Proteomic profile mapping and differential expression of protein in ovarian cancer - Tauseef, Ambreen; Karim, Asima; Ahmad, Gulfam; Gardner, Qurratulann Afza; Akhtar, Muhammad Waheed (Penerbit Universiti Kebangsaan Malaysia, 2021)
This study aimed to characterize differentially expressed proteins in malignant ovarian tissue to find out potential novel biomarkers in ovarian cancer (OC). We enrolled 20 ovarian cancer patients (40-65 years) and an equal number of age-matched healthy women to get malignant and healthy ovarian tissue samples for protein extraction and quantification after tissue lysis. The protein profile was analyzed using two-dimensional gel electrophoresis followed by MALDI-TOF mass spectrometry. Based on the information thus obtained, the proteins were identified using the relevant software and protein databank to analyze the malignant and non-malignant ovarian tissue samples (n = 20/group). In this proteomic analysis of the ovarian tissue, 112 proteins were detected. Based on a minimum of ≥ 1.5-fold expression difference (p-value ≤ 0.05; FDR ≤ 0.05 and PMF ≥ 79), 17 proteins were found to be upregulated while 27 were downregulated in the malignant ovarian tissue. Six of these proteins have not been previously reported in ovarian cancer. Out of these, three are upregulated while the other three are downregulated. The upregulated proteins are centrosomal protein of 290 kDa (Cep290), uncharacterized protein C1orf109 (C1orf109) and GTPase-activating Rap/Ran-GAP domain-like protein 3 (GARNL3), and the three downregulated proteins identified are actin-related protein 3 (ARP3), cytosolic carboxypeptidase 3 (AGBL3) and NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 10 (NDUFA10). This proteomic mapping not only provides data on protein profiling of ovarian cancer in Pakistani population for the first time but also reports six novel differentially expressed proteins, which have not been previously reported in ovarian cancer patients. They may serve as potential novel biomarkers after further validation for early diagnosis and prognosis of ovarian cancer. It also provides additional data to improve existing knowledge of already reported protein ovarian cancer biomarkers.