Abstract

Ovarian cancer (OC) accounts for about 4% of female cancers globally. While Ki67-immunopositive (Ki67⁺) cell density is commonly used to assess proliferation in OC, the two-dimensional (2D) distribution pattern of these cells is poorly understood. This study explores the 2D distribution pattern of Ki67⁺ cells in primary OC tissues and models the proliferation process to improve our understanding of this hallmark of cancer.

A total of 100 tissue cores, included in a tissue microarray (TMA) representing 5 clear cell carcinomas, 62 serous carcinomas, 10 mucinous adenocarcinomas, 3 endometrioid adenocarcinomas, 10 lymph node metastases from OC, and 10 samples of adjacent normal ovary tissue, were stained using a standardized immunohistochemical protocol. The computer-aided image analysis system assessed the 2D distribution pattern of Ki67⁺ proliferating cells, providing the cell number and density, patterns of randomness, and cell-to-cell closeness. Three computer models were created to simulate behavior and responses, aiming to gain insights into the variations in the proliferation process.

Significant differences in Ki67⁺ cell density were found between low- and high-grade serous carcinoma/mucinous adenocarcinomas (<i>p</i> = 0.003 and <i>p</i> = 0.01, respectively). The Nearest Neighbor Index of Ki67⁺ cells differed significantly between high-grade serous carcinomas and endometrioid adenocarcinomas (<i>p</i> = 0.01), indicating distinct 2D Ki67⁺ distribution patterns. Proxemics analysis revealed significant differences in Ki67⁺ cell-to-cell closeness between low- and high-grade serous carcinomas (<i>p</i> = 0.002). Computer models showed varied effects on the overall organization of Ki67⁺ cells and the ability to preserve the original 2D distribution pattern when altering the location and/or density of Ki67⁺ cells.

Cell proliferation is a hallmark of OCs. This study provides new evidence that investigating the Ki67⁺ cell density and 2D distribution pattern can assist in understanding the proliferation status of OCs. Moreover, our computer models suggest that changes in Ki67⁺ cell density and their location are critical for maintaining the 2D distribution pattern.

EDRN PI Authors

• Bresalier, Bob

Medline Author List

• Bresalier RS
• Chiriva-Internati M
• Grizzi F
• Hegazi MAAA
• Pasqualini F
• Taverna G

PubMed ID

Sources

• Cancer Data Expo

Appears In

Discov Med, 2024 Mar (issue 182)