Identification and Characterization of Tumor-Associated Antigens (TAAS) and Anti-Taas Autoantibodies as Biomarkers in Immunodiagnosis of Human Osteosarcoma by Serological Proteome Analysis (SERPA)

Jitian Li, University of Texas at El Paso

Abstract

Osteosarcoma (OS) is the most common highly malignant primary solid bone-tumor. Despite its relatively low incidence rate among overall cancers, it remains one of the most harmful primary malignant tumors in childhood and adolescence. Although some tumor markers like mutant p53 can be potentially used as biomarker to detect OS, its extensive association with the clinical outcome is poorly understood. The establishment of a methodology to identify patient with early stage of OS remains to be investigated. It is now evident that serum autoantibodies against tumor-associated antigens (TAAs) could be used as serological cancer biomarkers in types of cancers, which derives from the notion that anti-TAA autoantibodies are considered as immunological “sentinels” underlying molecular events associated with tumorigenesis. New insights into molecular and cellular biology and the differential diagnosis of cancers have also been obtained. Moreover, customized TAA arrays significantly increase sensitivity/specificity and provide a great promise for the early detection of cancer, monitoring cancer progression, discovery of novel therapeutic targets, and designing personalized therapeutic interventions. ^ During the past decade, proteomic approaches, such as serological proteome analysis (SERPA), have been used to identify the repertoire of immunoreactive proteins in various diseases. Recent several years, we have used this approach to extensively screen sera from patients with certain types of cancer such as hepatocellular carcinoma (HCC), esophageal squamous cell carcinoma (ESCC), Prostate Cancer (PCa) and Lung Cancer (LC), and sera from patients with pre-cancer conditions such as liver fibrosis to identify and characterize the potential TAAs. ^ We used SERPA to profile anti-TAA autoantibody responses in sera from patients with Osteosarcoma (OS), and Normal Human, and explore differences of these responses. This approach can detect autoantibodies to TAAs that could serve as clinical biomarkers and immunotherapeutic agents. Sera from OS, Osteochondroma (OC) and Normal Human Sera (NHS) were probed by immunoblotting against cellular proteins extracted from U2-OS and Saos-2 cell lines, with OS sera showing stronger immunoreactivity. MALDI-TOF/TOF Mass Spectrometry (MS) analysis of immunoreactive protein spots revealed that several OS sera contained autoantibodies to a number of proteins, particularly to alpha-enolase (ENO1). Analysis of 172 serum samples from patients with OS, OC and NHS by Enzyme-Linked Immunosorbent Assay (ELISA) showed higher frequency of anti-ENO1 autoantibodies in OS sera compared to others. Interestingly, descant of ENO1 immunoreactivity was observed in most patients after treatments, which may imply a potential association between anti-ENO1 autoantibody titers and disease progression. The expression of ENO1 in Osteosarcoma tissues was evaluated by immunohistochemistry (IHC) in Tumor Microarray (TMA). We observed the cumulative positive rate of autoantibodies against seven selected TAAs identified from SERPA (ENO1, NPM1, GAPDH, TPI1, HSP60, PDLIM1, STMN1) in OS reached 90.4%, significantly higher than that in normal control sera. These results support the central hypothesis of this proposed project that "customized" TAA arrays constitute promising and powerful tools for enhancing the serological detection of OS. Together, our intriguing findings demonstrate that ENO1 is one of autoantigens that elicit autoimmune responses in OS and can be used as biomarkers in immunodiagnosis and progression of OS. ^

Subject Area

Biology|Oncology

Recommended Citation

Li, Jitian, "Identification and Characterization of Tumor-Associated Antigens (TAAS) and Anti-Taas Autoantibodies as Biomarkers in Immunodiagnosis of Human Osteosarcoma by Serological Proteome Analysis (SERPA)" (2017). ETD Collection for University of Texas, El Paso. AAI10683595.
https://digitalcommons.utep.edu/dissertations/AAI10683595

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