Proliferative Markers in Breast Cancer and Chemotherapy Implications: A Comprehensive Review Publisher



Salahiniri A¹ ; Zarand P¹ ; Shojaeian F² ; Mansouri N¹ ; Yazdani O¹ ; Esbati R¹ ; Safavinaini SAA^{1, 3} ; Jahanbin B⁴ Show Affiliations
Source: Health Science Reports Published:2025

Abstract

Background and Aims: Breast cancer is the most common cancer and a leading cause of cancer-related death among women globally. Determining which patients will benefit from chemotherapy remains challenging. Proliferative markers such as Ki-67, mini chromosome maintenance (MCM) proteins, and proliferating cell nuclear antigen (PCNA) offer valuable insights into tumor growth and treatment response. This review evaluates their clinical roles, with a focus on chemotherapy implications and emerging digital pathology techniques for marker quantification. Methods: A narrative review was conducted by searching PubMed, Scopus, and Google Scholar for studies related to Ki-67, MCM, PCNA, breast cancer, and chemotherapy. Studies were thematically categorized into five areas. A bibliometric analysis of publications from 2000 to April 2023 was performed using the Bibliometrix R package and VOSviewer to assess research trends and thematic evolution. Results: Eighty studies were included in the narrative synthesis. Ki-67 is the most commonly used marker, particularly useful in predicting response to neoadjuvant chemotherapy (NAC). MCM proteins show promise for identifying proliferative potential across tumor grades, while PCNA is associated with aggressive tumor features and poor prognosis. Post-chemotherapy changes in Ki-67 levels are linked to survival outcomes. Bibliometric analysis revealed a shift in research focus from basic mechanisms to clinical applications and digital quantification. Conclusion: Proliferative markers play an essential role in breast cancer management. Ki-67 remains a key predictor of chemotherapy response, while MCM and PCNA offer complementary prognostic insights. Integration of these markers with digital pathology and AI-driven tools may enhance diagnostic accuracy and personalized treatment strategies. Standardization of assessment methods is crucial for broader clinical application. © 2025 The Author(s). Health Science Reports published by Wiley Periodicals LLC.