Serum amyloid a, a potential biomarker both in serum and tissue, correlates with ovarian cancer progression

• Main Authors: Ze Li, Yongwang Hou, Meng Zhao, Tianning Li, Yahui Liu, Jiao Chang, Li Ren
• Format: Article
• Language: English
• Published: BMC 2020-06-01
• Series: Journal of Ovarian Research
• Subjects: Serum amyloid a; Ovarian Cancer; Matrix metalloproteinases, epithelial–Mesenchymal transition
• Online Access: http://link.springer.com/article/10.1186/s13048-020-00669-w

Abstract Background Ovarian cancer is the most fatal gynecologic malignancy worldwide due to its vagueness, delay in diagnosis, recurrence, and drug resistance. Therefore, a new type of ovarian cancer treatment prediction biomarker is urgently needed to supplement existing tools. A total of 230 people participated in this study. Out of this figure, 100 participants were patients who underwent an ovarian tumor operation, another 100 participants were ovarian benign patients, and the remaining 30 participants were healthy women. Cancer (experimental) group were 100 patients who underwent ovarian tumor operation, while the control groups were 130 participants consisting of 100 ovarian benign patients and 30 healthy women. Levels of SAA, carbohydrate antigen-125 (CA-125), and human epididymis protein 4 (HE4) were assessed using standard laboratory protocols. A total of 5 ovarian cancer tissues and paracancerous tissues were collected and then stored at − 80 °C until the qRT-PCR assay was conducted. Results The ROC curve of SAA concentration in ovarian cancer was plotted to obtain the area under the curve AUC = 0.889, the cut-off value 17.05 mg/L, the sensitivity 78.4% and specificity 86.5%. Compared with pretreatment, the level of serum SAA decreased significantly after treatment. The results revealed that there was a significant correlation between the level of serum SAA and advanced FIGO stage, histology subtype, lymphatic invasion, and distant metastasis (p = 0.003,0.002,0.000 and 0.001). The quantitative Reverse transcription polymerase chain reaction (qRT-PCR) assay revealed that the Messenger RNA (mRNA) of SAA-1 and SAA-4 was much higher in cancer tissues than in adjacent tissues, and MMPs was up-regulation including MMP-1, MMP-9 and MMP- 12 in OVCAR-3 cell stimulated by SAA. The transwell assay revealed that SAA could promote OVCAR-3 cell migration. Moreover, SAA can regulate EMT markers and promote AKT pathway activation. Conclusions In summary, our results demonstrated that SAA may be a potential diagnosis and treatment prediction biomarker. The SAA promotes OVCAR-3 cell migration by regulating MMPs and EMT which may correlate with AKT pathway activation.