medRxiv preprint doi: https://doi.org/10.1101/2020.04.16.20061515; this version posted April 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 1 A transcriptomics-based meta-analysis combined with machine learning 2 approach identifies a secretory biomarker panel for diagnosis of pancreatic 3 adenocarcinoma 4 Indu Khatri1,3, Manoj K. Bhasin1,2* 5 6 Affiliations: 7 1Division of IMBIO, Department of Medicine, Beth Israel Lahey Health, Harvard Medical 8 School, Boston MA 02215 9 2Department of Pediatrics and Biomedical Informatics, Children Healthcare of Atlanta, Emory 10 School of Medicine, Atlanta, GA 30322 11 3Division of Immunohematology and Blood transfusion, Leiden University Medical Center, 12 Leiden, The Netherlands, 2333ZA 13 14 15 *Corresponding Author 16 Manoj K. Bhasin, PhD 17 E-mail:
[email protected] 18 Keywords: biomarker, pancreatic cancer, secretory, transcriptome, validation 19 NOTE: This preprint reports new research that has not been certified1 by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.04.16.20061515; this version posted April 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 20 Abstract 21 Pancreatic ductal adenocarcinoma (PDAC) is largely incurable due to late diagnosis and absence 22 of markers that are concordant with expression in several sample sources (i.e.