Endometrial Cancer: From Molecular Insights to Treatment
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pathology, Diagnostics, and Therapeutics".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 49
Special Issue Editor
Special Issue Information
Dear Colleagues,
Endometrial cancer is the most common malignancy in the female reproductive tract in developed countries, and its incidence is rising worldwide. While early-stage disease is often associated with favourable outcomes, advanced and recurrent cases remain a significant clinical challenge. In recent years, advances in molecular profiling, immunohistochemistry, and next-generation sequencing have revolutionized our understanding of endometrial carcinogenesis. The integration of molecular classification (such as the TCGA-based subgroups) into clinical practice has paved the way for more personalized and targeted therapeutic approaches.
Traditional risk stratification has relied on histopathologic parameters such as tumor grade, depth of myometrial invasion, and cervical or lymph node involvement. However, recent advances have emphasized the critical role of molecular classification, particularly the TCGA-based subgroups, in redefining risk categories and guiding treatment decisions.
This Special Issue seeks to explore the full spectrum of endometrial cancer, from molecular mechanisms to clinical applications. We welcome submissions on genetic and epigenetic alterations, immunohistochemical biomarkers (e.g., MMR, p53, L1CAM), tumor microenvironment interactions, and immunological targets. Original research, reviews, and clinical studies on novel prognostic markers, therapeutic resistance, molecular diagnostics, and precision oncology are encouraged.
Dr. Giuseppe Angelico
Guest Editor
Manuscript Submission Information
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Keywords
- endometrial cancer
- molecular classification
- TCGA
- precision oncology
- immunotherapy
- targeted therapy
- biomarkers
- tumor microenvironment
- genomics
- personalized medicine
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