Serum proteomics and disease-specific biomarkers of patients with advanced gastric cancer

Helgason,Helgi H.; Engwegen,Judith Y.M.N.; Zapatka,Mark; Cats,Annemieke; Boot,Henk; Beijnen,Jos H.; Schellens,Jan H.M.

doi:10.3892/ol_00000058

Serum proteomics and disease-specific biomarkers of patients with advanced gastric cancer

Authors:
- Helgi H. Helgason
- Judith Y.M.N. Engwegen
- Mark Zapatka
- Annemieke Cats
- Henk Boot
- Jos H. Beijnen
- Jan H.M. Schellens
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Affiliations: Division of Clinical Pharmacology, Department of Medical Oncology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, 1066 CX Amsterdam, The Netherlands
Published online on: March 1, 2010 https://doi.org/10.3892/ol_00000058
Pages: 327-333

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Abstract

Gastric cancer is a commonly diagnosed solid tumor which is associated with a dismal prognosis making early diagnosis essential. Thus, this study aimed to identify novel biomarkers in gastric cancer. Serum of patients with advanced gastric cancer was collected according to a predefined schedule: prior to first-line chemotherapy with epirubicin (50 mg/m2, day 1), cisplatin (60 mg/m2, day 1) and capecitabine (1,000 mg/m2, twice daily on days 1-14). The serum was collected serially before the treatment cycles and then analyzed by SELDI-TOF MS. Normal control subjects were matched according to age, gender and serum collection. Serum proteomic mass spectrometry data of all subjects were processed using the tbimass R-package and compared. We analyzed i) whether proteomic profile changes were associated with a response to chemotherapy and survival, and ii) whether changes in proteomic profiles occurring during the time period of chemotherapy were associated with tumor response. In total, 82 patients with adenocarcinoma of the stomach (mean age 57 years, males 69.5%) were treated with a mean number of five chemotherapy cycles. The overall tumor response rate, complete and partial remission combined, was 37%, median time to progression was 7 months (95% CI, 6-8) and median overall survival 11 months (95% CI, 9.5-12). By comparing 77 serum samples of patients with normal matched controls, we identified 32 proteins which discriminated the two groups. By selecting the most differentiating proteins, we built a classification model that correctly categorized 81% of the gastric cancer patients and 90% of the normal controls. Furthermore, we found a statistically significant correlation between the pre-treatment intensity of serum amyloid-α (SAA) and overall survival in gastric cancer patients, whereby a low intensity of SAA predicted a longer patient survival. A classification model, based on the 32 most discriminating proteins differentiating gastric cancer from normal controls, correctly classified subjects with relatively high sensitivity and specificity.

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