Gene and Protein Expression of Glycolytic Pathway Markers in Cholangiocarcinoma

• Grant number: 24/20076-6
• Support Opportunities: Scholarships in Brazil - Master
• Start date: April 01, 2025
• End date: February 28, 2026
• Field of knowledge: Health Sciences - Medicine - Pathological Anatomy and Clinical Pathology
• Principal Investigator: Dorotéia Rossi Silva Souza
• Grantee: Marcelly Araujo Ferraz
• Host Institution: Faculdade de Medicina de São José do Rio Preto (FAMERP). Secretaria de Desenvolvimento Econômico (São Paulo - Estado). São José do Rio Preto , SP, Brazil

Abstract

Introduction - Cholangiocarcinoma (CCA) is a malignant biliopancreatic neoplasm, classified by location as intrahepatic (iCCA) and extrahepatic (eCCA). The lack of specific symptoms complicates early diagnosis, limiting treatment options. Metabolic disorders may predispose individuals to primary liver cancer. Given that cancer cells are highly dependent on the glycolytic pathway to meet their energy needs, evaluating molecular markers involved in glucose metabolism associated with CCA may aid in diagnosis, as well as indicate therapeutic targets. Objectives - To analyze gene and protein expression of glucose transporter-1 (GLUT1; gene: SLC2A1), and the enzymes hexokinase II (HK2), phosphofructokinase-1 (PFK-1), lactate dehydrogenase A (LDHA), and pyruvate kinase M2 (PKM2; gene: PKM) in patients with CCA and their correlation with demographic (sex and age), clinical (type II diabetes), biochemical (levels of alkaline phosphatase, gamma-glutamyl transferase, glucose, and transaminases), and anatomopathological profiles (cell differentiation, vascular, perineural, lymphatic invasion, presence of necrosis, metastasis), as well as lifestyle habits (smoking and alcohol consumption). Cases and Methods - Sixty individuals will be studied: 30 patients with CCA and 30 individuals without clinical, biochemical, and histopathological signs of CCA (control group). Clinical, biochemical, anatomopathological data and lifestyle habits will be obtained from electronic medical records. RNA will be extracted from tissue samples (paraffin-embedded) for analysis of gene expression by real-time quantitative polymerase chain reaction (qPCR). Protein expression will be analyzed by immunohistochemistry and quantified using ImageJ software. Statistical analysis will include chi-square (¿²) or Fisher's test, ANOVA with post-hoc analysis, Wilcoxon, and Mann-Whitney tests. An alpha error of 5% will be considered.