Datasets: Sensitivity and protein digestion course of proteomic Filter Aided Sample Preparation

A common druggable signature of oncogenic c-Myc, mutant KRAS and mutant p53 reveals functional redundancy and competition among oncogenes in cancer

The major driver oncogenes MYC, mutant KRAS, and mutant TP53 often coexist and cooperate to promote human neoplasia, which results in anticancer therapeutic opportunities within their downstream molecular programs. However, little research has been conducted on whether redundancy and competition among oncogenes affect their programs and ability to drive neoplasia. By CRISPR‒Cas9-mediated downregulation we evaluated the downstream proteomics and transcriptomics programs of MYC, mutant KRAS, and mutant TP53 in a panel of cell lines with either one or three of these oncogenes activated, in cancers of the lung, colon and pancreas. Using RNAi screening of the commonly activated molecular programs, we found a signature of three proteins - RUVBL1, HSPA9, and XPO1, which could be efficiently targeted by novel drug combinations in the studied cancer types. Interestingly, the signature was controlled by the oncoproteins in a redundant or competitive manner rather than by cooperation. Each oncoprotein individually upregulated the target genes, while upon oncogene co-expression each target was controlled preferably by a dominant oncoprotein which reduced the influence of the others. This interplay was mediated by redundant routes of target gene activation - as in the case of mutant KRAS signaling to c-Jun/GLI2 transcription factors bypassing c-Myc activation, and by competition - as in the case of mutant p53 and c-Myc competing for binding to target promoters. The global transcriptomics data from the cell lines and patient samples indicate that the redundancy and competition of oncogenic programs are broad phenomena, that may constitute even a majority of the genes dependent on oncoproteins, as shown for mutant p53 in colon and lung cancer cell lines. Nevertheless, we demonstrated that redundant oncogene programs harbor targets for efficient anticancer drug combinations, bypassing the limitations for direct oncoprotein inhibition.

The molecular network of the proteasome machinery inhibition response is orchestrated by HSP70, revealing vulnerabilities in cancer cells

Proteasome machinery is a major proteostasis control system in human cells, actively compensated upon its inhibition. To understand this compensation, we compared global protein landscapes upon the proteasome inhibition with carfilzomib, in normal fibroblasts, cells of multiple myeloma, and cancers of lung, colon, and pancreas. Molecular chaperones, autophagy, and endocytosis-related proteins are the most prominent vulnerabilities in combination with carfilzomib, while targeting of the HSP70 family chaperones HSPA1A/B most specifically sensitizes cancer cells to the proteasome inhibition. This suggests a central role of HSP70 in the suppression of the proteasome downregulation, allowing to identify pathways impinging on HSP70 upon the proteasome inhibition. HSPA1A/B indeed controls proteasome-inhibition-induced autophagy, unfolded protein response, and endocytic flux, and directly chaperones the proteasome machinery. However, it does not control the NRF1/2-driven proteasome subunit transcriptional bounce-back. Consequently, targeting of NRF1 proves effective in decreasing the viability of cancer cells with the inhibited proteasome and HSP70.

Proteomic data of donkey's milk

Donkey's milk has been recognized as milk of high biological value and it also has the closest composition to human milk. However, the total protein content of donkey's milk has not been adequately identified. The aim of this analysis is to investigate the proteomic content of that milk. Specific commercially available only milk was analyzed by ``shotgun'' proteomic methods to identify the proteins it contained in as much detail as possible. The application of the above approach resulted in the identification of a total of 633 different proteins, which were grouped based on their molecular function and their biological process. Furthermore, the proteins visualized graphically according to the GeneOntology (GO) system. The identified proteins confirm the high nutritional value of the donkey milk, governing future steps in optimizing its characteristic and uses.

SPACEPro: A Software Tool for Analysis of Protein Sample Cleavage for Tandem Mass Spectrometry

The efficiency of shotgun proteomic analysis is dependent on the reproducibility of the peptide cleavage process during sample preparation. To generate rapid and useful metrics for peptide cleavage efficiency, as in enzymatic or chemical cleavage, SPACEPro was developed to evaluate efficiency and reproducibility of protein cleavage in peptide samples following data-dependent analysis by mass spectrometry. SPACEPro analyzes samples at the peptide-spectrum match (PSM), peptide, and protein levels to provide a comprehensive representation of the overall sample processing to peptides. All output is provided in human-readable text and JSON files that can be further processed to assess the cleavage efficiency on proteins within the sample. SPACEPro provides a snapshot of the protein cleavage efficiency through very minimal effort so that the user is informed of the quality of the sample processing efficiency and can accordingly develop protocols to improve the initial sample preparation for subsequent analyses.