Search Results
Department of Breast Surgery, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China
Search for other papers by Tian Zhou in
Google Scholar
PubMed
Department of Surgery, Second People's Hospital of Guizhou Province, Guiyang, Guizhou, China
Search for other papers by Dai-wei Zhao in
Google Scholar
PubMed
Search for other papers by Ning Ma in
Google Scholar
PubMed
Search for other papers by Xue-ying Zhu in
Google Scholar
PubMed
Search for other papers by Xing-hong Chen in
Google Scholar
PubMed
Search for other papers by Xue Luo in
Google Scholar
PubMed
Search for other papers by Song Chen in
Google Scholar
PubMed
Search for other papers by Qing-jun Gao in
Google Scholar
PubMed
Objective
Thyroid cancer (THCA) is the most common endocrine cancer in the world. Although most patients with THCA have a good prognosis, the prognosis of those with THCA who have an extra-glandular invasion, vascular invasion, and distant metastasis is poor. Therefore, it is very important to find potential biomarkers that can effectively predict the prognosis and progression of highly aggressive THCAs. It has been identified that forkhead box P4 (FOXP4) may be a new biomarker for the proliferation and prognosis for tumor diagnosis. However, the expression and function of FOXP4 in THCA remain to be determined.
Methods
In the present study, the function of FOXP4 in cells was investigated through the comprehensive analysis of data in The Cancer Genome Atlas and combined with experiments including immunohistochemistry (IHC), colony formation, Cell Counting Kit-8 assay, wound scratch healing, and transwell invasion assay.
Results
In the present study, relevant bioinformatic data showed that FOXP4 was highly expressed in THCA, which was consistent with the results of the IHC and cell experiments. Meanwhile, 10 FOXP4-related hub genes were identified as potential diagnostic genes for THCA. It was found in further experiments that FOXP4 was located in the nucleus of THCA cells, and the expression of FOXP4 in the nucleus was higher than that in the cytoplasm. FOXP4 knockdown inhibited in vitro proliferation of the THCA cells, whereas overexpression promoted the proliferation and migration of THCA cells. Furthermore, deficiency of FOXP4 induced cell-cycle arrest.
Conclusion
FOXP4 might be a potential target for diagnosing and treating THCA.
Search for other papers by Wenhao Lin in
Google Scholar
PubMed
Search for other papers by Jun Dai in
Google Scholar
PubMed
Search for other papers by Jialing Xie in
Google Scholar
PubMed
Search for other papers by Jiacheng Liu in
Google Scholar
PubMed
Search for other papers by Fukang Sun in
Google Scholar
PubMed
Search for other papers by Xin Huang in
Google Scholar
PubMed
Search for other papers by Wei He in
Google Scholar
PubMed
Search for other papers by Chen Fang in
Google Scholar
PubMed
Search for other papers by Juping Zhao in
Google Scholar
PubMed
Search for other papers by Danfeng Xu in
Google Scholar
PubMed
Purpose
To externally validate the performance of the S-GRAS score and a model from the Surveillance, Epidemiology, and End Results (SEER) database in a Chinese cohort of patients with adrenocortical carcinoma (ACC).
Methods
We first developed a model using data from the SEER database, after which we retrospectively reviewed 51 ACC patients hospitalized between 2013 and 2018, and we finally validated the model and S-GRAS score in this Chinese cohort.
Results
Patient age at diagnosis, tumor size, TNM stage, and radiotherapy were used to construct the model, and the Harrell’s C-index of the model in the training set was 0.725 (95% CI: 0.682–0.768). However, the 5-year area under the curve (AUC) of the model in the validation cohort was 0.598 (95% CI: 0.487–0.708). The 5-year AUC of the ENSAT stage was 0.640 (95% CI: 0.543–0.737), but the Kaplan–Meier curves of stages I and II overlapped in the validation cohort. The resection status (P = 0.066), age (P=0.68), Ki67 (P = 0.69), and symptoms (P = 0.66) did not have a significant impact on cancer-specific survival in the validation cohort. In contrast, the S-GRAS score group showed better discrimination (5-year AUC: 0.683, 95% CI: 0.602–0.764) than the SEER model or the ENSAT stage.
Conclusion
The SEER model showed favorable discrimination and calibration ability in the training set, but it failed to distinguish patients with various prognoses in our institution. In contrast, the S-GRAS score could effectively stratify patients with different outcomes.
