Gastroenteropancreatic neuroendocrine tumors in 2025: From molecular profiling to artificial intelligence-driven therapy

doi:10.4251/wjgo.v18.i3.114205

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World Journal of Gastrointestinal Oncology

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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Gastrointest Oncol. Mar 15, 2026; 18(3): 114205
Published online Mar 15, 2026. doi: 10.4251/wjgo.v18.i3.114205

Gastroenteropancreatic neuroendocrine tumors in 2025: From molecular profiling to artificial intelligence-driven therapy

Marcio J Concepción-Zavaleta, Jenyfer M Fuentes-Mendoza, José Paz-Ibarra, Luis A Concepción-Urteaga, Jeny Justina Mendoza-Godoy, Jhean G Gonzáles-Yovera, Juan Eduardo Quiroz-Aldave, Frederick Massucco-Revoredo, Augusto Aldave-Herrera, Regina Aquino-Salverredy

Marcio J Concepción-Zavaleta, Jenyfer M Fuentes-Mendoza, Grupo de Investigación en Neurociencias, Metabolismo, Efectividad Clínica y Salud Pública, Universidad Científica del Sur, Lima 15072, Peru

José Paz-Ibarra, School of Medicine, National University of San Marcos, Lima 15081, Peru

José Paz-Ibarra, Department of Endocrinology, Edgardo Rebagliati Martins National Hospital, Lima 15072, Peru

Luis A Concepción-Urteaga, School of Medicine, National University of Trujillo, Trujillo 13011, La Libertad, Peru

Jeny Justina Mendoza-Godoy, School of Medicine, Franklin Roosevelt Private University of Huancayo, Huancayo 120001, Junín, Peru

Jhean G Gonzáles-Yovera, Department of Gastroenterology, Guillermo Almenara Irigoyén National Hospital, Lima 15018, Peru

Juan Eduardo Quiroz-Aldave, Division of Medicine, Chepén Support Hospital, Chepén 13871, Peru

Frederick Massucco-Revoredo, Department of Endocrinology, National Guillermo Almenara Hospital, Lima 15033, Peru

Augusto Aldave-Herrera, Department of Gastroenterology, Hospital Regional Docente de Trujillo, Lima 13001, Peru

Regina Aquino-Salverredy, Department of Internal Medicine, Hospital Regional Docente de Trujillo, Lima 13001, Peru

Co-first authors: Marcio J Concepción-Zavaleta and Jenyfer M Fuentes-Mendoza.

Author contributions: Concepción-Zavaleta MJ and Fuentes-Mendoza JM conceptualized and designed the review and contributed equally as co-first authors; Paz-Ibarra J and Concepción-Urteaga LA supervised the project and provided critical revisions; Mendoza-Godoy JJ, Gonzáles-Yovera JG, Quiroz-Aldave JE, and Massucco-Revoredo F contributed to the literature review, data analysis, and drafting of sections of the manuscript; Aldave-Herrera A and Aquino-Salverredy R contributed to clinical interpretation, editing, and final approval. All authors read and approved the submitted version.

Conflict-of-interest statement: The authors report no relevant conflicts of interest for this article.

Corresponding author: Marcio J Concepción-Zavaleta, MSc, Grupo de Investigación en Neurociencias, Metabolismo, Efectividad Clínica y Salud Pública, Universidad Científica del Sur, 19 Panamericana Sur Km, Villa El Salvador, Lima 15072, Peru. mconcepcion@cientifica.edu.pe

Received: September 15, 2025
Revised: November 10, 2025
Accepted: December 23, 2025
Published online: March 15, 2026
Processing time: 179 Days and 19 Hours

Core Tip

Core Tip: Gastroenteropancreatic neuroendocrine tumors exhibit marked biological and clinical heterogeneity that extends beyond traditional histological classification. While molecular features distinguishing well-differentiated neuroendocrine tumors from poorly differentiated carcinomas provide a critical biological framework, they represent only one dimension of disease complexity. This review highlights how the integration of molecular profiling, artificial intelligence–based analytics, radiomics, liquid biopsy biomarkers, including NETest 2.0, and theranostic imaging enables a more comprehensive and dynamic approach to diagnosis, risk stratification, and therapeutic decision-making. We propose an integrative precision medicine model that addresses tumor heterogeneity and supports individualized, data-driven management strategies across the full spectrum of gastroenteropancreatic neuroendocrine tumors.