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Alternative splicing changes are frequently observed in cancer and are starting to be recognized as important signatures for tumor progression and therapy. However, their functional impact and relevance to tumorigenesis remain mostly unknown. We carried out a systematic analysis to characterize the potential functional consequences of alternative splicing changes in thousands of tumor samples. This analysis revealed that a subset of alternative splicing changes affect protein domain families that are frequently mutated in tumors and potentially disrupt protein-protein interactions in cancer-related pathways. Moreover, there was a negative correlation between the number of these alternative splicing changes in a sample and the number of somatic mutations in drivers. We propose that a subset of the alternative splicing changes observed in tumors may represent independent oncogenic processes that could be relevant to explain the functional transformations in cancer, and some of them could potentially be considered alternative splicing drivers (AS drivers). ; H.C.-G. and E.E. were supported by the MINECO and FEDER (BIO2014-52566-R), Consolider RNAREG (CSD2009-00080), AGAUR (SGR2014-1121), the European ITN Network RNP-Net (ID: 289007), and the Sandra Ibarra Foundation for Cancer (FSI2013). E.P.-P. and A.G. were supported by the SBP CC grant (P30 CA030199). All authors thank The Cancer Genome Atlas project for making their data publicly available. The Computational RNA Biology Group is part of the Research Programme on Biomedical Informatics (GRIB), which is a member of ELIXIR-Excelerate of the European Union Horizon 2020 Programme 2014-2020 (No. 676559) and of the Spanish National Bioinformatics Institute (INB), PRB2-ISCIII and is supported by grant PT13/0001/0023 of the PE I+D+I 2013-2016, funded by ISCIII and FEDER

A common problem encountered when performing large-scale MS proteome analysis is the loss of information due to the high percentage of unassigned spectra. To determine the causes behind this loss we have analyzed the proteome of one of the smallest living bacteria that can be grown axenically, Mycoplasma pneumoniae (729 ORFs). The proteome of M. pneumoniae cells, grown in defined media, was analyzed by MS. An initial search with both Mascot and a species-specific NCBInr database with common contaminants (NCBImpn), resulted in around 79% of the acquired spectra not having an assignment. The percentage of non-assigned spectra was reduced to 27% after re-analysis of the data with the PEAKS software, thereby increasing the proteome coverage of M. pneumoniae from the initial 60% to over 76%. Nonetheless, 33 413 spectra with assigned amino acid sequences could not be mapped to any NCBInr database protein sequence. Approximately, 1% of these unassigned peptides corresponded to PTMs and 4% to M. pneumoniae protein variants (deamidation and translation inaccuracies). The most abundant peptide sequence variants (Phe-Tyr and Ala-Ser) could be explained by alterations in the editing capacity of the corresponding tRNA synthases. About another 1% of the peptides not associated to any protein had repetitions of the same aromatic/hydrophobic amino acid at the N-terminus, or had Arg/Lys at the C-terminus. Thus, in a model system, we have maximized the number of assigned spectra to 73% (51 453 out of the 70 040 initial acquired spectra). ; This work was sup-ported by the European Research Council (ERC), the Fundación Marcelino Botín, the Spanish Ministerio de Economía y Com-petitividad BIO2007-61762 and the ISCIII (PI10/01702). TheCRG/UPF Proteomics Unit is part of the "Plataforma de Re-cursos Biomoleculares y Bioinform´aticos (ProteoRed)" supportedby grant PT13/0001 of Instituto de Salud Carlos III (ISCIII).We acknowledge the support of the Spanish Ministry of Economyand Competitiveness, 'Centro de Excelencia Severo Ochoa 2013–2017', SEV-2012-0208. This project has received funding fromthe European Union's Horizon 2020 research and innovationprogram under grant agreement No 634942