% and 3.3%, respectively. Moreover, the correlation between the expression levels of these MMR proteins in colorectal cancer and related clinicopathologic parameters in these subtypes was established for the first time. We further demonstrated that MSI in cancer can serve as a tool for screening Lynch syndrome (a genetic disorder) and predicting potential candidates for immunotherapy by PD1/PD-L1 blockade. To the best of our knowledge, this is the first example of quantitative multiplexed Raman imaging for fast detection of MSI in cancer.

Chemical ScienceVol. 16(24)
Binzhou Medical University (CN), Shandong University of Aeronautics (CN), Shaoxing University (CN), Chinese Academy of Sciences (CN), Yantai Institute of Coastal Zone Research (CN), Wuyi University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 10%
Cancer Genomics and Diagnostics
2.81
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