Ahn, Hee-Sung Sohn, Tae Sung Kim, Mi Jeong Cho, Byoung Kyu Kim, Su Mi Kim, Seung Tae Yi, Eugene C. Lee, Cheolju 2024-01-19T21:30:49Z 2024-01-19T21:30:49Z 2021-09-05 2018-11-15 2045-2322 https://pubs.kist.re.kr/handle/201004/120676 Gastric cancer (GC) patients usually receive surgical treatment. Postoperative therapeutic options such as anticancer adjuvant therapies (AT) based on prognostic prediction models would provide patient-specific treatment to decrease postsurgical morbidity and mortality rates. Relevant prognostic factors in resected GC patient's serum may improve therapeutic measures in a non-invasive manner. In order to develop a GC prognostic model, we designed a retrospective study. In this study, serum samples were collected from 227 patients at a 4-week recovery period after D2 lymph node dissection, and 103 cancer-related serum proteins were analyzed by multiple reaction monitoring mass spectrometry. Using the quantitative values of the serum proteins, we developed SEPROGADIC (SErum PROtein-based GAstric cancer preDICtor) prognostic model consisting of 6 to 14 serum proteins depending on detailed purposes of the model, prognosis prediction and proper AT selection. SEPROGADIC could clearly classify patients with good or bad prognosis at each TNM stage (113, 2, 3 and 4) and identify a patient subgroup who would benefit from CCRT (combined chemoradiation therapy) rather than CTX (chemotherapy), or vice versa. Our study demonstrated that serum proteins could serve as prognostic factors along with clinical stage information in patients with resected gastric cancer, thus allowing patient-tailored postsurgical treatment. English NATURE PUBLISHING GROUP LYMPH-NODE DISSECTION PLASMA-PROTEOME COMPANION DIAGNOSTICS BIOMARKER DISCOVERY RADIATION-THERAPY MASS-SPECTROMETRY ROC CURVES EXPRESSION TRIAL CHEMOTHERAPY SEPROGADIC-serum protein-based gastric cancer prediction model for prognosis and selection of proper adjuvant therapy Article 10.1038/s41598-018-34858-x 1 SCIENTIFIC REPORTS, v.8 SCIENTIFIC REPORTS 8 scie scopus 000450167700063 2-s2.0-85056665143 Multidisciplinary Sciences Science & Technology - Other Topics Article LYMPH-NODE DISSECTION PLASMA-PROTEOME COMPANION DIAGNOSTICS BIOMARKER DISCOVERY RADIATION-THERAPY MASS-SPECTROMETRY ROC CURVES EXPRESSION TRIAL CHEMOTHERAPY