Fig. 2
Development of a pipeline for MAP identification. A WGS data were generated from CT26 Mlh1+/+ and Mlh1-/- samples and analyzed using IDEA pipeline [28] in order to produce the alignment and variant calling files. B RNAseq data were further generated from CT26 Mlh1+/+ and Mlh1-/- cells 150 days after genome editing and after excision from the mice when tumors reached 1200 mm3 of volume in NOD-SCID mice. In the case of BALB/c mice, the tumors were excised when they reached volumes of 1100 mm3 and 800 mm3 for Mlh1+/+ and Mlh1-/- tumors, respectively. FastQ files were handled to produce the list of all putative peptides present in the transcriptome of each sample. In brief, every transcript sequence in the FastQ files underwent all-six frame translation; then the lists of 8–11 amino acid long peptides were generated using the KMER approach; finally, the peptide lists were compared to select only peptides targeted in tumors excised from immunocompetent mice (see methods). C CT26 Mlh1+/+ and Mlh1-/- tumor masses were explanted from NOD-SCID mice (n = 6 per group) and protein extraction was performed. MHC-I was isolated from whole protein lysates through H-2d antibodies conjugated to resin, then peptides were eluted from MHC-I and injected in mass spectrometer. The LC-MS/MS data were then analyzed using MaxQuant. Peptides were searched against the customized DB made of targeted peptides generated by RNAseq data. D Sequence results obtained from the immune-peptidomic pipeline were ultimately matched with WGS data to retrieve information about the genomic sources of targeted peptides (see “Methods”)