Abstract
Aims: Pancreatic cancer is a major disease to fatalities worldwide. To understand its molecular mechanisms is crucial for improving diagnosis and treatment. We aim to identify key biomarkers and biological pathways associated with pancreatic adenocarcinoma using RNA sequencing data from The Cancer Genome Atlas (TCGA). To analyze differentially expressed genes in pancreatic cancer, performed enrichment analysis to uncover crucial biological processes and cellular components, evaluated the impact of identified genes on patient survival and prognosis. Methods: We examined RNA sequencing data from TCGA to identify differentially expressed genes (DEGs), crucial biological processes, and cellular components associated with pancreatic cancer. Enrichment analysis was conducted to pinpoint significant genes involved in various pathways, and survival analysis was performed to assess the impact of these genes on patient outcomes. Results: Our analysis identified several significant genes linked to pancreatic cancer, including EDN1, KDM1A, KDM5D, KDM6A, NLGN4Y, RASGRP, SQLE, TMSB4Y, TNF, USP9Y, 1UTY, and ZRSR2. Notably, Ras guanyl nucleotide-releasing protein (RASGRP), tumor necrosis factor (TNF), and ZRSR2 showed lower expression levels than normal tissues, while KDM1A and KDM3A were significantly overexpressed, correlating with poor prognostic outcomes. Survival analysis indicated that EDN1, KDM1A, RASGRP, and squalene epoxidase (SQLE) are associated with mortality risk or disease recurrence. Conclusion: Our findings highlight key biomarkers and pathways involved in pancreatic cancer, emphasizing the potential of KDM1A and KDM3A as therapeutic targets. By identifying these biomarkers, we aim to contribute to developing targeted therapies that could enhance patient prognoses and improve treatment strategies for pancreatic cancer.
Published Version
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