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Related Concept Videos

Tumor Progression02:07

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
Tumor Progression02:07

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...

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Related Experiment Video

Updated: May 31, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
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Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

Decoding the 2023 FIGO Staging System in Endometrial Cancer: A Practical, Visually Guided Framework for Molecular

Anna Abacjew-Chmylko1,2, Yеlуzavеta Razghоnоva3, Przemyslaw Milosz4

  • 1Department of Gynecology, Obstetrics and Neonatology, Medical University of Gdansk, Gdansk, Poland. anabacjew@gumed.edu.pl.

Current Oncology Reports
|May 28, 2026
PubMed
Summary

The FIGO staging system for endometrial cancer now integrates pathology and molecular data for precise risk assessment. This evolution aids in optimizing treatment selection for better patient outcomes in endometrial cancer management.

Keywords:
Endometrial cancerFIGO 2023 stagingMismatch repair deficiency (MMRd)Molecular classificationP53-abnormal tumorsPOLE-mutated tumors

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Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy
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Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy

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Last Updated: May 31, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
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Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy
05:52

Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy

Published on: August 19, 2021

Area of Science:

  • Gynecologic Oncology
  • Pathology
  • Molecular Diagnostics

Background:

  • The FIGO staging system for endometrial cancer has undergone significant evolution over 50 years.
  • Previous systems relied on clinical and surgical criteria, with revisions in 1988 and 2009.
  • The latest 2023 revision incorporates pathological and molecular factors to better predict disease behavior.

Purpose of the Study:

  • To review the rationale behind the FIGO staging system revisions.
  • To clarify the clinical implications of the updated staging for endometrial cancer.
  • To provide an educational framework for implementing the new staging criteria.

Main Methods:

  • Review of historical FIGO staging revisions and recent updates.
  • Analysis of the 2023 FIGO staging criteria, including anatomic and molecular features.
  • Inclusion of the 2025 ESGO-ESTRO-ESP recommendations regarding estrogen receptor assessment.
  • Development of a visual educational framework with schematic representations and histopathological images.

Main Results:

  • The 2023 FIGO update refines anatomic criteria (myometrial invasion, cervical stroma, LVSI, nodal metastasis discrimination).
  • Molecular subgroups (POLEmut, p53abn, MMRd, NSMP) are formally integrated.
  • Estrogen receptor (ER) assessment is mandated for NSMP, identifying high-risk early-stage disease.
  • The combined approach creates a clinically actionable precision-staging model for endometrial cancer.

Conclusions:

  • The integration of refined anatomic staging with molecular and ER-informed risk stratification enhances prognostic accuracy.
  • This precision-staging model supports multidisciplinary communication and individualized treatment decisions.
  • Consistent application of the evolving framework is crucial for optimizing clinical outcomes in endometrial cancer.