Major breakthrough in cancer treatment has been achieved by harnessing the capabilities of the immune system to both identify and eliminate cancer, even metastasized cancer. Mutations in cancer leading to altered proteins are well documented as cancer neoantigens. However, exiting data indicates that genomic aberration can generate other types of tumor specific proteins like those derived from intron retention, unexpected novel coding regions, premature start codons, activated retroviral elements and other events.1,2 This poses a new challenge since effective discovery and analysis of such complex neoantigens require true integration of genomics and proteomics. We have generated tools that take advantage of massive genomics data by incorporating sequence information to the proteomics data-analysis pipeline. This will allow protein level analysis of gene variants as well as detection of novel protein coding regions1. To control error rate in variant detection, we have a combined experimental isoelectric point data from peptide fractions (HiRIEF LC-MS/MS) and bioinformatics approaches into the proteogenomics workflow (IPAW)2. A proteogenomics analysis of human tissues using the IPAW pipeline reveals novel protein coding regions. When applied on breast cancer tumor samples, we could demonstrate in-depth quantitative analysis revealing drug target correlations as well as discovers putative cancer neoantigens3. To gain knowledge of these novel proteins, we have analyzed subcellular location of these in human cell line models. For location analysis, we used SubCellBarcode based proteome wide location analysis4. Another application of the pipeline enabled detection of proteins transferring placenta during pregnancy, the relying on paternal protein variant detection, suggesting molecular communication between fetus and mother5. Finally, the systems level analysis of the tumor proteome represents the combined effect of epigenetic, transcriptional and translational regulation in relation to host immune response and will therefore provide an important molecular phenotype data layer on immune state and evasion mechanisms of tumors.

1. Branca R.M., Orre L-M., Johansson H.J., Granholm V., Huss M., Pérez-Bercoff Å., Forshed J., Käll L., Lehtiö J. HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics. Nature Methods, 2014 Jan;11(1):59-62.

2. Zhu Y, Orre LM, Johansson HJ, Huss M, Boekel J, Vesterlund M, Fernandez-Woodbridge A, Branca RMM, Lehtiö J. Discovery of coding regions in the human genome by integrated proteogenomics analysis workflow. Nature Commun. 2018 Mar 2;9(1):903.

3. Johansson HJ, Socciarelli F, Vacanti NM, Haugen MH, Zhu Y, Siavelis I, Fernandez A, Aure MR, Sennblad B, Vesterlund M, Branca RM, Orre LM, Huss M, Fredlund E, Beraki E, Garred Ø, Boekel J, Sauer T, Zhao W, Nord S, Höglander EK, Jans CD, Brismar H, Haukaas TH, Bathen TF, Schlichting E, Naume B, OSBREAC, Luders T, Borgen E, Kristensen VN, Russnes HG, Lingjærde OC, Mills GB, Sahlberg KK, Børresen-Dale A.L, Lehtiö J., Breast cancer quantitative proteome and proteogenomic landscape. Nature Comm, 10 Apr, 2019.

4. Orre LM, Vesterlund M, Pan Y, Arslan T, Zhu Y, Fernandez Woodbridge A, Frings O, Fredlund E, Lehtiö J. SubCellBarCode: Proteome-wide mapping of protein localization and relocalization. Mol Cell. 2019 Jan 3.

5. Pernemalm M, Sandberg A, Zhu Y, Boekel J, Tamburro D, Schwenk JM, Bjork A, Wahren-Herlenius M, Amark H, Ostenson C.G, Westgren M, Lehtiö J. In-depth human plasma proteome analysis captures tissue proteins and transfer of protein variants across the placenta. eLife, Apr. 8., 2019.