The data described was acquired as part of a clinical study with the aim to investigate the potential of tumor-reactive T-cell response as response to vaccination of pancreatic can-cer patients... Show moreThe data described was acquired as part of a clinical study with the aim to investigate the potential of tumor-reactive T-cell response as response to vaccination of pancreatic can-cer patients with an allogenic tumor cell lysate vaccine (Lau et al., 2022). Proteomics analysis was carried out to iden-tify tumor antigens that are shared between the allogeneic tumor cell lysate used for the vaccine and pancreatic duc-tal adenocarcinoma (PDAC) tissue samples. To this objective, cell lysates of the vaccine and of nine tissue samples were enzymatically digested and isotopically labeled with tandem mass tags (TMT) in a so-called six-plex manner (Thermo Fisher Scientific). Three pools were prepared by mixing the samples according to their TMT-labels. Subsequently, the three sample pools were fractionated into 24 fractions with high-pH reversed phase chromatography. These frac-tions were first analyzed on a nano-liquid chromatog-raphy (LC) system online coupled to a high-resolution Eclipse Orbitrap mass spectrometer (MS) equipped with a high-field asymmetric-waveform ion-mobility spectrome-try (FAIMS) source using a data-dependent MS2 shotgun method. Overall, 126,618 unique peptide sequences, on ba-sis of 768,638 peptide spectra matches and corresponding to 7,597 protein groups, were identified in the total sam-ple set including 61 tumor antigens (Supplement Table S2 in Lau et al. 2022) that were prioritized by Cheever and co-workers as vaccine target antigens on basis of a series of objective criteria (Cheever et al., 2009). In the second phase of the experiment, this set of tumor antigens was tar-geted using a serial precursor selection (SPS) MS3 method. From this data, ion trap MS2 and Orbitrap MS3 fragment spectra were extracted for peptide identification (protein se-quence database-dependent search) and relative quantifica-tion using the TMT labels, respectively. The dataset ulti-mately allowed the identification and quantification of 51 proteins and 163 related peptide precursors with the TMT labels (see Fig. 2B and Supplemental Fig. 8, Lau et al. 2022).(c) 2022 Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ) Show less
