SEPROGADIC – serum protein-based gastric cancer prediction model for prognosis and selection of proper adjuvant therapy. Issue 1 (December 2018)
- Record Type:
- Journal Article
- Title:
- SEPROGADIC – serum protein-based gastric cancer prediction model for prognosis and selection of proper adjuvant therapy. Issue 1 (December 2018)
- Main Title:
- SEPROGADIC – serum protein-based gastric cancer prediction model for prognosis and selection of proper adjuvant therapy
- Authors:
- Ahn, Hee-Sung
Sohn, Tae
Kim, Mi
Cho, Byoung
Kim, Su
Kim, Seung
Yi, Eugene
Lee, Cheolju - Abstract:
- 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.
- Is Part Of:
- Scientific reports. Volume 8:Issue 1(2018)
- Journal:
- Scientific reports
- Issue:
- Volume 8:Issue 1(2018)
- Issue Display:
- Volume 8, Issue 1 (2018)
- Year:
- 2018
- Volume:
- 8
- Issue:
- 1
- Issue Sort Value:
- 2018-0008-0001-0000
- Page Start:
- 1
- Page End:
- 13
- Publication Date:
- 2018-12
- Subjects:
- Natural history -- Research -- Periodicals
Biology -- Research -- Periodicals
Physical sciences -- Research -- Periodicals
Earth sciences -- Research -- Periodicals
Environmental sciences -- Research -- Periodicals
502.85 - Journal URLs:
- http://www.nature.com/ ↗
http://www.nature.com/srep/index.html ↗ - DOI:
- 10.1038/s41598-018-34858-x ↗
- Languages:
- English
- ISSNs:
- 2045-2322
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 10991.xml