![Figure 2. Comparative HLA ligandome profiling and identification of myeloma-associated antigens. (A) Saturation analysis of HLA class I ligand source protein identifications in MM patients. Number of unique HLA ligand source protein identifications as a function of cumulative HLA ligand source protein identifications in 10 MM patients. Exponential regression allowed for the robust calculation (R2 = 0.99) of the maximum attainable number of different source protein identifications (dashed line). The dotted line depicts the source proteome coverage achieved in our MM patient cohort. (B) Overlap analysis of HLA class I ligand source proteins of primary MM samples (n = 10), MCLs (n = 5), and HV samples (total n = 45: PBMC [n = 30], BMNC [n = 10], granulocytes [n = 5]). (C) Comparative profiling of HLA ligand source proteins based on the frequency of HLA-restricted presentation in MM and HV ligandomes. Frequencies of MMs/HVs positive for HLA-restricted presentation of the respective source protein (x-axis) are indicated on the y-axis. The box on the left highlights the subset of myeloma-associated antigens showing MM-exclusive presentation in >25% of myeloma samples. (D) Statistical assessment of false-positive myeloma-antigen IDs at different threshold values. The numbers of original TAAs identified based on the analysis of the MM and HV cohorts were compared with random virtual TAAs. Virtual MM and HV samples were generated in silico based on random weighted sampling from the entirety of protein identifications in both original cohorts. These randomized virtual ligandomes of defined size (n = 957 proteins, which is the mean number of protein identifications in all analyzed samples) were used to define TAAs based on simulated cohorts of 15 MM vs 45 HV samples. The process of protein randomization, cohort assembly, and TAA identification was repeated 1000 times and the mean value of resultant virtual TAAs was calculated and plotted for the different threshold values. The corresponding FDRs for any chosen TAA threshold are listed below the x-axis. sum, summary.](https://ash.silverchair-cdn.com/ash/content_public/journal/blood/126/10/10.1182_blood-2015-04-640532/4/1203f2.jpeg?Expires=1735841270&Signature=bTUNmrymQPUSusTLo53SGdrNYAOnzJn~ndzJAxhShs3Ks5AEHVTr24Fahq6gnqNtXNxvQokIy9cd2VjbMXZiW5n~OifkdKQhAV4NLiKGGjHDoKgA7vmQ89qAny10IEpqL5l2mxBD4P2W5GtY9dQuLjWxF-02kzPflj17-AaifHwwfxCs7PZZ0Hr-NIkwPFw62K7gFdsu9Q7zXferaDyigSre2gzfmlvbd6eQkqN~Q3fDZCGb3wwN63mUvErEsNSznfXcLuNUW2U9O6fmtaQ1Ro7cR5mej7VEfi1l6KTrSBgJCOUuoSPc0iNflCmJsm~OGv05vecUhfhLiz-4pRKMhg__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA)
Comparative HLA ligandome profiling and identification of myeloma-associated antigens. (A) Saturation analysis of HLA class I ligand source protein identifications in MM patients. Number of unique HLA ligand source protein identifications as a function of cumulative HLA ligand source protein identifications in 10 MM patients. Exponential regression allowed for the robust calculation (R2 = 0.99) of the maximum attainable number of different source protein identifications (dashed line). The dotted line depicts the source proteome coverage achieved in our MM patient cohort. (B) Overlap analysis of HLA class I ligand source proteins of primary MM samples (n = 10), MCLs (n = 5), and HV samples (total n = 45: PBMC [n = 30], BMNC [n = 10], granulocytes [n = 5]). (C) Comparative profiling of HLA ligand source proteins based on the frequency of HLA-restricted presentation in MM and HV ligandomes. Frequencies of MMs/HVs positive for HLA-restricted presentation of the respective source protein (x-axis) are indicated on the y-axis. The box on the left highlights the subset of myeloma-associated antigens showing MM-exclusive presentation in >25% of myeloma samples. (D) Statistical assessment of false-positive myeloma-antigen IDs at different threshold values. The numbers of original TAAs identified based on the analysis of the MM and HV cohorts were compared with random virtual TAAs. Virtual MM and HV samples were generated in silico based on random weighted sampling from the entirety of protein identifications in both original cohorts. These randomized virtual ligandomes of defined size (n = 957 proteins, which is the mean number of protein identifications in all analyzed samples) were used to define TAAs based on simulated cohorts of 15 MM vs 45 HV samples. The process of protein randomization, cohort assembly, and TAA identification was repeated 1000 times and the mean value of resultant virtual TAAs was calculated and plotted for the different threshold values. The corresponding FDRs for any chosen TAA threshold are listed below the x-axis. sum, summary.
