Integration of exosomal SNORD46 and AL592064.2 with conventional tumor markers improves diagnostic accuracy for colorectal cancer
6 affiliations
- 1Department of Clinical Laboratory, Binhai New Area Hospital of TCM, 300450 Tianjin, China
- 2Department of Surgery, Binhai New Area Hospital of TCM, 300450 Tianjin, China
- 3Chinese Medicine Clinical Research Center, Binhai New Area Hospital of TCM, 300450 Tianjin, China
- 4Department of Clinical Laboratory, The Affiliated Taian City Central Hospital of Qingdao University, Taian, 271000 China
- 5Shandong Provincial Key Medical and Health Laboratory of Anti-drug Resistant drug research, The Affiliated Taian City Central Hospital of Qingdao University, Taian, 271000 China
- 6Departments of Endocrinology, The Affiliated Taian City Central Hospital of Qingdao University, Taian, 271000 China
Abstract
Background: Extracellular vesicle (EV)-derived RNAs may provide complementary molecular information beyond conventional serum tumor markers for colorectal cancer (CRC) diagnosis. This study evaluated the diagnostic value of EV-derived SNORD46 and AL592064.2 alone and in combination with carcinoembryonic antigen (CEA) and carbohydrate antigen 19–9 (CA19-9).
Methods: An exploratory EV small-RNA microarray was performed using samples from three patients with CRC and three healthy donors. The clinical dataset included 160 patients with CRC and 160 healthy donors and was stratified into a model-development cohort (112 CRC and 112 healthy donors) and a frozen internal hold-out validation cohort (48 CRC and 48 healthy donors). A multivariable logistic regression model integrating SNORD46, AL592064.2, CEA, and CA19-9 was developed. The probability threshold was determined in the development cohort and applied unchanged to the validation cohort. Model performance was evaluated using discrimination, calibration, bootstrap validation, stage-specific analysis, reclassification metrics, and exploratory decision-curve analysis.
Results: In the internal hold-out validation cohort, the four-marker model achieved an AUC of 0.910 (95% CI 0.846–0.963), with a sensitivity of 77.1% and specificity of 91.7% at the prespecified probability threshold. The clinical reference model based on CEA and CA19-9 achieved an AUC of 0.801, and the four-marker model demonstrated a significant improvement in discrimination (ΔAUC = 0.109; 95% CI 0.032–0.186; DeLong P = 0.0053). For stage I-II and stage I CRC, the AUCs were 0.879 and 0.842, respectively. Model calibration in the validation cohort showed a calibration slope of 0.759 and a Brier score of 0.118.
Conclusion: The EV-derived SNORD46 and AL592064.2-based four-marker model improved diagnostic performance beyond conventional CEA and CA19-9 in an internally validated cohort. These findings support the potential value of EV-derived small RNA biomarkers as complementary components of future multimarker diagnostic strategies for CRC, while external validation and evaluation in clinically representative populations remain required.
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BibTeX
@article{yuan2026integration,
title = {{Integration of exosomal SNORD46 and AL592064.2 with conventional tumor markers improves diagnostic accuracy for colorectal cancer}},
author = {Ning Yuan and Yingying Ding and Yunping Wang and Changhai Zhang and Xiaochen Pang and Zhijun Zhang and Libo Yang and Xinmei Liang},
journal = {Journal of Cancer Research and Clinical Oncology},
year = {2026},
month = jul,
doi = {10.1007/s00432-026-06579-6},
url = {https://doi.org/10.1007/s00432-026-06579-6},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Integration of exosomal SNORD46 and AL592064.2 with conventional tumor markers improves diagnostic accuracy for colorectal cancer
AU - Ning Yuan
AU - Yingying Ding
AU - Yunping Wang
AU - Changhai Zhang
AU - Xiaochen Pang
AU - Zhijun Zhang
AU - Libo Yang
AU - Xinmei Liang
PY - 2026
DA - 2026/07/31
JO - Journal of Cancer Research and Clinical Oncology
DO - 10.1007/s00432-026-06579-6
UR - https://doi.org/10.1007/s00432-026-06579-6
AB - Background: Extracellular vesicle (EV)-derived RNAs may provide complementary molecular information beyond conventional serum tumor markers for colorectal cancer (CRC) diagnosis. This study evaluated the diagnostic value of EV-derived SNORD46 and AL592064.2 alone and in combination with carcinoembryonic antigen (CEA) and carbohydrate antigen 19–9 (CA19-9). Methods: An exploratory EV small-RNA microarray was performed using samples from three patients with CRC and three healthy donors. The clinical dataset included 160 patients with CRC and 160 healthy donors and was stratified into a model-development cohort (112 CRC and 112 healthy donors) and a frozen internal hold-out validation cohort (48 CRC and 48 healthy donors). A multivariable logistic regression model integrating SNORD46, AL592064.2, CEA, and CA19-9 was developed. The probability threshold was determined in the development cohort and applied unchanged to the validation cohort. Model performance was evaluated using discrimination, calibration, bootstrap validation, stage-specific analysis, reclassification metrics, and exploratory decision-curve analysis. Results: In the internal hold-out validation cohort, the four-marker model achieved an AUC of 0.910 (95% CI 0.846–0.963), with a sensitivity of 77.1% and specificity of 91.7% at the prespecified probability threshold. The clinical reference model based on CEA and CA19-9 achieved an AUC of 0.801, and the four-marker model demonstrated a significant improvement in discrimination (ΔAUC = 0.109; 95% CI 0.032–0.186; DeLong P = 0.0053). For stage I-II and stage I CRC, the AUCs were 0.879 and 0.842, respectively. Model calibration in the validation cohort showed a calibration slope of 0.759 and a Brier score of 0.118. Conclusion: The EV-derived SNORD46 and AL592064.2-based four-marker model improved diagnostic performance beyond conventional CEA and CA19-9 in an internally validated cohort. These findings support the potential value of EV-derived small RNA biomarkers as complementary components of future multimarker diagnostic strategies for CRC, while external validation and evaluation in clinically representative populations remain required.
SN - 0171-5216
SN - 1432-1335
ER -