Hepatocellular carcinoma (HCC) is a primary type of liver cancer and the third leading cause of cancer-related deaths. Non-resolving liver inflammation caused by a variety of etiological factors, such as viral hepatitis infections or alcohol abuse, initiates the transition from fibrosis to cirrhosis, and finally to cancer. Due to poor late-stage survival rates, novel biomarkers and therapeutic targets are desperately needed to improve HCC patient outcomes. Potential candidates include a group of Cancer Testes Antigens (CTAs), a large group of tumor‐associated antigens expressed in multiple tumor types. The melanoma-associated antigen (MAGE) subfamily of CTAs is overexpressed in HCC tumors and may drive tumor progression and tumorigenesis. However, little is known about the expression patterns of these CTAs in the multiple precursor liver diseases that contribute to HCC development, such as chronic hepatitis or cirrhosis. Furthermore, the mechanisms regulating the expression of these members in liver tissue prior to and following metastatic development have not been fully elucidated. Initial Enzyme-Linked Immunosorbent Assay (ELISA) results have demonstrated an autoimmune response to these proteins as tumor-associated antigens in serum from patients with precursor liver conditions. Using computational approaches, we have evaluated the expression patterns of these CTAs in publicly available liver disease transcriptomic datasets. The analyzed samples were stratified by disease etiology to provide a comprehensive view of the spectrum of the transition from healthy to diseased liver. Wet-lab approaches, including Immunohistochemistry (IHC), were employed to validate these responses at the protein level. Our findings indicate that MAGE subfamily CTAs are potential biomarkers of HCC development, with the activation of individual members varying during the transition from diseased liver to cancer. By elucidating the molecular mechanisms and pathways by which HCC-specific CTAs function, we will be able to develop them as diagnostic markers and therapeutic targets.