Objective: To establish a novel approach for diagnosing early- and midstage esophageal squamous cell carcinoma (ESCC).
Methods: The tumor suppressor gene phospholysine phosphohistidine inorganic pyrophosphate phosphatase (LHPP)-based miRNA signature was identified using next-generation sequencing and 3 biological online prediction systems. This retrospective study established and validated an ESCC prediction model using a test cohort and a validation cohort.
Results: Immunohistochemical staining and real-time quantitative polymerase chain reaction (RT-qPCR) results showed that LHPP protein levels were significantly lower in tissues with early- and midstage ESCC than in adjacent tissues (P < .01). Further, we confirmed that miR-15b-5p, miR-424-5p, miR-497-5p, miR-363-5p, and miR-195-5p inhibited LHPP. These 5 miRNAs were significantly elevated in the plasma of early- and midstage ESCC (P < .05). An ESCC prediction model combining these 5 miRNAs was established. Finally, in the external validation cohort, the model exhibited high discriminative value (sensitivity/specificity: 84.4%/93.3%).
Conclusions: The prediction model has potential implications for diagnosis of early- and midstage ESCC.
Keywords: biomarker; diagnosis; esophageal squamous cell carcinoma; logistic regression model; microRNA; next-generation sequencing.
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