| Literature DB >> 23947399 |
Mariel Garcia-Chagollan1, Luis F Jave-Suarez, Jesse Haramati, Pedro E Sanchez-Hernandez, Adriana Aguilar-Lemarroy, Miriam R Bueno-Topete, Ana L Pereira-Suarez, Mary Fafutis-Morris, Angel Cid-Arregui, Susana del Toro-Arreola.
Abstract
BACKGROUND: The NKG2D receptor confers important activating signals to NK cells via ligands expressed during cellular stress and viral infection. This receptor has generated great interest because not only is it expressed on NK cells, but it is also seen in virtually all CD8+ cytotoxic T cells and is classically considered absent in CD4+ T cells. However, recent studies have identified a distinctive population of CD4+ T cells that do express NKG2D, which could represent a particular cytotoxic effector population involved in viral infections and chronic diseases. On the other hand, increased incidence of human papillomavirus-associated lesions in CD4+ T cell-immunocompromised individuals suggests that CD4+ T cells play a key role in controlling the viral infection. Therefore, this study was focused on identifying the frequency of NKG2D-expressing CD4+ T cells in patients with cervical intraepithelial neoplasia (CIN) 1. Additionally, factors influencing CD4+NKG2D+ T cell expansion were also measured.Entities:
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Year: 2013 PMID: 23947399 PMCID: PMC3751941 DOI: 10.1186/1423-0127-20-60
Source DB: PubMed Journal: J Biomed Sci ISSN: 1021-7770 Impact factor: 8.410
HPV genotypes in patients with histologically confirmed diagnosis of CIN 1
| 1 | 37 | Negative | | |
| 2 | 30 | Negative | | |
| 3 | 25 | | | 51 |
| 4 | 38 | | | 51 |
| 5 | 20 | | | 16 |
| 6 | 44 | | | 58 |
| 7 | 25 | Negative | | |
| 8 | 34 | | | 59 |
| 9 | 49 | Negative | | |
| 10 | 61 | Negative | | |
| 11 | 24 | Negative | | |
| 12 | 37 | Negative | | |
| 13 | 23 | | 84, 72, 62, 61 | |
| 14 | 42 | | 62 | |
| 15 | 36 | | 6, 53, 61, 84 CP6108 | |
| 16 | 41 | | | 51 |
| 17 | 29 | | CP6018 | |
| 18 | 48 | | | 39 |
| 19 | 23 | Negative | | |
| 20 | 23 | | 84 | 16 |
| 21 | 34 | Negative | | |
| 22 | 28 | | | 33 |
| 23 | 38 | | 42 | 16 |
| 24 | 43 | Negative | | |
| 25 | 47 | Negative | | |
| 26 | 29 | | 66 | 51 |
| 27 | 37 | Negative | | |
| 28 | 28 | Negative | | |
| 29 | 23 | Negative | | |
| 30 | 27 | | 84 | 35 |
| 31 | 25 | Negative | | |
| 32 | 30 | Negative | | |
| 33 | 44 | Negative | ||
Figure 1CD8T cells are significantly increased in CIN 1 patients. Flow cytometric analysis of peripheral blood in CIN 1 patients or normal donors was performed in order to evaluate variations in the percentages of T cells and NK cells. Gate was drawn around the lymphocyte population, which was then analyzed separately with the corresponding antibodies (CD3+ FITC/CD4+ PECy5, CD3+ FITC/CD8+ PECy5, and CD3- FITC/CD56+ PECy5 for detection of CD4 T cells, CD8 T cells and NK cells, respectively). Analysis from the lymphocyte gate shows that both CD4+ T cells and CD8+ T cells were increased in CIN 1 patients, while NK cells were diminished; however, we only observed a significant increase in the CD8+ T cell population. Statistical analysis was performed through Mann–Whitney U test and data were expressed as mean ± SEM; *p = 0.015.
Figure 2NKG2D-expressing CD4T cells significantly increase in patients with CIN 1. Three-color flow cytometric analysis to detect the expression of NKG2D on peripheral CD4 T cells was carried out in CIN 1 patients and control donors. Cells from the lymphocyte gate were subgated based on CD3 expression and CD4 co-expression. Then, changes in NKG2D expression on CD4+ T cell populations were evaluated. The given percentages reflect the portion of cells positive for NKG2D within the given sub-population. There was a significant increase in CD4+NKG2D+ T cells in the group of CIN 1 patients when compared with normal donors (a). Representative experiment is showed in (b), CD3+CD4+ cells were divided into two populations: NKG2D- and NKG2D+ (gate P7 and P8, respectively). It can be clearly seen a control donor practically negative for CD4+NKG2D+ T cells. The other example in (c) shows a CIN 1 patient with a high percentage of CD4+NKG2D+ T cells. Statistical analysis was performed through Mann–Whitney U test and data are expressed as median, which are represented as horizontal lines and 10th and 90th percentiles as whiskers. Extreme values are also showed (•); *p < 0.001.
Figure 3The highest levels of soluble MICA and MICB are seen in CIN 1 patients. Levels of soluble MICA and MICB were detected using commercial ELISA kits. The highest levels for both MICA (a) and MICB (b) were found in CIN 1 patients when compared to healthy controls. While the group of CIN 1 patients showed only a non-significant trend to high soluble MICA, the levels of soluble MICB were significantly augmented in this group versus controls. Statistical analysis was performed through one-tailed Mann–Whitney U test and data are expressed as mean ± SEM (horizontal lines). Absorbance values are shown as pg/mL (MICA) and ng/mL (MICB); *p = 0.03.
Figure 4Trend to decrease TGF-β and increase pro-inflammatory cytokines is seen in CIN 1 patients. Serum profiles of TGF- β, TNF-α, and IL-15 in CIN 1 patients and control donors were quantified using commercial ELISA kits. While serum levels of TGF-β (a) were significantly lower in CIN 1 patients versus control group, TNF-α (b) and IL-15 (c) showed a trend to be increased, although we did not find statistical differences. Statistical analysis was performed through Mann–Whitney U test and data are expressed as mean ± SEM (horizontal lines). Absorbance values are shown as pg/mL (TNF-α and IL-15) and ng/mL (TGF-β); *p = 0.014.