The correlations between Tc17 cells and Th17 cells.

<p>(a, b) Linear regression analysis between frequencies of Tc17 cell and Th17 cells in the blood (r_CIN = 0.435, <i>P</i> = 0.042, n = 22; r_UCC = 0.403, <i>P</i> = 0.016, n = 36). (c, d) Linear regression analysis between the levels of Tc17 cells and Th17 cells in the cervical tissues (r_CIN = 0.441, <i>P</i> = 0.039, n = 17; r_UCC = 0.693, <i>P</i> = 0.026, n = 30).</p

Clinical Characteristics of UCC Patients.

<p>Abbreviation: FIGO, International Federation of Gynecologists and Obstetricians; SCC, squamous cell carcinoma; ADC, adenocarcinoma; ADSC, adenosquamous carcinoma.</p

The frequency of Tc17 cells by immunohistochemical staining.

<p>(a) Compared to healthy controls (n = 30), significantly increased numbers of Tc17 cells were found in both tissues of UCC patients (<i>P</i> = 0.0007, n = 46) and CIN patients (<i>P</i> = 0.026, n = 28). Significant difference was also found between CIN and UCC tissues (<i>P</i> = 0.0086). (b) In tumor region, those UCC patients with lymph node metastases (n = 30) were detected significantly statistical higher Tc17 cells frequency than those patients without lymph node metastases (<i>P</i> = 0.035, n = 16). *<i>P</i><0.05, **<i>P</i><0.01, ****<i>P</i><0.001.</p

The correlation between Tc17 cells and Foxp3-expressing T cells in the patients of CIN and UCC tissues

<p>(r = 0.713, <i>P</i><0.001, n = 47).</p

The correlations between Tc17 cells and microvessel density (MVD).

<p>(A) Linear regression analysis between the levels of Tc17 cells and MVD (Total: r = 0.987, <i>P</i><0.0001, n = 65; control: r = 0.814, <i>P</i><0.001, n = 18, CIN: r = 0.923, <i>P</i><0.001, n = 17; UCC: r = 0.938, <i>P</i><0.0001, n = 30). MVD from each sample was plotted against Tc17 cells level from the same person. (B) Representative immunohistochemical staining of MVD in cervical tissues of three groups. Representative sites with low (100×, upper panels) and high (400×, lower panels) magnification were shown.</p

The levels of circulation Tc17 cells in representative controls, CIN patients and UCC patients.

<p>Upper right quadrants are the domains of Tc17 (CD8⁺ IL-17⁺) cells and the percentages of them were shown in each panel.</p

The frequency of Tc17 cells by flow cytometry.

<p>(a) Tc17 frequencies in the three groups. Significantly increased Tc17 cells were found in untreated UCC patients (<i>P</i> = 0.0076, n = 49) and CIN patients (<i>P</i> = 0.0149, n = 25) compared to healthy controls (n = 28). (b) Tc17 frequency in positive or negative lymph node metastases in UCC patients. Compared with patients without lymph node metastases (n = 15), significantly increased Tc17 frequency (<i>P</i> = 0.0026) was found in lymph node metastases patients (n = 35). Student's t test was used and bars represent SD, *<i>P</i><0.05, **<i>P</i><0.01.</p

Clinical Characteristics of CIN Patients.

<p>Clinical Characteristics of CIN Patients.</p

Expression of Tc17 cells in cervical tissues of the three groups.

<p>(A) Immunohistochemical double staining for Tc17 cells in the control group (a and d), CIN group (b and e) and UCC group (c and f). Representative sites with low (200×, upper panels) and high (400×, lower panels) magnification were shown. (B) IL-17-producing cells were stained red (in the cytoplasm) and CD8⁺ cells were stained black (in the membrane). The co-expression of CD8 and IL-17 confirmed that a proportion of Tc17 cells.</p

Analysis of prognostic factors for cervical mucinous adenocarcinoma and establishment and validation a nomogram: a SEER-based study

Up to now, there are no relevant studies on prognostic factors of cervical mucinous adenocarcinoma. Therefore, we explored the prognostic factors for cervical mucinous adenocarcinoma, and established and validated the prognostic model using the SEER database. We selected the independent factors through univariate and multivariate analyses. LASSO regression analysis was conducted to identify potential risk factors. In conjunction with LASSO and multivariate analysis, the nomogram incorporated three variables, including age, tumour size, and AJCC stage for OS. The c-index was 0.794 and 0.831 in development and validated cohorts, indicating that this prediction model showed adequate discriminative ability in the development cohort. Besides, calibration curves showed good concordance for the development cohort, as well as the validation cohort. We constructed a first-of-its-kind nomogram to predict cervical mucinous adenocarcinomas OS and it showed better performance than AJCC and FIGO stages. Patients with cervical mucinous adenocarcinoma might benefit from using this model to develop tailored treatments.IMPACT STATEMENTWhat is already known on this subject? Cervical cancer has a variety of pathological types. The biological behaviour of each type is different, and the prognosis is quite different.What do the results of this study add? We analysed and explored the relevant factors affecting the prognosis of cervical mucinous adenocarcinoma.What are the implications of these findings for clinical practice and/or further research? Through the analysis of the SEER dataset, the prognostic factors affecting cervical mucinous adenocarcinoma were identified, and the first predictive model was created to predict the prognosis to help doctors develop individualised treatment plans and follow-up plans. What is already known on this subject? Cervical cancer has a variety of pathological types. The biological behaviour of each type is different, and the prognosis is quite different. What do the results of this study add? We analysed and explored the relevant factors affecting the prognosis of cervical mucinous adenocarcinoma. What are the implications of these findings for clinical practice and/or further research? Through the analysis of the SEER dataset, the prognostic factors affecting cervical mucinous adenocarcinoma were identified, and the first predictive model was created to predict the prognosis to help doctors develop individualised treatment plans and follow-up plans.</p