Carfilzomib-Resistant Non-Small Cell Lung Cancer Cell Lines

Characterization of carfilzomib-resistant non-small cell lung cancer cell lines.

Item Type Article

Authors Hanke, Neale T; Imler, Elliot; Marron, Marilyn T; Seligmann, Bruce E; Garland, Linda L; Baker, Amanda F

Citation Hanke, N. T., Imler, E., Marron, M. T., Seligmann, B. E., Garland, L. L., & Baker, A. F. (2018). Characterization of carfilzomib- resistant non-small cell lung cancer cell lines. Journal of cancer research and clinical oncology, 144(7), 1317-1327.

DOI 10.1007/s00432-018-2662-0

Publisher SPRINGER

Journal Journal of Cancer Research and Clinical Oncology

Rights © Springer-Verlag GmbH Germany, part of Springer Nature 2018.

Download date 30/09/2021 03:01:57

Item License http://rightsstatements.org/vocab/InC/1.0/

Version Final accepted manuscript

Link to Item http://hdl.handle.net/10150/628304 Authors: Neale T. Hanke, PhD,a Elliot Imler, PhD,b Marilyn T Marron, MS,b Bruce E. Seligmann, PhD,b Linda L. Garland, MD,a Amanda F. Baker, PharmD, PhDa,c,* a College of Medicine, University of Arizona Cancer Center, Tucson, AZ, USA bBioSpyder Technologies Inc., Carlsbad, CA, USA *Corresponding author

Title: Characterization of carfilzomib-resistant non small cell lung cancer cell lines

Disclosure: The authors declare no conflicts of interest.

Address for correspondence: cAmanda F. Baker, PharmD, PhD is now an employee Ventana Medical Systems, Inc., a Member of the Roche Group (instead of Roche Ventana Medical Systems, Inc.) 1910 East Innovation Park Drive, Tucson, Arizona 85755

[email protected]

Running Title: Carfilzomib-resistant lung cancer cell lines

Keywords: Carfilzomib, Pgp, Proteasome inhibitor, Non-small cell lung cancer Abstract

Purpose: We previously showed that carfilzomib (CFZ) has potent anti-proliferative and cytotoxic activity in a broad range of lung cancer cell lines. Here we investigate possible mechanisms of CFZ acquired resistance in lung cancer cell lines.

Methods: CFZ resistant non-small cell lung cancer (NSCLC) cell lines were developed by exposing A549 and H520 cells to stepwise increasing concentrations of CFZ. Resistance to CFZ and cross-resistance to bortezomib and other chemotherapy drugs was measured using the MTT assay. Cytotoxicity to CFZ was determined using a CytoTox assay. Western blot was used to measure apoptosis, autophagy, and drug efflux transporter related proteins. Quantitative targeted whole-transcriptome sequencing and quantitative RT-PCR was used to measure gene expression. Flow cytometry was used to analyze intracellular accumulation of doxorubicin.

Results: The CFZ IC50 value of the resistant cells increased versus parental lines (2.5-fold for A549, 122-fold for H520). Resistant lines showed reduced expression of apoptosis and autophagy markers and reduced death versus parental lines following CFZ treatment. Both resistant lines exhibited higher P-glycoprotein (Pgp) gene (TempO-Seq® analysis, increased 1.2-fold in A549, >9,000-fold in H520) and protein expression levels versus parental lines. TempO-Seq® analysis indicated other drug resistance pathways were upreglated. The resistant cell lines demonstrated less accumulation of intracellular doxorubicin, and were cross-resistant to other Pgp client drugs: bortezomib, doxorubicin, and paclitaxel, but not cisplatin.

Conclusions: Upregulation of Pgp appears to be an important but not only mechanism of CFZ resistance in NSCLC cell lines.

Keywords: Carfilzomib; drug resistance; lung cancer; cross-resistance

Acknowledgements: The authors also wish to thank Adrianna E. Pulver, BS for her technical assistance and the University of Arizona Cancer Center/Arizona Research Laboratories Flow Cytometry Core Facility which is partially funded by P30CA023074 from the National Cancer Institute (NCI).

Introduction

Intracellular proteins with short half-lives and those that are damaged or improperly folded are degraded via the ubiquitin-proteasome system. Cancer cells generally have higher levels of proteasome activity than normal cells due to their higher proliferative rate and are therefore more susceptible to cell death upon proteasome inhibition. Pharmacological inhibition of the proteasome has proven to be an efficacious treatment for multiple myeloma (MM) (Hideshima et al. 2001) and mantle cell lymphoma (O'Connor et al. 2005) using the first generation proteasome inhibitor, bortezomib (BTZ). Second generation proteasome inhibitors have been investigated both pre-clinically and clinically including carfilzomib (CFZ) (Baker et al. 2014; Papadopoulos et al. 2013; Siegel et al. 2012; Vij et al. 2012), which is approved by the Food and Drug Administration for the treatment of MM.

Proteasome inhibition as a therapeutic strategy for solid tumors has yielded less favorable clinical outcomes than for hematologic malignancies, implying that protein degradation may be a less important target in solid tumors. Solid tumors may also have different primary and acquired resistance mechanisms than hematologic malignancies. BTZ yielded disappointing results in clinical trials of solid tumors (Huang et al. 2014). Fewer clinical studies of CFZ in solid tumors have been reported; however, one phase I/II study reported limited antitumor activity across a broad range of solid tumors (Papadopoulos et al. 2013). Further clinical studies with CFZ in solid tumors and neuroendocrine malignancies are ongoing (see clinicaltrials.gov).

Patients acquire resistance to proteasome therapy (Rumpold et al. 2007; Schmidmaier et al. 2007), and the acquisition of such resistance may account for the limited efficacy of proteasome inhibitors in treating solid tumors. Understanding the mechanism of acquired resistance will be important to interpreting and guiding the clinical experience with CFZ in solid tumors.

One shared resistance mechanism across chemotherapeutic agents is an increased expression of drug efflux pumps that prevents or reduces intracellular accumulation of toxins and xenobiotics. The best-characterized transporters that have been implicated as major contributors to multidrug resistance in cancer are P-glycoprotein (Pgp), also known as multidrug resistance protein 1 (MDR1), multidrug resistance-associated protein 1 (MRP1), or ABCB1 (Eckford and Sharom 2009). A study utilizing multiple cell lines with various multidrug resistant transporters indicated that only Pgp was able to pump epoxyketone-based PI’s including CFZ out of the cells and facilitate resistance (Verbrugge et al. 2012). Another study using human lung and colon adenocarcinoma cell lines also determined that Pgp upregulation played a major role in acquired resistance to CFZ (Ao et al. 2012). However, while these studies in cell lines suggested Pgp mediated acquired CFZ resistance, clinically BTZ and CFZ do not always have the same mechanism of resistance, with patients who were refractory to BTZ often still being responsive to CFZ treatment (Jain et al. 2011).

Besides Pgp and other efflux pump mechanisms it has been reported that amplification or mutation of target proteasome subunits (Lu et al. 2008; Oerlemans et al. 2008), suppression of protein biosynthesis (Ruckrich et al. 2009), changes to the endoplasmic reticulum stress responses (Zhang et al. 2010), or formation of stress granules (Gareau et al. 2011), are other mechanisms of resistance to BTZ.

To investigate acquired mechanisms of resistance to CFZ in NSCLC, we generated two CFZ resistant cell lines. Upregulation of Pgp was observed in both CFZ-resistant cell lines. These results support prior observations by others, and highlight the need to consider this resistance pathway when designing clinical trials using CFZ and other proteasome inhibitors in solid tumors, including NSCLC.

Materials and methods

Reagents and Antibodies CFZ, supplied by Onyx Pharmaceuticals, Inc., an Amgen subsidiary (South San Francisco, CA), was dissolved in dimethyl sulfoxide (DMSO) (Sigma-Aldrich, St. Louis, MO) at a concentration of 10 mM with stock aliquots stored at -20°C. BTZ, obtained from Cell Signaling Technology (La Jolla, CA), was also prepared in DMSO and stored at -20°C in 10 mM aliquots. Paclitaxel (Sigma-Aldrich) was dissolved in DMSO and stored in 7 mM aliquots at -20°C. Doxorubicin (Sigma-Aldrich) was dissolved in saline at 2 mg/ml (3.68 mM) and stored in aliquots at -20°C. Paclitaxel (Sigma-Aldrich) was prepared in DMSO at 7 mM and stored as aliquots at -20°C. Cisplatin (Sigma-Aldrich) was dissolved in saline and stored at -20°C as 5.5 mM aliquots. Antibodies against cleaved caspase-3 (catalog #9664) and Pgp (MDR1/ABCB1) (catalog #13342) were purchased from Cell Signaling Technology (Beverly, MA). Antibodies against LC3B (catalog # L7543) were obtained from Sigma-Aldrich. Alpha-tubulin antibodies (catalog #MAB1864-I) were purchased from Calbiochem (La Jolla, CA). Secondary antibodies, HRP-conjugated goat anti-rabbit (catalog # 111-035-003) and HRP-conjugated goat anti-mouse (catalog # 115-035-003), were purchased from Jackson ImmunoResearch (West Grove, PA).

Cell Lines Two NSCLC cell lines, A549 and NCI-H520, were obtained from the American Tissue and Cell Collection (ATCC) (Manassas, VA). The A549 cells are alveolar basal epithelial adenocarcinoma that have mutated KRAS and functional EGFR. The H520 are squamous cell lung carcinoma that have considerably reduced p53 expression. A549 resistant cells (A549-R) and H520 resistant cells (H520-R) were created from the A549 and H520 parent cells through exposure to stepwise increasing doses of CFZ). Fresh CFZ dosed media was applied every two days over several months. All cells were cultured in RPMI 1640 (Cellgro) with 10% fetal bovine serum (FBS; Seradigm, USA), 1 mM sodium pyruvate, and 1× MEM non-essential amino acid solution. The resistant cell lines were maintained with exposure to CFZ (250 nM for A549-R and 500 nM for H520-R). All cells were grown in 5% CO2 at 37°C in a humidified tissue culture incubator. Cells were routinely tested for mycoplasma contamination using a MycoAlert mycoplasma detection kit (Lonza, Rockland, ME) and were found to be negative. To verify parent cell line authenticity, genomic DNA was extracted (Sigma GIN70-KT), diluted appropriately in TE buffer, and submitted to the University of Arizona Genomics Core (Human Origins Gentoyping Lab) for analysis. Autosomal STR typing was conducted across the 13 core STRs in CODIS and referenced against allelic peaks in cell lines of previously confirmed genotype. The cell lines were verified as authentic.

Proliferation Assay Cells (5 × 103) were seeded in 96-well plates and incubated overnight. Cultures were exposed to various concentrations of drug for a 48-hour treatment interval. Proliferation of cells was determined by 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT) assay. MTT dye (2 mg/ml) was added to the adherent cell culture and incubated for an additional 4 hours at 37oC. After removal of medium, the resulting formazan crystals were dissolved in DMSO for 5 minutes by shaking and the plates were then read in a spectrophotometer at 540 nm. Dose response curves were created using GraphPad Prism version 5.01 (GraphPad Software Inc, La Jolla, CA). IC50 values were calculated using CalcuSyn (Biosoft, Great Shelford, Cambridge, UK).

Cytotoxicity Assay Cell cytotoxicity based on detection of intracellular protease activity (dead-cell protease) was performed using the CytoTox-Glo assay (Promega). Cells (5 × 103) were seeded in 96- well white-walled plates and incubated overnight. Multiples of predetermined 48 hour IC50 doses of CFZ were applied to the cells. Following a further 48-hour incubation, the CytoTox-Glo kit was used according to the manufacturer’s instructions to determine the percentage of dead cells relative to the total amount of cells. Briefly, the cytotoxicity reagent was added to each well and after 15 minutes of incubation, luminescence was measured by a Beekman Coulter Multimode DTX880 microplate reader. A reagent containing digitonin was then added to lyse any remaining viable cells. After another 15- minute incubation, a second luminescence measurement was taken. The percentage of dead cells was calculated by dividing the first luminescence reading by the second after subtraction of the background signal from media only wells. Values are presented as a fold change compared to the vehicle-treated control.

Western Blot Analysis After various time points, the cells were rinsed with cold phosphate buffered saline (PBS) and harvested in a buffer containing 50 mM Tris HCl, 150 mM NaCl, 0.1% Triton X- 100, 2 mM EDTA supplemented with Halt protease and phosphatase inhibitor cocktail (Thermo Scientific, Rockford, IL). The cell lysate was sonicated and centrifuged at 10,000 ×g for 8 min at 4°C. Protein concentration of the resulting supernatant was determined using a 660 nm Protein Assay kit (Thermo Scientific). Twenty micrograms of total cell lysate were boiled for 5 min and resolved in a 10% acrylamide/bisacrylamide gel by electrophoresis at 125 V for 105 min. Proteins were then transferred to a polyvinylidene fluoride (PVDF) membrane (Millipore, Billerica, MA). Membranes were blocked with 5% milk in Tris-buffered saline containing 0.1% Tween-20 (TBST) for 30 min before overnight incubation at 4°C with various primary antibodies, typically at a 1:1000 dilution. Blots were rinsed with TBST and incubated for 2 hours at room temperature with secondary antibody at a 1:15,000 dilution. Reactive bands were visualized by exposure to film using Pierce Supersignal West Pico HRP Detection Reagent (Thermo Fisher Scientific, Rockford IL). Blots were stripped with OneMinute Plus Western Blot Stripping Buffer (GM Biosciences, Frederick, MD) and then re-probed for loading control using alpha-tubulin.

Differential gene expression analysis The gene expression patterns of the cell lines were analyzed and compared using TempO-Seq® human whole transcriptome reagent kits (BioSpyder Technologies, Inc., Carlsbad, CA). The Whole Transcriptome TempO-Seq assay measures 18,886 genes, the entire human transcriptome (Yeakley et al. 2017). The kits consist of a 2X Lysis Buffer for making cell lysates, a detector oligo (DO) cocktail for measurement of the whole transcriptome, Annealing, Nuclease and Ligation reagents, Amplification reagents for preparing libraries for sequencing on Illumina instruments, and a custom Index 1 sequencing primer. Additional reagents were obtained from VWR or Sigma Aldrich. The TempO-Seq assay was performed according to the manufacturer’s instructions, using a 96- well PCR plate in a BioRad C1000/CFX96 real time qPCR instrument. Briefly, cells were washed once with 1X PBS before lysis in 1X Lysis Buffer with 10 minutes of incubation at room temperature. The resulting cell lysate was either used that day or stored at -80°C until analysis. DO cocktail (2 µL) was added to 2 µL of the lysate, heated to 70ºC and then reduced to 45ºC over 50 minutes to permit the DOs to hybridize to their respective RNA targets. Nuclease Mix (24 µL) of was added with incubation at 37ºC for 90 minutes, followed by the addition of Ligase (24 µL) Mix and an additional incubation of 60 min. The mix was then incubated for 15 minutes at 80ºC. This product (15 µL) was then transferred into a second PCR plate pre-loaded with 10 µL of PCR Amplification mix containing the PCR primers (designed to add a different sample specific index sequence to each sample), a green fluorescent dsDNA dye, and polymerase. Six cycles were carried out at an annealing temperature of 54°C followed by 19 cycles at 66°C, with the yield monitored at each cycle using the dye. The amplified samples were then pooled together and the sequencing library was purified using the NucleoSpin Gel and PCR Clean-up kit (Macherey-Nagel cat# 740609.50) with no changes to kit formulations. Sequencing was performed by a service provider using the Illumina NextSeq instrument. In addition to the cell samples, a no sample input control was also processed through the TempO-Seq and PCR amplification assay steps to measure background. After sample demultiplexing using Illumina sequencer default settings, FASTQ files were aligned to the probe sequences using Bowtie, allowing for up to 2 mismatches in the 50 bp target sequence, using the data TempO-SeqR analysis software provided with the assay kits. Data normalization was carried out using a package in the TempO-SeqR analysis software, and differential expression analysis was carried out using the DESeq2 package in R (Love et al. 2014).

Q-RT-PCR Total cellular RNA was isolated using the RNeasy Plus Mini kit (Qiagen, Valencia, CA) and quantified with a spectrophotometer. cDNA was then generated from 0.5 ug of DNase- free RNA using the qScript cDNA Synthesis Kit (Quanta BioSciences, Gaithersburg, MD) following the manufacturer’s instructions. Reverse transcription (RT) was performed using a GeneAmp 7300 sequence detection system (PE Biosystems, Foster City, CA). Amplification reactions were run in a reaction volume of 20 μL using the Applied Biosystems TaqMan Universal PCR Mastermix (Applied Biosystems, Branchburg, NJ). PCR primers and TaqMan probe for PGP were synthesized and pre-optimized by Applied Biosystems (Assays on Demand, catalog #4351372) (Foster City, CA). Each reaction contained 1× PCR Mastermix, 900 nmol of each primer, and 250 nmol of the Fam probe. Reverse transcription was performed at 48°C for 30 minutes, samples incubated for 10 minutes at 95°C and then amplification over 40 cycles at 15 sec at 95°C followed by 1 minute at 60°C. Values were normalized to human large ribosomal protein (RPLPO) message using and quantitated using the delta CT method as described by Perkin-Elmer. The RPLPO PCR primers and TaqMan probe were synthesized and pre-optimized by Applied Biosystems (Assays on Demand, catalog #4331182) (Foster City, CA).

Flow Cytometry Cells were seeded in 100-mm plates and incubated overnight. Cells were treated with media only or treated with media containing 10 µM doxorubicin for 1 hour. The adherent cells were collected and rinsed 2X with PBS. The cells were analyzed by flow cytometry (FACSCanto II, BD Biosciences, San Jose, CA) with excitation at 488 nm and emission at 585 nm. Data analysis was performed using FlowJo software (Treestar Inc., Ashland, OR).

Results

Prolonged incremental drug exposure renders cells that are resistant to CFZ The A549-R and H520-R cells were created as described in the methods section. To evaluate these cells for CFZ sensitivity, the MTT assay was performed on the A549 and H520 parent and resistant cell lines. Cells were grown under selection pressure in the above indicated amounts of carfilzomib until 24 hours prior to seeding cells for MTT assays. Results from one representative experiment (n=6) are shown in Figure 1. For both cell lines, the 48-hour dose response curves show that the resistant cell line variant is less sensitive to CFZ than its respective parent cell line. The CFZ IC50 values were calculated from the dose response curves and are compared in Table 1. The A549-R cells showed approximately a 2.5-fold increase in CFZ IC50 value over its parent (from 127 nM to 311 nM), while the H520-R cells showed more than a 100-fold increase in the CFZ IC50 value over its parent (from 15 nM to 1,840 nM).

Resistant cells have reduced cell death, cleaved caspase-3 and autophagy in response to CFZ treatment The MTT assay results, based on mitochondrial activity, reflect changes related to both cytotoxicity and/or cell proliferation. To further investigate cytotoxicity, cell death was evaluated using the Promega CytoTox-Glo cytotoxicity assay. The release of “dead-cell protease activity” was initially measured as a result of CFZ treatment. The remaining viable cells were then lysed with digitonin and a second dead-cell protease activity measurement was obtained, reflecting total cells. The percentage of dead cells in each treatment group was obtained by dividing the first measurement by the second measurement and the values were then normalized to the untreated samples. Figure 2A shows that the rate of increase in the percent of dead cells with increasing CFZ dosage is lowered in the A549-R cells versus the A549 parent cells. While the H520 parent cells show an increase in the percent of dead cells with increasing CFZ treatment, the H520-R rate is less with no increase in dead cells since they remain completely resistant to CFZ at the doses used. Next, we examined the A549 and H520 parent and resistant cell lines for markers of apoptosis and autophagy using Western blot analysis. Levels of cleaved caspase-3, a marker of apoptosis, and LC3B-II, a marker of autophagy, were found to be lower for the same dose of CFZ in the resistant cells as compared to their parent (Figure 2B).

Pgp is upregulated in the CFZ resistant cells TempO-Seq analysis was performed to examine differentially expressed genes in the parent and CFZ resistant cell lines. The ABCB1 gene, which encodes Pgp, was found to have a modest but significant increase in expression in A549-R cells compared to its parent (43 counts in A549 vs 51 counts in A549-R, a 1.2-fold change). There was a much more dramatic increase in ABCB1 expression in the H520-R cells compared to its parent (0.7 counts in H520 vs 6,267 counts in H520-R, a 1>9,000-fold change). Refer to Supplemental Table 1 for data on ABCB1 and other select genes measured by TempO- Seq. To independently validate these results and further investigate Pgp as a pertinent mechanism of resistance to CFZ, quantitative RT-PCR and Western blot analysis was performed on the untreated parental and CFZ resistant cell lines. PCR analysis demonstrated that Pgp transcripts are approximately 2 fold higher in the A549-R cells versus the parent A549 cells and approximately 11 fold higher in the H520-R cells versus the parent H520 cells (Figure 3A), consistent with the TempO-Seq data. Additionally, Western blot analysis showed a similar trend with Pgp protein levels substantially higher in the A549-R cells versus the parent A549 cells, and exceedingly higher in the H520-R cells versus the H520 parent cells (Figure 3B). To confirm gene and protein expression related to functional activity, flow cytometry was performed to analyze the uptake of doxorubicin, a known client of Pgp. Following a 1-hour exposure to doxorubicin, the A549 and H520 parent and resistant cells were washed and analyzed. Doxorubicin autofluorescent intensity was measured to determine the amount of uptake into the cells. Consistent with the Pgp message and protein results, Figure 3C shows slightly less doxorubicin uptake in the A549-R cells versus the A549 parent cells and substantially less uptake of doxorubicin uptake in the H520-R cells versus the H520 parent cells.

Other upregulated pathways identified in CFZ resistant cells Having the whole transcriptome gene expression data from the TempO-Seq assay permitted us to look more broadly at mechanisms of drug resistance, in addition to Pgp, that were induced by the CFZ conditioning treatment. The gene expression data identified other putative mechanisms for drug resistance that deserve future exploration (Supplemental Table 1): 1) SLC6A15, the neutral amino acid transporter, increased 49-fold in H520-R and 41-fold in A549-R 2) ABCC2, a transporter of organic anions that may include cisplatin, increased 21-fold in H520-R 3) the metabolism enzyme gene CYP2J2, significantly increased (≥117-fold) in A549-R, but significantly decreased (90%) in H520-R 4) CYP4F11, a metabolism enzyme induced in both A549-R and H520-R cells To help confirm the relevance of the TempO-Seq gene expression observations, we focused on the change in KDM6A expression, a histone demethylase, which increased in the H520- R cells relative to their parent, but was not increased in A549-R cells. We exposed the cell lines to the single agent and combination treatments of CFZ and suberoylanilide hydroxamic acid (SAHA), a histone deacetylase inhibitor that increases histone acylation and has anti-growth activity against NSCLC cells (Komatsu et al. 2006). We have previously published evidence that combination treatment of CFZ plus SAHA was more efficacious that CFZ alone (Hanke et al. 2016). Since KDM6A is a histone demethylase, and SAHA is an inhibitor of histone deacetylases, the expectation is that SAHA would cause greater apoptosis and caspase-3 cleavage in the H520-R cells, where KDM6A was upregulated, than in A549-R cells, where KDM6A was not upregulated. Cleaved caspase- 3 following treatment with CFZ, SAHA or the combination is shown in Supplemental Figure 1. Consistent with increased KDM6A in H520-R cells but not A549-R, there was a greater effect of SAHA (greater caspase-3 cleavage indicative of greater SAHA-mediated apoptosis) in H520-R cells than A549-R cells compared to their parent. Interestingly, although co-treatment with CFZ+SAHA caused much greater cleavage of caspase-3 in A549-R cells then SAHA alone, the combined treatment was only effective in H520 cells, not the H520-R cells. This suggests that even though KDM6A increases the sensitivity of H520-R cells to SAHA, the much-reduced sensitivity to CFZ results in the combination therapy being less effective.

Sensitivity of CFZ resistant cell lines to other chemotherapy drugs To examine how the development of resistance to CFZ may affect sensitivity to other drugs that are known Pgp clients, MTT assays were performed on the cell lines following treatment with BTZ and other common cancer chemotherapies while cisplatin, which is not a Pgp client, was used as a control. The results from one representative experiment (n=6) are shown in Figure 4. The CFZ resistant cells showed cross resistance to the first generation proteasome inhibitor BTZ, a substrate of Pgp. The CFZ resistant cells also showed cross resistance to two other agents whose efflux are mediated by Pgp, doxorubicin and paclitaxel. However, the CFZ resistant cells became mildly sensitized to cisplatin which is not a substrate of the Pgp efflux pump. Table 2 provides a comparison of the IC50 values between the CFZ resistant and parent cell lines when treated with these chemotherapy agents. The fold change in IC50 of the CFZ resistant cells compared to parent is 2.4-fold and 19.5-fold for the first generation proteasome inhibitor BTZ in A549 and H520 cells, respectively. This is consistent with the greater resistance of the H520-R cells to CFZ then that of the A549-R cells, and consistent with the larger increase of Pgp expression over its parent found in the H520-R cells versus that of the A549-R cells. Cross- resistance of doxorubicin and paclitaxel, two non-proteasome targeted drugs whose efflux are mediated by Pgp, exhibited a similar 2.4- and 5.1-fold increase in IC50 values, respectively, in A549-R cells, and consistently greater 6.8- and 517-fold change in IC50 values, respectively, in H520-R cells. TempO-Seq analysis showed a more than 150 fold increase in expression of the TUBA4A gene (whose protein product is the target of paclitaxel) in the H520-R cells versus its parent (Supplemental Table 1). This directly correlates to the 517-fold increase in the paclitaxel IC50 value found in the H520-R cells versus its parent (Table 2). In contrast to the agents that are substrates of Pgp, sensitivity to cisplatin, whose efflux from cells is not mediated by Pgp, increased, with a 0.44-fold change in A549-R and a 0.41-fold change in H520-R cells.

Discussion

Although the use of first or second generation proteasome inhibitors in multiple myeloma and mantle cell lymphoma is frequently associated with initial robust clinical response, patients frequently become refractory or resistant to proteasome inhibitor based therapy (Mitra et al. 2014). Historically, solid tumors have demonstrated disappointing sensitivity to proteasome inhibitor therapy, in spite of inherent sensitivity to proteasome inhibitor treatment in in vitro solid tumor models. Multiple mechanisms of both inherent and acquired resistance to proteasome inhibition have been reported including upregulation of Pgp (Grogan et al. 1993), enhanced protection from oxidative stress via activation of nuclear factor kB (NFkB) and nuclear respiratory factor 2 (Nrf-2) transcription factors (Rushworth et al. 2012), inhibition of apoptotic pathways (Chauhan et al. 2007), and activation of pro-survival signaling pathways (Frassanito et al. 2016).

The results of our experiments demonstrate that NSCLC cell lines induce resistance to CFZ through chronic exposure. The development of resistance to CFZ is reflected by an increase in the dose response IC50 (Figure 1), a decrease in cytotoxicity (Figures 2A), and reduced markers of apoptosis and autophagy (Figure 2B). We observed that the resistant cell populations express higher levels of Pgp compared to their respective parent. Notably, A549 parent cells have higher basal levels of Pgp versus H520 parent cells and are also more inherently resistant to CFZ (A549 CFZ IC50 of 125 nM versus H520 CFZ IC50 of 15 nM) (Baker et al. 2014). While the A549-R cells show only a small fold increase in CFZ resistance over A549 parent cells, H520-R cells show a much larger increase in acquired resistance over H520 cells. Therefore, cells that are initially highly sensitive to CFZ because of low Pgp may have the potential to become highly resistant once Pgp upregulation occurs. In addition to Pgp, gene profiling has identified additional adaptive changes in the CFZ-resistant cells compared to parental cells (Mitra et al. 2017; Riz et al. 2015; Riz et al. 2016; Zheng et al. 2017).

Given the prevalence of Pgp mediated chemotherapy resistance in NSCLC tumors, there is an urgent need for improved biomarkers that can be applied serially to predict and monitor biologics and chemotherapy sensitivity and resistance. Importantly, we showed that gene expression of Pgp measured by the whole transcriptome RNA sequencing platform TempOseq correlates with protein and functional expression. TempOseq can be extended to single cell analysis and therefore has the potential to be applied directly to circulating tumor cells to characterize drug-resistant phenotypes using serial liquid biopsies. Other high-throughput gene profiling methods which have been applied to CTCs successfully (Park et al. 2016). A small series of case studies applying serial monitoring of CTC gene expression profiles have supported the potential use of CTCs to monitor therapeutic efficacy and to identify biomarkers of drug resistance (Bielcikova et al. 2017).

These findings provide insights into the complex mechanisms of acquired CFZ drug resistance and demonstrates how cross-therapy resistance can be detected by leveraging gene expression profiling.

Figure/Table Legends

Figure 1. Dose response curves show increased resistance to CFZ in the resistant cell line as compared to the parent in both A549 and H520 cells. Resistant cell lines were created by exposing parental cells to stepwise increasing concentrations of CFZ over many months. The parental and CFZ resistant cells were exposed to CFZ at various concentrations (nM) for 48 hours and assayed by MTT. One representative experiment is shown, n=6.

Table 1. Comparison of Parent and CFZ Resistant Cell CFZ 48 Hour IC50 Values

Figure 2. Cell death, cleaved caspase-3, and autophagy are reduced in the resistant cell lines as compared to the parental cell lines. A) Cells were treated with media only or treated with media containing increasing concentrations of CFZ based on parent 48 h IC50 dose (½×, 1×, 2×). After 48 hours the detection of dead cells was determined with CytoTox-Glo cytotoxicity assay (n=5) by measuring released protease activity in culture medium. Next, total cells were determined following the additional of digitonin. Relative ratio of dead cells per total cells is displayed. *p<0.05, **p<0.005 as compared to parent sample using Student’s t test in Excel (Microsoft). A) Cells were treated with media only or treated with media containing increasing concentrations of CFZ based on parent 48 h IC50 dose (1×, 5×, 20×). Detection of cleaved caspase-3 and LC3B by immunoblot in total extracts of cells harvested at 24 hours. Tubulin was used as a loading control.

Figure 3. PGP is upregulated in CFZ resistant cells, reducing their uptake of doxorubicin. A) Detection of Pgp transcripts by real time PCR in untreated cells. B) Immunoblot detection of Pgp protein levels in total cell lysate. Tubulin was used as a loading control. C) Intracellular accumulation of doxorubicin after 1 hour of treatment was measured by flow cytometry with excitation at 488 nm and emission at 585 nm. Untreated parental cells are shown as a control.

Figure 4. Cross-sensitivity of CFZ resistant cell lines to additional drugs. MTT dose response curves of A549 and H520 parent and resistant cell lines treated with listed drug for 48 hours; one representative experiment (n=6). The CFZ resistant cells show increased resistant to Pgp client drugs (bortezomib, doxorubicin, paclitaxel) with sensitivity to the non-Pgp client cisplatin.

Table 2. IC50 Value Comparison of Parent and CFZ Resistant Cells Exposed to Additional Chemotherapy Agents

Supplemental Table 1 (Page 1 of 3). Gene expression analysis using TempO-Seq to determine differences between parent and CFZ resistant cell lines. See methods for details. List of highest fold change genes of both cell lines sorted by H520 fold change.

Supplemental Table 1 (Page 2 of 3). Gene expression analysis using TempO-Seq to determine differences between parent and CFZ resistant cell lines. See methods for details. List of highest fold change genes of both cell lines sorted by H520 fold change.

Supplemental Table 1 (Page 3 of 3). Gene expression analysis using TempO-Seq to determine differences between parent and CFZ resistant cell lines. See methods for details. List of highest fold change genes of both cell lines sorted by H520 fold change.

Supplemental Figure 1. Upregulation of KDM6A corresponds to SAHA sensitivity in H520 CFZ resistant cells. TempO-Seq gene expression analysis showed upregulation of an HDACi sensitizer gene, KDM6A, in H520 CFZ resistant cells compared to its parent, but not in A549 CFZ resistant cells compared to its parent. To further evaluate, cells were left untreated or treated with CFZ and/or SAHA parent 48 h IC50 doses. Detection of cleaved caspase-3 by immunoblot in total extracts of cells harvested after 24 hours of treatment as indicated. Tubulin was used as a loading control.

Compliance with Ethical Standards

Funding: This work was supported by a research collaboration award by Onyx Pharmaceuticals, Inc., an Amgen subsidiary, and a Basic/Clinical translational partnership pilot grant award from the Arizona Cancer Center Support Grant P30CA023074 from the National Cancer Institute (NCI).

Conflict of Interest: Authors EI, MTM, and BES are employees of BioSpyder Technologies, Inc., the company that developed and now sells the TempO-Seq kits. The other authors have no conflicts to declare.

Ethical approval: This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent: No human participants were used in this study.

References

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A549 H520

CFZ Resistant CFZ Resistant Parent Parent A Figure 2 A549 H520

6.0 Parent CFZ Resistant 2.0 Parent CFZ Resistant 4.5 1.5 ** ** 3.0 * 1.0 * ** *

Fold change Fold 1.5 0.5 % of Dead Cells Deadof % 0.0 0.0 CFZ (nM)

B Parent CFZ Resistant

CFZ (nM) Cleaved caspase-3 LC3B - I

A549 LC3B - II Tubulin

CFZ (nM)

Cleaved caspase-3

LC3B - I

H520 LC3B - II Tubulin A Figure 3 A549 H520

14 14 )

Ct 12 12 ΔΔ - 10 10 8 8

6 6 / RPLP0 (2 / RPLP0 4 4

Pgp 2 2 0 0 Parent CFZ Resistant Parent CFZ Resistant

B A549 H520

CFZ CFZ Parent Resistant Parent Resistant

Pgp

Tubulin Figure 3 Continued

Untreated Parent Cells

Dox Treated CFZ Resistant Cells

Dox Treated Parent Cells

A549 H520 Counts

Fluorescence Intensity Parent CFZ Resistant Figure 4

A54 H52

9 0

Bortezomib

Doxorubicin

Paclitaxel

Survival Rate (% of control) of (% Rate Survival Cisplatin

Treatment (nM) Figure S1

Untreate CFZ SAHA CFZ+SAH d A Cleaved caspase-3

A549 Tubulin

Cleaved caspase-3

H520 Tubulin Table 1. Comparison of Parent and CFZ Resistant Cell CFZ IC50 Values

A549 H520 Parent CFZ Resist Fold Parent CFZ Resist Fold

CFZ IC50 (nM) CFZ IC50 (nM) Change CFZ IC50 (nM) CFZ IC50 (nM) Change 127.0 311.0 2.45 15.1 1840.0 121.85 Table 2. IC50 Value Comparison of Parent and CFZ Resistant Cells Exposed to Additional Chemotherapy Agents

A549 H520 Parent CFZ Resist Fold Parent CFZ Resist Fold

Drug IC50 (nM) IC50 (nM) Change IC50 (nM) IC50 (nM) Change Bortezomib 7.8 19.0 2.42 8.4 164.3 19.51 Doxorubicin 55.4 136.0 2.45 510.3 3482.9 6.83 Paclitaxel 1.8 9.2 5.13 3.9 2021.8 517.08 Cisplatin 9263.4 4035.3 0.44 32185.8 13109.4 0.41 Table S1

A549 H520 CFZ Fold CFZ Fold Gene Id Parent Resist Change Parent Resist Change Description (GeneCards; http://www.gencards.org) ABCB1 43.0 51.7 1.2 0.7 6267.3 9430.1 Energy-dependent efflux pump responsible for decreased drug accumulation in multidrug- resistant cells. TUBA4A 416.0 1070.3 2.6 3.0 461.8 152.9 Tubulin is the major constituent of microtubules. Microtubules of the eukaryotic cytoskeleton perform essential and diverse functions. FOSL1 121.0 930.6 7.7 0.7 47.7 71.7 FOS proteins have been implicated as regulators of cell proliferation, differentiation, and transformation. TMPRSS15 0.0 0.0 * 1.0 67.0 66.3 Encodes an enzyme that converts the pancreatic proenzyme trypsinogen to trypsin, which activates other proenzymes including chymotrypsinogen and procarboxypeptidases.. SCG2 37.0 9.7 0.3 6.7 364.1 54.5 A neuroendocrine secretory granule protein, which is the precursor for biologically active peptides. SLC6A15 39.5 1638.4 41.5 11.3 562.9 49.6 Functions as a sodium-dependent neutral amino acid transporter. Exhibits preference for the branched-chain amino acids, particularly leucine, valine, isoleucine, methionine. SHH 0.0 0.3 * 2.3 92.3 39.7 Sonic Hedgehog encodes a protein that is instrumental in intercellular signal essential for a variety of patterning events during development. LIX1 0.0 0.0 * 15.0 584.8 38.9 Limb And CNS Expressed 1.

SYT2 0.0 7.7 * 2.4 61.7 26.2 The encoded protein is a synaptic vesicle membrane protein thought to function as a calcium sensor in vesicular trafficking and exocytosis. PALM3 12.5 70.8 5.7 39.3 846.1 21.5 ATP-binding protein, which may act as a adapter in the Toll-like receptor (TLR) signaling.

ABCC2 290.5 255.3 0.9 9.3 198.5 21.3 Mediates hepatobiliary excretion of numerous organic anions. May function as a cellular cisplatin transporter. ALDH1A1 13946.9 3716.9 0.3 24.4 454.4 18.7 Binds free retinal and cellular retinol-binding protein-bound retinal. Can convert/oxidize retinaldehyde to retinoic acid. TDO2 9.0 320.4 35.6 1.0 17.8 17.9 This gene encodes a heme enzyme that plays a critical role in tryptophan metabolism by catalyzing the first step of the kynurenine pathway. ADAMTS1 0.0 88.1 * 6.0 78.7 13.1 Has angiogenic inhibitor activity. Active metalloprotease, which may be associated with various inflammatory processes. KRT6A 0.0 48.2 * 13.3 102.8 7.7 Involved in the activation of follicular keratinocytes after wounding, while it does not play a major role in keratinocyte proliferation or migration. REEP1 2.5 159.3 63.7 52.4 342.3 6.5 Required for endoplasmic reticulum (ER) network formation, shaping and remodeling; it links ER tubules to the cytoskeleton. HSPA6 0.0 73.5 * 1.0 6.4 6.4 Hsp70s helps stabilize preexistent proteins against aggregation and mediate the folding of newly translated polypeptides. Table S1 (continued)

A549 H520 CFZ Fold CFZ Fold Gene Id Parent Resist Change Parent Resist Change Description (GeneCards; http://www.genecards.org) EGF 2.5 331.7 132.7 152.5 707.1 4.6 EGF stimulates the growth of various epidermal and epithelial tissues in vivo and in vitro and of some fibroblasts in cell culture. ST6GALNA 0.0 30.0 * 102.7 433.4 4.2 Catalyzes the transfer of sialic acid to cell surface proteins to modulate cell-cell interactions. C5 FBN2 0.0 26.7 * 109.6 379.9 3.5 The protein encoded by this gene is a component of connective tissue microfibrils and may be involved in elastic fiber assembly. ZEB2 0.0 88.7 * 3.0 6.3 2.1 Transcriptional inhibitor that binds to DNA sequence 5-CACCT-3 in different promoters. Represses transcription of E-cadherin. MCC 1.5 117.0 77.9 47.7 70.7 1.5 Suppresses proliferation and the Wnt/b-catenin pathway in colorectal cancer. Inhibits DNA binding of b-catenin transcription factors. MXD1 0.0 10.0 * 50.3 55.8 1.1 Transcriptional repressor. MAD binds with MAX to antagonize MYC transcriptional activity by competing for MAX. NEFL 0.0 28.3 * 891.3 724.4 0.8 Neurofilaments usually contain three intermediate filament proteins: L, M, and H which are involved in the maintenance of neuronal caliber. LCP1 4.0 111.2 27.8 4.3 3.3 0.8 Plays a role in the activation of T-cells in response to costimulation through TCR/CD3 and CD2 or CD28. CXorf57 0.0 70.8 * 301.0 220.3 0.7 Chromosome X Open Reading Frame 57.

KCNQ3 5.5 165.0 30.0 113.5 79.0 0.7 Probably important in the regulation of neuronal excitability.

CASZ1 0.5 17.1 34.2 181.1 90.6 0.5 Transcription factor involved in vascular assembly and morphogenesis through direct transcriptional regulation of EGFL7. TMTC1 1.0 76.0 76.0 1689.4 537.8 0.3 Transmembrane And Tetratricopeptide Repeat Containing 1

KCNQ5 0.0 20.0 * 846.0 265.1 0.3 Probably important in the regulation of neuronal excitability.

TSPAN12 0.0 30.3 * 647.6 123.6 0.2 Regulator of cell surface receptor signal transduction. Plays a central role in retinal vascularization,y regulating norrin (NDP) signal transduction. HSPB8 570.0 20710.1 36.3 21.7 4.0 0.2 Displays temperature-dependent chaperone activity.

CYP2J2 0.0 117.9 * 610.0 53.7 0.1 Member of the cytochrome P450 family which catalyze many reactions in drug metabolism and synthesis of cholesterol, steroids, other lipids. SNAI2 7.0 176.0 25.1 52.4 2.7 0.1 Transcriptional repressor involved in the generation and migration of neural crest cells Table S1 (continued)

A549 H520 CFZ Fold CFZ Fold Gene Id Parent Resist Change Parent Resist Change Description (GeneCards; http://www.genecards.org) MME 0.0 15.7 * 5018.0 196.3 0.0 Biologically important in the destruction of opioid peptides such as Met- and Leu- enkephalins by cleavage of a Gly-Phe bond IFI16 2.5 104.8 41.9 235.4 0.6 0.0 Binds preferentially to supercoiled DNA and cruciform DNA structures. Seems to be involved in transcriptional regulation. ALDH8A1 1.0 0.7 0.7 0.0 125.6 * Converts 9-cis-retinal to 9-cis-retinoic acid. Has lower activity towards 13-cis-retinal. Has much lower activity towards all-trans-retinal. ARHGEF28 942.5 452.1 0.5 0.0 19.9 * A RHOA-specific guanine nucleotide exchange factor regulating signaling pathways downstream of integrins and growth factor receptors. B4GALNT1 35.5 74.1 2.1 0.0 37.6 * Involved in the biosynthesis of gangliosides GM2, GD2 and GA2.

CCL26 0.0 333.9 * 0.0 2.6 * Chemotactic for eosinophils and basophils. Binds to CCR3.

CLEC2B 1.5 383.2 255.6 0.0 0.0 * Has diverse functions, such as cell adhesion, cell-cell signalling, glycoprotein turnover, roles in inflammation and immune response. COL4A1 198.0 537.9 2.7 0.0 23.4 * A major structural component of glomerular basement membranes forming a meshwork with laminins, proteoglycans, entactin/nidogen. COL4A2 205.0 237.9 1.2 0.0 14.9 * A major structural component of glomerular basement membranes forming a meshwork with laminins, proteoglycans, entactin/nidogen. CYP4F11 26.0 158.2 6.1 0.0 15.1 * Member of the cytochrome P450 family which catalyze many reactions in drug metabolism and synthesis of cholesterol, steroids, other lipids. IL32 1.0 155.8 155.9 0.0 2.7 * Cytokine that may play a role in innate and adaptive immune responses.

KDM6A 145.5 54.5 0.4 0.0 48.9 * Histone demethylase that specifically demethylates Lys-27 of histone H3, thereby playing a central role in histone code. SERPINB5 0.0 13.1 * 0.0 104.1 * Tumor suppressor. It blocks the growth, invasion, and metastatic properties of mammary tumors. STX11 0.5 55.4 110.8 0.0 0.6 * Syntaxins have been implicated in the targeting and fusion of intracellular transport vesicles. May regulate protein transport. UTY 244.0 109.8 0.4 0.0 25.3 * Male-specific histone demethylase that catalyzes trimethylated Lys-27 (H3K27me3) demethylation in histone H3.