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To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.

Introduction: Therapeutic options for diffuse malignant peritoneal mesothelioma (DMPM) are limited to surgery and locoregional chemotherapy. Despite improvements in survival rates, patients eventually succumb to disease progression. We investigated splicing deregulation both as molecular prognostic factor and potential novel target in DMPM, while we tested modulators of SF3b complex for antitumor activity. Methods: Tissue-microarrays of 64 DMPM specimens were subjected to immunohistochemical assessment of SF3B1 expression and correlation to clinical outcome. Two primary cell cultures were used for gene expression profiling and in vitro screening of SF3b modulators. Drug-induced splicing alterations affecting downstream cellular pathways were detected through RNA sequencing. Ultimately, we established bioluminescent orthotopic mouse models to test the efficacy of splicing modulation in vivo. Results: Spliceosomal genes are differentially upregulated in DMPM cells compared to normal tissues and high expression of SF3B1 correlated with poor clinical outcome in univariate and multivariate analysis. SF3b modulators (Pladienolide-B, E7107, Meayamycin-B) showed potent cytotoxic activity in vitro with IC50 values in the low nanomolar range. Differential splicing analysis of Pladienolide-B-treated cells revealed abundant alterations of transcripts involved in cell cycle, apoptosis and other oncogenic pathways. This was validated by RT-PCR and functional assays. E7107 demonstrated remarkable in vivo antitumor efficacy, with significant improvement of survival rates compared to vehicle-treated controls. Conclusions: SF3B1 emerged as a novel potential prognostic factor in DMPM. Splicing modulators markedly impair cancer cell viability, resulting also in potent antitumor activity in vivo. Our data designate splicing as a promising therapeutic target in DMPM. Keywords: Mesothelioma, Therapy, SF3b modulation, Splicing, RNA-sequencing