Lymphocyte subsets predictive value and possible involvement of human papilloma virus infection on breast cancer molecular subtypes

• Published in: World journal of clinical oncology Vol. 9; no. 7; pp. 123 - 132
• Main Authors: Fernandes, Andreína, Pesci-Feltri, Adriana, García-Fleury, Isabel, López, Marco, Guida, Vincent, De Macedo, Marisol, Correnti, María
• Format: Journal Article
• Language: English
• Published: United States Baishideng Publishing Group Inc 10-11-2018
• Subjects: Basic Study; T lymphocytes; Human papilloma virus; Molecular subtypes; NK cells; Breast cancer; Immune response
• ISSN: 2218-4333; 2218-4333
• DOI: 10.5306/wjco.v9.i7.123

To detect human papilloma virus (HPV) presence and to characterize cellular immune response in breast cancer patients.
A total of 74 women were included, of which 48 samples were from patients diagnosed with breast cancer and 26 patients with benign pathology of the breast. Molecular subtype classification was performed based on the immunohistochemical reports of the tumor piece. HPV genome detection and genotyping from fresh breast biopsies was performed using the INNO-LIPA HPV Genotyping Extra test (Innogenetics, Ghent, Belgium). CD3+, CD4+, CD8+ and natural killer (NK)+ cells levels from peripheral blood samples from patients with breast cancer and benign pathology were measured by flow cytometry.
Luminal A was the most frequent breast cancer molecular subtype (33.33%). HPV was detected in 25% of the breast cancer patients, and genotype 18 was the most frequent in the studied population. The mean of CD3+, CD4+ and CD8+ subpopulations were decreased in patients with breast cancer, in relation to those with benign pathology, with a statistically significant difference in CD8+ values (
= 0.048). The mean of NK+ cells was increased in the benign pathology group. The average level of CD3+, CD4+, CD8+ and NK+ cells decreased as the disease progressed. HER2+ and Luminal B HER2+ tumors had the lowest counts of cell subsets. HPV breast cancer patients had elevated counts of cellular subsets.
Determining level changes in cellular subsets in breast cancer patients is a useful tool to evaluate treatment response.