Deep Learning Improves Pancreatic Cancer Diagnosis Using RNA-Based Variants.

ABSTRACT: For optimal pancreatic cancer treatment, early and accurate diagnosis is vital. Blood-derived biomarkers and genetic predispositions can contribute to early diagnosis, but they often have limited accuracy or applicability. Here, we seek to exploit the synergy between them by combining the biomarker CA19-9 with RNA-based variants. We use deep sequencing and deep learning to improve differentiating pancreatic cancer and chronic pancreatitis. We obtained samples of nucleated cells found in peripheral blood from 268 patients suffering from resectable, non-resectable pancreatic cancer, and chronic pancreatitis. We sequenced RNA with high coverage and obtained millions of variants. The high-quality variants served as input together with CA19-9 values to deep learning models. Our model achieved a

SUBMITTER: Al-Fatlawi A 

PROVIDER: S-EPMC8199344 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature