ArticleWorld journal of clinical oncology2018
Lymphocyte subsets predictive value and possible involvement of human papilloma virus infection on breast cancer molecular subtypes.
Article in World journal of clinical oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 5 citations in OpenAlex.
- Frequency of CD4+ regulatory T cells, CD8+ T cells, and human papilloma virus infection in Egyptian Women with breast cancer.International journal of immunopathology and pharmacologyArticle
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimTo detect human papilloma virus (HPV) presence and to characterize cellular immune response in breast cancer patients.
methodsA 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.
resultsLuminal 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 (
conclusionDetermining level changes in cellular subsets in breast cancer patients is a useful tool to evaluate treatment response.
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