Here we present a dataset generated using formalin-fixed paraffin-embedded archival samples from two rare lung neuroendocrine tumor subtypes (namely, two atypical carcinoids, ACs, and two large-cell neuroendocrine carcinomas, LCNECs). Samples were subjected to a shotgun proteomics pipeline, comprising full-length protein extraction, SDS removal through spin columns, in solution trypsin digestion, long gradient liquid chromatography peptide separation and LTQ-Orbitrap mass spectrometry analysis. A total of 1260 and 2436 proteins were identified in the AC and LCNEC samples, respectively, with FDR <1%. MS data are available in the PeptideAtlas repository at http://www.peptideatlas.org/PASS/PASS00375.

Atypical carcinoid and large cell neuroendocrine carcinoma of the lung : A proteomic dataset from formalin-fixed archival samples / A. Tanca, M.F. Addis, S. Pisanu, M. Abbondio, D. Pagnozzi, A. Eccher, G. Rindi, P. Cossu Rocca, S. Uzzau, G. Fanciulli. - In: DATA IN BRIEF. - ISSN 2352-3409. - 7(2016 Jun), pp. 529-531. [10.1016/j.dib.2016.02.083]

Atypical carcinoid and large cell neuroendocrine carcinoma of the lung : A proteomic dataset from formalin-fixed archival samples

M.F. Addis
;
2016

Abstract

Here we present a dataset generated using formalin-fixed paraffin-embedded archival samples from two rare lung neuroendocrine tumor subtypes (namely, two atypical carcinoids, ACs, and two large-cell neuroendocrine carcinomas, LCNECs). Samples were subjected to a shotgun proteomics pipeline, comprising full-length protein extraction, SDS removal through spin columns, in solution trypsin digestion, long gradient liquid chromatography peptide separation and LTQ-Orbitrap mass spectrometry analysis. A total of 1260 and 2436 proteins were identified in the AC and LCNEC samples, respectively, with FDR <1%. MS data are available in the PeptideAtlas repository at http://www.peptideatlas.org/PASS/PASS00375.
archival tissues; FFPE; mass spectrometry; neuroendocrine tumors; proteomics; 3304; multidisciplinary
Settore BIO/10 - Biochimica
giu-2016
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/492704
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