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. 2024 Feb 7;7(3):787–796. doi: 10.1021/acsptsci.3c00316

Chemical Proteomics Reveals that the Anticancer Drug Everolimus Affects the Ubiquitin–Proteasome System

Anna A Lobas †, Amir Ata Saei ‡,§,∥, Hezheng Lyu ‡, Roman A Zubarev ‡,⊥,*, Mikhail V Gorshkov †,*
PMCID: PMC10928898  PMID: 38481686

Abstract

graphic file with name pt3c00316_0007.jpg

Rapamycin is a natural antifungal, immunosuppressive, and antiproliferative compound that allosterically inhibits mTOR complex 1. The ubiquitin–proteasome system (UPS) responsible for protein turnover is usually not listed among the pathways affected by mTOR signaling. However, some previous studies have indicated the interplay between the UPS and mTOR. It has also been reported that rapamycin and its analogs can allosterically inhibit the proteasome itself. In this work, we studied the molecular effect of rapamycin and its analogs (rapalogs), everolimus and temsirolimus, on the A549 cell line by expression proteomics. The analysis of differentially expressed proteins showed that the cellular response to everolimus treatment is strikingly different from that to rapamycin and temsirolimus. In the cluster analysis, the effect of everolimus was similar to that of bortezomib, a well-established proteasome inhibitor. UPS-related pathways were enriched in the cluster of proteins specifically upregulated upon everolimus and bortezomib treatments, suggesting that both compounds have similar proteasome inhibition effects. In particular, the total amount of ubiquitin was significantly elevated in the samples treated with everolimus and bortezomib, and analysis of the polyubiquitination patterns revealed elevated intensities of the ubiquitin peptide with a GG modification at the K48 residue, consistent with a bottleneck in proteasomal protein degradation. Moreover, the everolimus treatment resulted in both ubiquitin phosphorylation and generation of a significant amount of semitryptic peptides, illustrating the increase in the protease activity. These observations suggest that everolimus affects the UPS in a unique way, and its mechanism of action is different from that of its close chemical analogs, rapamycin and temsirolimus.

Keywords: drug treatment, cell line, expression proteomics, rapamycin, everolimus, ubiquitin–proteasome system, ubiquitination, diglycine modification, semitryptic peptides

Introduction

Hyperactivation of mammalian TOR (mTOR) complex 1 (mTORC1) is observed in numerous human cancers due to gain-of-function mutations in oncogenes, such as PI3K and AKT, or the loss-of-function mutations in tumor suppressors.1 Rapamycin (sirolimus) is a natural compound known in cancer therapy for its antiproliferative properties, acting as an allosteric inhibitor of mTORC1.1 The two rapamycin analogs (rapalogs), everolimus and temsirolimus, are believed to share the same mechanism of action.2 Due to the numerous processes regulated by the mTOR complex, its inhibition has multiple effects on the protein synthesis, cell cycle, autophagy, etc.3 Specifically, the rapalogs inhibit cell proliferation and induce cell cycle arrest with accumulation of cells in the G1 phase, which is reportedly behind their anticancer efficacy.2

Different rapalogs have distinct pharmacokinetics and bioavailability. For example, the bioavailability of everolimus and temsirolimus is higher than that of rapamycin, but their half-lifes in blood are shorter (26–30 and 9–27 h, respectively, vs 46–78 h).4,5 These differences may explain the various clinical applications of these drugs.6−8

While rapamycin’s mechanism of action mainly includes the inhibition of mTORC1,3 it is speculated that its long-term administration leads to mTORC2 inhibition,1 resulting in numerous side-effects, including the impact on the glucose homeostasis. It was shown in a mouse model that, presumably due to shorter blood half-lives, the use of everolimus and temsirolimus instead of rapamycin may have a significantly lower impact on the glucose homeostasis.9 On the other hand, a cell-based study showed similar effects on the mTORC2 complex formation by all three compounds,10 and despite different pharmacokinetic and pharmacodynamic properties, rapamycin’s analogs showed similar toxicity profiles in the clinics to that of the parent compound.11

The ubiquitin–proteasome system (UPS) is a crucial pathway for the intracellular protein degradation that regulates homeostasis and various cellular events, including those involved in carcinogenesis.12−17 In eukaryotic cells, targeted proteins are marked by polyubiquitin followed by their degradation into peptides by the proteasome.18,19 Many of the proteins that undergo ubiquitin-dependent proteolysis are the regulators of physiological and/or pathological processes in cells, and their degradation plays an essential role in cell cycle progression, differentiation, and proliferation, as well as apoptosis and mitosis.14,20−22 Furthermore, the UPS is responsible for the degradation of misfolded and mutated proteins,23 thus ensuring normal cell functioning. On one hand, a malfunctioning UPS may cause an aberrant regulation of cell cycle proteins, which may affect cell division in an uncontrolled manner, further leading to carcinogenesis.24−26 On the other hand, proteasome inhibition may exhibit potential as an anticancer treatment by targeting the protein function responsible for tumor growth and progression.15,27,28 In particular, proteasome inhibitors confine cancer progression by interfering with the temporal degradation of the regulatory proteins, thus sensitizing cancer cells to apoptosis.29 While targeting the proteasome seems counterintuitive at first glance because of the essential role of the UPS in cellular homeostasis, several studies demonstrated that proteasome inhibition may lead to the accumulation of pro-apoptotic proteins in cancer cells rather than in normal ones.30−32 Indeed, some earlier reports indicated possible cytotoxic effects of proteasome inhibitors,33,34 and searching for those with potential for cancer treatment has been the subject of intense investigations in drug discovery,35,36 including recent studies on drug repurposing.37−41

In the rather short list of proteasome inhibitors with clinical potential for cancer treatment, bortezomib was the first one approved by the US FDA for the treatment of multiple myeloma and mantle cell lymphoma.42−45 One of the proposed mechanisms of its antitumor activity is the promotion of the degradation of antiapoptotic proteins and the prohibition of the degradation of the pro-apoptotic proteins through proteasome inhibition, which together result in tumor cell death. The approval for the clinical use of proteasome inhibitors confirmed that targeting the UPS is a feasible approach to treating different types of cancers.46−48 However, in addition to the toxic side effects, the use of currently approved proteasome inhibitors for cancer treatment is limited due to drug resistance.49,50 This stimulated ongoing efforts to identify and/or develop the next generation of anticancer drugs targeting the UPS.51−54

Since both mTOR and the UPS play a key role in protein turnover, there are ongoing debates on the possible impact of mTOR inhibitors on proteasome function. It remains unclear, for example, whether UPS-based proteolysis increases when mTOR activity decreases.55,56 Different reports provide contradictory views on the issue, one suggesting that mTORC1 inhibition reduces proteolysis by suppressing the proteasome expression, whereas the others posit that it results in an increase in the cellular content of K48-linked ubiquitinated proteins and, thus, enhances UPS-dependent proteolysis.55 There is also a study suggesting that rapamycin can allosterically inhibit the proteasome itself.56

To better understand the mechanistic similarities and differences in the molecular effects of rapamycin and its rapalogs, we performed expression proteomic analysis of the A549 cell line treated with 4 drugs, including rapamycin, everolimus, temsirolimus, and bortezomib, using the FITExP approach.57 The study was further extended by reanalysis of a publicly available expandable proteome signature library of 56 anticancer molecules in cancer cell lines, ProTargetMiner,58 with the specific purpose of searching for drugs exhibiting the proteasome inhibitor activity.

Materials and Methods

Sample Preparation

Human A549 cells (ATCC, USA) were grown in Dulbecco’s modified Eagle medium (DMEM) (Fisher Scientific) supplemented with 10% fetal bovine serum (FBS) (Fisher Scientific), 2 mM l-glutamine (Fisher Scientific), and 100 units per mL of penicillin/streptomycin (Thermo Fisher) followed by incubation at 37 °C in 5% CO2. Rapamycin (S1039), everolimus (S1120), temsirolimus (S1044), and bortezomib (S1013) were purchased from Selleckchem as 10 mM solutions in dimethyl sulfoxide (DMSO).

For LC50 determination, the cells were seeded at a density of 4000 per well in 96-well plates and, after a day of growth, treated using different drug concentrations for 48 h. After that, the cell viability was measured using the CellTiter-Blue cell viability assay (Promega; cat. no. G8081) according to the manufacturer’s protocol.

Cells were seeded at a density of 250,000 per well and allowed to grow for 24 h in biological triplicates. Next, cells were treated with either the vehicle (DMSO) or drugs at IC50 concentrations (25 μM for both rapamycin and temsirolimus, 50 μM for everolimus, and 0.15 μM for bortezomib) for 48 h. The treated cells were then collected, washed twice with PBS (Fisher Scientific), and lysed using 8 M urea, 1% SDS, and 50 mM Tris at pH 8.5 with protease inhibitors (Sigma; Cat#05892791001). The cell lysates were subjected to 1 min sonication on ice using a Branson probe sonicator and 3-s on/off pulses at 30% amplitude. Protein concentration was then measured for each sample using a BCA Protein Assay Kit (Fisher Scientific; cat. no. PI23227), and 25 μg of each sample was reduced with DTT (final concentration 10 mM) (Sigma; cat. no. D0632) for 1 h at room temperature. Subsequently, iodoacetamide (Sigma; Cat #I6125) was added to a final concentration of 50 mM. The samples were incubated at room temperature for 1 h in the dark, and the reaction was stopped by the addition of 10 mM DTT. After precipitation of proteins using methanol/chloroform, the semidry protein pellet was dissolved in 25 μL of 8 M urea in 20 mM EPPS (pH 8.5) (Sigma; Cat #E9502) and diluted with EPPS buffer to reduce the urea concentration to 4 M. Lysyl endopeptidase (LysC) (Wako; cat. no. 125-05061) was added at a 1:75 w/w ratio to protein and incubated at room temperature overnight. After diluting urea to 1 M, trypsin (Promega; cat. no. V5111) was added at a ratio of 1:75 w/w, and the samples were incubated for 6 h at room temperature.

Acetonitrile (Fisher Scientific; cat. no. 1079-9704) was added to a final concentration of 20% v/v. TMTpro16 reagents (Thermo Fisher Scientific; cat. no. 90110) were added 4× by weight to each sample, followed by incubation for 2 h at room temperature. The reaction was quenched by the addition of 0.5% hydroxylamine (Thermo Fisher Scientific; cat. no. 90115). Samples were combined, acidified with trifluoroacetic acid (Sigma; cat no. 302031-M), cleaned, and dried using Sep-Pak (Waters; cat. no. WAT054960) and a DNA 120 SpeedVac concentrator (Thermo Fisher Scientific), respectively.

The pooled dried sample was resuspended in 20 mM ammonium hydroxide and separated into 96 fractions on an XBrigde BEH C18 2.1 × 150 mm column (Waters; cat. no. 186003023), using a Dionex Ultimate 3000 2DLC system (Thermo Fisher Scientific) over a 48 min gradient of 1–63% B (B = 20 mM ammonium hydroxide in acetonitrile) in three steps (1–23.5% B in 42 min, 23.5–54% B in 4 min, and then 54–63% B in 2 min) at 200 μL min–1 flow. Fractions were then concatenated into 24 fractions (e.g., A1, C1, E1, and G1). After drying and resuspension in 0.1% formic acid (FA) (Fisher Scientific), each fraction was analyzed over a 100 min gradient (total method time of 120 min) in random order.

Chemical Proteomics Analysis

Samples were loaded with buffer A (0.1% FA in water) onto a 50 cm EASY-Spray column (75 μm internal diameter, packed with PepMap C18, 2 μm beads, 100 Å pore size) connected to a nanoflow Dionex UltiMate 3000 UPLC system (Thermo) and eluted in an increasing organic solvent gradient from 4 to 28% over 90 min and up to 34% until 100 min (B: 98% ACN, 0.1% FA, and 2% H2O) at a flow rate of 300 nL/min. Mass spectra were acquired using an Orbitrap Lumos mass spectrometer (Thermo Fisher Scientific) in the data-dependent mode with MS1 scan at 120,000 resolution and MS2 at 50,000 (@200 m/z), in the m/z range from 400 to 1600. The isolation window was set at 1.6 Da. Peptide fragmentation was performed via higher-energy collision dissociation with the energy set at 35 NCE. The mass spectrometry data have been deposited in the ProteomeXchange Consortium via the PRIDE59 partner repository with the data set identifier PXD045774.

Data Source

Additional data analysis was also performed on a previously obtained ProTargetMiner data set.58 The data set presents the results of 229 liquid chromatography tandem mass spectrometry (LC–MS/MS)-based expression proteomics analyses of A549 cells treated with 56 anticancer drugs.

Data Analysis

The raw data from the TMT-based LC-MS/MS runs were converted to the mzML format by msconvert (https://proteowizard.sourceforge.io/tools/msconvert.html) and analyzed by IdentiPy, version 0.3.7,60 followed by a postsearch validation using Scavager, version 0.2.12.61 MS/MS data were searched against the SwissProt protein sequence database (Human, version 04_2021, 20,395 entries). Cysteine carbamidomethylation was used as a fixed modification, whereas methionine oxidation and protein N-terminal acetylation were selected as variable modifications. Trypsin was selected for enzyme specificity. No more than two missed cleavages were allowed. A false discovery rate (FDR) of 1% was used as a filter at both the protein and peptide levels. The molecular mass tolerance was 10 ppm, and the minimum peptide length was 5 residues. To analyze proteolysis products, a semitryptic peptide search with similar parameters was performed. For the polyubiquitination search, a limited database containing only ubiquitin sequences with different sites of ubiquitination (addition of GG residues to the K residue, Table S1) was used with the same settings and the addition of serine phosphorylation as variable modification. Postsearch validation as well as extraction and quantification of the TMT reporter ions in the mass spectra were performed using Scavager. Quantitation results were normalized to the sum of all intensities within a TMT channel. Gene ontology (GO) enrichment analyses for biological processes were performed using Enrichr62 (https://maayanlab.cloud/Enrichr/), and the set of genes corresponding to all identified proteins was used as a background. GO terms with adjusted p-values < 0.05 were considered. Motif enrichment was performed using an in-house developed script that compared the amino acid frequencies at each position to that of random background samples with a p-value threshold of 0.05.

Results and Discussion

Overview of the A549 Proteome upon Treatment

We performed multiplex expression proteomics analysis of A549 cells treated with rapamycin, everolimus, temsirolimus, and bortezomib at their respective IC50 values after 48 h of treatment. The latter drug is a proteasome inhibitor and was used as a positive control. Hierarchical clustering analysis revealed significant differences between the molecular fingerprints of rapamycin and its analogs. Specifically, the cellular responses to rapamycin and temsirolimus were similar but that to everolimus differed dramatically from both (Figure 1A). On the other hand, the effects of everolimus and bortezomib were similar, suggesting the possible involvement of everolimus in the proteasome inhibition. Furthermore, 740 proteins, the majority of which were specifically upregulated in the samples treated with everolimus and bortezomib (cluster 8 shown in Figure 1A), were mapped to proteasome-related GO terms in the enrichment analysis (Figure 1B,C).

Figure 1.

Figure 1

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(A) Hierarchical clustering of proteomics data of the A549 cell line treated with four drugs showing similarity between proteome signatures of everolimus- and bortezomib-treated samples. Three replicates are shown for each drug treatment. Proteins are clustered into eight main groups; cluster 8 is highlighted in dark red. (B) Distributions of mean protein fold changes of protein cluster 8 and (C) major enriched GO terms of protein cluster 8.

To evaluate the effect of each drug on the cell line proteome, the statistical t-test with Benjamini–Hochberg (BH) correction was employed, and volcano plots were generated for all four drugs. The number of outliers was determined using the following threshold values: fold change of <0.5 and >2 in measured expression for down- and upregulated proteins, respectively, and the FDR BH < 0.05, as depicted in Figure 2. The drug with the fewest outliers was temsirolimus, followed by rapamycin, whereas both bortezomib and everolimus produced the most outliers, suggesting that the latter two drugs had the highest impact on the proteome. All test results are summarized in Table S2.

Figure 2.

Figure 2

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Volcano plots showing the disturbance of the A549 cell line proteome by the four studied drugs. The numbers of outliers are shown for the following thresholds: fold change >2 or <0.5, FDR BH < 0.05.

Figure 3 shows the numbers of shared outliers between different drugs. Upregulated proteins are shown in red, while downregulated ones are depicted in blue. The Venn diagrams for the shared outliers are shown in Figure S1. The largest numbers of both positive and negative outliers were obtained for everolimus and bortezomib, consistent with these two drugs having similar action mechanisms. It is worth noting that in terms of protein outliers, rapamycin and bortezomib treatments share much more similarity than that observed in the hierarchical clustering of the whole proteome.

Figure 3.

Figure 3

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Number of shared protein outliers between different treatments. Up- and downregulated outliers are shown as shades of red and blue, respectively.

GO enrichment was performed for the outlier lists for each of the drugs, and the results are summarized in Table S3. The terms related to the UPS were enriched in the outlier gene sets corresponding to bortezomib and rapamycin treatment but not for everolimus. Analysis of the shared GO terms (Figure S2A) revealed significant similarity between the GO terms affected by rapamycin and bortezomib treatments. The sets of up- and downregulated proteins for these two drugs were then used separately for GO enrichment, and a comparison of the resulting terms (Figure S2b) showed that the downregulated proteins were mostly responsible for the similarity. The corresponding GO terms are listed in Table S4. Among the shared GO terms, the following are related to the UPS: Positive Regulation of Ubiquitin Protein Ligase Activity (GO: 1904668), Positive Regulation of Ubiquitin Protein Transferase Activity (GO: 0051,443), and Regulation of Ubiquitin Protein Ligase Activity (GO: 1904666). Note, however, that the GO-term enrichment analysis of the outliers did not lead to similarly enriched pathways, perhaps indicating that the identity of the proteins affected by everolimus is distinct from that of bortezomib.

Polyubiquitination Patterns

Protein polyubiquitination is the primary stage of proteasome-mediated protein degradation. Ubiquitin molecules form polyubiquitin chains by covalently binding to each other in one of the following eight sites: N-terminus, K6, K11, K27, K29, K33, K48, and K63.63,64 Among these sites, the K48 linkage is most frequently associated with proteasomal degradation, although there is evidence that all other lysine-linked polyubiquitin chains may also serve as degradation signals for proteasome.65,66

To assess the effect of the drugs on the UPS, we searched the proteomic data for polyubiquitination patterns by performing a search over a limited sequence database. The limited database included a set of ubiquitin sequences with GG added to all potential ubiquitination sites (Table S1). Trypsin cleavage of ubiquitin-modified protein results in diglycine (GG) modification of the corresponding lysine residue (K), which cannot be directly modified by TMT: the latter binds to the N-terminus of GG instead. The use of a limited search space increases the search sensitivity at the price of a higher probability of false matches. To reduce the latter, all search results were filtered to exclude the C-terminal position of GG-modified K residues, because trypsin cannot cleave the peptide bond after the modification.

For each potential modification site, both modified and unmodified peptides were quantified. Peptides not containing any potential ubiquitination sites were quantified separately. Figure 4 shows the results of this analysis. The overall ubiquitin abundance was significantly increased for both bortezomib- and everolimus-treated samples, whereas rapamycin and temsirolimus treatments resulted in only a marginal increase. The GG-modified peptides also demonstrated similar polyubiquitination patterns for both bortezomib and everolimus, specifically, exhibiting high abundances of K11 and K48 linkages associated with proteasomal protein degradation. K63-linked polyubiquitin appeared more pronounced for everolimus treatment, whereas K29-linked polyubiquitin was more abundant in the bortezomib-treated sample. For the two remaining compounds, the K48 linkage was also observed, even though the ubiquitin abundance upshift was barely present.

Figure 4.

Figure 4

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Fold changes in ubiquitin peptides obtained from a limited database search (see the text). The peptides were grouped based on the appearance of GG-modification sites. FCs of unmodified peptides are shown as box plots, whereas those of the GG-modified ones are presented as dots, with each dot representing one peptide-spectrum match (PSM). For each site, three box plots correspond to three replicates.

A recently discovered mechanism of UPS regulation involves enzymatic phosphorylation of ubiquitin by PINK1 at residue S65.67−69 This modifications results in changes in the conformational states of polyubiquitin, further impacting the quaternary arrangements of polyubiquitin subunits and, thus, inhibiting the activities of enzymes responsible for attaching and removing polyubiquitins.70,71 This mechanism is also known as mitophagy initiation signaling.72 The limited ubiquitin search of the proteomic data under study revealed differentially abundant S65 phosphorylation of ubiquitin (Figure 5). Specifically, we found that everolimus treatment resulted in a significant increase in ubiquitin phosphorylation, indicating a unique interplay between phosphorylation signaling and UPS triggered by this drug.

Figure 5.

Figure 5

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Fold changes in S65-phosphorylated ubiquitin. Bars show the mean values of the three corresponding PSMs, while the error bars show the standard deviation. For each drug, 3 bar plots correspond to three replicates.

The stoichiometry of ubiquitin phosphorylation in the control sample was estimated using the following formula

graphic file with name pt3c00316_m001.jpg 1

where FC stands for fold changes between the control and everolimus-treated samples of the protein (FCprotein), S65-containing unmodified (FCunmod), and phosphorylated peptide (FCphospho). Protein fold change was estimated as the median FC of all ubiquitin peptides without any GG- or phospho- modification site. The stoichiometry upon drug treatment is then calculated as follows

graphic file with name pt3c00316_m002.jpg 2

where the FC correspond to the treatment. The stoichiometries of S65 phosphorylation were 13, 21, 45, 15, and 5% in the control sample and after treatment with rapamycin, everolimus, temsirolimus, and bortezomib, respectively. Everolimus treatment led to the highest phosphorylation rate, illustrating the specific cellular mechanism invoked by this drug.

Polyubiquitination in the ProTargetMiner Data Set

For additional verification of our findings, the same limited ubiquitin search approach was then applied to an earlier published ProTargetMiner58 data set, including expression proteomic analysis of the A549 cell line treated with 56 anticancer compounds. Figure S3 summarizes the results obtained for all experiments. The threshold value for the statistically significant fold change (compared to untreated controls) of the ubiquitin level set at 2 was exceeded for four drugs: auranofin, bortezomib, b-AP15, and everolimus. The results for the first three drugs were expected because they are known as proteasome inhibitors.73−77 Everolimus treatment resulted in a significantly elevated ubiquitin level, further supporting the results of this study. In addition, temsirolimus included in the panel of drugs analyzed in the ProTargetMiner study did not change the level of ubiquitin in the cells.

The results of the search using the generated GG-peptide database are shown in Figure S4 as relative intensities (log2 fold change compared to untreated control) of PSMs corresponding to GG-modified and phosphorylated ubiquitin peptides across the panel of 56 drugs. Because the multibatch design of the ProTargetMiner data set was prone to missing values, only K29 and K48 linkages were universally identified for most drug treatments considered and were included in the plot for clarity. In general, these modifications correlate with the total amount of ubiquitin in the samples (shown as horizontal lines), with a small number of outliers probably corresponding to false matches. Significant upregulation of K48-linked ubiquitin after everolimus treatment indicates that a significant portion of the excessive ubiquitin corresponds to polyubiquitination of the proteins tagged for proteasomal degradation. Figure S4 also shows that the concentration of S65-phosphorylated ubiquitin is clearly elevated in response to certain drugs, including everolimus, further supporting the results of this study. An extremely elevated phosphorylated ubiquitin was also observed after sorafenib treatment, which is a known protein kinase inhibitor.78 At the same time, the ubiquitin phosphorylation level after sorafenib treatment did not correlate with the elevated total ubiquitin concentration or K48-linked polyubiquitin. Regarding the rapalogs, the observations from the ProTargetMiner data set seem very similar to our main data set.

Proteolytic Activity Observed in Everolimus-Treated Samples

Because the UPS is responsible for protein degradation, it is possible to detect degradation products in proteomes by performing a database search with semitryptic protease specificity. The identified semitryptic peptides are of particular interest if they have significantly higher FC while the FC values of the corresponding proteins are low. Figure 6A shows the FC of the identified semitryptic peptides and the corresponding proteins in the everolimus-treated samples. A distinguished group of up-shifted semitryptic peptides was observed exclusively for this drug treatment, suggesting that the treatment induced some protease activity, which may be attributed to the proteasome. The group of 174 up-shifted semitryptic peptides marked by red dots in Figure 6A was selected using the following filters: FC > 2 for semitryptic peptide, FDR BH < 0.05, and FC < 2 for the corresponding protein. Plots for all four drugs are shown in Figure S5.

Figure 6.

Figure 6

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(A) Fold changes (log2-transformed) of semitryptic peptides identified in the sample treated with everolimus and the corresponding proteins. A group of 174 peptides depicted as red dots was selected using the following filters: FC > 2 for semitryptic peptide, FDR BH < 0.05, and FC < 2 for the corresponding protein. (B) Motif enrichment was performed for the set of semitryptic peptides up-shifted upon everolimus treatment. The vertical dashed line shows the cleavage site. A DXLD motif similar to that of several caspases71 was observed.

We performed motif enrichment for this set of 174 peptides, corresponding to 167 unique cleavage sites, and found that 32 of them correspond to a cleavage at the aspartate residue. Moreover, the clear DXLD motif N-terminal to the cleavage site was enriched for this set of semitryptic peptides (Figure 6B), which is similar to the cleavage specificity of some caspases.79 GO enrichment of the corresponding gene set revealed mostly structural proteins (Table S5). Because the nature of this proteolytic activity is unknown, one possible explanation is that it is due to proteasomal degradation. To test this assumption, another limited search for GG-modified peptides was performed on a subset of the proteins corresponding to the 174 peptides. The output was validated manually, and GG modification was found for the heat shock cognate 71 kDa protein. Although this protein is highly ubiquitinated in both everolimus- and bortezomib-treated samples (Figure S6A), only everolimus treatment resulted in a significant upshift of its semitryptic peptides (Figure S6B). This indicates that everolimus may indeed invoke proteasomal degradation of this protein, whereas bortezomib inhibited the proteasome, leaving HSP7C ubiquitinated and not cleaved.

Proteolytic activity invoked by everolimus treatment may be associated with both caspases, or other proteases, and the proteasome. This indicates the unique mechanism of action of this drug that is strikingly different from those of rapamycin, temsirolimus, and even bortezomib, with which it otherwise shares many similar features.

Note that the differences in treatment outcome between everolimus and temsirolimus revealed in this proteomic study have been noted in clinical practice before, indirectly indicating the differences in their pharmacodynamics. Namely, everolimus treatment of metastatic renal cell carcinoma patients resulted in higher overall survival than temsirolimus treatment. This difference is due either to the different mechanisms of action, as our results demonstrated, or the drug administration guidelines.7,8 Indeed, these two drugs are prescribed following different indications: everolimus is recommended for patients previously treated with an anti-VEGFR tyrosine kinase inhibitor, whereas temsirolimus is recommended as the first-line treatment in patients with poor-risk features. In addition, there exists an assumption about the interconnection of mTOR and NFkB pathways, including proteasome activity regulation,80 that may be responsible for the observed effects. A synergistic therapeutic effect was also shown for a combination of everolimus with bortezomib in multiple myeloma cells where inhibition of the AKT/mTOR pathway was presented as the potential mechanism.81

Conclusions

The mechanisms of action of rapamycin and its analogs, everolimus and temsirolimus, were investigated using expression proteomics, with a particular focus on the UPS activity. Interestingly, the proteomes affected by everolimus and bortezomib showed striking similarity, especially in the expression changes of proteins related to the UPS pathway. The levels of ubiquitin and its tryptic peptides with GG modification of residues K11 and K48 indicated similar polyubiquitination patterns resulting from these two treatments. However, no significant changes in ubiquitin abundance were observed for rapamycin and temsirolimus in either the ProTargetMiner data or the separate experiments performed in this study. Despite this, GO enrichment analysis revealed a similarity between the sets of genes downregulated by both rapamycin and bortezomib, including some UPS-related terms, perhaps indicating that a unique population of proteins is affected by each drug. Another interesting observation was the significantly elevated level of S65 phosphorylation of ubiquitin in the case of evelolimus, which may further shed light on the mechanism of its action. This finding is similar to that observed for sorafenib, which inhibits multiple intracellular serine/threonine kinases. In addition, everolimus treatment resulted in an increased proteolytic activity, which could be associated with both proteases and the proteasome, providing further evidence of its distinct mechanism of action. However, no specific upregulation upon everolimus treatment was observed for any of the caspases. Overall, proteomic data suggest the involvement of the UPS in the mechanism of action of everolimus and emphasize the difference between the actions of chemically analogous compounds, highlighting the need for further studies to better understand the pharmacodynamics of analogs. Overall, these findings may help explain the distinct clinical indications of these drugs in disease therapy.

Acknowledgments

This work in parts of experimental data processing and analysis, as well as development of related bioinformatic approaches, was supported by the Russian Science Foundation (continuation project #20-14-00229 to M.V.G.). R.A.Z. also acknowledges support from The Ministry of Science and Higher Education of the Russian Federation, agreement no. 075-15-2020-899, and the Karolinska Institutet in parts of acquiring and providing experimental data for the analysis.

Data Availability Statement

Data are available via ProteomeXchange with the identifier PXD045774.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsptsci.3c00316.

  • Ubiquitin sequences with GG modification used for the limited database search described in the “Polyubiquitination Patterns” section; all proteins identified in the proteomics analysis of the A549 cell line treated with four drugs; GO enrichment for biological processes performed for the sets of outliers corresponding to each drug; enriched GO terms for the sets of upregulated and downregulated protein outliers for rapamycin and bortezomib treatment; and GO terms enriched for sets of genes associated with up-shifted semitryptic peptides in the everolimus-treated sample (XLSX)

  • Number of shared upregulated and downregulated protein outliers between different treatments; number of shared GO terms enriched on the basis of upregulated and downregulated proteins; relative quantity of ubiquitin in the A549 cell line treated with 56 anticancer compounds from the ProTargetMiner data set; relative intensities of PSMs corresponding to ubiquitinated and phosphorylated ubiquitin in the ProTargetMiner data set; fold changes of semitryptic peptides and the corresponding proteins identified in the sample treated with four drugs; and fold changes of the GG-modified peptide from the HSP7C protein and a volcano plot of semitryptic peptides corresponding to this protein (PDF)

The authors declare no competing financial interest.

Supplementary Material

pt3c00316_si_001.xlsx (2.2MB, xlsx)
pt3c00316_si_002.pdf (953.6KB, pdf)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

pt3c00316_si_001.xlsx (2.2MB, xlsx)
pt3c00316_si_002.pdf (953.6KB, pdf)

Data Availability Statement

Data are available via ProteomeXchange with the identifier PXD045774.

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