期刊
CANCERS
卷 11, 期 2, 页码 -出版社
MDPI
DOI: 10.3390/cancers11020155
关键词
pancreatic ductal adenocarcinoma; systems biology; meta-analysis; machine learning; next-generation sequencing; transcriptomics; diagnostic biomarker; prognostic biomarker
类别
资金
- National Research Foundation of Korea (NRF) - Korean government (MSIP) [NRF-2018R1A5A2024425]
- National Research Foundation of Korea (NRF) [2018R1A2A1A05077263]
- BK21 Plus Program in 2018
- National Research Foundation of Korea [2018R1A2A1A05077263] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Substantial alterations at the multi-omics level of pancreatic cancer (PC) impede the possibility to diagnose and treat patients in early stages. Herein, we conducted an integrative omics-based translational analysis, utilizing next-generation sequencing, transcriptome meta-analysis, and immunohistochemistry, combined with statistical learning, to validate multiplex biomarker candidates for the diagnosis, prognosis, and management of PC. Experiment-based validation was conducted and supportive evidence for the essentiality of the candidates in PC were found at gene expression or protein level by practical biochemical methods. Remarkably, the random forests (RF) model exhibited an excellent diagnostic performance and LAMC2, ANXA2, ADAM9, and APLP2 greatly influenced its decisions. An explanation approach for the RF model was successfully constructed. Moreover, protein expression of LAMC2, ANXA2, ADAM9, and APLP2 was found correlated and significantly higher in PC patients in independent cohorts. Survival analysis revealed that patients with high expression of ADAM9 (Hazard ratio (HR)(OS) = 2.2, p-value < 0.001), ANXA2 (HROS = 2.1, p-value < 0.001), and LAMC2 (HRDFS = 1.8, p-value = 0.012) exhibited poorer survival rates. In conclusion, we successfully explore hidden biological insights from large-scale omics data and suggest that LAMC2, ANXA2, ADAM9, and APLP2 are robust biomarkers for early diagnosis, prognosis, and management for PC.
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