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Development of a fit-for-purpose multi-marker panel for early diagnosis of pancreatic ductal adenocarcinoma.
Kim, Hyeonji; Huh, Sunghyun; Park, Jungkap; Han, Youngmin; Ahn, Kyung-Geun; Noh, Yiyoung; Lee, Seong-Jae; Chu, Hyosub; Kim, Sung-Soo; Jung, Hye-Sol; Yun, Won-Gun; Cho, Young Jae; Kwon, Wooil; Jang, Jin-Young; Kang, Un-Beom.
  • Kim H; Bertis R&D Division, Bertis Inc., Gyeonggi-do 13840, Republic of Korea.
  • Huh S; Bertis R&D Division, Bertis Inc., Gyeonggi-do 13840, Republic of Korea.
  • Park J; Bertis Inc., Seoul 06108, Republic of Korea.
  • Han Y; Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, Republic of Korea.
  • Ahn KG; Bertis R&D Division, Bertis Inc., Gyeonggi-do 13840, Republic of Korea.
  • Noh Y; Bertis R&D Division, Bertis Inc., Gyeonggi-do 13840, Republic of Korea.
  • Lee SJ; Bertis R&D Division, Bertis Inc., Gyeonggi-do 13840, Republic of Korea.
  • Chu H; Bertis R&D Division, Bertis Inc., Gyeonggi-do 13840, Republic of Korea.
  • Kim SS; Manufacturing and Technology Division, Bertis Inc., Gyeonggi-Do, 16954, Republic of Korea.
  • Jung HS; Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, Republic of Korea.
  • Yun WG; Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, Republic of Korea.
  • Cho YJ; Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, Republic of Korea.
  • Kwon W; Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, Republic of Korea.
  • Jang JY; Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, Republic of Korea. Electronic address: jangjy4@snu.ac.kr.
  • Kang UB; Bertis R&D Division, Bertis Inc., Gyeonggi-do 13840, Republic of Korea. Electronic address: unbeom.kang@bertis.com.
Mol Cell Proteomics ; : 100824, 2024 Aug 01.
Article en En | MEDLINE | ID: mdl-39097268
ABSTRACT
Pancreatic ductal adenocarcinoma (PDAC) suffers from lack of an effective diagnostic method, which hampers improvement in patient survival. Carbohydrate antigen 19-9 (CA19-9) is the only FDA-approved blood biomarker for PDAC, yet its clinical utility is limited due to suboptimal performance. Liquid chromatography-mass spectrometry (LC-MS) has emerged as a burgeoning technology in clinical proteomics for discovery, verification, and validation of novel biomarkers. A plethora of protein biomarker candidates for PDAC have been identified using LC-MS, yet few has successfully transitioned into clinical practice. This translational standstill is owed partly to insufficient considerations of practical needs and perspectives of clinical implementation during biomarker development pipelines, such as demonstrating analytical robustness of proposed biomarkers which is critical for transitioning from research-grade to clinical-grade assays. Moreover, throughput and cost-effectiveness of proposed assays ought to be considered concomitantly from early phases of the biomarker pipelines for enhancing widespread adoption in clinical settings. Here, we developed a fit-for-purpose multi-marker panel for PDAC diagnosis by consolidating analytically robust biomarkers as well as employing a relatively simple LC-MS protocol. In discovery phase, we comprehensively surveyed putative PDAC biomarkers from both in-house data and prior studies. In verification phase, we developed a multiple-reaction monitoring (MRM)-MS-based proteomic assay using surrogate peptides that passed stringent analytical validation tests. We adopted a high-throughput protocol including short gradient (<10 min) and simple sample preparation (no depletion or enrichment steps). Additionally, we developed our assay using serum samples, which are usually the preferred biospecimen in clinical settings. We developed predictive models based on our final panel of 12 protein biomarkers combined with CA19-9, which showed improved diagnostic performance compared to using CA19-9 alone in discriminating PDAC from non-PDAC controls including healthy individuals and patients with benign pancreatic diseases. A large-scale clinical validation is underway to demonstrate the clinical validity of our novel panel.

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article