Aim and Scope
Aim: The Journal of Precision Molecular and Clinical Oncology (JPMCO) is an international, peer-reviewed, open-access journal dedicated to advancing precision cancer medicine through the integration of molecular science, clinical oncology, and translational research. The journal aims to provide a scholarly platform for oncologists, molecular biologists, pathologists, geneticists, and healthcare researchers to publish innovative findings that enhance cancer diagnosis, treatment, prevention, and patient outcomes. JPMCO promotes interdisciplinary research that bridges laboratory discoveries with clinical applications, supporting the development of personalized and evidence-based cancer care.
Expanded scope:
Precision Oncology & Personalized Cancer Therapy: Research focused on biomarker-driven treatment strategies, targeted therapeutics, immunotherapy, pharmacogenomics, and individualized cancer management approaches that optimize therapeutic efficacy and patient outcomes.
Cancer Genomics & Molecular Oncology: Studies investigating genomic alterations, epigenetic regulation, transcriptomics, proteomics, tumor heterogeneity, and molecular pathways involved in cancer initiation, progression, metastasis, and treatment resistance.
Clinical Oncology & Therapeutic Advances: Original research, clinical investigations, and evidence-based studies covering medical oncology, surgical oncology, radiation oncology, multidisciplinary cancer care, and emerging treatment modalities.
Cancer Diagnostics & Biomarker Research: Development and validation of molecular diagnostics, liquid biopsies, circulating tumor biomarkers, companion diagnostics, and innovative technologies that support early detection, prognosis, and treatment monitoring.
Translational Cancer Research: Studies that translate fundamental cancer biology into clinical applications, including preclinical models, therapeutic target identification, experimental therapeutics, and bench-to-bedside innovations.
Computational Oncology & Digital Health: Research exploring bioinformatics, artificial intelligence, machine learning, systems oncology, predictive modeling, and data-driven approaches that improve cancer diagnosis, prognosis, and therapeutic decision-making.
