Date of Award

2024-12-01

Degree Name

Doctor of Philosophy

Department

Biological Sciences

Advisor(s)

Jian-Ying J. Zhang

Second Advisor

Giulio G. Francia

Abstract

Prostate cancer (PCa) is the second most frequent cancer in males with 1.47 million new cases and 396,700 deaths worldwide in 2022. It is the second leading cause of cancer-related deaths among males in the United States with over 35,000 estimated deaths in 2024. PCa is a type of indolent cancer that can progress to an advanced metastatic castration-resistant (mCRPC) stage if not detected and treated early. Screening precancerous lesions or early tumor detection is an effective strategy to reduce the mortality of cancer. Despite the development of effective screening methods, such as the prostate-specific antigen (PSA) test, the specificity and sensitivity of current diagnostic tests for PCa are still suboptimal, leading to unnecessary biopsies or overtreatment. It is imperative to identify novel blood-based biomarkers that could complement PSA for the early detection of PCa with high sensitivity and specificity. This would be of enormous benefit to high-risk groups, including men of African Ancestry and certain Hispanic/Latino subgroups, who have higher PCa incidence and poor survival rates compared to other groups. Genomic alterations can drive tumorigenesis, and understanding the immune response to those alterations may aid in developing new targets for diagnosis and therapy. Tumor-associated antigens (TAAs) are self-antigens that are abnormally expressed in tumors. Autoantibodies against TAAs have been considered as reporters of early carcinogenesis and indicators of cancer prognosis. These autoantibodies are abundant, detectable, and stable in the patientâ??s circulating blood. This study aimed to profile autoantibodies to common TAAs, and autoantibodies to overexpressed proteins or driver gene-related proteins (DRPs) in PCa. First, the Luminex technology was used to evaluate a panel of anti-TAAs autoantibodies in PCa, which included 14 common cancer-related autoantibodies. A total of 163 serum samples were screened to determine the levels of the autoantibodies, twelve autoantibodies exhibited significantly high frequencies ranging from 19.8% to 51.6% in the PCa group. The results of Luminex were further confirmed by enzyme-linked immunosorbent assay (ELISA). In addition, 29 targets including 14 overexpressed proteins, and 15 DRPs were screened via serological proteome analysis, and bioinformatics analysis respectively. ELISA was then performed to assess their corresponding autoantibodies in 293 serum samples. Nineteen autoantibodies showed significantly higher serum levels in PCa group than in normal controls. A panel with four AAbs (PIK3CA, SPOP, IF4H, HSP60) was developed, showing an AUC of 0.901. A differential autoantibody response to these four TAAs was observed in racially/ethnically diverse PCa populations, with autoantibodies to PIK3CA and IF4H detected at significantly higher frequencies in Hispanic American and African American patients compared to European American patients. The panel was evaluated across six other common cancers including 445 serum samples, showing potential for multi-cancer detection. The expression of the four TAAs targeted by autoantibodies was analyzed by IHC and high expression of all these TAAs was found in PCa tissues. These findings suggest that overexpressed proteins or DRPs may have altered immunogenicity, leading to the production of corresponding autoantibodies. Identifying autoantibodies associated with altered TAA expression in PCa could offer novel opportunities for discovering autoantibody-based biomarkers and novel therapeutic targets. Additionally, an optimized multi-autoantibody panel can improve the potential of using autoantibodies as biomarkers, and it can serve as a relatively simple tool to evaluate large numbers of patient samples for cancer detection.

Language

en

Provenance

Recieved from ProQuest

File Size

134 p.

File Format

application/pdf

Rights Holder

Cuipeng Qiu

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Included in

Biology Commons

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