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.
Highlights
The death toll of gastric cancer (GC) was about 819,000 worldwide in 2015, ranking the third in mortality
To identify Gastric cancer (GC) biomarker candidates for LC-multiple reaction monitoring (MRM)-mass spectrometry (MS) validation process, we conducted literature data mining to create potential list of GC biomarkers, including proteins that were expressed differentially between GC tissues and matched normal tissues[13], differentially secreted proteins between GC cells and normal cells[14], serum proteins expressing in different levels between healthy controls and patients with locally advanced or metastatic GC15, and proteins that corresponded to genes expressed differentially between GC tissues and normal tissues[16]
For deep-down profiling, we carried out prefractionation by basic reversed phase liquid chromatography and two LC-MS/MS runs for each prefractionated sample as described in Methods
Summary
The death toll of gastric cancer (GC) was about 819,000 worldwide in 2015, ranking the third in mortality. It was 13,000 in South Korea[1]. Different options for lymphadenectomy and AT have been tested in various clinical trials, including SWOG/INT-01163, MAGIC4, NCC5, and ARTIST (Adjuvant chemoRadioTherapy In Stomach Tumors)[6]. Despite the availability of blood biomarkers, their clinical interventional roles have been insufficient in current medical situation[11]. We quantified a total of 93 serum biomarker candidates by multiple reaction monitoring (MRM)-MS, composed multi-marker panels using quantification results, and built a disease prediction model SEPROGADIC (SErum PROtein-based GAstric cancer preDICtor) to help predict the prognosis and suggest suitable AT for patients postoperatively. SEPROGADIC can stratify high or low risk groups in combination with clinical stage values and evaluate population of patients who could benefit from CTX or CCRT as adjuvant modalities (Fig. 1)
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