| Literature DB >> 30616690 |
Shahnawaz Imam1, Pervaiz Dar1, Rodis Paparodis1, Khalil Almotah1, Ahmed Al-Khudhair1, Syed Abdul-Moiz Hasan1, Nancy Salim1, Juan Carlos Jaume2.
Abstract
BACKGROUND: Thyroid cancer and thyroid autoimmunity are considered opposite extremes of immune-responses. However, several studies have suggested that thyroid cancer coexists with autoimmune thyroid diseases like Hashimoto Thyroiditis (HT) and Graves disease (GD). We have shown that the risk of developing thyroid cancer is higher in patients with a silent form of autoimmune thyroid disease -Euthyroid Hashimoto Thyroiditis-(EHT).Entities:
Keywords: Graves disease; Hashimoto thyroiditis; Macrophage-NK cells cross talk; Thyroid cancer; Tumor immunity
Year: 2019 PMID: 30616690 PMCID: PMC6323721 DOI: 10.1186/s40425-018-0483-y
Source DB: PubMed Journal: J Immunother Cancer ISSN: 2051-1426 Impact factor: 13.751
Fig. 1Relationship of Graves Disease (GD), Hashimoto Thyroiditis (HT) and Differentiated Thyroid Cancer (DTC) in patients undergoing thyroidectomy. Study design with benign (BEN) vs. malignant (DTC) outcome as related with either autoimmune (GD and HT with subgroups euthyroid and hypothyroid) or non-autoimmune (Non-AITD) (a). Bar graph for frequency of DTC in each group (b) and Hashimoto’s subgroups (c). Bar graph for distribution of DTC based on tumor size (d)
Differentiated thyroid cancer incidence and pathological features in patients with and without autoimmune thyroid diseases
| Non-AITD | HT | GD | EHT | Hypo-HT | |
|---|---|---|---|---|---|
| DTC, n/total (%) | 600/1851 (32.4%) | 256/576 (44.4%) | 16/206 (7.8%) | 175/365 (47.9%) | 81/211 (38.4%) |
| OR vs. Non-AITD 95% CI | n/a | ||||
| Comparisons Between subgroups | n/a | OR = | OR = | ||
| Size (cm) SEM | 1.8 (1.7) | 1.5 (1.3) | 0.7 (0.3) | 1.5 (1.2) | 1.5 (1.4) |
| n/a |
|
|
| 0.062 | |
| n/a |
| 0.831 | |||
| Macro n (%) | 369 (66.4%) | 142 (55.9%) | 2 (12.5%) | 98 (56.9%) | 44 (57.8%) |
| OR vs. Non-AITD 95% CI | n/a | 1.44 0.84–2.34 0.158 | |||
| OR 95% CI | n/a | 0.96 0.56–1.66 1.000 | |||
| FTC n (%) | 46 (7.7%) | 12 (4.7%) | 0 0% | 9 (5.1%) | 3 (3.7%) |
| OR vs. Non-AITD 95% CI p value | n/a | 1.69 0.88–3.24 0.112 | 2.77 0.16–46.9 0.623 | 1.53 0.73–3.20 0.316 | 2.16 0.66–7.11 0.254 |
| OR 95% CI | n/a | 1.69 0.10–29.8 1.000 | 1.41 0.37–5.35 0.758 | ||
| FVPTC n (%) | 130 (21.7%) | 56 (21.9%) | 2 (12.5%) | 36 (20.6%) | 20 (24.7%) |
| OR vs. Non-AITD 95% CI | n/a | 0.99 0.69–1.41 1.000 | 1.94 0.43–8.63 0.542 | 1.07 0.71–1.62 0.834 | 0.84 0.49–1.45 0.568 |
| OR 95% CI | n/a | 1.96 0.43–8.88 0.535 | 0.79 0.42–1.48 0.516 | ||
| Other PTC variants n (%) | 12 (2.0%) | 10 (3.9%) | 0 0% | 4 (2.3%) | 6 (7.4%) |
Abbreviations: Non-AITD subjects without any form of autoimmune disease by pathology, HT subjects with Hashimoto’s thyroiditis, GD subjects with Graves’ disease, EHT subjects with Hashimoto’s thyroiditis by pathology and normal thyroid function, Hypo-HT subjects with hypothyroidism due to Hashimoto’s disease, Macro differentiated thyroid cancer larger than 1cm in maximum diameter, FVPTC follicular variant of papillary thyroid cancer, Other variants other forms of papillary thyroid cancer, i.e. oncocytic, solid, tall cell variants, Mets distant metastases, I-131 post-operative treatment with at least one dose of I-131
Comparison of thyroid cancer features with Fischer's exact test, between thyroid cancers found in the background of thyroid autoimmunity and those found in the absence of autoimmune thyroid diseases (Non-AITD). Odds ratios are reported as a comparison of the proportions between subjects with Non-AITD and subjects with autoimmune thyroid disorders
Odds ratios for the presence of DTC are estimated between subgroups of subjects with AITD and subjects without (Non-AITD). The odds ratios for DTC are estimated between different subgroups as well
Bold indicates a statistically significant difference between ratios
Fig. 2Flow cytometry analysis of natural killer (NK) cells. Bar graphs of statistical analysis of NK cell present in patient samples (a) and functionality as measured by Interferon gamma (INFg) from patients with Euthyroid Hashimoto Thyroiditis (EHT) (n = 8) and Graves disease (GD) (n = 8) (b). Flow cytometry raw data sample of NK cells in EHT or GD and bar graph statistical quantification based on production of cytotoxic enzymes: Granulysin, Granzyme B and Perforin (c). Statistical significance was determined by using t-test: two samples assuming unequal variance. depicts the difference (P < 0.05) between the groups
Fig. 3Macrophage and B cell comparison under induction/stimulation. Macrophages in EHT (n = 8) and GD (n = 8) before and after induction/stimulation (a) as analyzed by flow cytometry were compared with B cells from same patients (b) induction/stimulation under high dose of LPS (100 ng/ml) for 54 h
Fig. 4Intra-thyroidal immune profiling of M1 and M2 macrophage polarization using Flow Cytometry Analysis. Flow cytometry analysis of M1 macrophages (FACS) contour plots (Upper panel) of representative patients and Bar graphs (Lower panel) of statistical analysis of leukocyte specimens from patients with Euthyroid Hashimoto Thyroiditis (EHT) (n = 8) and Graves disease (GD) (n = 8). Leukocyte specimens gated for CD3-ve and subsequently sorted for macrophages (CD14 and CD68). Macrophages were re-gated for the M1 macrophage activation marker Viz. CCR2, CXCR1, IL12, TNFa and iNOS, Uninduced (a) and Induced (b) are shown. Macrophages were again re-gated for the M2 macrophage activation marker Viz. Arginase 1, Dectin 1 and IL10. Uninduced (c) and Induced (d) are shown. Statistical significance was determined by using t-test: two samples assuming unequal variance
Fig. 5NK-Macrophage crosstalk. Peripheral Blood M1-M2 differentiation and quantification of final product. M1 (a) and M2 (b) structural phenotype shown. Macrophages were labeled with CD68-PE (Red), Cytoskeleton stained with phalloidin-Alexa Fluor 488 (Green) and nuclei stained with DAPI (Blue). Bar graph of proportions of M1 and M2 as well as NK cells in active (NA) or resting (N0) form as quantified by flow cytometry (c). Naïve/resting NK cells were activated by using IL-2 at the dose rate of 50 ng/ml. Macrophages were differentiated from human PBMCs into M1 and M2 macrophages. Differentiated macrophages (M1 and M2) and NK (NA and N0) cells were co-cultured. All the experiments were executed in triplicate and mean of the three were considered as an individual observation (n = 3–6). Autologous co-cultures of M1/M2 macrophage with NA/N0 NK cells were stained with M1/M2 phenotype markers. Phenotypic characterization of differentiated macrophages (M1 and M2) were done using Flow cytometer. Single live cells were gated and subsequently sorted for macrophages (CD68) and re-gated for the M1 macrophages activation marker Viz. CCR2, CX3CR1 for surface chemokine and IL-12 and TNFa for intracellular cytokines (d-f). In the same autologous co-culture experiment the macrophages were re-gated for CD68 and gated for M2 macrophage activation marker Viz. Arginase 1, Dectin 1 and IL-10 (g-i). Again in the same autologous co-culture experiment single cells were gated for NK cell markers (CD56+ CD3-) and subsequently sorted for intracellular cytokines and multimeric complexes viz. GZB, IFNg, and Perforin (j-l). Statistical significance was determined by using t-test: two samples assuming equal variance. NK cells were co-culture against macrophages at different Effector to Target (E:T) ratios: Resting and activated NK (N0 and NA) cells cytotoxicity against macrophage (M0, M1 and M2) is shown (m). Cytotoxicity was assessed in flow cytometer using CFSE-FITC for alive and 7 Aminoactinomycin D (AAD)-PE for dead cells. depict the difference between the groups within a ratio and depict the difference (P < 0.05) among the ratios within a group