Literature DB >> 22966303

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

Helgi H Helgason1, Judith Y M N Engwegen, Mark Zapatka, Annemieke Cats, Henk Boot, Jos H Beijnen, Jan H M Schellens.   

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/m(2), day 1), cisplatin (60 mg/m(2), day 1) and capecitabine (1,000 mg/m(2), 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.

Entities:  

Year:  2010        PMID: 22966303      PMCID: PMC3436443          DOI: 10.3892/ol_00000058

Source DB:  PubMed          Journal:  Oncol Lett        ISSN: 1792-1074            Impact factor:   2.967


  24 in total

1.  New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada.

Authors:  P Therasse; S G Arbuck; E A Eisenhauer; J Wanders; R S Kaplan; L Rubinstein; J Verweij; M Van Glabbeke; A T van Oosterom; M C Christian; S G Gwyther
Journal:  J Natl Cancer Inst       Date:  2000-02-02       Impact factor: 13.506

2.  Algorithms for alignment of mass spectrometry proteomic data.

Authors:  Neal Jeffries
Journal:  Bioinformatics       Date:  2005-05-06       Impact factor: 6.937

3.  Identification of serum proteins discriminating colorectal cancer patients and healthy controls using surface-enhanced laser desorption ionisation-time of flight mass spectrometry.

Authors:  Judith Y M N Engwegen; Helgi H Helgason; Annemieke Cats; Nathan Harris; Johannes M G Bonfrer; Jan H M Schellens; Jos H Beijnen
Journal:  World J Gastroenterol       Date:  2006-03-14       Impact factor: 5.742

4.  Estimation of validity of mass screening program for gastric cancer in Osaka, Japan.

Authors:  R Murakami; H Tsukuma; T Ubukata; K Nakanishi; I Fujimoto; T Kawashima; H Yamazaki; A Oshima
Journal:  Cancer       Date:  1990-03-01       Impact factor: 6.860

5.  Serum peptidome patterns that distinguish metastatic thyroid carcinoma from cancer-free controls are unbiased by gender and age.

Authors:  Josep Villanueva; Andrew J Martorella; Kevin Lawlor; John Philip; Martin Fleisher; Richard J Robbins; Paul Tempst
Journal:  Mol Cell Proteomics       Date:  2006-08-08       Impact factor: 5.911

Review 6.  Adjuvant therapy in gastric cancer.

Authors:  Lionel Lim; Michael Michael; G Bruce Mann; Trevor Leong
Journal:  J Clin Oncol       Date:  2005-09-01       Impact factor: 44.544

Review 7.  Chemotherapy in advanced gastric cancer: a systematic review and meta-analysis based on aggregate data.

Authors:  Anna D Wagner; Wilfried Grothe; Johannes Haerting; Gerhard Kleber; Axel Grothey; Wolfgang E Fleig
Journal:  J Clin Oncol       Date:  2006-06-20       Impact factor: 44.544

8.  SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancer.

Authors:  Emanuel F Petricoin; Lance A Liotta
Journal:  Curr Opin Biotechnol       Date:  2004-02       Impact factor: 9.740

Review 9.  Clinical proteomics in breast cancer: a review.

Authors:  Marie-Christine W Gast; Jan H M Schellens; Jos H Beijnen
Journal:  Breast Cancer Res Treat       Date:  2008-12-11       Impact factor: 4.872

10.  Comparison of normalisation methods for surface-enhanced laser desorption and ionisation (SELDI) time-of-flight (TOF) mass spectrometry data.

Authors:  Wouter Meuleman; Judith Ymn Engwegen; Marie-Christine W Gast; Jos H Beijnen; Marcel Jt Reinders; Lodewyk Fa Wessels
Journal:  BMC Bioinformatics       Date:  2008-02-07       Impact factor: 3.169

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  1 in total

Review 1.  Mass spectrometry-based serum and plasma peptidome profiling for prediction of treatment outcome in patients with solid malignancies.

Authors:  Mariette Labots; Lisette M Schütte; Johannes C van der Mijn; Thang V Pham; Connie R Jiménez; Henk M W Verheul
Journal:  Oncologist       Date:  2014-09-03
  1 in total

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