SWATH-MS proteomics of PANC-1 and MIA PaCa-2 pancreatic cancer cells allows identification of drug targets alternative to MEK and PI3K inhibition
Alain Aguilar-Valde´s a, b, Lilia G. Noriega c, Armando R. Tovar c,
María de J. Ibarra-Sa´nchez d, Víctor A. Sosa-Herna´ndez a, Jose´ L. Maravillas-Montero a,
Juan Martínez-Aguilar a, *
a Red de Apoyo a la Investigacio´n, Coordinacio´n de la Investigacio´n Científica, Universidad Nacional Auto´noma de M´exico-Instituto Nacional de Ciencias M´edicas y Nutricio´n Salvador Zubira´n, 14080, Mexico City, Mexico
b Escuela Nacional de Ciencias Biolo´gicas, Instituto Polit´ecnico Nacional, 11340, Mexico City, Mexico
c Departamento de Fisiología de la Nutricio´n, Instituto Nacional de Ciencias M´edicas y Nutricio´n Salvador Zubira´n, 14080, Mexico City, Mexico
d Departamento de Bioquímica, Instituto Nacional de Ciencias M´edicas y Nutricio´n Salvador Zubira´n, 14080, Mexico City, Mexico

a r t i c l e i n f o

Article history:
Received 4 February 2021
Accepted 3 March 2021
Available online 16 March 2021

Keywords: Pancreatic cancer MEK inhibition PI3K inhibition Drug targets Proteomics
Mass spectrometry
a b s t r a c t

Pancreatic cancer remains one of the most lethal diseases with dismal five-year survival rates. Although mutant KRas protein-driven activation of downstream MAPK Raf/MEK/ERK and PI3K/Akt signaling pathways represent major oncogenic alterations, signaling blockade with MEK and PI3K inhibitors has shown that intrinsic resistance may hamper the effectiveness of this targeted approach. However, there have been no mass spectrometry-based proteomic studies for in-depth comparison of protein expression differences between pancreatic cancer cells with sensitivity and resistance to MEK and PI3K kinase in- hibitors. In this work, we compared PANC-1 and MIA PaCa-2 pancreatic cancer cells which are, respectively, resistant and sensitive to MEK- and PI3K-targeted therapy. We conducted a label-free data- independent acquisition mass spectrometry (SWATH-MS) study with extensive peptide fractionation to quantitate 4808 proteins and analyze differential expression of 743 proteins between resistant and sensitive cells. This allowed identification of the tumor suppressor protein phosphatase 2A (PP2A) and proteins from mitochondrial respiratory complex I implicated in oxidative phosphorylation as alternative candidate drug targets for cells resistant to MEK and PI3K inhibition. PP2A activator DT-061 decreased viability of PANC-1 cells and this was accompanied by reduced expression of c-Myc. PANC-1 cells also showed response to metformin and the novel complex I inhibitor IACS-010759. These findings provide insights into the distinct cellular proteomes and point out alternative pharmacological targets for MEK and PI3K inhibition-resistant pancreatic cancer cells.

© 2021 Elsevier Inc. All rights reserved.

⦁ Introduction

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal types of cancer. Five-year survival rate after diagnosis is 7e9% and median survival for localized-stage disease is 6e9 months [1,2]. According to GLOBOCAN, in 2018 there were 458 918 newly diagnosed pancreatic cancer cases and 432 242

* Corresponding author. Universidad Nacional Auto´noma de Me´xico, Red de Apoyo a la Investigacio´n. INCMNSZ, Vasco de Quiroga 15, 14080, Mexico City, Mexico.
E-mail address: [email protected] (J. Martínez-Aguilar).
deaths worldwide, underlining the high lethality associated with the disease [3]. PDAC is the third most frequent cause of cancer- related death in several countries, including the USA, and the prognosis remains very poor with standard chemotherapy drugs. Emergent pharmacologic approaches are trying to exploit molec- ular vulnerabilities in pancreatic cancer cells that may render them susceptible to targeted therapy.
Activating point mutations in KRAS (Kirsten rat sarcoma viral oncogene homolog) gene are present in >90% of PDAC cases [2]. GTP hydrolysis to GDP is impaired by mutant KRas protein, which disrupts control of cellular growth thereby leading to sustained activation of two important signaling pathways: mitogen-activated


0006-291X/© 2021 Elsevier Inc. All rights reserved.

protein kinase (MAPK) Raf/MEK/ERK and phosphatidylinositol 3- kinase/protein kinase-B PI3K/Akt [4,5]. The MAPK pathway con- trols several transcription factors, cell cycle progression and pro- liferation. Key cellular functions under control of the PI3K/Akt pathway include protein synthesis, cell growth and survival.
The small molecule MEK inhibitor AZD6244 and PI3K inhibitor GDC-0941 have been used recently with some success in cancer setting. However, recent attempts to halt pancreatic cancer cell proliferation by targeted inhibition of Raf/MEK/ERK and PI3K/Akt pathways with these drugs have shown only transient response [6,7]. Notably, some pancreatic cancer cells have intrinsic resistance to MEK and PI3K inhibition. PANC-1 pancreatic cancer cells exhibit such resistance while MIA PaCa-2 cells have shown sensitivity to MEK- and PI3K-targeted therapy [8,9]. Both cell lines are widely employed in pancreatic cancer research and share similar genetic alterations including mutant KRAS [10]. Comparison of their respective proteomes is thus needed to gain insights into the un- derlying molecular differences and to identify additional pharma- cological targets.
Data-independent acquisition (DIA) mass spectrometry (MS) has demonstrated exceptional capability for large-scale proteome analysis. To the best of our knowledge, there are no previous studies comparing differences in protein expression between pancreatic cancer cells with distinct response to MEK and PI3K inhibition. In this study, we conducted an in-depth proteomic comparison of PANC-1 and MIA PaCa-2 pancreatic cancer cells with extensive peptide fractionation and analysis by the label-free DIA-MS method known as SWATH (sequential window acquisition of all theoretical fragment ion spectra). Our proteomic study allowed quantitative comparison of 4808 proteins and provided biological insights into the composition of the cellular proteomes, further facilitating the discovery of alternative drug targets for the cells resistant to MEK and PI3K kinase inhibitors.

⦁ Materials and methods

⦁ Cell culture

PANC-1, MIA PaCa-2 and SU 86.86 human pancreatic adeno- carcinoma cells were obtained from the American Type Culture Collection (ATCC) and cultured in DMEM or RPMI (SU 86.86) me- dium supplemented with GlutaMAX, 10% fetal bovine serum (FBS), 1% antibiotics and 10 mM HEPES (Gibco, USA). Medium for MIA PaCa-2 cells was further supplemented with 2.5% horse serum (ATCC). Cell cultures were maintained at 37 ◦C in humidified at- mosphere with 5% CO2.

⦁ Drugs and cell viability determination

MEK inhibitor AZD6244 was purchased from ApexBio and PI3K inhibitor GDC-0941 was from Selleck Chemicals. PP2A activator DT- 061, complex I inhibitor IACS-010759 and 2-deoxy-D-glucose (2DG) were from MedChemExpress. Metformin was from ApexBio. Cells were seeded on 96-well plates and treated for 72 h with increasing drug concentrations. Cell viability was assessed employing the cell counting kit-8 (CCK-8, Dojindo) or crystal violet staining. See the Supplementary Methods for more details.

⦁ Cell lysis and protein quantitation

Cells were lysed with 1% sodium deoxycholate in 100 mM triethylammonium bicarbonate buffer. Total protein content was determined using Pierce BCA protein assay kit (Thermo Fisher, USA).
⦁ Peptide fractionation

Protein extracts were reduced with 10 mM dithiothreitol and alkylated with 25 mM iodoacetamide. Samples were digested with trypsin (Promega) overnight. Strong anion-exchange peptide frac- tionation was carried out following a previously described method [11]. Reversed phase fractionation at basic pH was accomplished using the Pierce high pH fractionation kit (Thermo Fisher, USA).

⦁ LC-MS analysis

The spectral library for SWATH-MS was built by information- dependent acquisition (IDA) MS of unfractionated samples and the 28 peptide fractions. They were loaded onto a ChromXP C18CL trap with an Eksigent nanoLC 425 system. Separation was achieved on a ChromXP C18 column with a water-acetonitrile system. Mass spectrometry was performed on a TripleTOF 5600 platform (AB Sciex). For SWATH-MS, 100 windows of variable m/z over the range 350e1250 m/z were employed. Three independent biological rep- licates per sample were analyzed. See the Supplementary Methods for details.

⦁ Protein identification and quantitative analysis

Spectra from IDA-MS experiments were analyzed using Pro- teinPilot 5.0.1 software and searched against the UniProtKB/Swiss- Prot human protein database. IDs with minimum protein confi- dence of 95%, FDR<1%, were imported into PeakView 2.2 software, excluding shared peptides. An extended ion library was created with iSwathX [12]. SWATH data were processed with SWATH acquisition MicroApp 2.0.

⦁ Gene ontology (GO) and functional enrichment analysis

Functional GO enrichment analysis was carried out using ClueGO 2.5.4, taking the complete list of quantitated proteins as reference set with kappa score level 0.4 and Bonferroni step- down correction with significance level of 0.05. Protein interac- tion network of differentially expressed proteins was generated using the StringApp. Clusters were identified by clustermarker with Markov clustering and enrichment was performed with p < 0.05.

⦁ Western blotting

Proteins were separated on 4e12% Bis-Tris Plus gels and trans- ferred onto a nitrocellulose membrane, which was blocked with 3% bovine serum albumin (phosphoproteins) or 5% skim milk (total proteins) in TBS. Primary antibodies were incubated with the membrane overnight at 4 ◦C followed by detection with secondary
antibody using SuperSignal West Pico PLUS chemiluminescent substrate (Thermo Fisher, USA) with the ChemiDoc imaging system (Bio-Rad). The list of primary antibodies employed can be found on the Supplementary Methods.

⦁ High-resolution multiple-reaction monitoring (MRM-HR)

Same SWATH-MS LC conditions were employed. Peptide iden- tity, Q1 and Q3 values can be found on Supplementary Table S1.

⦁ Evaluation of mitochondrial function (respiration activity)

Seahorse XF cell mito stress test kit and the XFe96 Extracellular Flux Analyzer were used (Agilent Technologies). Sequential injec- tion of oligomycin, FCCP and rotenone/antimycin A was performed with three measurements after each compound addition. Hoechst

Fig. 1. MEK and PI3K inhibition and sample preparation workflow. Viability of MIA PaCa-2 and PANC-1 cells treated with A) MEK inhibitor AZD6244 and B) PI3K inhibitor GDC-0941. Error bars indicate SD. *p < 0.05, **p < 0.01, ***p < 0.001. C) Western blot showing changes in Akt and ERK phosphorylation. D) In-depth proteomic analysis was achieved using SWATH-MS with extensive peptide fractionation.

33 342 was also injected to dye the nucleus and normalize the oxygen consumption rate (OCR) and the extracellular acidification rate (ECAR) data. See Supplementary Methods.

⦁ siRNA transfection and flow cytometry analysis PPP2R1A gene knockdown was performed by siRNA transfection.
c-Myc expression was examined by flow cytometry. See Supple- mentary Methods.

⦁ Statistical analysis

Statistical analysis of SWATH data was performed with Perseus

1.6. Differentially expressed proteins were identified by unpaired t- test (p < 0.05) and fold change (fc) 2. Only proteins with two or more peptides were considered. Statistical analysis of cell viability data was performed with GraphPad Prism 7. Experiments comparing single and corresponding combination treatment were analyzed by unpaired t-test corrected for multiple comparisons using Holm-Sidak method (a 0.05). Comparisons between vari- able and a fixed drug concentration were analyzed by one-way ANOVA followed by Dunnett’s post hoc test with family-wise sig- nificance of 0.05.
⦁ Results

⦁ Viability of PANC-1 and MIA PaCa-2 pancreatic cancer cells under MEK and PI3K inhibition

MIA PaCa-2 cells showed concentration-dependent decrease in cell viability when treated with AZD6244 (IC50 0.33 ± 0.05 mM). On the contrary, viability of PANC-1 cells remained above 50% even with 100 mM AZD6244 (Fig. 1A). GDC-0941 also decreased the viability of MIA PaCa-2 cells (IC50 1.80 ± 0.16 mM). In contrast, PANC-1 cells viability kept near 50% with GDC-0941 concentrations of 2 mM or higher (Fig. 1B). Combined treatment of MIA PaCa-2 cells with AZD6244 and GDC-0941 showed synergistic reduction of cell viability (Supplementary Fig. 1A), while dual treatment of PANC- 1 cells required several times higher AZD6244 concentrations to reach similar response (Supplementary Fig. 1B).
MEK inhibitor AZD6244 reduced ERK phosphorylation, and PI3K inhibition by GDC-0941 decreased Akt phosphorylation in both cell lines, at least in the first 48 h (Fig. 1C). We also observed that MEK inhibition induced Akt phosphorylation while treatment with the PI3K inhibitor showed induction of ERK phosphorylation in a time- dependent manner. Concurrent MEK and PI3K inhibition led to reduced phosphorylation of both ERK and Akt.

⦁ SWATH-MS proteomic comparison of PANC-1 and MIA PaCa-2 pancreatic cancer cells

Proteomic comparison of PANC-1 and MIA PaCa-2 pancreatic cancer cells was carried out using SWATH-MS [13] and extensive

Fig. 2. Functional enrichment analysis and protein expression. A) Volcano plot showing differentially expressed proteins between PANC-1 and MIA PaCa-2 cells; dots of proteins with ≤2 peptides/protein are colored in red or blue. B) ClueGO functional GO enrichment analysis. C) PPI network analysis showing Oxidative phosphorylation and D) PP2A complex. E) Differentially expressed proteins from the “oxidoreductase activity” GO category linked to OXPHOS and F) Expression of PP2A complex proteins. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

peptide fractionation (Fig. 1D). This in-depth proteomic analysis allowed identification of 6024 proteins and relative quantitation of 4808 proteins. 743 proteins were found to be differentially expressed between PANC-1 and MIA PaCa-2 cells. 407 proteins were found higher expressed whereas 336 proteins showed lower expression in PANC-1 cells in comparison with MIA PaCa-2 cells (Fig. 2A). The complete list of all differentially expressed proteins is shown on Supplementary Table S2.

⦁ Functional annotation and PPI analysis

Functional gene ontology enrichment analysis of the 743 differentially expressed proteins showed “oxidoreductase activity” as the top enriched GO term followed by “response to drug” (Fig. 2B). Supplementary Table S3 shows the associated genes for each significant GO term. Further biological interpretation was obtained by protein-protein interaction (PPI) network analysis, which revealed two PPI clusters associated with “oxidative phos- phorylation (OXPHOS)” and “protein phosphatase 2A complex” (Fig. 2C and 2D). The former was comprised of several proteins belonging to mitochondrial complexes I, III and IV of the electron transport chain (ETC), which participate in oxidoreductase activity through OXPHOS. Fig. 2E shows that all these proteins were found higher expressed in PANC-1 cells. LDHB and IDH2 were another two proteins with oxidoreductase activity and linked to OXPHOS [14,15] with higher expression in PANC-1 cells. The PP2A cluster belongs to the enriched GO term “response to drug” and included the three subunits of PP2A complex, namely PP2Aa (catalytic), PR65a
(scaffold), PR55a (regulatory) as well as the PP2A activation chap- erone PTPA (Fig. 2D). These four PP2A proteins were found with lower expression in PANC-1 cells (Fig. 2F).
PP2A is an important tumor suppressor that modulates onco- genic signaling and transformation [16,17]. OXPHOS activity by mitochondrial protein complexes of the ETC is a key player in cell metabolism and driver of cell proliferation [18]. Therefore, we set out to investigate the susceptibility of PANC-1 and MIA PaCa-2 cells to PP2A activation or ETC complex I inhibition.

⦁ Verification of protein expression

Protein expression was corroborated by MRM-HR (Fig. 3A) and immunoblotting (Fig. 3B). As a general validation of our proteomics findings, proteins from mitochondrial complexes I, III and IV, PP2A, LDHB and IDH2 were included. Results were in agreement with the SWATH-MS results. Given the extensive amount of data gathered by our in-depth proteomic analysis, we also confirmed the expression of another sixteen proteins which were annotated in the enriched GO categories “oxidoreductase activity” or “response to drug” and which may also represent potential drug targets (Fig. 3C).

⦁ Activation of protein phosphatase PP2A

DT-061 is a novel small-molecule activator of PP2A that binds directly to the scaffold subunit PR65a [19]. PANC-1 cells treated with DT-061 showed marked decrease in cell viability (IC50 ¼ 10.5 ± 0.2 mM). 13 mM DT-061 reduced PANC-1 cells viability

Fig. 3. Drug targets and verification of protein expression. Differential expression was confirmed by A) MRM-HR and B) Immunoblot. C) Global MRM-HR verification for several proteins associated with the top two enriched GO categories. D) Treatment with PP2A activator DT-061. PANC-1 cells were treated with DT-061 in combination with E) GDC-0941 or

to 14%. Conversely, MIA PaCa-2 cells maintained viability levels above 90% (Fig. 3D). When DT-061 was combined with the PI3K inhibitor GDC-0941, further reduction in PANC-1 cells viability was observed with GDC-0941 concentrations as low as 0.1 mM (Fig. 3E). The combination with MEK inhibitor AZD6244 also showed reduced viability (Fig. 3F). As follow-up to these findings, the SU
86.86 pancreatic cancer cell line was identified to be resistant to AZD6244 (Supplementary Fig. 2) and to present lower PP2A expression in comparison with MIA PaCa-2 cells. (Fig. 3G). Treat- ment of SU 86.86 cells with 13 mM DT-061 abated the viability down to only 2.2% (IC50 10 ± 0.07 mM, Fig. 3D). Mechanistically, DT-061 treatment of either PANC-1 or SU 86.86 cells led to decreased expression of the transcription factor c-Myc while its expression in MIA PaCa-2 cells was unchanged (Fig. 3H and Supplementary Fig. 3). Enhanced ERK phosphorylation was found in all cases (Fig. 3H), whereas cell specific changes in Akt and p70S6K kinase phosphorylation were observed (Supplementary Fig. 4). Further- more, PANC-1 cells showed reduced sensitivity to DT-061 after PP2A subunit PR65a knockdown by siRNA (Supplementary Figs. 5 and 6). Notably, PR65a siRNA-transfected PANC-1 cells main- tained the c-Myc protein level when treated with DT-061, in contrast to cells transfected with the siRNA control, which showed decreased c-Myc expression (Fig. 3I).

⦁ Measure of respiration activity

Analysis of oxygen consumption rate (OCR) revealed that PANC- 1 cells present significantly higher levels of mitochondrial basal respiration than MIA PaCa-2 cells (40.7 vs 17.7 pmol O2/min per 1000 cells), Fig. 3J. Likewise, PANC-1 cells were found to have significantly higher ATP production, maximal respiration and non- mitochondrial respiration (Fig. 3K). The extracellular acidification rate (ECAR) was found to be significantly lower in PANC-1 cells (9.2 vs 15.7 mpH/min per 1000 cells), Fig. 3L. Additionally, it was found that PANC-1 cells maintained their basal respiration levels under MEK (AZD6244) or PI3K (GDC-0941) inhibition and had only slightly lower OCR when exposed to the dual treatment. 2DG did not alter the OCR of PANC-1 cells but metformin almost completely suppressed their respiration activity (Fig. 3M).
The higher OCR/ECAR ratio of PANC-1 cells with respect to MIA PaCa-2 cells (4.4 vs 1.1 pmol O2/mpH) also points toward an oxidative metabolism and less dependence on glucose metabolism. Treatment with the glucose analogue 2DG decreased the viability of MIA PaCa-2 cells (IC50 1.65 ± 0.12 mM). MIA PaCa-2 cells treated with 10 mM 2DG showed viability of only 2.8% whereas that of PANC-1 cells was 58% (Fig. 3N). Moreover, when grown in low glucose medium, only PANC-1 cells maintained its metabolic ac- tivity (Fig. 3O).

⦁ Mitochondrial complex I inhibition

Inhibition of mitochondrial complex I by treatment with met- formin [20] significantly decreased PANC-1 cells viability (IC50 15.8 ± 02.8 mM) in comparison with that observed in MIA PaCa-2 cells (IC50 29.4 ± 2.2 mM), Fig. 3P. Viability of PANC- 1 cells was also significantly reduced by treatment with the novel selective inhibitor of complex I IACS-010759 [21] (IC50 30.8 ± 4.2 mM), in contrast with MIA PaCa-2 cells, which were less responsive (Fig. 3Q).
⦁ Discussion

Targeted molecular therapy aims to find important and specific vulnerabilities within the molecular make-up of cancer cells to halt cellular viability and cancer progression. MEK and PI3K inhibition have been employed with relative success in other types of cancer but their effectiveness in pancreatic cancer has been variable and somewhat limited [6e9]. It is of utmost importance to understand the underlying molecular features of pancreatic cancer cells that could represent new or additional pharmacological targets.
The observed cross-talk between MAPK and PI3K pathways is in consonance with the recognized negative regulation between them [22]. Combined MEK and PI3K inhibition acted as an effective blockade of the cross-regulatory mechanisms. However, treatment of PANC-1 cells was still less effective than treatment of MIA PaCa- 2 cells, which supports the study of these cells as a model to search for alternative drug targets.
Our SWATH-MS proteomic analysis combined with enrichment of GO categories and retrieval of protein interaction networks enabled the identification of two groups of proteins with a key role in the viability of PANC-1 cells: protein phosphatase 2A (PP2A) complex and OXPHOS proteins from mitochondrial complexes of the ETC. Remarkably, all proteins in each group showed consistency in the directionality of expression, which was confirmed by high- resolution targeted MS and Western blot.
Protein phosphatase 2A is a serine/threonine phosphatase with critical role in cellular functions involved in proliferation and sur- vival. Widely regarded as a tumor suppressor, it has gained increasing attention as a key player in the cellular response to drugs, including kinase inhibition therapy [16,17]. The lower expression of catalytic, scaffold and regulatory subunits in PANC- 1 cells is in line with the PP2A functional inactivation found in other types of cancer and with overexpression of PP2A inhibitors previ- ously found in pancreatic cancer [23].
Our results showed that PP2A activation with DT-061 alone was able to suppress the viability of PANC-1 and SU 86.86 cells and thus these findings hold potential therapeutic application as an alter- native to MEK and PI3K kinase inhibition. Loss of cell viability upon DT-061 treatment was associated with reduced levels of c-Myc protein and we found that siRNA knockdown of PP2A subunit PR65a allowed sustained c-Myc expression and higher viability of PANC-1 cells. c-Myc controls expression of a plethora of genes, many of them implicated in cell proliferation, growth and survival, and hence it is regarded as a therapeutic target [24]. DT-061 treatment elicited cell specific changes in phosphorylation of ki- nases such as Akt and p70S6K. Nevertheless, increased ERK phos- phorylation was a common result, which is in agreement with the induction of Raf/MEK/ERK signaling by PP2A that has previously been reported [25]. Although ERK is known to stabilize c-Myc, PP2A activity promotes its degradation [26]. Our results demonstrate that PP2A may be a candidate drug target for resistant cells, acting via c-Myc inhibition.
The higher respiration activity of PANC-1 cells in comparison to MIA PaCa-2 cells is concordant with the higher expression of mitochondrial proteins of ETC complexes that drive OXPHOS. As a major pathway for ATP production, OXPHOS supports cellular en- ergy demand through the transference of electrons from NADH to oxygen through a series of mitochondrial enzyme complexes. Many of the proteins found belong to complex I. These results also explain

F) AZD6244. Statistical significance between single and combination experiments is shown in asterisk brackets, and between fixed DT-061 concentration and combination ex- periments with asterisks above combination bar. G) PP2A PR65a expression in SU 86.86 and MIA PaCa-2 cells. H) c-Myc and p-ERK expression after DT-061 (DT) treatment. I) c-Myc expression in PR65a siRNA knockdown cells treated with DT-061. Mitochondrial function experiments were performed to obtain J) OCR curves, K) OCR parameters, L) ECAR values and M) OCR after treatment of PANC-1 cells with inhibitors. N) Treatment with 2DG. O) Culture in high or low glucose medium. Mitochondrial complex I inhibition was carried out with P) Metformin and Q) IACS-010759. Error bars indicate SD, ns: not significant, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

the higher levels of ATP production found in PANC-1 cells and point toward OXPHOS or mitochondrial complex I as candidate drug targets.
Recent studies highlight the role of OXPHOS in cancer therapy resistance [18]. It is known that OXPHOS not only supports cellular energy demands but also biosynthesis of aspartate, a precursor of nucleotides and proteins [27]. We found that OCR levels in PANC- 1 cells were maintained during treatment with MEK or PI3K in- hibitors. Notably, our results are in agreement with one previous study showing that cells surviving genetic suppression of KRAS rely on OXPHOS for energy production and survival [28]. As mentioned above, mutant KRas is considered the main oncogene and driver of MAPK and PI3K signaling in pancreatic cancer cells. LDHB and IDH2 protein expression in PANC-1 cells is also in agreement with an oxidative metabolic phenotype. Higher expression of LDHB has been previously linked to oxidative metabolism and higher ATP levels in pancreatic cancer cells [14] and IDH2 is thought to confer protection against OXPHOS-derived oxidative damage [15]. We have corroborated the susceptibility of PANC-1 cells to inhibition of respiratory complex I using the biguanide drug metformin and the specific complex I inhibitor IACS-010759.
Altogether, our proteomic study demonstrates the feasibility of identifying alternative candidate drug targets for MEK and PI3K inhibition-resistant pancreatic cancer cells. This study provided a list of potential targets, of which PP2A and mitochondrial complex I were verified. We are currently working on further confirmation of these findings in a larger group of samples. The present study has given the basis for these future experiments.
The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD016493.


We thank CONACYT for financial support through project A1-S- 15577 and INFRA-302510. We also thank DGAPA-UNAM PAPIIT
IA205919. We thank the Flow Cytometry Unit of RAI.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.bbrc.2021.03.018.


R.L.⦁ Siegel, K.D. Miller, A. Jemal, Cancer statistics, 2019, CA Cancer J Clin. 69 ⦁ (2019)⦁ ⦁ 7e⦁ 34.
J. Kleeff, M. Korc, M. Apte, et al., Pancreatic cancer, Nat Rev Dis Primers ⦁ 2 ⦁ (2016)⦁ ⦁ 16022.
⦁ J. Ferlay, M. Ervik, F. Lam, et al., Global cancer observatory: cancer today, Available from: https://gco.iarc.fr/today. (Accessed 10 December 2020).
E.A.⦁ ⦁ Collisson,⦁ ⦁ C.L.⦁ ⦁ Trejo,⦁ ⦁ J.M.⦁ ⦁ Silva,⦁ ⦁ et⦁ ⦁ al.,⦁ ⦁ A⦁ ⦁ central⦁ ⦁ role⦁ ⦁ for⦁ ⦁ RAF⦁ –⦁ >⦁ MEK⦁ –⦁ >⦁ ERK ⦁ signaling in the genesis of pancreatic ductal adenocarcinoma, Canc. Discov. ⦁ 2 ⦁ (2012)⦁ ⦁ 685e⦁ 693.
S.⦁ ⦁ Eser,⦁ ⦁ N.⦁ ⦁ Reiff,⦁ ⦁ M.⦁ ⦁ Messer,⦁ ⦁ et⦁ ⦁ al.,⦁ ⦁ Selective⦁ ⦁ requirement⦁ ⦁ of⦁ ⦁ PI3K/PDK1⦁ ⦁ signaling
for Kras oncogene-driven pancreatic cell plasticity and cancer, Canc. Cell 23 (2013) 406e420.
M.R. Junttila, V. Devasthali, J.H. Cheng, et al., Modeling targeted inhibition ⦁ of ⦁ MEK and PI3 kinase in human pancreatic cancer, Mol. Canc. Therapeut. ⦁ 14 ⦁ (2015)⦁ ⦁ 40e⦁ 47.
B. Alagesan, G. Contino, A.R. Guimaraes, et al., Combined MEK and PI3K ⦁ in- ⦁ hibition in a mouse model of pancreatic cancer, Clin. Canc. Res. 21 (2015) ⦁ 396e⦁ 404.
C.G. Langdon, J.T. Platt, R.E. Means, et al., Combinatorial screening of pancre- ⦁ atic adenocarcinoma reveals sensitivity to drug combinations including ⦁ bro- ⦁ modomain inhibitor plus neddylation inhibitor, Mol. Canc. Therapeut. ⦁ 16 ⦁ (2017)⦁ ⦁ 1041e⦁ 1053.
H.⦁ Zhong, C. Sanchez, D. Spitzer, et al., Synergistic effects of concurrent ⦁ blockade of PI3K and MEK pathways in pancreatic cancer preclinical models, ⦁ PloS One 8 (2013)⦁ ⦁ e77243.
E.L.⦁ Deer, ⦁ J. ⦁ Gonzalez-Hernandez, J.D. Coursen, et al., Phenotype and genotype ⦁ of⦁ ⦁ pancreatic⦁ ⦁ cancer⦁ ⦁ cell⦁ ⦁ lines,⦁ ⦁ Pancreas⦁ ⦁ 39⦁ ⦁ (2010)⦁ ⦁ 425e⦁ 435.
J.R.⦁ ⦁ ⦁ W⦁ i⦁ ´⦁ sniewski,⦁ ⦁ ⦁ A.⦁ ⦁ ⦁ Zougman,⦁ ⦁ ⦁ M.⦁ ⦁ ⦁ Mann,⦁ ⦁ ⦁ Combination⦁ ⦁ ⦁ of⦁ ⦁ ⦁ FASP⦁ ⦁ ⦁ and⦁ ⦁ ⦁ StageTip- ⦁ based fractionation allows in-depth analysis of the hippocampal membrane ⦁ proteome,⦁ ⦁ J.⦁ ⦁ Proteome⦁ ⦁ Res.⦁ ⦁ 8⦁ ⦁ (2009)⦁ ⦁ 5674e⦁ 5678.
Z.⦁ Noor, J.X. Wu, D. Pascovici, et al., iSwathX: an interactive web-based ⦁ application for extension of DIA peptide reference libraries, Bioinformatics ⦁ 35 (2019)⦁ ⦁ 538e⦁ 539.
L.C.⦁ Gillet, P. Navarro, S. Tate, et al., Targeted data extraction of the ⦁ MS/MS ⦁ spectra generated by data-independent acquisition: a new⦁ ⦁ concept ⦁ for ⦁ consistent and accurate proteome analysis, Mol. Cell. Proteomics 11 (2012). ⦁ O111.01671⦁ 7.
J. ⦁ Cui, M. Quan, W. Jiang, et al., Suppressed expression of LDHB promotes ⦁ pancreatic cancer progression via inducing glycolytic phenotype, Med. ⦁ Oncol. ⦁ 32⦁ (2015)⦁ ⦁ 143.
⦁ þ
S.H. Jo, M.K. Son, H.J. Koh, et al., Control of mitochondrial redox balance and ⦁ cellular defense against oxidative damage⦁ ⦁ by mitochondrial NADP ⦁ - ⦁ dependent⦁ isocitrate dehydrogenase, ⦁ J. ⦁ Biol. Chem. 276 (2001)⦁ ⦁ 16168e⦁ 16176.
D.⦁ ⦁ Perrotti,⦁ ⦁ P.⦁ ⦁ Neviani,⦁ ⦁ Protein⦁ ⦁ phosphatase⦁ ⦁ 2A:⦁ ⦁ a⦁ ⦁ target⦁ ⦁ for⦁ ⦁ anticancer⦁ ⦁ therapy, ⦁ Lancet⦁ Oncol. 14 (2013)⦁ ⦁ e229e⦁ 238.
J. ⦁ Westermarck, Targeted therapies don⦁ ’⦁ t work for a reason; the neglected ⦁ tumor suppressor phosphatase PP2A strikes back, FEBS ⦁ J. ⦁ 285 (2018) ⦁ 4139e⦁ 4145.
C. Bosc, M.A. Selak, J.E. Sarry, Resistance is futile: targeting mitochondrial ⦁ energetics and metabolism to overcome drug resistance in cancer treatment, ⦁ Cell⦁ Metabol. 26 (2017)⦁ ⦁ 705e⦁ 707.
J. Sangodkar, A. Perl, R. Tohme, et al., Activation of tumor suppressor protein ⦁ PP2A inhibits KRAS-driven tumor growth, J. Clin. Invest. 127 (2017) ⦁ 2081e⦁ 2090.
W.W. Wheaton, S.E. Weinberg, R.B. Hamanaka, et al., Metformin inhibits ⦁ mitochondrial complex I of cancer cells⦁ ⦁ to reduce tumorigenesis, eLife ⦁ 3 ⦁ (2014)⦁ ⦁ e02242.
J.R.⦁ Molina, Y. Sun, M. Protopopova, et al., An inhibitor of oxidative ⦁ phos- ⦁ phorylation exploits cancer vulnerability, Nat. Med. 24 (2018)⦁ ⦁ 1036e⦁ 1046.
M.C.⦁ ⦁ Mendoza,⦁ ⦁ E.E.⦁ ⦁ Er,⦁ ⦁ J.⦁ ⦁ Blenis,⦁ ⦁ The⦁ ⦁ Ras-ERK⦁ ⦁ and⦁ ⦁ PI3K-mTOR⦁ ⦁ pathways:⦁ ⦁ cross- ⦁ talk⦁ ⦁ and⦁ ⦁ compensation,,⦁ ⦁ Trends⦁ ⦁ Biochem.⦁ ⦁ Sci.⦁ ⦁ 36⦁ ⦁ (2011)⦁ ⦁ 320e⦁ 328.
A.S.⦁ Farrell, B. Allen-Petersen, C.J. Daniel, et al., Targeting inhibitors of ⦁ the ⦁ tumor suppressor PP2A for the treatment of pancreatic cancer, Mol. Canc. ⦁ Res. ⦁ 12 (2014)⦁ ⦁ 924e⦁ 939.
N.M.⦁ Sodir, R.M. Kortlever, V.J.A. Barthet, et al., MYC instructs and maintains ⦁ pancreatic adenocarcinoma phenotype, Canc. Discov. 10 (2020)⦁ ⦁ 588e⦁ 607.
D.G.⦁ Adams, R.L. Coffee, H. Zhang, et al., Positive regulation of Raf1-MEK1/2- ⦁ ERK1/2 signaling by protein serine/threonine phosphatase 2A ⦁ holoenzymes, ⦁ J.⦁ ⦁ Biol. Chem. 280 (2005)⦁ ⦁ 42644e⦁ 42654.
E.⦁ ⦁ Yeh,⦁ ⦁ M.⦁ ⦁ Cunningham,⦁ ⦁ H.⦁ ⦁ Arnold,⦁ ⦁ et⦁ ⦁ al.,⦁ ⦁ A⦁ ⦁ signalling⦁ ⦁ pathway⦁ ⦁ controlling⦁ ⦁ c- ⦁ Myc degradation that impacts oncogenic transformation of human cells, ⦁ Nat. ⦁ Cell⦁ Biol. 6 (2004)⦁ ⦁ 308e⦁ 318.
L.B.⦁ ⦁ Sullivan,⦁ ⦁ D.Y.⦁ ⦁ Gui,⦁ ⦁ A.M.⦁ ⦁ Hosios,⦁ ⦁ et⦁ ⦁ al.,⦁ ⦁ Supporting⦁ ⦁ aspartate⦁ ⦁ biosynthesis⦁ ⦁ is ⦁ an essential function of respiration in proliferating cells, Cell 162 (2015) ⦁ 552e⦁ 563.
A. Viale, P. Pettazzoni, C.A. Lyssiotis, et al., Oncogene ablation-resistant ⦁ pancreatic⦁ ⦁ cancer cells depend on mitochondrial function, Nature ⦁ 514 ⦁ (2014)⦁ ⦁ 628e⦁ 632.