Highlights d Integrated proteogenomic characterization in 103 ccRCC cases d Delineation of chromosomal translocation events leading to chromosome 3p loss d Tumor-specific proteomic/phosphoproteomic alterations unrevealed by mRNA analysis d Immune-based subtypes of ccRCC defined by mRNA, proteome, and phosphoproteome

No abstract

In the originally published version of this article, Daniel Geiszler's last name was misspelled. This error has now been corrected in the article online.

Identification of post-translationally or chemically modified peptides in mass spectrometry-based proteomics experiments is a crucial yet challenging task. We have recently introduced a fragment ion indexing method and the MSFragger search engine to empower an open search strategy for comprehensive analysis of modified peptides. However, this strategy does not consider fragment ions shifted by unknown modifications, preventing modification localization and limiting the sensitivity of the search. Here we present a localization-aware open search method, in which both modification-containing (shifted) and regular fragment ions are indexed and used in scoring. We also implement a fast mass calibration and optimization method, allowing optimization of the mass tolerances and other key search parameters. We demonstrate that MSFragger with mass calibration and localization-aware open search identifies modified peptides with significantly higher sensitivity and accuracy. Comparing MSFragger to other modification-focused tools (pFind3, MetaMorpheus, and TagGraph) shows that MSFragger remains an excellent option for fast, comprehensive, and sensitive searches for modified peptides in shotgun proteomics data.

Ion mobility brings an additional dimension of separation to liquid chromatography-mass spectrometry, improving identification of peptides and proteins in complex mixtures. A recently introduced timsTOF mass spectrometer (Bruker) couples trapped ion mobility separation to time-of-flight mass analysis. With the parallel accumulation serial fragmentation (PASEF) method, the timsTOF platform achieves promising results, yet analysis of the data generated on this platform represents a major bottleneck. Currently, MaxQuant and PEAKS are most commonly used to analyze these data. However, due to the high complexity of timsTOF PASEF data, both require substantial time to perform even standard tryptic searches. Advanced searches (e.g. with many variable modifications, semi- or non-enzymatic searches, or open searches for post-translational modification discovery) are practically impossible. We have extended our fast peptide identification tool MSFragger to support timsTOF PASEF data, and developed a label-free quantification tool, IonQuant, for fast and accurate 4-D feature extraction and quantification. Using a HeLa data set published by Meier et al. (2018), we demonstrate that MSFragger identifies significantly (~30%) more unique peptides than MaxQuant (1.6.10.43), and performs comparably or better than PEAKS X+ (~10% more peptides). IonQuant outperforms both in terms of number of quantified proteins while maintaining good quantification precision and accuracy. Runtime tests show that MSFragger and IonQuant can fully process a typical two-hour PASEF run in under 70 minutes on a typical desktop (6 CPU cores, 32 GB RAM), significantly faster than other tools. Finally, through semi-enzymatic searching, we significantly increase the number of identified peptides. Within these semi-tryptic identifications, we report evidence of gas-phase fragmentation prior to MS/MS analysis.

Highlights d Proteogenomics characterization of 218 pediatric brain tumor samples of 7 histologies d Proteomic clusters reveal actionable biological features spanning histological boundaries d Proteomics reveal downstream effects of DNA alterations not evident in transcriptomics d Kinase activity analyses provide insights into pathway activities and druggable targets

Highlights d A systematic inventory of HNSCC-associated proteins, phosphosites, and pathways d Three multi-omic subtypes linked to targeted treatment approaches and immunotherapy d Widespread deletion of immune modulatory genes accounts for loss of immunogenicity d Two modes of EGFR activation inform response to anti-EGFR monoclonal antibodies

The dia-PASEF technology uses ion mobility separation to reduce signal interferences and increase sensitivity in proteomic experiments. Here we present a two-dimensional peak-picking algorithm and generation of optimized spectral libraries, as well as take advantage of neural network-based processing of dia-PASEF data. Our computational platform boosts proteomic depth by up to 83% compared to previous work, and is specifically beneficial for fast proteomic experiments and those with low sample amounts. It quantifies over 5300 proteins in single injections recorded at 200 samples per day throughput using Evosep One chromatography system on a timsTOF Pro mass spectrometer and almost 9000 proteins in single injections recorded with a 93-min nanoflow gradient on timsTOF Pro 2, from 200 ng of HeLa peptides. A user-friendly implementation is provided through the incorporation of the algorithms in the DIA-NN software and by the FragPipe workflow for spectral library generation.