Tumor-Infiltrating Lymphocytes in Endometrial Cancer

NCT06976333 | Completed DMC

• 1 other identifier: 118.0043.1.433.2024
• Study Type: observational
• Target: 52
• Locations: 1 country
• Sites: 1

Brief Summary

Endometrial cancer (EC) is a leading cancer among women globally. The tumor microenvironment in EC is characterized by complex interactions between cancer cells and immune components. Among these proteins, CD133, WNT-1, and mTOR have emerged as key molecular markers with potential prognostic and therapeutic implications in EC. Understanding the association between these molecular alterations and the immune contexture of EC can provide valuable insights into EC biology and lead to the identification of novel therapeutic targets. In this study, the spatial organization of tumor-infiltrating lymphocytes (TILs) in EC and their correlations with tumor grade, stage, and subcellular CD133, WNT-1, and mTOR expression were investigated. Artificial intelligence-assisted image analysis was performed to quantify TIL metrics, including TIL percentage, grey level co-occurrence matrix (GLCM M1 and M2) parameters, and fractal dimension (FD).

Conditions

Endometrium Cancer; Tumor Infiltration

Keywords

endometrial cancer; tumor-infiltrating lymphocytes; response biomarkers; artificial intelligence; immune microenvironment

Outcome Measures

Primary Outcomes (4)

• TIL percentage [%]

  TIL percentage is the area occupied by lymphocytes divided by the cancer area, expressed as a percentage \[%\]

  up to 6 months

• GLCM M1 (×10⁶)

  GLCM is a second-order statistical method for texture feature extraction. Structured images typically contain numerous pixel pairs with co-occurring low- and high-intensity values. After GLCM calculation, different weights were applied to each matrix element to derive two measures: M1 and M2, representing areas with low and high intensities, respectively. Lower M1 and higher M2 values characterize more structured images with distinct TIL patterns. GLCM M1 values are scaled and expressed in millions (×10⁶), with lower values indicating more structured TIL patterns.

  up to 6 months

• FD

  FD provides a statistical index of pattern complexity in geometric structures. Higher FD values thus indicate more structured and complex TIL distribution patterns

  up to 6 months

• GLCM M2 (×10³)

  GLCM is a second-order statistical method for texture feature extraction. Structured images typically contain numerous pixel pairs with co-occurring low- and high-intensity values. After GLCM calculation, different weights were applied to each matrix element to derive two measures: M1 and M2, representing areas with low and high intensities, respectively. Lower M1 and higher M2 values characterize more structured images with distinct TIL patterns. GLCM M2 values are scaled and expressed in thousands (×10³), with higher values indicating increased TIL clustering.

  up to 6 months

Study Arms (2)

Low-grade Endometrial Cancer

Histological grade G1 and G2

Diagnostic Test: Tumor-infliltrating lymphocyte (TIL) percentage; Diagnostic Test: Grey level co-occurrence matrix (GLCM); Diagnostic Test: Fractal dimension (FD)

High-grade Endometrial Cancer

Histological grade G3

Diagnostic Test: Tumor-infliltrating lymphocyte (TIL) percentage; Diagnostic Test: Grey level co-occurrence matrix (GLCM); Diagnostic Test: Fractal dimension (FD)

Interventions

Tumor-infliltrating lymphocyte (TIL) percentage DIAGNOSTIC_TEST

TIL percentage was calculated as the area occupied by lymphocytes divided by the cancer area, expressed as a percentage \[%\]

High-grade Endometrial Cancer; Low-grade Endometrial Cancer

Grey level co-occurrence matrix (GLCM) DIAGNOSTIC_TEST

The GLCM is a second-order statistical method for texture feature extraction. Structured images typically contain numerous pixel pairs with co-occurring low- and high-intensity values. After GLCM calculation, different weights were applied to each matrix element to derive two measures: M1 and M2, representing areas with low and high intensities, respectively. Lower M1 and higher M2 values characterized more structured images with distinct TIL patterns.

High-grade Endometrial Cancer; Low-grade Endometrial Cancer

Fractal dimension (FD) DIAGNOSTIC_TEST

Quantification of the complexity of TIL

High-grade Endometrial Cancer; Low-grade Endometrial Cancer

Eligibility Criteria

• Age: 18 Years+
• Sex: female
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Archival properly stored formalin-fixed paraffin-embedded tissue blocks from endometrial cancer tissue of women age at leat 18.

You may qualify if:

• confirmed diagnosis of EC
• adequate quality of archival material
• absence of prior neoadjuvant treatment
• complete medical documentation

You may not qualify if:

• none

Sponsors & Collaborators

• Jagiellonian University: lead

Study Sites (1)

Jagiellonian University

Krakow, Poland

Location

Biospecimen

Retention: SAMPLES WITHOUT DNA

archival formalin-fixed paraffin-embedded tissue blocks

MeSH Terms

Conditions

Endometrial Neoplasms

Condition Hierarchy (Ancestors)

Uterine Neoplasms; Genital Neoplasms, Female; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Uterine Diseases; Genital Diseases, Female; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Genital Diseases

Study Officials

• Milosz Pietrus, PhD

  Jagiellonian University

  STUDY CHAIR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: May 9, 2025
• First Posted: May 16, 2025
• Study Start: December 1, 2024
• Primary Completion: April 30, 2025
• Study Completion: May 8, 2025
• Last Updated: May 16, 2025

Record last verified: 2025-05

Locations

PL (1)