Biomolecules · 2026
Serum microRNA Profiles Reflect Differentiation Status and Age in Early Gastric Cancer.
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Shekfeh Marwa, Konaté Mariam M, Sankaran Hari, Li Ming-Chung, Zhao Yingdong
Аннотация
BACKGROUND: Age at diagnosis and histologic differentiation are clinically relevant in early gastric cancer (GC), as poorly differentiated tumors and those diagnosed in younger patients often demonstrate more aggressive characteristics. Serum microRNAs (miRNAs) may provide insights into the molecular basis of these features.
METHODS: We compared expression profiles between undifferentiated and differentiated early GC cases to identify differentially expressed miRNAs (DEmiRNAs) and associated enriched pathways. Using Lasso regression, we developed and cross-validated a histologic differentiation classifier based on miRNA profiles from 1399 early GC serum samples. Finally, cancer-specific miRNA differences between adolescent and young adult (AYA) and non-AYA patients were evaluated using samples from cancer cases and normal controls.
RESULTS: We identified 75 differentiation-associated DEmiRNAs targeting genes enriched in cancer hallmark pathways such as TP53 and PI3K/AKT/mTOR signaling. In the validation set, the combined Lasso model predicted differentiation status with a sensitivity of 69.2%, specificity of 75.3%, positive predictive value (PPV) of 66.9%, negative predictive value (NPV) of 77.2%, an overall accuracy of 73.1%, and an area under the curve (AUC) of 79.7%. Comparison of AYA and non-AYA groups identified 52 cancer-specific and age-related miRNAs. Notably, three components of a previously reported four-miRNA GC diagnostic signature were significantly associated with age.
CONCLUSIONS: Age-related variation in miRNA expression suggests that patient age may influence the performance of the existing four-miRNA diagnostic signature in early GC. Overall, our findings demonstrate the utility of miRNA profiling for predicting differentiation status in early GC and reveal age-associated variation in cancer-specific miRNAs.
METHODS: We compared expression profiles between undifferentiated and differentiated early GC cases to identify differentially expressed miRNAs (DEmiRNAs) and associated enriched pathways. Using Lasso regression, we developed and cross-validated a histologic differentiation classifier based on miRNA profiles from 1399 early GC serum samples. Finally, cancer-specific miRNA differences between adolescent and young adult (AYA) and non-AYA patients were evaluated using samples from cancer cases and normal controls.
RESULTS: We identified 75 differentiation-associated DEmiRNAs targeting genes enriched in cancer hallmark pathways such as TP53 and PI3K/AKT/mTOR signaling. In the validation set, the combined Lasso model predicted differentiation status with a sensitivity of 69.2%, specificity of 75.3%, positive predictive value (PPV) of 66.9%, negative predictive value (NPV) of 77.2%, an overall accuracy of 73.1%, and an area under the curve (AUC) of 79.7%. Comparison of AYA and non-AYA groups identified 52 cancer-specific and age-related miRNAs. Notably, three components of a previously reported four-miRNA GC diagnostic signature were significantly associated with age.
CONCLUSIONS: Age-related variation in miRNA expression suggests that patient age may influence the performance of the existing four-miRNA diagnostic signature in early GC. Overall, our findings demonstrate the utility of miRNA profiling for predicting differentiation status in early GC and reveal age-associated variation in cancer-specific miRNAs.