SEPROGADIC – serum protein-based gastric cancer prediction model for prognosis and selection of proper adjuvant therapy View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-11-15

AUTHORS

Hee-Sung Ahn, Tae Sung Sohn, Mi Jeong Kim, Byoung Kyu Cho, Su Mi Kim, Seung Tae Kim, Eugene C. Yi, Cheolju Lee

ABSTRACT

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 (1b, 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. More... »

PAGES

16892

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-018-34858-x

DOI

http://dx.doi.org/10.1038/s41598-018-34858-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1109841500

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30442939


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