Proteogenomic-based method for identifying tumor-specific antigens

[0228] Example 1: Materials and methods

[0229] Mice. C57BL / 6 mice were obtained from Jackson Laboratories (Bar Harbor, ME). Mice were housed under specific pathogen-free conditions.

[0230] Cell lines. The EL4 T-lymphoblastic lymphoma cell line, CT26 colorectal carcinoma cell line and B-cell hybridoma HB-124 were obtained from the American Type Culture Collection (ATCC). EL4 and CT26 cells were cultured in RPMI 1640 / HEPES supplemented with 10% heat-inactivated fetal calf serum, 1% L-glutamine and 1% penicillin-streptomycin. Cell culture medium was further supplemented with 1% non-essential amino acids and 1% sodium pyruvate or only 1% sodium pyruvate for EL4 and CT26 cells, respectively. For the production of anti-CDR2 antibodies, HB-124 cells were cultured in IMDM supplemented with 10% heat-inactivated fetal bovine serum. Unless otherwise stated, all reagents were purchased from

[0231]Human primary samples. The primary leukemia samples used in this study (four B-AL...

[0250] Example 2: Rationale and design of a proteomics approach for TSA discovery.

[0251] Attempts to computationally predict TSA using various algorithms are fraught with extremely high false discovery rates 27 . Thus, system-level molecular definition of MAP libraries is only possible through high-throughput MS studies 3 . Current methods use MS / MS software tools such as Peaks28 , which relies on a user-defined protein database to match each acquired MS / MS spectrum and peptide sequence. Since the reference proteome does not contain TSAs, MS-based TSA discovery workflows must use proteomics strategies to build customized databases derived from tumor RNA-sequencing (RNA-Seq) data 29 , the database should ideally contain all proteins expressed in the tumor sample under consideration, even unannotated proteins. Due to the inability of current MS / MS software tools to process full-frame translation of all RNA-Seq reads 30,31 Given the huge search space created, proteomic st...

[0252] Example 3: Noncoding regions are the main source of TSA.

[0253] At a false discovery rate of 5%, 1,875 MAPs on CT26 cells and 783 MAPs on EL4 cells were identified. Among those, if (i) their 33 nucleotide long MAP coding sequence (MCS) derived from the pan-cancer-restricted 33 nucleotide long k-mer is absent in the mTEChi transcriptome or if ( ii) Their 24-to-30 nt long MCS derived from a truncated version of the cancer-restricted 33 nt long k-mer in the transcriptome of cancer compared to mTEC hi Cells overexpressed at least 10-fold ( Figure 8A ), then mTEC hi MAPs absent in the proteome were considered TSA candidates. During the MS-related validation step and assignment of genomic localization ( Figure 8B -C) Afterwards, a total of 6 mTSA candidates and 15 aeTSA candidates were obtained: 14 presented by CT26 cells and 7 presented by EL4 cells ( Figure 2A -B). MAPs that are both mutated and aberrantly expressed are included in the mTSA category. All of thes...