bioRxiv preprint Identification of key genes and associated pathways in neuroendocrine tumors through bioinformatics analysis and predictions of small drug molecules (which wasnotcertifiedbypeerreview)istheauthor/funder.Allrightsreserved.Noreuseallowedwithoutpermission. 1 2 3 4 5 Praveenkumar Devarbhavi , Basavaraj Vastrad , Anandkumar Tengli , Chanabasayya Vastrad* Iranna Kotturshetti doi: https://doi.org/10.1101/2020.12.23.424165 1. Department of Endocrinology and Metabolism, Subbaiah Institute of Medical Sciences and Research Centre, Shimoga 577222, Karnataka, India 2. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 3. Department of Pharmaceutical Chemistry, JSS College of Pharmacy, Mysuru and JSS Academy of Higher Education & Research, Mysuru- 570015, Karnataka, India. 4. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. ; 5. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron 562209, Karanataka, India. this versionpostedDecember24,2020. The copyrightholderforthispreprint * Chanabasayya Vastrad Email:
[email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, bioRxiv preprint Dharwad 580001 , Karanataka, India (which wasnotcertifiedbypeerreview)istheauthor/funder.Allrightsreserved.Noreuseallowedwithoutpermission. Abstract doi: https://doi.org/10.1101/2020.12.23.424165 Neuroendocrine tumor (NET) is one of malignant cancer and is identified with high morbidity and mortality rates around the world. With indigent clinical outcomes, potential biomarkers for diagnosis, prognosis and drug target are crucial to explore. The aim of this study is to examine the gene expression module of NET and to identify potential diagnostic and prognostic biomarkers as well as to find out new drug target. The differentially expressed genes (DEGs) identified from GSE65286 dataset was used for pathway enrichment analyses and gene ontology (GO) enrichment analyses and protein - protein interaction (PPI) analysis and module analysis.