Ultrasensitive rapid quantitative CRISPR-based detection of cervical cancer tumor marker proteins SCCA and CEA

• This system converts the detection of proteins into the detection of nucleic acids , enabling ultra-sensitive quantitative detection of tumor marker proteins. • This system is rapid, thermostatic, quantitative, easy to operate, and has low requirements for equipment. • This system is modular and highly adjustable, allowing the detection of tumor markers for other cancers by switching antibodies. Cervical cancer is the second leading cause of cancer death among women in developing countries. The most common screening methods for cervical cancer are cytology and HPV DNA detection, but their sensitivity and specificity are limited. Early detection of cervical cancer biomarkers can improve screening accuracy and help clinicians make timely diagnoses, predict treatment responses, and monitor disease progression. Here, we report a dual RPA-CRISPR protein detection system (DRC-PDS) for ultrasensitive quantitative detection of cervical cancer tumor marker proteins SCCA and CEA. This method adapts CRISPR-based nucleic acid detection assays for detecting proteins that utilize Cas12a and Cas13a for dual-target detection in a single tube, enabling the detection of marker proteins as low as 10 aM. At the same time, this method has high specificity. The entire reaction process can be completed in a single step with a handheld instrument without opening the lid, avoiding aerosol contamination during the reaction. Combined with a handheld instrument, the detection system has great potential for use in the community and at the point of temporary care.

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Publication Details

Journal
Chemical Engineering Journal
Published
2025-04-08
DOI
https://doi.org/10.1016/j.cej.2025.162465
Citations
4
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
3.22

Funders

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article

Ultrasensitive rapid quantitative CRISPR-based detection of cervical cancer tumor marker proteins SCCA and CEA

Xiaowen Wang, Xuehui Pang, Lei Chen, Michael G. Mauk
4 citations
Chemical Engineering Journal
CRISPR and Genetic Engineering
3.22
article

Ultrasensitive rapid quantitative CRISPR-based detection of cervical cancer tumor marker proteins SCCA and CEA

Xiaowen Wang, Xuehui Pang, Lei Chen, Michael G. Mauk
article en
4 citations

Abstract

• This system converts the detection of proteins into the detection of nucleic acids , enabling ultra-sensitive quantitative detection of tumor marker proteins. • This system is rapid, thermostatic, quantitative, easy to operate, and has low requirements for equipment. • This system is modular and highly adjustable, allowing the detection of tumor markers for other cancers by switching antibodies. Cervical cancer is the second leading cause of cancer death among women in developing countries. The most common screening methods for cervical cancer are cytology and HPV DNA detection, but their sensitivity and specificity are limited. Early detection of cervical cancer biomarkers can improve screening accuracy and help clinicians make timely diagnoses, predict treatment responses, and monitor disease progression. Here, we report a dual RPA-CRISPR protein detection system (DRC-PDS) for ultrasensitive quantitative detection of cervical cancer tumor marker proteins SCCA and CEA. This method adapts CRISPR-based nucleic acid detection assays for detecting proteins that utilize Cas12a and Cas13a for dual-target detection in a single tube, enabling the detection of marker proteins as low as 10 aM. At the same time, this method has high specificity. The entire reaction process can be completed in a single step with a handheld instrument without opening the lid, avoiding aerosol contamination during the reaction. Combined with a handheld instrument, the detection system has great potential for use in the community and at the point of temporary care.

Chemical Engineering JournalVol. 512
Tiangong University (CN), Shandong Normal University (CN), University of Pennsylvania (US)
National Key Research and Development Program of China
Good health and well-being
Openalex Percentile: Top 9%
CRISPR and Genetic Engineering
3.22
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