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Z-score-based approach for differential diagnosis of malignant and benign liver neoplasms using transcriptional biomarkers

Abstract

Mikhail S Chesnokov

Hepatocellular carcinoma (HCC) is the most common and aggressive type of liver tumors. It is usually diagnosed at advanced stages due to lack of clear symptoms and reliable biomarkers. HCC diagnosis is further complicated by high similarity between early HCC stages and benign liver neoplasms, especially hepatocellular adenoma. Efficient methods of HCC identification are required for establishing precise diagnosis and choosing optimal treatment strategy. Our group previously identified five genes (IQGAP3, RAB3B, GPC3, PRRX1 and CENPF) specifically overexpressed in HCC, but not in benign neoplasms or normal liver tissue. Present study evaluates the diagnostic efficiency of combinational indexes generated using expression levels of these genes and z-score approach. We examined paired samples of neoplastic and normal liver tissue collected from 50 HCC patients and 15 patients with hepatocellular adenoma or focal nodular hyperplasia. Gene expression levels were estimated using RT-qPCR, zscores were calculated for single genes and all possible gene combinations. Z-scorebased indexes were statistically processed using cohort comparison tests and ROC analysis to evaluate their usefulness for discerning HCC samples from normal liver tissue and benign neoplasms. IQGAP3, GPC3, PRRX1 and CENPF were significantly (p<0.05) overexpressed in HCC samples, but not in benign neoplasms, when compared to non-tumor liver tissue. RAB3B expression was increased in benign cohort and further elevated in HCC cohort

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