In the last decade advances in genomics, uptake of targeted therapies, and the advent of personalized treatments have fueled a dramatic change in cancer care. However, the effectiveness of most targeted therapies is short lived, as tumors evolve and develop resistance. Combinations of drugs offer the potential to overcome resistance. The space of possible combinations is vast, and significant advances are required to effectively find optimal treatment regimens tailored to a patient's tumor. DREAM and AstraZeneca hosted a Challenge open to the scientific community aimed at computational prediction of synergistic drug combinations and predictive biomarkers associated to these combinations. We released a data set comprising ~11,500 experimentally tested drug combinations, coupled to deep molecular characterization of the respective 85 cancer cell lines. Among 150 submitted approaches, those that incorporated prior knowledge of putative drug targets showed superior performance predicting drug synergy across independent data. Genomic features of best-performing models revealed putative mechanisms of drug synergy for multiple drugs in combination with PI3K/AKT pathway inhibitors.All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
52We describe the rapid and reproducible acquisition of quantitative proteome maps for the 53 NCI-60 cancer cell lines and their use to reveal cancer biology and drug response 54 determinants. Proteome datasets for the 60 cell lines were acquired in duplicate within 30 55 working days using pressure cycling technology and SWATH mass spectrometry. We 56 consistently quantified 3,171 SwissProt proteotypic proteins across all cell lines, generating a 57 data matrix with 0.1% missing values, allowing analyses of protein complexes and pathway 58 activities across all the cancer cells. Systematic and integrative analysis of the genetic 59 variation, mRNA expression and proteomic data of the NCI-60 cancer cell lines uncovered 60complementarity between different types of molecular data in the prediction of the response to 61 240 drugs. We additionally identified novel proteomic drug response determinants for 62 clinically relevant chemotherapeutic and targeted therapies. We anticipate that this study 63 represents a landmark effort toward the translational application of proteotypes, which reveal 64 biological insights that are easily missed in the absence of proteomic data. 65 96 consistently quantified 3,171 SwissProt proteotypic proteins across all cell lines, generating a 97 data matrix (120 proteomes vs. 3171 proteins) with 0.1% missing values. Raw signals of each 98 peptide and protein in each sample were curated with an expert system. The NCI-60 human 99 5 cancer cell line panel contains 60 lines from 9 different tissue types 12 . The NCI-60 have been 100 molecularly and pharmacologically characterized with unparalleled depth and coverage, 101 offering a prime in vitro model to further our understanding of cancer biology and cellular 102 responses to anti-cancer agents 12, 13 . Discoveries enabled by the NCI-60 in recent years 103 include the development of the FDA approved drugs oxaliplatin for the treatment of colon 104 cancers 14 , eribulin for metastatic breast cancers 12 , bortezomib for the treatment of multiple 105 myeloma 15 , and rhomidepsin for cutaneous T-cell lymphomas 16 . The sensitivity of the NCI-106 60 has been measured for over 100,000 synthetic or natural compounds derived from a wide 107 range of academic and industrial sources 12 , constructing the most comprehensive resource for 108 cancer pharmacological research. The proteomic data complement the existing NCI-60 109 molecular landscapes, allowing systematic investigation of the complementarity among 110 genomics, transcriptomics and proteomics in a number of applications. 111 112 The proteome of the NCI-60 cells has been analyzed previously by data dependent 113 analysis (DDA), a commonly used discovery mass spectrometry technique 17 . Whereas the 114 study reported the cumulative identification of 10,350 IPI proteins from about 1,000 115 fractionated and kinase-enriched sample runs, only 492 IPI proteins were quantified across the 116 NCI-60 cell lines without missing value. The present study thus extends the number of 117 consistently qua...
Parkinson's disease (PD) is the second most common neurodegenerative disorder whose prevalence is rapidly increasing worldwide. The disease mechanisms of sporadic PD are not yet completely understood. Therefore, causative therapies are still lacking. To obtain a more integrative view of disease-mediated alterations, we investigated the molecular landscape of PD in human post-mortem midbrains. Tissue from 13 PD patients and 10 controls was subjected to small RNA sequencing, transcriptomics, and proteomics analysis. Differential expression analyses were performed reveal multiple deregulated molecular targets linked to known pathomechanisms of PD as well as novel processes. We found significant differential expression of miR-539-3p, miR-376a-5p, miR-218-5p, and miR-369-3p, the valid miRNA-mRNA interacting pairs of miR-218-5p/RAB6C, and miR-369-3p/GTF2H3, as well as multiple proteins relevant in the pathology of PD, including CHI3L1, SELENBP1, PRDX1, HSPA1B, and TH. Vertical integration of multiple omics analyses allowed to validate disease-mediated molecular alterations across different molecular layers and functional annotation of differentially expressed targets identified a strong enrichment of pathways related to inflammation and activation of the immune response. This suggests that neuroinflammation may significantly contribute to disease progression in PD and may be a promising therapeutic target in advanced stages of PD.
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