Ovarian cancer is one of the deadliest gynecological cancers worldwide. One promising therapeutic approach is the use of combined biomarkers. The Risk of Ovarian Malignancy Algorithm (ROMA) which combines CA125 with Human Epididymal Protein 4 (HE4) is an example of combining biomarkers to gain an optimal predictive outcome. Tumor Protein p53 (TP53) is a transcription factor with tumor suppressor properties. Mutations in TP53 constitute the most frequent genetic alterations observed in ovarian cancer. In contrast to conventional markers such as CA125, circulating tumor DNA (ctDNA) provides information about tumor mutations and insights into treatment response. Analysis of ctDNA enables the identification of tumor-associated mutations. Non-coding RNAs (ncRNAs) also influence cellular processes and act as effectors in oncogenic pathways by binding to RNA or proteins. One effector is Metastasis-Associated Lung Adenocarcinoma Transcript 1 (MALAT1), whose increased expression is associated with an aggressive tumor phenotype. MicroRNAs (miRNAs) are crucial in regulating the expression of genes associated with ovarian cancer development and progression. Exosomes carrying various molecules, including miRNAs and lncRNAs, contribute to ovarian cancer progression. Adipocytokines play an important role in the regulation of metabolic and inflammatory processes. Despite their diagnostic potential, the identified biomarkers require further validation.