Identification of prothymosin alpha (PTMA) as a biomarker for esophageal squamous cell carcinoma (ESCC) by label-free quantitative proteomics and Quantitative Dot Blot (QDB)

Yanping Zhu; Xiaoying Qi; Cuicui Yu; Shoujun Yu; Chao Zhang; Yuan Zhang; Xiuxiu Liu; Yuxue Xu; Chunhua Yang; Wenguo Jiang; Geng Tian; Xuri Li; Jonas Bergquist; Jiandi Zhang; Lei Wang; Jia Mi

doi:10.1186/s12014-019-9232-6

Identification of prothymosin alpha (PTMA) as a biomarker for esophageal squamous cell carcinoma (ESCC) by label-free quantitative proteomics and Quantitative Dot Blot (QDB)

Clin Proteomics. 2019 Apr 5:16:12. doi: 10.1186/s12014-019-9232-6. eCollection 2019.

Authors

Yanping Zhu^#¹, Xiaoying Qi^#¹, Cuicui Yu^#², Shoujun Yu³, Chao Zhang¹, Yuan Zhang¹, Xiuxiu Liu¹, Yuxue Xu¹, Chunhua Yang¹, Wenguo Jiang¹, Geng Tian¹, Xuri Li⁴, Jonas Bergquist^{1

5}, Jiandi Zhang^{1

6}, Lei Wang⁷, Jia Mi¹

Affiliations

¹ 1Precision Medicine Research Center, Binzhou Medical University, No. 346 Guanhai Rd., Laishan District, Yantai, 264003 Shandong Province People's Republic of China.
² Department of Anesthesiology, The Affiliated Yantai Yuhuangding Hospital of Qing Dao University, No. 20 Yudong Rd., Zhifu District, Yantai, S264009 Shandong People's Republic of China.
³ 3Department of Ultrasound, Yantai Affiliated Hospital of Binzhou Medical University, No. 717 Jinfu Rd., Muping District, Binzhou, 264100 Shandong Province People's Republic of China.
⁴ 4State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060 People's Republic of China.
⁵ 5Department of Chemistry, BMC, Uppsala University, PO Box 599, Husargatan 3, 75124 Uppsala, Sweden.
⁶ Yantai Zestern Biotechnique Co. LTD, 39 Keji Ave. Bioasis, Yantai, People's Republic of China.
⁷ 7Department of Thoracic Surgery, The First Affiliated Hospital of Harbin Medical University, No. 23, Youzheng Street, Nangang District, Harbin, 150000 Heilongjiang Province People's Republic of China.

^# Contributed equally.

Abstract

Background: Esophageal cancer (EC) is one of the malignant tumors with a poor prognosis. The early stage of EC is asymptomatic, so identification of cancer biomarkers is important for early detection and clinical practice.

Methods: In this study, we compared the protein expression profiles in esophageal squamous cell carcinoma (ESCC) tissues and adjacent normal esophageal tissues from five patients through high-resolution label-free mass spectrometry. Through bioinformatics analysis, we found the differentially expressed proteins of ESCC. To perform the rapid identification of biomarkers, we adopted a high-throughput protein identification technique of Quantitative Dot Blot (QDB). Meanwhile, the QDB results were verified by classical immunohistochemistry.

Results: In total 2297 proteins were identified, out of which 308 proteins were differentially expressed between ESCC tissues and normal tissues. By bioinformatics analysis, the four up-regulated proteins (PTMA, PAK2, PPP1CA, HMGB2) and the five down-regulated proteins (Caveolin, Integrin beta-1, Collagen alpha-2(VI), Leiomodin-1 and Vinculin) were selected and validated in ESCC by Western Blot. Furthermore, we performed the QDB and IHC analysis in 64 patients and 117 patients, respectively. The PTMA expression was up-regulated gradually along the progression of ESCC, and the PTMA expression ratio between tumor and adjacent normal tissue was significantly increased along with the progression. Therefore, we suggest that PTMA might be a potential candidate biomarker for ESCC.

Conclusion: In this study, label-free quantitative proteomics combined with QDB revealed that PTMA expression was up-regulated in ESCC tissues, and PTMA might be a potential candidate for ESCC. Since Western Blot cannot achieve rapid and high-throughput screening of mass spectrometry results, the emergence of QDB meets this demand and provides an effective method for the identification of biomarkers.

Keywords: Esophageal squamous cell carcinoma (ESCC); Label-free quantitative proteomics; Prothymosin alpha (PTMA); Quantitative Dot Blot (QDB).