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Balluff, B. ; Rauser, S. ; Meding, S. ; Elsner, M. ; Schöne, C. ; Feuchtinger, A. ; Schuhmacher, C.* ; Novotny, A.* ; Jütting, U. ; Maccarrone, G.* ; Sarioglu, H. ; Ueffing, M. ; Braselmann, H. ; Zitzelsberger, H. ; Schmid, R.M. ; Höfler, H. ; Ebert, M.P.* ; Walch, A.K.

MALDI imaging identifies prognostic seven-protein signature of novel tissue markers in intestinal-type gastric cancer.

Am. J. Pathol. 179, 2720-2729 (2011)

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Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.

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Proteomics-based approaches allow us to investigate the biology of cancer beyond genomic initiatives. We used histology-based matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry to identify proteins that predict disease outcome in gastric cancer after surgical resection. A total of 181 intestinal-type primary resected gastric cancer tissues from two independent patient cohorts were analyzed. Protein profiles of the discovery cohort (n = 63) were directly obtained from tumor tissue sections by MALDI imaging. A seven-protein signature was associated with an unfavorable overall survival independent of major clinical covariates. The prognostic significance of three individual proteins identified (CRIP1, HNP-1, and S100-A6) was validated immunohistochemically on tissue microarrays of an independent validation cohort (n = 118). Whereas HNP-1 and S100-A6 were found to further subdivide early-stage (Union Internationale Contre le Cancer [UICC]-I) and late-stage (UICC II and III) cancer patients into different prognostic groups, CRIP1, a protein previously unknown in gastric cancer, was confirmed as a novel and independent prognostic factor for all patients in the validation cohort. The protein pattern described here serves as a new independent indicator of patient survival complementing the previously known clinical parameters in terms of prognostic relevance. These results show that this tissue-based proteomic approach may provide clinically relevant information that might be beneficial in improving risk stratification for gastric cancer patients.

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