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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...
Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
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Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
Cancer Survival Analysis01:21

Cancer Survival Analysis

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Related Experiment Video

Updated: Jun 4, 2026

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
09:08

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer

Published on: January 12, 2020

Predictive Features Specific to FIGO IIIA1 Ovarian Cancer: What Drives Prognosis.

Matteo Bruno1, Davide Arrigo2, Marco Paratore2

  • 1Dipartimento Scienze della Salute della Donna, del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Rome, Italy.

Annals of Surgical Oncology
|June 2, 2026
PubMed
Summary

For FIGO stage IIIA1 ovarian cancer, nodal topography and burden are key prognostic indicators. Systematic lymphadenectomy and tumor microenvironment features aid risk stratification in epithelial ovarian cancer.

Keywords:
Host inflammatory markersEpithelial ovarian cancerLymph node ratioLymphadenectomyNodal metastasisPara‑aortic lymph nodesPrognostic factors

Related Experiment Videos

Last Updated: Jun 4, 2026

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
09:08

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer

Published on: January 12, 2020

Area of Science:

  • Gynecologic Oncology
  • Pathology
  • Surgical Oncology

Background:

  • FIGO stage IIIA1 ovarian cancer is characterized by lymph node-only metastasis, representing a distinct subtype of epithelial ovarian cancer.
  • While IIIA1 patients generally have better outcomes than those with peritoneal spread, prognostic factors within this group are not well-defined.

Purpose of the Study:

  • To review and define the prognostic determinants in FIGO stage IIIA1 ovarian cancer.
  • To identify reliable indicators for risk stratification and guide future treatment strategies.

Main Methods:

  • A narrative review using concept-based searches of eligible reports addressing stage IIIA1 or node-positive subsets of stage III ovarian cancer.
  • No quantitative pooling was performed due to heterogeneity in surgical practices and patient cohorts.

Main Results:

  • Nodal size and FIGO IIIA1(i)/(ii) subdivisions did not consistently predict survival; however, nodal topography showed prognostic relevance.
  • The lymph node ratio (LNR) was the most robust outcome determinant. Systematic lymphadenectomy (≥10-20 nodes) improved staging accuracy and survival.
  • Tumor microenvironment features offered additional prognostic stratification, but IIIA1-specific molecular data were limited.

Conclusions:

  • Nodal topography and burden are the most reliable prognostic indicators in FIGO stage IIIA1 ovarian cancer.
  • Systematic lymphadenectomy benefits selected patients, and tumor microenvironment features provide complementary risk stratification.
  • Future research should focus on genomically characterized IIIA1 cohorts to refine risk-adapted strategies for epithelial ovarian cancer.