Munenori Kawai, Akihisa Fukuda, Ryo Otomo, Shunsuke Obata, Kosuke Minaga, Masanori Asada, Atsushi Umemura, Yoshito Uenoyama, Nobuhiro Hieda, Toshihiro Morita, Ryuki Minami, Saiko Marui, Yuki Yamauchi, Yoshitaka Nakai, Yutaka Takada, Kozo Ikuta, Takuto Yoshioka, Kenta Mizukoshi, Kosuke Iwane, Go Yamakawa, Mio Namikawa, Makoto Sono, Munemasa Nagao, Takahisa Maruno, Yuki Nakanishi, Mitsuharu Hirai, Naoki Kanda, Seiji Shio, Toshinao Itani, Shigehiko Fujii, Toshiyuki Kimura, Kazuyoshi Matsumura, Masaya Ohana, Shujiro Yazumi, Chiharu Kawanami, Yukitaka Yamashita, Hiroyuki Marusawa, Tomohiro Watanabe, Yoshito Ito, Masatoshi Kudo, Hiroshi Seno
Br J Cancer . 2024 Aug 28. doi: 10.1038/s41416-024-02794-5. Online ahead of print.
Background: Pancreatic cancer is often diagnosed at advanced stages, and early-stage diagnosis of pancreatic cancer is difficult because of nonspecific symptoms and lack of available biomarkers.
Methods: We performed comprehensive serum miRNA sequencing of 212 pancreatic cancer patient samples from 14 hospitals and 213 non-cancerous healthy control samples. We randomly classified the pancreatic cancer and control samples into two cohorts: a training cohort (N = 185) and a validation cohort (N = 240). We created ensemble models that combined automated machine learning with 100 highly expressed miRNAs and their combination with CA19-9 and validated the performance of the models in the independent validation cohort.
Results: The diagnostic model with the combination of the 100 highly expressed miRNAs and CA19-9 could discriminate pancreatic cancer from non-cancer healthy control with high accuracy (area under the curve (AUC), 0.99; sensitivity, 90%; specificity, 98%). We validated high diagnostic accuracy in an independent asymptomatic early-stage (stage 0-I) pancreatic cancer cohort (AUC:0.97; sensitivity, 67%; specificity, 98%).
Conclusions: We demonstrate that the 100 highly expressed miRNAs and their combination with CA19-9 could be biomarkers for the specific and early detection of pancreatic cancer.